CN110442898B - Power transmission line health condition model online optimization method - Google Patents

Abstract

The invention discloses an online optimization method for a health condition model of a power transmission line tower, which comprises the following steps: initializing a power transmission tower health condition model; controlling the power transmission line tower to start to be used; acquiring health condition data of a power transmission line tower; determining a power transmission tower health condition model according to the power transmission tower health condition data comparison result; acquiring data of factors affecting the health condition of the power transmission line tower; and determining a full life cycle health condition model of the power transmission line tower by judging data of factors affecting the health condition of the power transmission line tower. According to the invention, the health condition data of the power transmission tower is updated and the iterative update of the health condition model of the power transmission tower is carried out, so that the health condition model of the power transmission tower in the whole life cycle can be obtained, and the power transmission tower can be conveniently and comprehensively researched and monitored.

Description

An online optimization method for the health status model of transmission line towers

technical field

The invention belongs to the technical field of transmission line towers, in particular to an online optimization method for a health status model of transmission line towers.

Background technique

The transmission line tower is a structure that supports the conductors and lightning protection lines of high-voltage or ultra-high-voltage overhead transmission lines. According to its shape, it is generally divided into five types: wine glass type, cat head type, upper type, dry type and barrel type. towers), terminal towers and spanning towers, etc. Transmission line towers have the characteristics of large flexibility, small damping, etc., and are sensitive to wind, so wind damage is the main cause of loss of transmission line towers.

At present, in order to facilitate the research on transmission line towers, a health status model of transmission line towers is proposed, but in the process of application, there is a deviation between the output value of the initially set health status model of transmission line towers and the actual health status of transmission line towers , is not applicable to the health status of the transmission line tower in the whole life cycle, so it is necessary to optimize the model structure and parameters online.

Contents of the invention

In view of the above problems, the present invention provides an online optimization method for a transmission line tower health model, the method comprising:

Initialize the transmission line tower health model;

Control transmission line pylons come into use;

Obtain data on the health status of transmission line towers;

Determine the health status model of the transmission line tower according to the comparison results of the health status data of the transmission line tower;

Obtain data on factors affecting the health of transmission line towers;

The health status model of the whole life cycle of the transmission line tower is determined by judging the data of factors affecting the health status of the transmission line tower.

Further, the health status data of the transmission line tower includes the health status data generated in real time by the transmission line tower and the data output by the health status model of the transmission line tower.

Further, the real-time generated health status data of the transmission line tower includes data fed back by sensors on the transmission line tower and data fed back by manual inspection.

Further, the determination of the health status model of the transmission line tower according to the comparison result of the health status data of the transmission line tower includes:

The error between the output data of the transmission line tower health status model and the real-time health status data generated by the transmission line tower is less than the set threshold: continue to operate according to the existing transmission line tower health status model;

The error between the data output by the transmission line tower health status model and the real-time health status data generated by the transmission line tower is not less than the set threshold: adjust the parameters and structure of the transmission line tower health status model according to the latest real-time health status data generated by the transmission line tower, Return to Get Power Tower Health Data.

Further, the factors affecting the health status of transmission line towers include wind power and life span of transmission line towers.

Further, the determination of the health status model of the whole life cycle of the transmission line tower by judging the data of factors affecting the health status of the transmission line tower includes:

The wind power reaches the damage intensity of the transmission line tower: update the health status data of the transmission line tower and adjust the parameters and structure of the health status model of the transmission line tower according to the latest real-time health status data of the transmission line tower, and return to the above to obtain the health status data of the transmission line tower ;

The wind force does not reach the damage intensity to the transmission line tower: judge the life span of the transmission line tower.

Further, said judging the life span of transmission line tower includes:

The life of the transmission line tower reaches the design life: according to the existing data, the health status model of the transmission line tower is improved to form a health status model of the whole life cycle of the transmission line tower;

The life of the transmission line tower has not reached the design life: continue to operate according to the existing health status model of the transmission line tower, and return the data of the factors affecting the health status of the transmission line tower.

Further, the optimization of the health status model of the transmission line tower is completed and archived when the health status model of the whole life cycle of the transmission line tower is formed.

The invention can obtain the health status model of the whole life cycle of the transmission line tower by updating the health status data of the transmission line tower and iteratively updating the health status model of the transmission line tower, which is convenient for comprehensive research and monitoring of the transmission line tower. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure pointed out in the written description, claims hereof as well as the appended drawings.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

Fig. 1 shows the flow chart of the online optimization method for the transmission line tower health model of the present invention;

Fig. 2 shows a schematic flow chart of the online optimization process of the transmission line tower health model of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

The present invention provides a method for online optimization of the health status model of transmission line towers. Figure 1 shows the flow chart of the online optimization method for the health status model of transmission line towers of the present invention. The method includes the following steps:

Step 1: Initialize the health status model of the transmission line tower; that is, the health status of the transmission line tower is the initial status (complete health), and at the same time, the health status model of the transmission line tower is also the initial status model, including the parameters and structure of the model.

Step 2: Control the transmission line tower to start using;

Step 3: Obtain the health status data of the transmission line tower; specifically, the health status data of the transmission line tower includes the health status data generated in real time by the transmission line tower and the data output by the health status model of the transmission line tower. Further, the real-time generated health status data of the transmission line tower includes data fed back by sensors on the transmission line tower and data fed back by manual inspection.

Step 4: Determine the health status model of the transmission line tower according to the comparison result of the health status data of the transmission line tower; specifically, the determination of the health status model of the transmission line tower according to the comparison result of the health status data of the transmission line tower includes:

The error between the output data of the transmission line tower health status model and the real-time health status data generated by the transmission line tower is less than the set threshold: continue to operate according to the existing transmission line tower health status model;

The error between the data output by the transmission line tower health model and the real-time health status data generated by the transmission line tower is not less than the set threshold (the threshold is determined according to the structural strength of the tower design): according to the latest health status data generated in real time by the transmission line tower Adjust the parameters and structure of the transmission line tower health model, and return to the acquisition of transmission line tower health data.

Step 5: Obtain data on factors affecting the health status of transmission line towers; specifically, the factors affecting the health status of transmission line towers include wind power and life span of transmission line towers.

Step 6: Determine the health status model of the whole life cycle of the transmission line tower by judging the data of factors affecting the health status of the transmission line tower. Specifically, the determination of the health status model of the whole life cycle of the transmission line tower by judging the data of factors affecting the health status of the transmission line tower includes:

The wind power reaches the damage intensity of the transmission line tower: update the health status data of the transmission line tower and adjust the parameters and structure of the health status model of the transmission line tower according to the latest real-time health status data of the transmission line tower, and return to the above to obtain the health status data of the transmission line tower ;

The wind force does not reach the damage intensity to the transmission line tower: judge the life span of the transmission line tower.

Further, said judging the life span of transmission line tower includes:

The life of the transmission line tower reaches the design life: according to the existing data, the health status model of the transmission line tower is improved to form the health status model of the transmission line tower in the whole life cycle, and the existing data is the actual health status data of the transmission line tower in different operation periods;

The life of the transmission line tower has not reached the design life: continue to operate according to the existing health status model of the transmission line tower, and return the data of the factors affecting the health status of the transmission line tower.

When the health status model of the whole life cycle of the transmission line tower is formed, the optimization of the health status model of the transmission line tower is completed and archived.

Exemplarily, Fig. 2 shows a schematic flow chart of the online optimization process of the transmission line tower health model of the present invention, as shown in Fig. 2:

The first step: control the transmission line tower to start using. When the transmission line tower starts to use, the default health state of the transmission line tower is the initial state (complete health), and at the same time, the health state model of the tower is also the initial state, including the parameters and structure of the model, namely formula (1).

Step 2: Update transmission line tower health data. Replace the original data with the newly acquired health status data of the transmission line tower. When the health state of the transmission line tower is the initial state (full health), there is no need to update the health status data of the transmission line tower.

Step 3: Adjust the parameters and structure of the health status model based on the latest data. After adjusting the parameters and structure according to the latest data, a new health status model is formed. When the health state of the transmission line tower is the initial state (complete health), there is no need to adjust the parameters and structure of the health state model, that is, formula (1).

The new health status model is continuously iteratively updated on the basis of the initial transmission line tower health status model. Specifically, the initial health status model of the transmission line tower is established based on the cumulative amount of the bending moment of the structural surface of the transmission line tower with respect to time, the structure of the transmission line tower itself, materials, external environmental variables, construction age, aging process, etc. , where the indicator is: Transmission Line Tower Health Index--TLTHI (Transmission Line Tower Health Index) can be expressed by the transmission line tower health model:

In formula (1), t is time, z is height, M _eff (t) is the effective breaking moment; Age _eff (t) is the effective aging equation of SMTHPt; there is a relationship between M _eff (t) and Age _eff (t) A and B are adjustment parameters, which represent the aging results of transmission line towers caused by two different mechanisms; M ₁ is the structural surface bending moment of the design wind load on the transmission line tower; M _R is the structural surface resistance Bending resistance; rud represents a redundant parameter, when M ₁ (z,t)>rud M _R (z) occurs, it indicates that the transmission line tower is affected by the wind load at least at a certain point, and its section bending moment exceeds the redundant parameter Rated design value, tower collapse is very likely to happen, but it is not absolute (assuming rud = 1.2). However, in this case, we assume that the health status of the tower itself has reached "0" and requires a comprehensive overhaul and recovery. Among them, the detailed definition of M _eff (t) can refer to the following formulas (2) and (3):

where H is the total height of the transmission line tower.

The detailed expression of the SMTHPt effective aging equation Age _eff (t) is as follows (4):

Age _eff (t)＝f(S _structure , _Material ,T _em p _erature , _Humidity ,PH) (4)

In the formula, S _structure is the structure index; Material is the material _index ; the two index parameters locate the characteristics of transmission line towers under different design standards. _Temperature is the air temperature; _Humidity is the air humidity; PH is the air pH coefficient. Under different coefficient conditions, the accumulation of time produces different aging effects of transmission line towers. The current aging rate of the transmission line tower is coupled with the health index of the transmission line tower, but in order to simplify the analysis and preliminary modeling requirements, here we assume that this coupling relationship can be ignored.

In the transmission line tower structure, there is a vibration interaction between the transmission line tower and the transmission line, which constitutes a non-linear system coupled with each other. Therefore, the structural surface bending moment effect caused by the design wind load on the transmission line tower body is composed of the force acting directly on the transmission line tower body and the force acting on the tower body by the transmission line. When the time t is determined, the value of M ₁ (z, t) is only related to the height. When the height z _{of the transmission line tower is determined, z is defined as the required calculation section height z 0 .} The bending moment generated by the wind load can be defined as M ₁ (z ₀ ), and M ₁ (z ₀ ) can be expressed by the following formula (5):

In the formula, z ₀ is the height of the calculation section; F(z) is the equivalent design wind load of the transmission line tower body, F(z) is affected by the height change, and the expression is as follows (6):

In the formula, ρ _air is the air density, ω _max (z) is the maximum basic wind speed of the wind load at the z height of the transmission line tower, C _flg is the aerodynamic shape coefficient, C _dyn is the dynamic response factor, and A _f is the windward area of the tower .

For a transmission line system in equilibrium under static force, the horizontal components of the tensile force cancel each other out, and the vertical component increases the structural weight. At this time, the tensile force does not produce a bending moment on the structural surface. Under the design wind load, the transmission line produces downwind displacement and deformation, and the components along the wire direction are balanced due to the existence of insulators; however, under the action of the component perpendicular to the transmission line direction, the bending moment on the structural surface of the transmission tower occurs. The static analysis of the transmission line can be carried out through finite element modeling, so as to obtain the bending moment of the tower body section.

However, the method of obtaining the bending moment of the transmission line tower structural surface through finite element mechanical analysis consumes a lot of computing resources, and the time cost is very high, which is not conducive to the real-time evaluation and prediction of transmission line towers under wind disasters. It is necessary to obtain a simple analytic formula that is convenient for real-time analysis and calculation based on mechanical analysis, empirical formula and off-line experimental database to solve this problem.

Under the bending moment of the transmission line tower, the bending resistance of the deconstructed section is distributed exponentially along the height. Therefore, the bending resistance M _R of the structural surface can be expressed by the following formula (7):

M _R (z) = αe ^{- βz} + γ (7)

In the formula, α, β, and γ are undetermined parameters, and different transmission line towers will have different characteristics, which require finite element analysis or mechanical test to fit the undetermined parameters.

The adjustment coefficient B can be defined as the following equation (8):

In the formula, a standard transmission line tower structure and material are selected, and an ideal aging ambient air is selected. For example, the temperature is 25° C., the humidity is 60%, and the pH is neutral PH=7 as an example, but it is not limited thereto. T _total is the rated full life design cycle of the transmission line tower under ideal environment and static wind conditions, that is, after this time, due to structural aging and fatigue, the transmission line tower can no longer support the section bending moment corresponding to the rated wind load.

The adjustment coefficient A can be defined as the following equation (9):

In the formula, M _fall (z) is the bending moment of the tower section corresponding to the wind load F _fall , which is a constant; F _fall is uniformly applied to the tower body through a horizontal direction during the whole life cycle of the tower, and just at the end of the design life of the tower The moment T _total leads to a collapsed tower phenomenon in which a certain cross-section cannot support the real-time bending moment. The force F _fall of this process can be obtained through multi-physical quantity coupling finite element analysis, so as to obtain the numerical solution of A. At this point, the modeling of the health status of transmission line towers ends.

Step 4: Determine whether the error between the model output and the actual health status is less than the set threshold. The model output is the data output by the current existing transmission line tower health model, and the actual health status is the real-time health status data of the transmission line tower, including the data fed back by sensors on the transmission line tower and the data fed back by manual inspection. Exemplarily, take the output data of the existing transmission line tower health status model as m, the actual health status is the health status data generated in real time by the transmission line tower as n, and the threshold value is w as an example. When |m-n|> =w, return to the third step, adjust the parameters and structure of the existing transmission line tower health model according to the health status data n generated in real time by the transmission line tower, so as to form a new transmission line tower health status model. Execute the fourth step again, iteratively update the optimized transmission line tower health status model, until |m-n|<w, end the iteration, and execute the fifth step.

Step 5: Run according to the existing health status model. After the transmission line tower health model is iteratively updated, the latest transmission line tower health model is temporarily formed, and the transmission line tower continues to operate according to the latest transmission line tower health model.

Step 6: Determine whether the wind force has reached the intensity of damage to the transmission line tower. Assess the strength of the wind while the pylon continues to operate according to the latest current pylon health model. When the wind force reaches the damage intensity to the transmission line tower, return to the second step, update the health status data of the transmission line tower, and iteratively update the health status model of the transmission line tower until the wind force does not reach the damage intensity to the transmission line tower, forming further optimization The health status model of the transmission line tower; when the wind force does not reach the damage intensity to the transmission line tower, execute the seventh step.

Step 7: Determine whether the transmission line tower has reached the design life. When the transmission line tower has not reached the design life, return to the fifth step, and continue to operate according to the latest health status model of the transmission line tower until the transmission line tower reaches the design life; when the transmission line tower reaches the design life, execute the eighth step.

Step 8: Improve the life cycle health status model of transmission line towers based on existing data. Make a final update to the latest health status model of transmission line towers to form a health status model for the whole life cycle of transmission line towers.

Step 9: Model optimization is completed and archived.

In the present invention, the same symbols represent the same meanings.

The invention can obtain the health status model of the whole life cycle of the transmission line tower by updating the health status data of the transmission line tower and iteratively updating the health status model of the transmission line tower, which is convenient for comprehensive research and monitoring of the transmission line tower.

Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: they can still modify the technical solutions described in the aforementioned embodiments, or perform equivalent replacements for some of the technical features; and these The modification or replacement does not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims (6)

1. An online optimization method for a health status model of a power transmission line tower, which is characterized by comprising the following steps:

initializing a power transmission tower health condition model;

controlling the power transmission line tower to start to be used;

acquiring health condition data of a power transmission line tower;

determining a power transmission tower health condition model according to the power transmission tower health condition data comparison result;

acquiring data of factors affecting the health condition of the power transmission line tower;

determining a full life cycle health model of the power transmission line tower by judging data affecting the health factors of the power transmission line tower, comprising: wind power reaches the damage strength to the power transmission line tower: updating the health condition data of the power transmission tower, adjusting parameters and structures of a health condition model of the power transmission tower according to the health condition data generated by the latest power transmission tower in real time, and returning to the acquisition of the health condition data of the power transmission tower;

wind power does not reach the damage strength to the power transmission line tower: judging power transmission line tower life-span size includes: the service life of the power transmission line tower reaches the design service life: forming a full life cycle health condition model of the power transmission tower according to the existing data to improve the health condition model of the power transmission tower;

the life of the power transmission line tower does not reach the design life: and continuing to operate according to the existing power transmission tower health condition model, and returning the acquired data of the factors affecting the power transmission tower health condition.

2. The on-line optimization method of a health model of a power transmission tower according to claim 1, wherein the health data of the power transmission tower includes health data generated in real time by the power transmission tower and data outputted by the health model of the power transmission tower.

3. The on-line optimization method of a health status model of a power transmission tower according to claim 2, wherein the health status data generated in real time by the power transmission tower comprises data fed back by a sensor on the power transmission tower and data fed back by manual inspection.

4. A method for online optimization of a health model of a power transmission line tower according to any one of claims 1-3, wherein determining the health model of the power transmission line tower based on the comparison of the health data of the power transmission line tower comprises:

the error between the data output by the power transmission tower health condition model and the health condition data generated by the power transmission tower in real time is smaller than a set threshold value: continuing to operate according to the existing power transmission line tower health condition model;

the error between the data output by the power transmission tower health condition model and the health condition data generated by the power transmission tower in real time is not smaller than a set threshold value: and adjusting parameters and structures of a power transmission tower health condition model according to the health condition data generated by the latest power transmission tower in real time, and returning to the acquired power transmission tower health condition data.

5. A method of on-line optimization of a health model of a power transmission line according to any of claims 1-3, characterized in that said factors affecting the health of the power transmission line include wind power and life of the power transmission line.

6. The on-line optimization method of a power transmission line health model according to claim 1, wherein the power transmission line health model optimization and archiving is finished when the power transmission line full life cycle health model is formed.

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