JP2012008782A - Method for diagnosing function of plant, and plant monitoring device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To diagnose function of a plant easily and accurately.SOLUTION: A measurement data acquisition part 101 acquires measurement data and influence data from a plant. Next, an efficiency calculation part 102 substitutes the measurement data acquired by the measurement data acquisition part 101 for a calculation formula of efficiency expressed by preliminarily determined measurement data, and generates an efficiency parameter. Then, a correction efficiency calculation part 103 generates a correction efficiency parameter showing efficiency of a gas turbine in a reference state which is an operation condition to be the reference by using the efficiency parameter generated by the efficiency calculation part 102 and the influence data acquired by the measurement data acquisition part 101. Subsequently, a correction efficiency collection part 104 collects the correction efficiency parameters and forms a correction efficiency group. Then a function of the plant is diagnosed using a correction quality parameter group and a latest correction quality parameter.

Description

  The present invention relates to a method for monitoring the operation status of a plant and diagnosing the function of the plant, and a plant monitoring apparatus.

  Conventionally, in plant operation, function diagnosis is performed during operation in order to prevent damage due to plant stoppage or failure due to abnormality. In general, diagnosis of plant functions is performed by observing operation data during plant operation and detecting a significant difference to determine an abnormality, or by using the operation data to calculate quality parameters. Is used. A quality parameter is information which shows the quality of a plant, for example, plant efficiency, compressor efficiency of a gas turbine, turbine efficiency, etc. are mentioned.

  However, in a gas turbine plant, for example, even if it is operating normally at rated operation, the quality parameter depends on influencing factors that affect the kinetic energy of the combustion gas that rotates the turbine, such as fuel composition, intake air temperature, and atmospheric pressure. Change. Therefore, even if the quality parameter in a certain operation situation is compared with the quality parameter in another operation situation, the plant function cannot be properly diagnosed.

As a method for solving this problem, Patent Literature 1 discloses a technique for displaying associations between plant quality parameters and influencing factors in groups based on time.
Thus, by visualizing the quality parameters of the plant in association with the influence factors, the diagnostician can clearly diagnose the long-term change in performance of the plant.

Another solution is to normalize the measured values by evaluating and correcting variations in sensor measured values caused by plant operating conditions and fuel, etc., and apply the measured values to generate quality parameters. Thus, a method of generating a quality parameter normalized to a predetermined condition is conceivable.
As described above, by performing the comparison using the quality parameters indicating the unified conditions, the diagnostician can easily diagnose the plant.

JP 2008-151008 A

  When diagnosing the function of a plant in consideration of the influence of a plurality of influence factors using the method described in Patent Document 1, the monitoring device displays a graph showing the relationship between the quality parameter and the influence factor for each of the influence factors. Generated and displayed, the diagnostician compares each graph and makes a diagnosis. Therefore, when the number of influencing factors is small, the diagnostician can easily diagnose the function of the plant. However, when the number of influencing factors is large, it is difficult for the diagnostician to diagnose the function of the plant.

  In addition, the correlation between plant quality parameters and influencing factors is complex, and furthermore, this correlation varies from plant to plant, so it is difficult to accurately represent the correlation between quality parameters and influencing factors in one plant. is there. For this reason, even if the normalized quality parameter is calculated using the corrected measurement value as described above, if the correlation between the quality parameter and the influencing factor is not accurately expressed, the value of the quality parameter is accurate. The value is not correct. For this reason, there is a problem that the diagnostician cannot accurately diagnose the plant function.

  The present invention has been made to solve the above-described problem, and is a method for diagnosing the function of a plant, wherein measurement data required for calculating a quality parameter indicating the quality of the plant in a current operating situation is obtained. In the first step, the quality parameter is calculated by substituting the acquired measurement data into the quality parameter calculation formula represented by the measurement data obtained in advance, and the first step. Using the calculated quality parameter and the influence data which is measurement data different from the measurement data and which influences the value of the quality parameter according to a change in the operation state of the plant, A second step of calculating a corrected quality parameter indicating the quality of the plant in a reference situation which is an operating situation A third step of collecting the correction quality parameters by repeatedly executing the first step and the second step to form a correction quality parameter group; and a correction quality parameter group formed in the third step And a fourth step of diagnosing the function of the plant using the latest correction quality parameter.

  Further, in the present invention, the second step includes a first sub-step for calculating a difference between the influence data and the influence data in the reference situation, and a difference calculated in the first sub-step. A second sub-step for calculating an influence value obtained by multiplying a sensitivity indicating a degree of influence of data on the quality parameter, and an influence value calculated in the second sub-step for the quality parameter obtained in the first step And a third sub-step for calculating the correction quality parameter by adding.

  Further, in the third step of the present invention, the correction quality parameter is associated with the operation state of the plant at the time of calculating the correction quality parameter, a correction quality parameter group is formed for each operation state of the plant, and the fourth step In this step, the function of the plant is diagnosed using the correction quality parameter group associated with the operation state of the plant when the latest correction data is calculated and the latest correction quality parameter.

  In the fourth step of the present invention, a confidence interval of the correction specific data group is calculated from the correction quality parameter group formed in the third step, and the latest correction quality parameter exists in the confidence interval. It is characterized by determining whether or not there is an abnormality in the plant by determining whether or not to do so.

  Further, in the fourth step of the present invention, the latest correction quality parameter and the correction quality parameter group formed in the third step are associated in the order of elapsed time from the time when the plant operating state transitions to the intermediate load state. Then, a confidence interval is calculated, and it is determined whether or not there is an abnormality in the plant by determining whether or not the latest correction quality parameter exists within the confidence interval.

  Further, in the fourth step of the present invention, the degree of deterioration of the plant is determined by associating the corrected quality parameter with the operation time of the plant and comparing the relationship between the quality parameter and time obtained in advance. It is characterized by that.

  Further, the present invention provides a measurement data acquisition unit for acquiring measurement data required for calculation of a quality parameter indicating the quality in the current operating state of the plant from the plant, and the quality represented by the measurement data obtained in advance. A quality parameter calculation unit that calculates the quality parameter by substituting the acquired measurement data into a parameter calculation formula, and the quality parameter that is measurement data different from the measurement data and changes according to a change in the operation state of the plant An influence data acquiring unit that acquires at least one measurement data that affects the value of the value from the plant, a quality parameter calculated by the quality parameter calculating unit, and an influence data acquired by the influence data acquiring unit. Used to indicate the quality of the plant in the standard situation, which is the standard operating situation. The correction quality parameter is calculated by repeatedly executing the correction specific data calculation unit for calculating the quality parameter, the measurement data acquisition unit, the measurement data calculation unit, the influence data acquisition unit, and the correction specific data calculation unit. And a correction specific data collection unit that collects and forms a correction quality parameter group.

  According to the present invention, a corrected quality parameter indicating the quality of a plant in a reference situation is calculated using the quality parameter and at least one influence data, and the function of the plant is diagnosed using the corrected quality parameter. Thereby, since the quality parameter of a plant can be normalized and compared, the diagnostician can diagnose the function of the plant easily and accurately.

It is a schematic block diagram of the gas turbine used as the monitoring object of a plant monitoring apparatus. It is a schematic block diagram which shows the structure of the plant monitoring apparatus which concerns on 1st Embodiment. It is a 1st flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 1st Embodiment. It is a 2nd flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 1st Embodiment. It is a figure which shows an example of the information which a display part displays. It is a schematic block diagram which shows the structure of the plant monitoring apparatus which concerns on 2nd Embodiment. It is a flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 2nd Embodiment. It is a 1st figure which shows the operation | movement which estimates the deterioration degree of a gas turbine. It is a schematic block diagram which shows the structure of the plant monitoring apparatus which concerns on 3rd Embodiment. It is a flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 3rd Embodiment. It is a 2nd figure which shows the operation | movement which estimates the deterioration degree of a gas turbine. It is a schematic block diagram which shows the structure of the plant monitoring apparatus which concerns on 4th Embodiment. It is a 1st flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 4th Embodiment. It is a 2nd flowchart which shows operation | movement of the plant monitoring apparatus which concerns on 4th Embodiment. It is a figure which shows an example of the information which a display part displays.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a schematic configuration diagram of a gas turbine to be monitored by a plant monitoring apparatus.
The gas turbine 500 installed in a plant to be monitored by the plant monitoring device compresses the intake air A sucked into the compressor 501 from the atmosphere (external air) by the compressor 501 and supplies the compressed air to the combustor 502 for combustion. The generator 502 mixes the fuel F with the fuel F and burns it to generate combustion gas G, which is supplied into the turbine 503, thereby rotating the rotor 504 with a blade structure (not shown) and generating power with the generator 505. Is possible. Further, the flow rate of fuel flowing into the combustor 502 is controlled by a fuel adjustment valve 506.

  The output of the gas turbine 500 depends on various influential factors that affect the kinetic energy of the combustion gas G that rotates the turbine 503, such as the atmospheric temperature, atmospheric pressure, fuel pressure, fuel temperature, and the volume ratio of fuel combustion operation main components. Change. For example, when the temperature of the intake air A rises, the density of the intake air A decreases and the weight flow rate of the air decreases, so that the kinetic energy of the combustion gas G decreases and the output of the gas turbine 500 decreases. Thus, since the output of the gas turbine 500 varies depending on various influential factors, the plant monitoring apparatus uses the measurement data obtained from the gas turbine 500 to determine the efficiency parameter (quality parameter) indicating the plant efficiency of the gas turbine 500. Are properly compared and displayed. Thereby, the diagnostician can accurately diagnose the quality of the gas turbine 500 and the plant including the gas turbine.

The gas turbine 500 is provided with an atmospheric temperature / pressure sensor 401, a fuel pressure / temperature sensor 402, a fuel composition measuring device 403, and a wattmeter 404.
The atmospheric temperature / atmospheric pressure sensor 401 is a sensor that measures the temperature and atmospheric pressure of the intake air A sucked into the compressor 501 of the gas turbine 500.
The fuel pressure / temperature sensor 402 is a sensor that measures the pressure of the fuel F supplied to the combustor 502 of the gas turbine 500 and the temperature of the fuel F.
The fuel composition measuring device 403 is a device that measures the composition of the fuel F supplied to the combustor 502 of the gas turbine 500 and measures the volume ratio in the fuel F of the main components of the combustion operation such as methane, ethane, and propane. .
The wattmeter 404 is a sensor that measures the amount of output power from the generator 505 of the gas turbine 500.
The operation status of such a gas turbine 500 is monitored by a plant monitoring device shown below.

(First embodiment)
Hereinafter, the plant monitoring apparatus 100 according to the first embodiment will be described.
FIG. 2 is a schematic block diagram illustrating the configuration of the plant monitoring apparatus according to the first embodiment.
The plant monitoring apparatus 100 includes a measurement data acquisition unit 101, an efficiency calculation unit 102, a correction efficiency calculation unit 103, a correction efficiency collection unit 104, a rated operation efficiency storage unit 105-1, an intermediate load efficiency storage unit 105-2, and an efficiency comparison unit. 106 and a display unit 107.

  The measurement data acquisition unit 101 (influence data acquisition unit) acquires measurement data from various sensors 401 to 404 installed in the gas turbine 500. Specifically, the measurement data acquisition unit 101 acquires measurement data indicating the atmospheric temperature and atmospheric pressure from the atmospheric temperature / pressure sensor 401. The measurement data acquisition unit 101 acquires measurement data indicating the fuel pressure, fuel temperature, and fuel flow rate from the fuel pressure / temperature / flow rate sensor 402. In addition, the measurement data acquisition unit 101 acquires measurement data indicating the volume ratio of the main component of the combustion operation in the fuel from the fuel composition measurement device 403. Then, the fuel composition measuring device 403 calculates the heat generation amount of the fuel from the measurement data indicating the volume ratio of the main component of the combustion operation in the fuel. Further, the measurement data acquisition unit 101 acquires measurement data indicating the output power amount of the gas turbine 500 from the wattmeter 404.

The efficiency calculation unit 102 calculates the plant efficiency of the gas turbine 500 in the current operation state using the fuel flow rate and output power amount acquired by the measurement data acquisition unit 101 and the heat generation amount of the fuel calculated by the measurement data acquisition unit 101. Then, an efficiency parameter (quality parameter) indicating the plant efficiency is generated. The calculation formula used for calculating the plant efficiency is obtained in advance and stored in the internal memory of the efficiency calculation unit 102.
The corrected efficiency calculation unit 103 uses the efficiency parameter generated by the efficiency calculation unit 102 and the atmospheric temperature, atmospheric pressure, fuel pressure, fuel temperature, and the volume ratio of the main components of the combustion operation of the fuel acquired by the measurement data acquisition unit 101. Then, a correction efficiency parameter (correction quality parameter) indicating the plant efficiency of the gas turbine 500 in the reference situation which is the reference operation situation is calculated.

The correction efficiency collection unit 104 sets the correction efficiency parameter calculated by the correction efficiency calculation unit 103 according to the operation state (rated operation state / intermediate load state) of the gas turbine 500 or the rated operation efficiency storage unit 105-1 or the intermediate load. It records in the efficiency memory | storage part 105-2.
The rated operation efficiency storage unit 105-1 stores the correction efficiency parameter calculated by the correction efficiency calculation unit 103 during the rated operation of the gas turbine 500.
The intermediate load efficiency storage unit 105-2 stores the correction efficiency parameter calculated by the correction efficiency calculation unit 103 during the intermediate load of the gas turbine 500.

The efficiency comparison unit 106 acquires a plurality of correction efficiency parameters from the rated operation efficiency storage unit 105-1 or the intermediate load efficiency storage unit 105-2, and calculates a confidence interval of the correction efficiency parameter at the time of rated operation or intermediate load. . The confidence interval is information that stochastically indicates a range in which a population exists, and for example, indicates a range in which the population average of the correction efficiency parameter is included with a probability of 95%.
Further, the efficiency comparison unit 106 determines whether or not the correction efficiency parameter calculated by the correction efficiency calculation unit 103 exists within the calculated confidence interval.
The display unit 107 calculates the correction efficiency parameter stored in the rated operation efficiency storage unit 105-1 or the intermediate load efficiency storage unit 105-2, the correction efficiency parameter calculated by the correction efficiency calculation unit 103, and the efficiency comparison unit 106. Display confidence intervals on the screen.

  When the plant monitoring apparatus 100 has the above-described configuration, the measurement data acquisition unit 101 acquires measurement data required for calculation of plant efficiency in the current operation state of the gas turbine 500 from the gas turbine 500. The measurement data acquisition unit 101 is measurement data different from the measurement data used for calculating the plant efficiency, and is at least one measurement data that affects the value of the efficiency parameter in accordance with a change in the operating state of the gas turbine 500. The atmospheric temperature, atmospheric pressure, fuel pressure, fuel temperature, and volume ratio of the main components of the combustion operation of the fuel, which are influence data, are acquired from the gas turbine 500.

Next, the efficiency calculation unit 102 generates an efficiency parameter by substituting the measurement data acquired by the measurement data acquisition unit 101 into a plant efficiency calculation formula represented by measurement data obtained in advance. Next, the correction efficiency calculation unit 103 uses the efficiency parameter generated by the efficiency calculation unit 102 and the influence data acquired by the measurement data acquisition unit 101 to use the plant efficiency of the gas turbine in the reference situation that is the reference operating situation. A correction efficiency parameter indicating is generated. Then, the correction efficiency collection unit 104 collects correction efficiency parameters and forms a correction efficiency group by repeatedly executing the processing by the measurement data acquisition unit 101, the efficiency calculation unit 102, and the correction efficiency calculation unit 103.
Thereby, the diagnostician can diagnose the function of the plant easily and accurately.

Hereinafter, the operation of the plant monitoring apparatus 100 according to the first embodiment will be described.
First, an operation when the plant monitoring apparatus 100 collects a correction efficiency parameter indicating the plant efficiency of the gas turbine 500 and records it in the rated operation efficiency storage unit 105-1 or the intermediate load efficiency storage unit 105-2 will be described.
FIG. 3 is a first flowchart showing the operation of the plant monitoring apparatus according to the first embodiment.
When the plant monitoring apparatus 100 is activated, the measurement data acquisition unit 101 acquires measurement data from the various sensors 401 to 404 installed in the gas turbine 500 (step S1). Specifically, the measurement data acquisition unit 101 acquires measurement data indicating the atmospheric temperature and atmospheric pressure from the atmospheric temperature / pressure sensor 401. The measurement data acquisition unit 101 acquires measurement data indicating fuel pressure, fuel temperature, and fuel flow rate from the fuel pressure / temperature / flow rate sensor 402. In addition, the measurement data acquisition unit 101 acquires measurement data indicating the volume ratio of the main component of the combustion operation in the fuel from the fuel composition measurement device 403. Then, the fuel composition measuring device 403 calculates the heat generation amount of the fuel from the measurement data indicating the volume ratio of the main component of the combustion operation in the fuel. Further, the measurement data acquisition unit 101 acquires measurement data indicating the output power amount of the gas turbine 500 from the wattmeter 404.

Then, the measurement data acquisition unit 101 calculates the fuel flow rate and output power amount, which are measurement data required for calculating the plant efficiency of the gas turbine 500 in the current operation state, and the calculated heat generation amount of the fuel among the acquired measurement data. The result is output to the efficiency calculation unit 102.
In addition, the measurement data acquisition unit 101 includes, among the acquired measurement data, atmospheric temperature, atmospheric pressure, fuel pressure, which is measurement data (influence data) that affects plant efficiency in accordance with changes in the operating status of the gas turbine 500. The fuel temperature and the volume ratio of the main components of the combustion operation of the fuel are output to the correction efficiency calculation unit 103.

  Next, the efficiency calculation unit 102 calculates the following equation (1) using the fuel flow rate, the output power amount, and the heat generation amount of the fuel input from the measurement data acquisition unit 101 (step S2), and the calculated plant An efficiency parameter indicating the efficiency η is output to the correction efficiency calculation unit 103.

However, (eta) shows the plant efficiency in the present operating condition of the gas turbine 500. FIG. _WG represents the amount of output power. _FF represents the fuel flow rate. Further, W _F indicates the amount of heat generated per unit mass of fuel. Incidentally, the heating value W _F per unit mass of fuel, the measurement data obtaining unit 101, in which is calculated from the measured data that indicates the volume ratio of the combustion operation main components in the fuel.
Note that the plant efficiency eta, the output power amount _{W G,} the fuel flow rate _{F F,} in addition to the heating value _{W F} per unit mass, the air temperature _{x 1,} atmospheric pressure _{x 2,} the fuel pressure _{x 3,} fuel temperature _x 4, Since it varies depending on various influencing factors such as the volume ratio x _{5 of the} main component of the combustion operation of the fuel, it can be expressed as a function shown in equation (2).

Next, the corrected efficiency calculation unit 103 is the atmospheric temperature x ₁ , atmospheric pressure x ₂ , fuel pressure x ₃ , and fuel temperature that are the efficiency parameters input from the efficiency calculation unit 102 and the influence data input from the measurement data acquisition unit 101. A corrected efficiency parameter indicating the plant efficiency of the gas turbine 500 in the reference situation, which is the reference operating situation, using the following equation (3) using x ₄ and the volume ratio x _{5 of the} fuel combustion operation main component: The calculated correction efficiency parameter η _n is output to the correction efficiency collection unit 104 (step S3).

However, x _i represents the value of the impact data input from the measurement data obtaining unit 101. Moreover, ∂f / ∂x _i shows effects data input from the measurement data obtaining unit 101 is a sensitivity indicating the degree of influence on the plant efficiency. Incidentally, the sensitivity ∂f / ∂x _i is previously determined by the design specification or experiments, are stored in the internal memory of the measurement data obtaining unit 101. Δx _i indicates the difference between the influence data input from the measurement data acquisition unit 101 and the value of the influence factor in the reference situation.

  That is, the correction efficiency calculation unit 103 calculates the difference between the influence data input from the measurement data acquisition unit 101 and the value of the influence factor in the reference situation, calculates the influence value obtained by multiplying the difference by sensitivity, and the efficiency calculation unit The corrected efficiency parameter is calculated by adding the calculated influence value to the plant efficiency indicated by the efficiency parameter input from 102.

  When the correction efficiency calculation unit 103 calculates the correction efficiency parameter in step S3, the correction efficiency collection unit 104 determines whether the operation state of the gas turbine 500 is a rated operation state or an intermediate load state (step S4). The determination of the operating state of the gas turbine 500 may be performed as follows, for example.

(1) Determination by Input from Operator The plant monitoring apparatus 100 further includes an input unit (not shown) and an operation state storage unit (not shown). When an operator who operates the gas turbine 500 performs an operation of shifting the operation of the gas turbine 500 to the intermediate load state, information indicating that the operation state is the intermediate load state is input to the input unit of the plant monitoring apparatus 100. input. Next, the input unit records information indicating an intermediate load state in the operation state storage unit. Further, when the operation of the gas turbine 500 transitions to the rated operation, the operator inputs information indicating that the operation state is the rated operation state to the input unit of the plant monitoring apparatus 100. Then, the correction efficiency collection unit 104 determines the operation state by determining whether the operation state stored in the operation state storage unit indicates the rated operation state or the intermediate load state.

(2) Determination Based on Measurement Data The measurement data acquisition unit 101 acquires measurement data indicating the opening degree of a valve provided in the gas turbine 500, ON / OFF of a switch, and exhaust gas temperature. Then, the correction efficiency collection unit 104 inputs the measurement data, whether the opening degree of the valve is equal to or greater than a predetermined threshold, whether the predetermined switch is ON, whether the exhaust gas temperature is a predetermined threshold It is determined whether or not this is the case, and the operating state is determined from these combinations.
Various other methods are conceivable as a method for determining the operating state of the gas turbine 500, but the method is not limited to this, and it is preferable to use a method suitable for each plant.

When the correction efficiency collection unit 104 determines that the operation state of the gas turbine 500 is the rated operation state by the method described above (step S4: rated operation), the correction input from the correction efficiency calculation unit 103 in step S3. The efficiency parameter is recorded in the rated operation efficiency storage unit 105-1 (step S5).
On the other hand, when the correction efficiency collection unit 104 determines that the operation state of the gas turbine 500 is an intermediate load state (step S4: intermediate load), the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S3 is the intermediate load. It records in the efficiency memory | storage part 105-2 (step S6).
The plant monitoring apparatus 100 accumulates the correction efficiency parameters in the rated operation efficiency storage unit 105-1 and the intermediate load efficiency storage unit 105-2 by repeatedly executing the above-described processing, and forms a correction efficiency parameter group.

Next, the operation when the diagnostician diagnoses the function of the gas turbine 500 using the plant monitoring device 100 will be described.
FIG. 4 is a second flowchart showing the operation of the plant monitoring apparatus according to the first embodiment.
When the diagnostician starts a comparison process between the current state and the past state of the function of the gas turbine 500 by, for example, pressing a state comparison button (not shown) of the plant monitoring apparatus 100, the measurement data acquisition unit 101 Then, measurement data is acquired from the various sensors 401 to 404 installed in the gas turbine 500, and the calorific value of the fuel is calculated (step S11). Then, the measurement data acquisition unit 101 outputs the fuel flow rate, the output power amount, and the heat generation amount of the fuel to the efficiency calculation unit 102, and the atmospheric temperature, the atmospheric pressure, the fuel pressure, the fuel temperature, and the fuel combustion operation as influence data The volume ratio of the main component is output to the correction efficiency calculation unit 103.

  Next, the efficiency calculation unit 102 calculates the plant efficiency in the current operation state of the gas turbine 500 by the equation (1) using the fuel flow rate, the output power amount, and the heat generation amount of the fuel input from the measurement data acquisition unit 101. (Step S12). Next, the correction efficiency calculation unit 103 uses the efficiency parameter input from the efficiency calculation unit 102 and the influence data input from the measurement data acquisition unit 101 to calculate the correction efficiency parameter using Equation (3) (step S13). ), And outputs the correction efficiency parameter to the efficiency comparison unit 106.

When the correction efficiency calculation unit 103 calculates the correction efficiency parameter, the efficiency comparison unit 106 determines whether the operation state of the gas turbine 500 is a rated operation state or an intermediate load state (step S14). Note that the operation state determination by the efficiency comparison unit 106 may use the same method as the operation state determination by the correction efficiency collection unit 104 described above.
When the efficiency comparison unit 106 determines that the operation state of the gas turbine 500 is the rated operation state (step S14: rated operation), the efficiency comparison unit 106 reads a correction efficiency parameter group from the rated operation efficiency storage unit 105-1 (step S15).
On the other hand, when the efficiency comparison unit 106 determines that the operation state of the gas turbine 500 is an intermediate load state (step S14: intermediate load), the efficiency comparison unit 106 reads a correction efficiency parameter group from the intermediate load efficiency storage unit 105-2 (step S16). ).

  Next, the efficiency comparison unit 106 calculates a confidence interval of the correction specific data group from the correction efficiency parameter group read in step S15 or step S16 (step S17). The confidence interval can be obtained using Equation (4) shown below.

However, I _max indicates the upper limit of the confidence interval. I _min indicates the lower limit of the confidence interval. Moreover, a shows the average value of the plant efficiency in a correction | amendment efficiency parameter. Further, t represents a numerical value at which the area of the distribution determined in the confidence interval is a predetermined ratio (for example, 95%) with respect to the total number of correction efficiency parameters. Note that t can be obtained in advance from a normal distribution table (1.96 if 95%). SE represents the standard error of the correction efficiency parameter group.

  When the efficiency comparison unit 106 calculates the confidence interval, the efficiency comparison unit 106 determines whether the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S13 is included in the calculated confidence interval. Is determined (step S18). Then, the efficiency comparison unit 106, the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S13, the correction efficiency parameter group read in step S15 or step S16, the confidence interval calculated in step S17, and the determination result in step S18 Is displayed on the display unit 107 (step S19).

FIG. 5 is a diagram illustrating an example of information displayed on the display unit.
As shown in FIG. 5, the display unit 107 displays the corrected efficiency parameter input from the corrected efficiency calculating unit 103 in step S13 and the corrected efficiency parameter group read out in step S15 or step S16 as the fuel composition and the plant efficiency. Display in different colors on the graph showing the relationship. The display unit 107 displays the confidence interval calculated in step S17 on a graph showing the relationship between the fuel composition and the plant efficiency. When the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S13 is within the confidence interval, the display unit 107 displays “no abnormality” as the determination result, and in step S13, the correction efficiency calculation unit 103 If the correction efficiency parameter input from the above does not exist within the confidence interval, “abnormal” is displayed as the determination result.

  Thus, according to the first embodiment, the diagnostician compares the normalized current plant efficiency displayed on the display unit 107 with the normalized past plant efficiency, and further performs plant monitoring. By referring to the determination result by the apparatus 100, the function of the plant can be diagnosed. Thereby, the diagnostician can diagnose the function of the plant easily and accurately.

(Second Embodiment)
Hereinafter, the plant monitoring apparatus 110 according to the second embodiment will be described. The plant monitoring apparatus 110 according to the second embodiment estimates the degree of deterioration of the gas turbine 500 and the operation time until maintenance.
FIG. 6 is a schematic block diagram illustrating the configuration of the plant monitoring apparatus according to the second embodiment.
The plant monitoring apparatus 110 further includes an indicator deterioration comparison unit 201 in addition to the plant monitoring apparatus 100 according to the first embodiment.
The index deterioration comparison unit 201 derives a function indicating the relationship between the operation time of the gas turbine 500 and the correction efficiency parameter from the correction efficiency parameter group stored in the rated operation efficiency storage unit 105-1, and the degree of deterioration of the gas turbine 500. Estimate operating time until maintenance.

When the plant monitoring apparatus 110 according to the second embodiment collects the correction efficiency parameter indicating the plant efficiency of the gas turbine 500 and records it in the rated operation efficiency storage unit 105-1 or the intermediate load efficiency storage unit 105-2. Is the same as that of the plant monitoring apparatus 100 according to the first embodiment.
The operation when the diagnostician diagnoses the function of the gas turbine 500 using the plant monitoring device 110 is the same as that of the plant monitoring device 100 according to the first embodiment.

Next, an operation in which the plant monitoring apparatus 110 estimates the degree of deterioration of the gas turbine 500 using the correction efficiency parameter stored in the rated operation efficiency storage unit 105-1 will be described.
FIG. 7 is a flowchart showing the operation of the plant monitoring apparatus according to the second embodiment.
FIG. 8 is a first diagram illustrating an operation of estimating the degree of deterioration of the gas turbine.
When the diagnostician starts a deterioration estimation process of the gas turbine 500 by pressing a deterioration estimation button (not shown) of the plant monitoring device 110, for example, the index deterioration comparison unit 201 is changed from the rated operation efficiency storage unit 105-1. A correction efficiency parameter group is read (step S21).

  Next, the index deterioration comparison unit 201 performs a curve fitting process on the read correction efficiency parameter group, and derives a function indicating the plant efficiency transition performance of the gas turbine 500 as shown in FIG. 8 (step S22). . As an execution method of the curve fitting process, for example, there is a method in which the index deterioration comparison unit 201 estimates an optimum function by a least square method using a correction efficiency parameter group as an objective variable and an operation time as an explanatory variable. However, the execution method of the curve fitting process is not limited to the least square method, and the explanatory variable is not limited to the operation time.

Next, the indicator deterioration comparison unit 201 differentiates the function derived in step S22, and derives a tangential function with a point indicating the plant efficiency at the current time as a contact point as shown in FIG. 8 (step S23). Next, the index deterioration comparison unit 201 calculates an operation time at which the plant efficiency of the gas turbine 500 becomes a predetermined efficiency deterioration limit value from the function derived in step S23, and the operation time and the current operation time are calculated. By calculating the difference, the operation time until the maintenance of the gas turbine 500 is estimated (step S24).
Then, the indicator deterioration comparison unit 201 causes the display unit 107 to display the estimated operation time until maintenance (step S25).

  Thus, according to the present embodiment, the plant monitoring apparatus 110 estimates and displays the degree of deterioration of plant efficiency due to deterioration with time of the gas turbine 500 from the rated operation efficiency storage unit 105-1. Thus, the diagnostician can easily and accurately evaluate the deterioration of the plant.

(Third embodiment)
Hereinafter, the plant monitoring apparatus 120 according to the third embodiment will be described. The plant monitoring apparatus 120 according to the third embodiment estimates the degree of deterioration of the gas turbine 500 and the operating time until maintenance, as in the second embodiment.
FIG. 9 is a schematic block diagram illustrating a configuration of a plant monitoring apparatus according to the third embodiment.
The plant monitoring device 120 further includes an indicator deterioration model storage unit 202 in addition to the plant monitoring device 110 according to the second embodiment. Further, the operation of the indicator deterioration comparison unit 201 is different from that of the second embodiment.

The indicator deterioration model storage unit 202 stores an indicator deterioration function that is an indicator of the degree of deterioration. The index deterioration function is a function indicating the relationship between the plant operation time and the correction efficiency parameter, which is derived from the operation history from a plant of the same standard and format as the plant to be monitored.
The index deterioration comparison unit 201 receives the correction efficiency parameter from the correction efficiency calculation unit 103 and uses the index deterioration function stored in the index deterioration model storage unit 202 to determine the degree of deterioration of the gas turbine 500 and the operation time until maintenance. presume.

When the plant monitoring apparatus 120 according to the third embodiment collects the correction efficiency parameter indicating the plant efficiency of the gas turbine 500 and records it in the rated operation efficiency storage unit 105-1 or the intermediate load efficiency storage unit 105-2. Is the same as that of the plant monitoring apparatus 100 according to the first embodiment.
The operation when the diagnostician diagnoses the function of the gas turbine 500 using the plant monitoring device 120 is the same as that of the plant monitoring device 100 according to the first embodiment.

Next, an operation in which the plant monitoring apparatus 120 estimates the degree of deterioration of the gas turbine 500 using the index deterioration function stored in the index deterioration model storage unit 202 will be described.
FIG. 10 is a flowchart showing the operation of the plant monitoring apparatus according to the third embodiment.
FIG. 11 is a second diagram illustrating an operation for estimating the degree of deterioration of the gas turbine.
When the diagnostician starts the deterioration estimation process of the gas turbine 500 by pressing a deterioration estimation button (not shown) of the plant monitoring device 120, for example, the measurement data acquisition unit 101 includes various sensors installed in the gas turbine 500. Measurement data is acquired from 401 to 404 (step S31). Then, the measurement data acquisition unit 101 outputs the fuel flow rate, the output power amount, and the heat generation amount of the fuel to the efficiency calculation unit 102, and the atmospheric temperature, the atmospheric pressure, the fuel pressure, the fuel temperature, and the fuel combustion operation as influence data The volume ratio of the main component is output to the correction efficiency calculation unit 103.

  Next, the efficiency calculation unit 102 calculates the plant efficiency in the current operation state of the gas turbine 500 by the equation (1) using the fuel flow rate, the output power amount, and the heat generation amount of the fuel input from the measurement data acquisition unit 101. (Step S32). Next, the correction efficiency calculation unit 103 uses the efficiency parameter input from the efficiency calculation unit 102 and the influence data input from the measurement data acquisition unit 101 to calculate the correction efficiency parameter using Equation (3) (step S33). ), And outputs the correction efficiency parameter to the indicator deterioration comparison unit 201.

Next, the index degradation comparison unit 201 reads the index degradation function as shown in FIG. 11 from the index degradation model storage unit 202, and has the same value as the plant efficiency indicated by the correction efficiency parameter input from the correction efficiency calculation unit 103. The operating time is calculated (step S34). Next, the indicator deterioration comparison unit 201 calculates an operation time in which the plant efficiency becomes a predetermined efficiency deterioration limit value in the indicator deterioration function (step S35). Then, the correction efficiency calculation unit 103 calculates the difference between the operation time calculated in step S34 and the operation time calculated in step S35, and estimates the time of the difference as the operation time until the maintenance of the gas turbine 500 ( Step S36).
Then, the indicator deterioration comparison unit 201 causes the display unit 107 to display the estimated operating time until maintenance (step S37).

  As described above, according to the present embodiment, the plant monitoring apparatus 120 estimates and displays the degree of deterioration of plant efficiency due to deterioration with time of the gas turbine 500 using the index deterioration function stored in the index deterioration model storage unit 202. To do. Thus, the diagnostician can easily and accurately evaluate the deterioration of the plant.

(Fourth embodiment)
Hereinafter, the plant monitoring apparatus 130 according to the fourth embodiment will be described. Unlike the first embodiment, the plant monitoring apparatus 130 according to the fourth embodiment monitors a plant for each segment of the intermediate load state. As the classification of the intermediate load state, for example, a startup operation state until the operation of the plant shifts from the operation stop to the rated operation, a stop operation state until the operation of the plant shifts from the rated operation to the operation stop, and the like.

Here, the reason why the plant is monitored for each intermediate load state is described.
At an intermediate load from the stop to the rated operation and from the rated operation to the stop, various operations for operation control are frequently performed on the plant as compared with the rated operation. On the other hand, these various operations are generally performed in an automatic sequence. Therefore, compared with the time of rated operation, plant efficiency changes with the elapsed time from the time which changed to the intermediate load state. Moreover, such a change in plant efficiency differs for each intermediate load state category. Therefore, at the time of intermediate load, it is effective to monitor the plant efficiency in association with the elapsed time from the start time for each category of the intermediate load state.

FIG. 12 is a schematic block diagram illustrating a configuration of a plant monitoring apparatus according to the fourth embodiment.
The plant monitoring device 130 according to the fourth embodiment stores a startup operation efficiency memory instead of the rated operation efficiency storage unit 105-1 and the intermediate load efficiency storage unit 105-2 in the plant monitoring device 130 according to the first embodiment. Unit 105-3 and stop operation efficiency storage unit 105-4.
Further, the operations of the correction efficiency collection unit 104 and the efficiency comparison unit 106 are different from those of the plant monitoring apparatus 100 according to the first embodiment.

The correction efficiency collection unit 104 sets the correction efficiency parameter calculated by the correction efficiency calculation unit 103 in accordance with the intermediate load state classification (starting operation state / stopping operation state) of the gas turbine 500. Alternatively, it is recorded in the stop operation efficiency storage unit 105-4.
The startup operation efficiency storage unit 105-3 stores the correction efficiency parameter calculated by the correction efficiency calculation unit 103 during the startup operation of the gas turbine 500.
The stop operation efficiency storage unit 105-4 stores the correction efficiency parameter calculated by the correction efficiency calculation unit 103 during the stop operation of the gas turbine 500.
The efficiency comparison unit 106 acquires a plurality of correction efficiency parameters from the startup operation efficiency storage unit 105-3 or the stop operation efficiency storage unit 105-4, and calculates a confidence interval of the correction efficiency parameter in the intermediate load state.

  When the plant monitoring apparatus 130 according to the fourth embodiment collects the correction efficiency parameter indicating the plant efficiency of the gas turbine 500 and records it in the startup operation efficiency storage unit 105-3 or the stop operation efficiency storage unit 105-4. Is the same as that of the plant monitoring apparatus 100 according to the first embodiment.

Hereinafter, the operation of the plant monitoring apparatus 130 according to the fourth embodiment will be described.
First, an operation when the plant monitoring apparatus 130 collects a correction efficiency parameter indicating the plant efficiency of the gas turbine 500 and records it in the startup operation efficiency storage unit 105-3 or the stop operation efficiency storage unit 105-4 will be described.

FIG. 13 is a first flowchart showing the operation of the plant monitoring apparatus according to the fourth embodiment.
When the plant monitoring apparatus 130 is activated, the measurement data acquisition unit 101 acquires measurement data from the various sensors 401 to 404 installed in the gas turbine 500 (step S41). Then, the measurement data acquisition unit 101 calculates the fuel flow rate, the output power amount, and the heat generation amount of the fuel, which are measurement data required for calculating the plant efficiency of the gas turbine 500 in the current operation state, among the acquired measurement data. To 102. Further, the measurement data acquisition unit 101 outputs the atmospheric temperature, atmospheric pressure, fuel pressure, fuel temperature, and volume ratio of the main components of the combustion operation of the fuel among the acquired measurement data to the correction efficiency calculation unit 103. To do.

  Next, the efficiency calculation unit 102 uses the fuel flow rate, the output power amount, and the heat generation amount of the fuel input from the measurement data acquisition unit 101 to calculate the equation (1) (step S42), and calculates the calculated plant efficiency η. The efficiency parameter shown is output to the correction efficiency calculation unit 103.

  Next, the correction efficiency calculation unit 103 is the atmospheric temperature, atmospheric pressure, fuel pressure, fuel temperature, and fuel combustion operation, which are the efficiency parameters input from the efficiency calculation unit 102 and the influence data input from the measurement data acquisition unit 101 Using the volume ratio of the main components, a correction efficiency parameter indicating the plant efficiency of the gas turbine 500 in the reference situation, which is the reference operation situation, is calculated by the equation (3) (step S43), and the calculated correction efficiency parameter is calculated. Output to the correction efficiency collection unit 104.

Next, when the operation state of the gas turbine 500 is an intermediate load state, the correction efficiency collection unit 104 determines whether the classification is a start operation state or a stop operation state (step S44). This determination is performed using the same method as the determination of the operation state in the first embodiment.
When the correction efficiency collection unit 104 determines that the intermediate load state of the gas turbine 500 is the startup operation state (step S44: startup operation), the correction efficiency collection unit 104 starts the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S3. It records in the operation efficiency memory | storage part 105-3 (step S45).
On the other hand, when the correction efficiency collection unit 104 determines that the intermediate load state of the gas turbine 500 is the stop operation state (step S44: stop operation), the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S3. Is recorded in the stop operation efficiency storage unit 105-4 (step S46).
The plant monitoring apparatus 130 repeatedly executes the above-described processing, thereby accumulating the correction efficiency parameters in the startup operation efficiency storage unit 105-3 and the stop operation efficiency storage unit 105-4, thereby forming a correction efficiency parameter group.

Next, an operation when the diagnostician diagnoses the function of the gas turbine 500 using the plant monitoring device 130 will be described.
FIG. 14 is a second flowchart showing the operation of the plant monitoring apparatus according to the fourth embodiment.
When the diagnostician starts a comparison process between the current state and the past state of the function of the gas turbine 500 by pressing a state comparison button (not shown) of the plant monitoring device 130, for example, the measurement data acquisition unit 101 Measurement data is acquired from the various sensors 401 to 404 installed in the gas turbine 500 (step S51). Then, the measurement data acquisition unit 101 outputs the fuel flow rate, the output power amount, and the heat generation amount of the fuel to the efficiency calculation unit 102, and the atmospheric temperature, the atmospheric pressure, the fuel pressure, the fuel temperature, and the fuel combustion operation as influence data The volume ratio of the main component is output to the correction efficiency calculation unit 103.

  Next, the efficiency calculation unit 102 calculates the plant efficiency in the current operation state of the gas turbine 500 by the equation (1) using the fuel flow rate, the output power amount, and the heat generation amount of the fuel input from the measurement data acquisition unit 101. (Step S52). Next, the correction efficiency calculation unit 103 uses the efficiency parameter input from the efficiency calculation unit 102 and the influence data input from the measurement data acquisition unit 101 to calculate the correction efficiency parameter using equation (3) (step S53). ), And outputs the correction efficiency parameter to the efficiency comparison unit 106.

When the correction efficiency calculation unit 103 calculates the correction efficiency parameter, the efficiency comparison unit 106 determines whether the classification is the start operation state or the stop operation state when the operation state of the gas turbine 500 is an intermediate load state. (Step S54). The determination of the intermediate load state classification by the efficiency comparison unit 106 may use the same method as the determination of the intermediate load state classification by the correction efficiency collection unit 104 described above.
When the efficiency comparison unit 106 determines that the intermediate load state of the gas turbine 500 is the start-up operation state (step S54: start-up operation), the efficiency comparison parameter near the current load from the start-up operation efficiency storage unit 105-3. A group is read out (step S55).
On the other hand, when the efficiency comparison unit 106 determines that the intermediate load state of the gas turbine 500 is the stop operation state (step S54: stop operation), the efficiency comparison unit 106-4 corrects the vicinity of the current load from the stop operation efficiency storage unit 105-4. An efficiency parameter group is read (step S56).

  Next, the efficiency comparison unit 106 calculates a confidence interval of the correction specific data group from the correction efficiency parameter group read in step S55 or step S56 (step S57). The calculation of the confidence interval can be obtained using Equation (4).

  When the efficiency comparison unit 106 calculates the confidence interval, the efficiency comparison unit 106 determines whether or not the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S53 is included in the calculated confidence interval. Is determined (step S58). Then, the efficiency comparison unit 106, the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S53, the correction efficiency parameter group read in step S55 or step S56, the confidence interval calculated in step S57, and the determination result in step S18 Is displayed on the display unit 107 (step S59).

FIG. 15 is a diagram illustrating an example of information displayed on the display unit. FIG. 15 shows an example of a graph showing the transition of plant efficiency during start-up operation.
As shown in FIG. 15, the display unit 107 displays the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S53 and the correction efficiency parameter group read in step S55 or step S56 at the start time (in the intermediate load state). It is displayed in a different color on a graph showing the relationship between the elapsed time from the transition time) and the plant efficiency. The display unit 107 displays the confidence interval calculated in step S57 on a graph indicating the relationship between the fuel composition and the plant efficiency. When the correction efficiency parameter input from the correction efficiency calculation unit 103 in step S53 is within the confidence interval, the display unit 107 displays “no abnormality” as the determination result, and in step S53, the correction efficiency calculation unit 103 If the correction efficiency parameter input from the above does not exist within the confidence interval, “abnormal” is displayed as the determination result.

  As described above, according to the fourth embodiment, the diagnostician can display the current plant efficiency and the past plant normalized on the display unit 107 and normalized separately for each category at the time of intermediate load. The efficiency can be compared. Therefore, the diagnostician can monitor the plant efficiency without considering the difference in the operating state, and can easily and accurately diagnose the plant function. Thereby, for example, when the monitoring target is a gas turbine as in the present embodiment, the diagnostician can make an execution plan such as blade cleaning more accurately.

As described above, the embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to that described above, and various design changes and the like can be made without departing from the scope of the present invention. It is possible to
For example, in the first embodiment and the fourth embodiment, the case where the efficiency comparison unit 106 determines the presence or absence of an abnormality has been described in step S18 (step S58). However, the present invention is not limited to this. For example, a plant monitoring device 100 does not determine whether there is an abnormality, and the diagnostician compares the normalized current plant efficiency displayed on the display unit 107 with the normalized past plant efficiency, whereby the abnormality of the gas turbine 500 is detected. You may determine the presence or absence of.

  Moreover, although this embodiment demonstrated the case where the plant monitoring apparatus 100,110,120,130 performed monitoring of the plant efficiency which is one of the quality parameters of the gas turbine 500, it is not restricted to this, For example, compression Other quality parameters such as machine efficiency and turbine efficiency may be monitored.

  In this embodiment, the gas turbine is used as an example of the plant equipment to be monitored. However, the present invention is not limited to this, and the present invention is also used for monitoring other equipment such as a nuclear fusion reactor of a nuclear power plant. The plant monitoring device according to the invention can be used.

  Further, in the second embodiment, the operation time until maintenance is estimated using the efficiency transition record of the target plant, and in the third embodiment, the operation time until maintenance is estimated using the efficiency deterioration function. However, the present invention is not limited to this, and the operation time until maintenance may be estimated using another method.

  Further, in the second embodiment and the third embodiment, the case where the actual operation time is used as the operation time has been described. However, the present invention is not limited to this, and stress on the blades due to start / stop, trip, load fluctuation, etc. The estimation and display may be performed using the converted operation time (equivalent operation time) in consideration of the above.

  In the first, second, and third embodiments, one intermediate load storage device 105-1 is used. However, a high load except a low rated operation load to a low load is divided into a plurality of sections. An intermediate load storage device 105-1 may be provided.

  In the first, second, third and fourth embodiments, the measurement data acquisition unit 101 acquires the measurement data indicating the fuel flow rate from the fuel pressure / temperature / flow rate sensor 402, but from the fuel adjustment valve 506. Measurement data indicating valve opening, measurement data indicating fuel pressure from the fuel pressure / temperature / flow rate sensor 402, and measurement data indicating fuel pressure from a pressure sensor (not shown) installed downstream of the fuel adjustment valve 506 are used. May be calculated.

  In step S23 of the second embodiment, a case has been described in which a tangential function is derived and the operation time until maintenance is estimated using the function. However, the present invention is not limited to this. The operation time until maintenance may be estimated by approximating with a simple function.

  Y represents the plant efficiency of the gas turbine 500. X indicates the operating time of the gas turbine 500. In step S23, the indicator deterioration comparison unit 201 substitutes appropriate coefficients for a, b, and c, creates a function that approximates the efficiency transition, and estimates the operation time until maintenance using the function. To do.

  The above plant monitoring apparatus has a computer system inside. The operation of each processing unit described above is stored in a computer-readable recording medium in the form of a program, and the above processing is performed by the computer reading and executing this program. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.

  The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

  DESCRIPTION OF SYMBOLS 100, 110, 120, 130 ... Plant monitoring apparatus 101 ... Measurement data acquisition part 102 ... Efficiency calculation part 103 ... Correction efficiency calculation part 104 ... Correction efficiency collection part 105-1 ... Rated operation efficiency memory | storage part 105-2 ... Intermediate load efficiency Storage unit 105-3 ... Starting operation efficiency storage unit 105-4 ... Stop operation efficiency storage unit 106 ... Efficiency comparison unit 107 ... Display unit 201 ... Index degradation comparison unit 202 ... Index degradation model storage unit 401 ... Atmospheric temperature / pressure sensor 402 ... fuel pressure / temperature / flow rate sensor 403 ... fuel composition measuring device 404 ... wattmeter 500 ... gas turbine 501 ... compressor 502 ... combustor 503 ... turbine 504 ... rotor 505 ... generator 506 ... fuel adjustment valve

Claims (7)

A method for diagnosing plant function,
Measurement data required to calculate a quality parameter indicating the quality of the plant in the current operating state is acquired from the plant, and the acquired measurement data is added to the quality parameter calculation formula represented by the measurement data obtained in advance. Substituting and calculating the quality parameter,
The quality data calculated in the first step and the measurement data different from the measurement data, which are at least one measurement data that influences the value of the quality parameter according to a change in the operation status of the plant A second step of calculating a corrected quality parameter indicating the quality of the plant in a reference situation which is a reference operation situation,
A third step of collecting the correction quality parameters by repeatedly executing the first step and the second step to form a correction quality parameter group;
A method for diagnosing a plant function, comprising: a fourth step of diagnosing the function of the plant using the correction quality parameter group formed in the third step and the latest correction quality parameter. The second step includes
A first sub-step of calculating a difference between the influence data and the influence data in the reference situation;
A second sub-step of calculating an influence value obtained by multiplying the difference calculated in the first sub-step by a sensitivity indicating a degree of influence of the influence data on the quality parameter;
And a third sub-step of calculating the correction quality parameter by adding the influence value calculated in the second sub-step to the quality parameter obtained in the first step. The method of diagnosing the function of the plant described in 2. In the third step, the correction quality parameter is associated with the operation state of the plant at the time of the correction quality parameter calculation, and a correction quality parameter group is formed for each operation state of the plant,
In the fourth step,
The function of the plant is diagnosed using a correction quality parameter group associated with the operation state of the plant when the latest correction data is calculated and the latest correction quality parameter. Item 3. A method for diagnosing the function of the plant according to Item 2. In the fourth step,
A confidence interval of the correction quality parameter group is calculated from the correction quality parameter group formed in the third step, and it is determined whether or not the latest correction quality parameter exists in the confidence interval. The method for diagnosing the function of the plant according to any one of claims 1 to 3, wherein presence or absence of abnormality is determined. In the fourth step,
The latest correction quality parameter and the correction quality parameter group formed in the third step are associated with each other in order of elapsed time from the time when the operation state of the plant transitions to the intermediate load state, and a confidence interval is calculated. The presence or absence of an abnormality of the plant is determined by determining whether or not a parameter exists within the confidence interval. The method according to any one of claims 1 to 3, characterized in that: Of diagnosing the functioning of a plant. In the fourth step,
4. The degree of deterioration of the plant is determined by associating the corrected quality parameter with the operation time of the plant and comparing the relationship between the quality parameter and time obtained in advance. The method of diagnosing the function of the plant of any one of these. A measurement data acquisition unit for acquiring measurement data required for calculation of a quality parameter indicating the quality in the current operation status of the plant from the plant;
A quality parameter calculation unit that calculates the quality parameter by substituting the acquired measurement data into the quality parameter calculation formula represented by the measurement data obtained in advance;
An influence data acquisition unit that acquires influence data that is measurement data different from the measurement data and that is influence data that is at least one measurement data that affects the value of the quality parameter in accordance with a change in the operation status of the plant;
Using the quality parameter calculated by the quality parameter calculation unit and the influence data acquired by the influence data acquisition unit, a correction quality for calculating a correction quality parameter indicating the quality of the plant in a reference situation that is a reference operation situation A parameter calculation unit;
Correction specification for collecting the correction quality parameters and forming a correction quality parameter group by repeatedly executing the processing by the measurement data acquisition unit, the quality parameter calculation unit, the influence data acquisition unit, and the correction quality parameter calculation unit A plant monitoring apparatus comprising: a data collection unit.

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