KR102231900B1 - Data measure system for performance verification test of marine large engine and method thereof - Google Patents

Abstract

Disclosed are a data measurement system and a method for commissioning a large ship engine.
The system sets a group for each sensor by grouping multiple types of sensors used for engine performance analysis according to the degree of measurement data variability, collects measurement data from sensors installed in the engine being tested, and identifies each group of sensors. Then, according to the determined group for each sensor, filtering for each of the measurement data collected from the sensors is selectively applied to compensate for measurement data deviation.
Accordingly, when a high measurement data deviation occurs due to severe vibration of various sensors attached to the engine, the reliability of engine performance analysis can be improved by reducing the data deviation.
Furthermore, it is possible to maximize the efficiency of data deviation reduction through selective data filtering in consideration of engine driving characteristics, combustion processes, and sensor installation locations.

Description

Data measurement system and method for trial operation of large ship engines {DATA MEASURE SYSTEM FOR PERFORMANCE VERIFICATION TEST OF MARINE LARGE ENGINE AND METHOD THEREOF}

The present invention relates to a data measurement system and a method for test operation of a large ship engine, and in particular, to a data measurement system and a method for testing a large ship engine to improve the reliability of engine performance analysis by reducing measurement data deviation. .

Referring to Patent Document 1, the data measurement system for commissioning large engines of ships collects data measured through various pressure sensors, temperature sensors, vibration sensors, etc. attached to large engines to be commissioned in an integrated database, and collects the collected data. Analyze and determine the engine's performance index.

When the measurement data collected from various sensors is to be used for engine performance analysis, the reliability of engine performance analysis can also be increased when the accuracy of the data measured by various sensors is high.

However, when the large engine of a ship is operated, since various sensors attached to the engine receive severe vibrations by themselves, a large deviation occurs in measurement data input from the corresponding sensors, which makes it impossible to accurately analyze engine performance.

Korean Patent Application Publication No. 10-2010-0116429

The present invention has been proposed to solve the problems of the prior art as described above, and its object is to reduce the data deviation when various sensors attached to the engine receive severe vibration and high measurement data deviation occurs, thereby reducing the reliability of engine performance analysis. It is intended to provide a data measurement system for commissioning large-sized ship engines that can improve the system.

In addition, it is intended to provide a data measurement system for large vessel engine commissioning that maximizes the efficiency of data deviation reduction through selective data filtering in consideration of engine driving characteristics, combustion processes, and sensor installation locations.

The technical problem to be achieved by the present invention is not limited to the technical problems mentioned above, and other technical problems that are not mentioned can be clearly understood by those of ordinary skill in the technical field to which the present invention belongs from the following description. There will be.

A data measurement system for commissioning a large ship engine according to the present invention for achieving the above object comprises: a setting unit for setting a group for each sensor by grouping a plurality of types of sensors used for engine performance analysis according to the degree of measurement data variability; A data collection unit that collects measurement data from sensors installed in the engine to be tested; A group determination unit for determining a group of each of the sensors; And a data deviation compensation unit that compensates for measurement data deviation by selectively applying filtering for each of the measurement data collected from the sensors according to each sensor-specific group determined by the group determination unit.

The data measurement system for commissioning a large ship engine according to the present invention may further include a display unit that collects filtered and unfiltered measurement data and displays them as engine performance data in real time.

In the data measurement system for commissioning a large ship engine according to the present invention, the data deviation compensation unit may perform data smoothing by applying a moving average filter.

On the other hand, the method of measuring data for a large ship engine test drive according to the present invention comprises the steps of: setting a group for each sensor by grouping a plurality of types of sensors used for engine performance analysis according to the degree of measurement data variability; Collecting measurement data from sensors installed in an engine in which the system is commissioned; Determining, by the system, a group of each of the sensors; And compensating for measurement data deviation by selectively applying, by the system, filtering for each of the measurement data collected from the sensors according to the determined group for each sensor.

In the data measurement method for trial operation of a large ship engine according to the present invention, each sensor group is classified into a high deviation group with high measurement data variability and a low deviation group with low measurement data variability, and selectively moves only to sensors of a high deviation group. Measurement data deviation can be compensated for by applying an average filter.

In the data measurement method for commissioning a large ship engine according to the present invention, sensors for measuring pressure data are classified into high deviation groups, but only some of the sensors for which high measurement data variability is predicted based on the installation position in the engine are selected and then analyzed. They can be classified into groups of deviations.

In the method of measuring data for trial operation of a large ship engine according to the present invention, sensors for measuring intake air pressure data and exhaust pressure data can be classified into high deviation groups.

In the method for measuring data for commissioning of a large ship engine according to the present invention, a sensor measuring fluid pressure including coolant, lubricating oil, and fuel and a sensor measuring temperature data can be classified into a low deviation group.

In the method of measuring data for trial operation of a large vessel engine according to the present invention, the high deviation group is subdivided into groups of multiple levels according to the degree of measurement data variability, and the number of moving average filters in the higher level group having high measurement data variability in the high deviation group Can be applied by increasing.

According to the data measurement system for commissioning a large ship engine according to the present invention, when high measurement data deviation occurs due to severe vibrations of various sensors attached to the engine, it is possible to improve the reliability of engine performance analysis by reducing the data deviation.

Further, according to the data measurement system for commissioning a large ship engine according to the present invention, it is possible to maximize the efficiency of data deviation reduction through selective data filtering in consideration of the driving characteristics of the engine, the combustion process, and the sensor installation location.

1 is a view schematically showing the configuration of a data measurement system for a large ship engine test drive according to an embodiment of the present invention.
2 is a diagram illustrating measurement data collected according to an exemplary embodiment of the present invention.
3 is a processing diagram for explaining a data measurement method for a large ship engine test drive according to an embodiment of the present invention.
4 is a diagram illustrating an exemplary data measurement screen provided according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings will be described in detail a data measurement system and method for a large ship engine trial operation according to a preferred embodiment of the present invention.

1 is a view schematically showing the configuration of a data measurement system for a large ship engine test drive according to an embodiment of the present invention.

In FIG. 1, a plurality of various sensors 10 are attached to each part of a large engine to be tested to measure various engine performance data necessary for engine performance analysis, such as pressure, temperature, vibration, and speed, and store the measurement data in a data collection unit ( 30).

For example, a plurality of pressure sensors (sensors A1 to An) and a plurality of temperature sensors (sensors B1 to Bm) distributed in various parts of the engine measure the pressure and temperature of each part of the engine and output it to the data collection unit 30 in real time. can do.

The data collection unit 30 collects measurement data in the form of an analog signal transmitted from various sensors 10, converts the received measurement data in the form of an analog signal to A/D (Analog to Digital), and then converts this measurement data. Is stored in the integrated database as engine performance data.

Various measurement data stored in the integrated database is used to determine the performance index of the engine.

At this time, when the performance of the large engine is analyzed based on the measurement data in which accuracy is inferior, the deviation of the measurement data inevitably caused by the vibrations received by the various sensors 10 attached to the engine is overlooked and the performance of the large engine is analyzed. The reliability of this is greatly reduced.

Accordingly, the data deviation compensation unit 50 compensates for the data deviation by applying filtering to some measurement data according to the degree of data variability before storing the measurement data collected by the data collection unit 30 in the integrated database.

As an example, the data deviation compensation unit 50 can significantly reduce the deviation by applying a moving average filter to the measured data from a specific sensor 10 and smoothing the data. Therefore, the accuracy and reliability of the performance analysis of large engines can be greatly improved.

However, in order to reduce data deviation, a simple application of extensive filtering on all types of sensors 10 and their measured data may reduce data processing speed or increase computational complexity, which may be rather inefficient.

Therefore, by implementing selective data filtering in consideration of engine driving characteristics, combustion process, sensor type, sensor number, sensor installation location, etc., the efficiency of reducing data deviation can be maximized.

To this end, a plurality of types of sensors 10 used for engine performance analysis are grouped according to the degree of measurement data variability to set a group for each sensor, and group information for each sensor is stored in the setting unit 20.

The group determination unit 40 determines a group of each of the plurality of sensors 10 outputting measurement data to the data collection unit 30.

For example, when a specific sensor 10 transmits measurement data to the data collection unit 30, the group determination unit 40 determines and sets the sensor 10 using sensor identification information such as sensor number or connection port information. It is possible to determine which group the sensor 10 determined by the unit 20 belongs to.

The data deviation compensation unit 50 selectively applies filtering for each of the various measurement data collected by the data collection unit 30 from the plurality of sensors 10 according to each sensor-specific group determined by the group determination unit 40 To compensate for measurement data deviation.

In this case, the group of each sensor 10 may be used as a criterion for determining whether to filter each of the measurement data collected from the various sensors 10 and the number of filters when measuring data for engine performance analysis.

The group to which each sensor belongs may be set in consideration of the driving characteristics or combustion process of the engine, the sensor installation location, and the like.

For example, each sensor group may be classified into a high deviation group with high measurement data variability and a low deviation group with low measurement data variability.

According to the degree of variability of the measurement data, various sensors 10 used for data measurement for engine performance analysis are grouped to set a group for each sensor, but the sensors 10 with high variability in measurement data are selected to be a high deviation group. It is set to.

In this case, measurement data filtering (typically, a moving average filter) may be selectively applied to only the sensors 10 of the high deviation group among the plurality of various sensors 10 to compensate for the deviation.

After the deviation compensation for specific measurement data is completed, the data collection unit 30 collects the filtered and unfiltered measurement data and stores it in the integrated database as engine performance data, and in real time through the screen of the display unit 60. Indicate.

Trends of various measurement data collected through the data collection unit 30 may be displayed as illustrated in FIG. 2 through a screen of the display unit 60.

Referring to FIG. 2, it can be seen that the measurement data of some specific sensors 10 has almost no deviation (top 3 graphs, DA), whereas the measurement data of other specific sensors 10 shows a large deviation (lower 5 graphs, DB).

That is, there is a difference in the magnitude of the measurement data deviation according to each sensor 10 installed in the engine, and the reason is as follows.

Engine performance data is primarily pressure and temperature. Of these, temperature data rarely fluctuates instantly, but pressure data may fluctuate significantly.

In particular, the intake/exhaust pressure may be very volatile due to shock wave propagation and fluctuations in flow rate due to combustion processes such as intake/explosion/exhaust that are sequentially generated.

In addition, in the case of the back pressure of the turbine of the turbocharger (T/C), the fluctuation of the exhaust pressure at the front of the turbine (in bar) is transmitted as it is, and the fluctuation is greater due to the small unit (mmAq).

Eventually, in the case of the intake/exhaust pressure measured during the combustion process such as intake/explosion/exhaust while the engine is running, there may be a large deviation, so they apply filtering to collect the smoothed measurement data and analyze the performance of the engine. This is a way to increase the accuracy and reliability of engine performance analysis.

On the other hand, there is no need to apply filtering (moving average filter, etc.) because the pressure of the fluid supplied to the centrifugal and gear pumps, such as coolant, lubricant, and fuel, has relatively little variability.

3 is a processing diagram for explaining a data measurement method for a large ship engine test drive according to an embodiment of the present invention.

First, a plurality of types of sensors used for engine performance analysis are grouped according to the degree of measurement data variability to set a group for each sensor, and the set group information for each sensor is stored in the setting unit 20 of the system (S10).

Thereafter, the data collection unit 30 of the system collects measurement data in the form of analog signals output from the plurality of sensors 10 installed in each part of the engine to be tested in real time (S20).

The data collection unit 30, which collects measurement data in the form of analog signals from a plurality of sensors 10 through the above step S20, converts the collected measurement data in the form of analog signals into digital signals, and then converts them into digital signals. The measured measurement data is stored as engine performance data in an integrated database.

In this process, before the measurement data collected by the data collection unit 30 is stored in the integrated database, it is effective to selectively apply filtering to the measurement data of some sensors 10 to compensate for the data deviation.

Accordingly, the group determination unit 40 is based on the group information for each sensor stored in the group setting unit 20 so that the data deviation compensation unit 50 can selectively filter data on the specific sensors 10. Each group of the plurality of sensors 10 providing measurement data is determined (S30).

The data deviation compensation unit 50 of the system compensates for the measurement data deviation by selectively applying filtering for each of the measurement data collected from the plurality of sensors 10 according to each sensor-specific group determined through the above-described step S30. Do (S40).

For example, the data deviation compensation unit 50 may perform data smoothing by applying a moving average filter only to measurement data of a specific sensor 10 designated as a high deviation group.

Thereafter, the data collection unit 30 collects the measured data collected through the step S20 and then filtered and compensated for deviation (S42), and the remaining unfiltered (S44) measurement data collected through the step S20. As engine performance data, it is stored in the integrated database and displayed in real time through the display unit 60 (S50).

Various measurement data stored in the integrated database through the data collection unit 30 of the system are used to determine the performance index of the engine.

Each sensor-specific group designated in step S10 can be classified into a high deviation group having high measurement data variability and a low deviation group having low measurement data variability.

In this case, in step S40, the data deviation compensating unit 50 of the system may compensate for the measurement data deviation by selectively applying filtering (moving average filter, etc.) to only the sensors 10 of the high deviation group (S42). ).

For example, intake/exhaust pressure sensors that measure intake pressure data and exhaust pressure data may be classified into a high deviation group. A fluid pressure sensor that measures fluid pressure including coolant, lubricating oil, and fuel, and a temperature sensor that measures temperature data may be classified into a low deviation group.

When the sensors 10 measuring pressure data are classified into a high deviation group, some of the plurality of sensors 10 are predicted to have high measurement data variability based on the installation position in the engine (e.g., at the rear end of the turbine of the turbocharger). It may be more efficient to select only the installed pressure sensors) and classify them into high deviation groups.

Furthermore, the high deviation group may be subdivided into groups of multiple levels according to the degree of variability in measurement data.

In this case, the data deviation compensation unit 50 increases the number of filters as the higher level group with high measurement data variability in the high deviation group subdivided into several levels, thereby obtaining smooth data irrespective of the initial degree of variability. .

FIG. 4 is a diagram illustrating a data measurement screen provided according to an embodiment of the present invention as an example, illustrating a trend of measurement data of three pressure sensors collected every second during operation of a large engine.

(a) shows the trend of measurement data in a state in which the moving average filter is not applied, and (b) shows the result of applying the moving average filter to it.

When the moving average filter is not applied, as shown in (a), the maximum deviation of the collected measurement data occurred up to 0.09 bar per second, and five moving average filters were applied to the measured data and the average value for the previous 5 seconds. If changed to, as shown in (b), it can be seen that the maximum deviation of the data is reduced to 0.013 bar, which is remarkably improved.

The configuration of the data measurement system and method for commissioning a large ship engine according to the present invention is not limited to the above-described embodiment, and can be implemented by various modifications within the scope permitted by the technical idea of the present invention.

10: sensor, 20: setting unit,
30: data collection unit, 40: group determination unit,
50: data deviation compensation unit, 60: display unit

Claims (9)

A setting unit for setting a group for each sensor by grouping a plurality of types of sensors used for engine performance analysis according to a degree of measurement data variability;
A data collection unit that collects measurement data from sensors installed in the engine to be tested;
A group determination unit for determining a group of each of the sensors; And
Measurement of data for trial operation of a large ship engine including a data deviation compensation unit that compensates for measurement data deviation by selectively applying filtering on each of the measurement data collected from the sensors according to each sensor group determined by the group determination unit system.
The method of claim 1,
A data measurement system for commissioning a large ship engine further comprising a display unit that collects filtered and unfiltered measurement data and displays it as engine performance data in real time.
The method of claim 1,
The data deviation compensation unit,
A data measurement system for commissioning large ship engines that performs data smoothing by applying a moving average filter.
Setting a group for each sensor by grouping, by the system, a plurality of types of sensors used for engine performance analysis according to a degree of measurement data variability;
Collecting measurement data from sensors installed in an engine in which the system is commissioned;
Determining, by the system, a group of each of the sensors; And
And compensating for measurement data deviation by selectively applying, by the system, filtering for each of the measurement data collected from the sensors according to the determined group for each sensor.
The method of claim 4,
Each sensor group is classified into a high deviation group and a low deviation group according to the degree of variability of the measurement data,
A data measurement method for commissioning large ship engines that compensates for measurement data deviations by selectively applying a moving average filter to only the sensors of the high deviation group.
The method of claim 5,
A method of measuring data for trial operation of a large ship engine in which sensors measuring pressure data are classified into a high deviation group, and only some of the sensors are selected based on an installation location in the engine and classified as a high deviation group.
The method of claim 6,
A data measurement method for commissioning large ship engines that classifies sensors that measure intake air pressure data and exhaust pressure data into high deviation groups.
The method of claim 5,
A data measurement method for commissioning large ship engines that classifies sensors for measuring fluid pressure including coolant, lubricant and fuel, and sensors for measuring temperature data into low deviation groups.
The method of claim 5,
The high deviation group is subdivided into groups of multiple levels according to the degree of measurement data variability,
A data measurement method for commissioning large ship engines that applies by increasing the number of moving average filters for higher-level groups with high measurement data variability in the high deviation group.

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