Power equipment temperature rise load performance index characteristic diagnosis method, electronic equipment, storage medium

Abstract

The present invention provides a method for diagnosing the characteristics of temperature rise load performance indicators of electric equipment, including the steps of defining the characteristics of temperature rise load performance indicators of equipment, diagnosing the surface transition diagram of temperature rise load performance indicator characteristics, diagnosing the characteristic parameters of temperature rise load performance indicators, and diagnosing the trend of temperature rise load performance indicator characteristic parameters. The present invention relates to an electronic device and a storage medium for executing the method for diagnosing the characteristics of temperature rise load performance indicators of electric equipment. The present invention solves the inherent problems existing in the status monitoring and diagnosis of electric equipment, is an important means to realize the status maintenance management of electric equipment and improve the lean level of power production and operation management, improves the accuracy and reliability of monitoring and diagnosis of electric equipment, designs and formulates fault diagnosis indicators for judging the operating status, fault status, health status, and hidden danger warning of equipment, so as to realize alarm in case of trouble, early warning, and comprehensive diagnosis.

Description

Technical Field

[0001] The present invention relates to the technical field of online monitoring of electric power equipment, and in particular to a method for diagnosing temperature rise load performance index characteristics of electric power equipment, electronic equipment, and a storage medium. Background Art

[0002] In recent years, as global energy issues have become increasingly severe, countries around the world have carried out research on smart grids. The ultimate goal of smart grids is to build a panoramic real-time system covering the entire production process of the power system, including power generation, transmission, transformation, distribution, power consumption and dispatching. Power equipment status monitoring and diagnosis is an important part of the smart grid. The implementation of its key technologies can extend the service life of equipment, reduce the occurrence of sudden failures, and improve the power supply reliability of power equipment. Therefore, it has been widely used in power systems.

[0003] The online monitoring data of power equipment is growing in real time. Current sensors and temperature sensors have gradually become popular. The amount of monitoring data is huge and the speed of monitoring data generation is extremely fast. Especially on load current heating power equipment, such as power switchgear, cables and other equipment. In the industry, a large amount of load current and temperature data of field equipment has been collected, and most of them only use threshold judgment for alarm. The status monitoring of power equipment has the disadvantage of insufficient diagnosis and early warning functions, which greatly restricts the comprehensive promotion and application of power equipment status monitoring technology. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method for diagnosing the characteristics of temperature rise load performance indicators of power equipment, which can effectively solve the inherent problems existing in the status monitoring and diagnosis of power equipment, and is an important means to realize the status maintenance management of power equipment and improve the lean level of power production and operation management.

[0005] The present invention provides a method for diagnosing temperature rise load performance index characteristics of electric power equipment, comprising the following steps:

[0006] Define the equipment temperature rise load performance index characteristics, fit the equipment temperature rise load performance index value with the function of the conductor temperature and the ambient temperature as the equipment temperature rise load performance index characteristics, and for specific sensors and monitoring locations, call the correlation linear equation the equipment temperature rise load performance index characteristic equation;

[0007] Diagnosis of temperature rise load performance index characteristic surface transition diagram, calculating characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, drawing a three-dimensional characteristic surface, superimposing each three-dimensional characteristic surface to form a three-dimensional characteristic distribution space, setting the characteristic allowable space domain of the three-dimensional characteristic distribution space, and judging the equipment fault state through the characteristic allowable space domain;

[0008] Diagnosis of characteristic parameters of temperature rise load performance index, calculating characteristic equation parameters through the characteristic equation of the temperature rise load performance index of the equipment, setting the allowable range of the characteristic equation parameters, and judging the equipment fault state through the allowable range;

[0009] The temperature rise load performance index characteristic parameter change trend diagnosis calculates the change trend of the characteristic equation parameter, sets the allowable deviation range of the change trend of the characteristic equation parameter, and judges the equipment fault state according to the allowable deviation range.

[0010] Furthermore, the characteristic equation of the equipment temperature rise load performance index is:

[0011] K Rλ =a1T1+a2T0+a3

[0012] T1∈[273.15, 393.15]K, T0∈[273.15, 353.15]K

[0013] Among them, a1 corresponds to the loop resistivity, a2 corresponds to the thermal resistance coefficient of heat conduction to the environment, and a3 is the reference value.

[0014] Furthermore, the temperature rise load performance index characteristic surface shift diagram diagnosis step includes the following steps:

[0015] Draw a three-dimensional characteristic surface. In each monitoring cycle, the characteristic equation of the equipment temperature rise load performance index is used to calculate a set of characteristic equation parameters. In the three-dimensional drawing space, T1 is the x-axis, T0 is the y-axis, and K Rλ is the z-axis, draw the characteristic surface;

[0016] Draw the three-dimensional feature distribution space. In multiple monitoring cycles over a long period of time, in the same three-dimensional drawing space, the feature surfaces of each monitoring cycle are superimposed and drawn to form a set of feature surfaces. The range surrounded by all the feature surfaces is called the three-dimensional feature distribution space.

[0017] Set the feature admissible space domain. In the same three-dimensional drawing space, set and draw the upper and lower boundary threshold surfaces respectively as the boundaries of the three-dimensional feature distribution space. The enclosed space is called the feature admissible space domain.

[0018] Result diagnosis: if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state.

[0019] Furthermore, in the step of setting the feature admissible space domain, the upper boundary threshold surface equation is:

[0020] K Rλ=a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=10.1

[0021] The equation of the lower boundary threshold surface is:

[0022] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=4.1.

[0023] Furthermore, the result diagnosis step also includes for a specific K Rλ , using the upper boundary threshold surface equation and the lower boundary threshold surface equation, the corresponding boundary threshold is calculated according to the monitoring data for diagnosis.

[0024] Furthermore, in the result diagnosis step, if it exceeds the upper boundary, it is determined that the temperature rise load performance of the equipment is abnormal; if it exceeds the lower boundary, it is determined that the monitoring system is abnormal.

[0025] Furthermore, the temperature rise load performance index characteristic parameter diagnosis step includes the following steps:

[0026] The characteristic parameter function is expressed by calculating a set of characteristic equation parameters (a1, a2, a3) through the characteristic equation of the temperature rise load performance index of the equipment in each monitoring period, and obtaining a series of equation parameter groups in multiple monitoring periods over a long period of time;

[0027] Threshold diagnosis of characteristic parameters sets the allowable range of characteristic equation parameters (a1, a2). If a1 exceeds the upper limit, it is judged as a equipment load performance failure; if a1 exceeds the lower limit, it is judged as a monitoring system abnormality; if a2 exceeds the upper limit, it is judged as an abnormal equipment environmental condition; if a2 exceeds the lower limit, it is judged as equipment environmental condition optimization.

[0028] Furthermore, the temperature rise load performance index characteristic parameter change trend diagnosis step includes the following steps:

[0029] The change trend of the characteristic parameters is calculated by taking the derivative of the function of the characteristic equation parameters with respect to time to obtain the change trend of the characteristic parameters. The formula is:

[0030]

[0031] Calculate and draw the trend lines of a1′(t), a2′(t), and a3′(t) over time respectively;

[0032] Diagnosis of the changing trend of characteristic parameters: if a1′(t) exceeds the upper limit, it is judged as a hidden danger of equipment load performance; if a1′(t) exceeds the lower limit, it is judged as an abnormality of the monitoring system; when the heat dissipation conditions of the equipment change, a2(t) will shift in trend. If a2′(t) exceeds the upper limit, it is judged as the optimization of equipment environment conditions; if a2′(t) exceeds the lower limit, it is judged as the deterioration of equipment environment conditions.

[0033] An electronic device comprises: a processor; a memory; and a program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes a method for executing a characteristic diagnosis method of temperature rise load performance index of electric power equipment.

[0034] A computer-readable storage medium stores a computer program, wherein the computer program is executed by a processor to diagnose the characteristics of temperature rise load performance indicators of power equipment.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention provides a method for diagnosing the characteristics of temperature-rise load performance indicators of electric power equipment, comprising the following steps: defining the characteristics of the temperature-rise load performance indicators of the equipment, fitting the functions of the temperature-rise load performance indicator value of the equipment with the conductor temperature and the ambient temperature as the characteristics of the temperature-rise load performance indicators of the equipment, and for specific sensors and monitoring parts, calling the correlation linear equation the characteristic equation of the temperature-rise load performance indicators of the equipment; diagnosing the characteristic surface shift diagram of the temperature-rise load performance indicators, calculating the characteristic equation parameters through the characteristic equation of the temperature-rise load performance indicators of the equipment, drawing a three-dimensional characteristic surface, superimposing each three-dimensional characteristic surface to form a three-dimensional characteristic distribution space, setting the characteristic allowable space domain of the three-dimensional characteristic distribution space, and judging the equipment fault state through the characteristic allowable space domain; diagnosing the characteristic parameters of the temperature-rise load performance indicators, calculating the characteristic equation parameters through the characteristic equation of the temperature-rise load performance indicators of the equipment, setting the allowable range of the characteristic equation parameters, and judging the equipment fault state through the allowable range; diagnosing the change trend of the characteristic parameters of the temperature-rise load performance indicators, calculating the change trend of the characteristic equation parameters, setting the allowable deviation range of the change trend of the characteristic equation parameters, and judging the equipment fault state through the allowable deviation range. The present invention relates to an electronic device and a storage medium for executing a method for diagnosing the characteristics of temperature rise load performance indicators of electric power equipment. The present invention solves the inherent problems existing in the state monitoring and diagnosis of electric power equipment, is an important means to realize the state maintenance management of electric power equipment and improve the lean level of power production and operation management, improves the accuracy and reliability of electric power equipment monitoring and diagnosis, designs and formulates fault diagnosis indicators for judging the operating state, fault state, health state, and hidden danger warning of equipment, so as to realize alarm in case of trouble, early warning, and comprehensive diagnosis.

[0037] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. The specific implementation of the present invention is given in detail by the following embodiments and their accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0039] Figure 1 Flow chart of the method for diagnosing the temperature rise load performance index characteristics of power equipment of the present invention

[0040] Figure 2 It is a flow chart of the diagnostic steps of the characteristic surface shift diagram of the temperature rise load performance index of the present invention. DETAILED DESCRIPTION

[0041] The present invention is further described below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form a new embodiment.

[0042] The diagnostic method of the temperature rise load performance index characteristics of power equipment, such as Figure 1 As shown, the following steps are included:

[0043] Define the characteristics of the equipment temperature rise load performance index. Under any steady-state condition, for a specific sensor and monitoring location, the equipment temperature rise load performance index K Rλ The value is a stable constant. Rλ The value will move slowly with the change of conductor temperature and ambient temperature. Because the total loop resistance R is linearly related to the conductor temperature T1, and the heat dissipation coefficient λ between the monitored part and the environmental reference point is also approximately linearly related to the conductor temperature T1 and the ambient temperature T0, the equipment temperature rise load performance index is also approximately linearly related to the conductor temperature T. Using a linear function, the equipment temperature rise load performance index K Rλ Value as a function of conductor temperature and ambient temperature K Rλ (T1, T0) is fitted as the temperature rise load performance index characteristic of the equipment, also known as the temperature rise load performance index characteristic equation. It is expressed in geometric form as a three-dimensional surface, so it is also called a characteristic surface.

[0044] In the tracking diagnosis of long-term data, the load current and temperature relationship model coefficient K Rλ As a function, we study the characteristic function K Rλ(T1, T0) can be tracked for a long time to diagnose the equipment's operating status and fault status.

[0045] For specific sensors and monitoring locations, the linear equation of correlation is called the characteristic equation of the equipment temperature rise load performance index:

[0046] K Rλ =a1T1+a2T0+a3

[0047] T1∈[273.15, 393.15]K, T0∈[273.15, 353.15]K

[0048] Among them, a1 corresponds to the loop resistivity coefficient, a2 corresponds to the thermal resistance coefficient of heat conduction to the environment, and a3 is the reference value. For specific sensors and monitored equipment, a1, a2, and a3 are determined constant coefficients. Under normal conditions of the equipment, within a short period, the empirical coefficients of the characteristic equation of the equipment temperature rise load performance index can be obtained by analyzing and fitting the experimental data. Through steady-state experimental data, as long as 3 or more monitoring data of different states are measured to form a set of simultaneous equations, the empirical values ​​of the three coefficients can be obtained. In this embodiment, the temperature sensor monitoring situation at the 400A cable outlet connector of a domestic low-voltage cabinet is used, and the original characteristic equation parameters are: a1=0.034, a2=-0.027, a3=8.1.

[0049] The temperature rise load performance index characteristic surface transition diagram diagnosis calculates the characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, draws a three-dimensional characteristic surface, superimposes each three-dimensional characteristic surface to form a three-dimensional characteristic distribution space, sets the characteristic allowable space domain of the three-dimensional characteristic distribution space, and judges the equipment fault status through the characteristic allowable space domain. Specifically, Figure 2 As shown, the following steps are included:

[0050] Draw a three-dimensional characteristic surface. In actual engineering, each monitoring cycle, preferably, one week is set as a monitoring cycle. According to the solution method of the characteristic equation of the equipment temperature rise load performance index, a set of characteristic equation parameters can be calculated, that is, the characteristic equation within the cycle is obtained. In a three-dimensional drawing space, T1 is the x-axis, T0 is the y-axis, K Rλ is the z-axis, draw the characteristic surface;

[0051] Draw the three-dimensional feature distribution space. In multiple monitoring cycles over a long period of time, in the same three-dimensional drawing space, the characteristic surfaces of each monitoring cycle are superimposed and drawn to form a set of characteristic surfaces. The range surrounded by all the characteristic surfaces is called the three-dimensional feature distribution space. The physical meaning is K Rλ The distribution of values ​​under different working and environmental conditions.

[0052] Set the feature allowable space domain. In the same three-dimensional drawing space, set and draw the upper and lower boundary threshold surfaces respectively as the boundaries of the three-dimensional feature distribution space. The enclosed space is called the feature allowable space domain. For normal equipment, K Rλ There is a certain allowable range of variation (threshold value). If the allowable range is exceeded, it is an abnormal state. In the diagnostic transition diagram, the upper and lower boundary threshold surfaces are set, corresponding to K under different conditions. Rλ The threshold boundary.

[0053] The upper boundary threshold surface equation is:

[0054] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=10.1

[0055] The equation of the lower boundary threshold surface is:

[0056] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=4.1.

[0057] The lower boundary value is small because K Rλ The smaller the value, the better the temperature rise load performance of the equipment. However, for certain equipment, the temperature rise load performance has a limit. When the calculation result exceeds this limit, it may not be that the temperature rise load performance of the equipment has improved, but that there may be an abnormality in the monitoring system itself.

[0058] Result diagnosis, if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state.

[0059] For feature shift diagram diagnosis, all three-dimensional feature surfaces should be within the feature allowable space domain. If any of them exceed the range, it is an abnormal situation.

[0060] Feature shift threshold diagnosis, for a specific K Rλ , it is necessary to use the upper and lower boundary threshold surface equations to calculate the corresponding boundary thresholds for diagnosis based on the monitoring data.

[0061] The above two judgment methods are equivalent diagnostic methods, and the diagnostic conclusions are the same. If the upper boundary is exceeded, it is judged that the temperature rise load performance of the equipment is abnormal; if the lower boundary is exceeded, it is judged that the monitoring system is abnormal.

[0062] When the temperature rise load performance status of the equipment is different, a1, a2, and a3 will change accordingly. According to the physical meaning of a1, a2, and a3, the value of (a1(t), a2(t), and a3(t)) is determined and compared with the allowable threshold range, which can be used to determine the status of the temperature rise load performance of the electrical equipment. Because a3 plays the role of adjusting the reference value in the characteristic function, no parameter analysis is required.

[0063] The temperature rise load performance index characteristic parameter diagnosis calculates the characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, sets the allowable range of the characteristic equation parameters, and judges the equipment fault status through the allowable range. Specifically, it includes the following steps:

[0064] Representation of characteristic parameter function. In actual engineering, a set of characteristic equation parameters (a1, a2, a3) is calculated through the characteristic equation of equipment temperature rise load performance index in each monitoring cycle. In multiple monitoring cycles over a long period of time, a series of equation parameter groups are obtained, which are expressed in the form of a matrix:

[0065] a1=[a1(t1),a1(t2),…,a1(t n )]

[0066] a2=[a2(t1),a2(t2),…,a2(t n )]

[0067] Expressed in geometric form: for each value of each of the above parameters, draw a point in a two-dimensional plane with time as the horizontal axis and parameter value as the vertical axis, and connect adjacent points into a smooth curve, which becomes the trend line of each parameter.

[0068] Expressed in function form: Each of the above trend lines can be expressed in function form as: (a1(t), a2(t)). When necessary, the function expression of the parameter can be numerically fitted to obtain a specific function form. However, in the diagnosis of this method, it is only necessary to determine the trend of each parameter, and it is not necessary to perform function fitting calculations.

[0069] Threshold diagnosis of characteristic parameters, set the allowable range of characteristic equation parameters (a1, a2), all calculated characteristic equation parameters (a1, a2) should be within the above allowable range, if there is an out-of-range, it is an abnormal situation. If a1 exceeds the upper limit, it is judged as a load performance failure of the equipment (contact resistance is too large, local overheating); if a1 exceeds the lower limit, it is judged as an abnormal monitoring system; if a2 exceeds the upper limit, it is judged as abnormal equipment environmental conditions (for example, the heater in the cabinet is overheated, the heat dissipation channel is abnormally blocked, and the heat dissipation fan fails); if a2 exceeds the lower limit, it is judged as the equipment environmental conditions are optimized (for example, the heat dissipation fan is turned on, the external air conditioner is turned on, etc.). Preferably, the allowable range is: a1∈(0.025, 0.045), a2∈(-0.037, -0.017).

[0070] When the temperature rise load performance of the equipment begins to change, a1 and a2 change accordingly, but the changes are not obvious at the beginning, but the trends of a1(t) and a2(t) change significantly. That is, judging the size of a1′(t) and a2′(t) can be used to judge the trend of the change in the temperature rise load performance of electrical equipment. When the equipment has hidden dangers (failure has not occurred), a1(t) and a2(t) will change in trend. Because a3 plays the role of baseline value adjustment in the characteristic function, parameter trend analysis is not required.

[0071] The temperature rise load performance index characteristic parameter change trend diagnosis calculates the change trend of the characteristic equation parameters, sets the allowable deviation range of the change trend of the characteristic equation parameters, and judges the equipment fault status through the allowable deviation range. Specifically, it includes the following steps:

[0072] The change trend of the characteristic parameters is calculated by taking the derivative of the function of the characteristic equation parameters with respect to time, and the change trend of the characteristic parameters is obtained. The formula is:

[0073]

[0074] Calculate and draw the trend lines of a1′(t), a2′(t), and a3′(t) over time respectively;

[0075] Diagnosis of the changing trend of characteristic parameters. Ideally, a1 and a2 are close to constants, which can be expressed mathematically as follows: a1′(t)≈0, a2′(t)≈0. If a1′(t) exceeds the upper limit, it is judged as a hidden danger in the equipment load performance (contact resistance mutation or other heating factors occur). If a1′(t) exceeds the lower limit, it is judged as an abnormality in the monitoring system. When the heat dissipation conditions of the equipment change, a2(t) has a trend shift. If a2′(t) exceeds the upper limit, it is judged as the optimization of the equipment environment conditions (for example, when the cooling fan is turned on, the external air conditioner is started, the cooling channel is turned on, etc.). If a2′(t) exceeds the lower limit, it is judged as the deterioration of the equipment environment conditions (for example, the heater in the cabinet is started, the cooling channel is abnormally blocked, the cooling fan fails, etc.).

[0076] Taking into account the system deviation and fluctuation, the allowable deviation range of a1′(t) and a2′(t) is set. When the calculation result exceeds the set deviation range, the system will issue an abnormal alarm. The diagnostic index of the temperature rise load performance characteristic function parameter trend is obtained based on a large amount of empirical data statistics. Preferably, the allowable deviation range is: a1′(t)∈(-0.02, 0.02) / day, a2′(t)∈(-0.02, 0.02) / day.

[0077] The diagnostic step of the characteristic parameter change trend of the temperature rise load performance index can diagnose the hidden danger status of the equipment, that is, the change of performance degradation of the equipment can be found in a period of time before the equipment failure occurs.

[0078] An electronic device, comprising: a processor;

[0079] A memory; and a program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes a method for executing a temperature rise load performance index characteristic diagnosis method of an electric power device.

[0080] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to diagnose the characteristics of temperature rise load performance indicators of power equipment.

[0081] The present invention provides a method for diagnosing the characteristics of temperature-rise load performance indicators of electric power equipment, comprising the following steps: defining the characteristics of the temperature-rise load performance indicators of the equipment, fitting the functions of the temperature-rise load performance indicator value of the equipment with the conductor temperature and the ambient temperature as the characteristics of the temperature-rise load performance indicators of the equipment, and for specific sensors and monitoring parts, calling the correlation linear equation the characteristic equation of the temperature-rise load performance indicators of the equipment; diagnosing the characteristic surface shift diagram of the temperature-rise load performance indicators, calculating the characteristic equation parameters through the characteristic equation of the temperature-rise load performance indicators of the equipment, drawing a three-dimensional characteristic surface, superimposing each three-dimensional characteristic surface to form a three-dimensional characteristic distribution space, setting the characteristic allowable space domain of the three-dimensional characteristic distribution space, and judging the equipment fault state through the characteristic allowable space domain; diagnosing the characteristic parameters of the temperature-rise load performance indicators, calculating the characteristic equation parameters through the characteristic equation of the temperature-rise load performance indicators of the equipment, setting the allowable range of the characteristic equation parameters, and judging the equipment fault state through the allowable range; diagnosing the change trend of the characteristic parameters of the temperature-rise load performance indicators, calculating the change trend of the characteristic equation parameters, setting the allowable deviation range of the change trend of the characteristic equation parameters, and judging the equipment fault state through the allowable deviation range. The present invention relates to an electronic device and a storage medium for executing a method for diagnosing the characteristics of temperature rise load performance indicators of electric power equipment. The present invention solves the inherent problems existing in the state monitoring and diagnosis of electric power equipment, is an important means to realize the state maintenance management of electric power equipment and improve the lean level of power production and operation management, improves the accuracy and reliability of electric power equipment monitoring and diagnosis, designs and formulates fault diagnosis indicators for judging the operating state, fault state, health state, and hidden danger warning of equipment, so as to realize alarm in case of trouble, early warning, and comprehensive diagnosis.

[0082] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in any form. Any ordinary technician in the industry can smoothly implement the present invention as shown in the drawings and above. However, any equivalent changes, modifications and evolutions made by technicians familiar with the profession without departing from the scope of the technical solution of the present invention using the technical content disclosed above are all equivalent embodiments of the present invention. At the same time, any equivalent changes, modifications and evolutions made to the above embodiments based on the essential technology of the present invention are still within the protection scope of the technical solution of the present invention.

Claims

1. A method for diagnosing the characteristics of temperature rise load performance indicators of power equipment, characterized in that: The following steps are involved: Define the equipment temperature rise load performance index characteristics, fit the equipment temperature rise load performance index value with the function of the conductor temperature and the ambient temperature as the equipment temperature rise load performance index characteristics, and for specific sensors and monitoring locations, call the correlation linear equation the equipment temperature rise load performance index characteristic equation; Diagnosis of temperature rise load performance index characteristic surface transition diagram, calculating characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, drawing a three-dimensional characteristic surface, superimposing each three-dimensional characteristic surface to form a three-dimensional characteristic distribution space, setting the characteristic allowable space domain of the three-dimensional characteristic distribution space, and judging the equipment fault state through the characteristic allowable space domain; Diagnosis of characteristic parameters of temperature rise load performance index, calculating characteristic equation parameters through the characteristic equation of the temperature rise load performance index of the equipment, setting the allowable range of the characteristic equation parameters, and judging the equipment fault state through the allowable range; Diagnose the change trend of characteristic parameters of temperature rise load performance index, calculate the change trend of the characteristic equation parameters, set the allowable deviation range of the change trend of the characteristic equation parameters, and judge the equipment fault status according to the allowable deviation range; The characteristic equation of the equipment temperature rise load performance index is: <h2 style=";text-align:left;direction:ltr">K<h2 style=";text-align:left;direction:ltr"> Rλ <h2 style=";text-align:left;direction:ltr"> =a1T1+a2T0+a3 T1∈[273.15,393.15]K,T0∈[273.15,353.15]K Among them, K Rλ is the equipment temperature rise load performance index, T1 is the conductor temperature, T0 is the ambient temperature, a1 corresponds to the circuit resistivity, a2 corresponds to the thermal resistance coefficient of heat conduction to the environment, and a3 is the reference value; The temperature rise load performance index characteristic surface shift diagram diagnosis step comprises the following steps: Draw a three-dimensional characteristic surface. In each monitoring cycle, a set of characteristic equation parameters are calculated through the characteristic equation of the equipment temperature rise load performance index. In the three-dimensional drawing space, T1 is the x-axis, T0 is the y-axis, and K Rλ is the z-axis, draw the characteristic surface; Draw the three-dimensional feature distribution space. In multiple monitoring cycles over a long period of time, in the same three-dimensional drawing space, the feature surfaces of each monitoring cycle are superimposed and drawn to form a set of feature surfaces. The range surrounded by all the feature surfaces is called the three-dimensional feature distribution space. Set the feature admissible space domain. In the same three-dimensional drawing space, set and draw the upper and lower boundary threshold surfaces respectively as the boundaries of the three-dimensional feature distribution space. The enclosed space is called the feature admissible space domain. Result diagnosis: if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state.

2. The method for diagnosing the temperature rise load performance index characteristics of electric power equipment according to claim 1, characterized in that: In the step of setting the feature admissible space domain, the upper boundary threshold surface equation is: <h2 style=";text-align:left;direction:ltr">K<h2 style=";text-align:left;direction:ltr"> Rλ <h2 style=";text-align:left;direction:ltr"> = a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=10.1 The equation of the lower boundary threshold surface is: <h2 style=";text-align:left;direction:ltr">K<h2 style=";text-align:left;direction:ltr"> Rλ <h2 style=";text-align:left;direction:ltr"> (a1T1+a2T0+a3), (a1) = 0.034, (a2) = -0.027, (a3) ​​= 4.

1.

3. The method for diagnosing the temperature rise load performance index characteristics of electric power equipment according to claim 2, characterized in that: The result diagnosis step also includes for a specific K Rλ , using the upper boundary threshold surface equation and the lower boundary threshold surface equation, the corresponding boundary threshold is calculated according to the monitoring data for diagnosis.

4. The method for diagnosing the temperature rise load performance index characteristics of electric power equipment according to claim 3, characterized in that: In the result diagnosis step, if the upper limit is exceeded, it is determined that the temperature rise load performance of the equipment is abnormal; If it exceeds the lower boundary, it is judged that an abnormality has occurred in the monitoring system.

5. The method for diagnosing the temperature rise load performance index characteristics of electric power equipment according to claim 1, characterized in that: The temperature rise load performance index characteristic parameter diagnosis step comprises the following steps: The representation of the characteristic parameter function is that a set of characteristic equation parameters (a1, a2, a3) is calculated through the characteristic equation of the temperature rise load performance index of the equipment in each monitoring cycle, and a series of equation parameter groups are obtained in multiple monitoring cycles over a long period of time; Threshold diagnosis of characteristic parameters sets the allowable range of characteristic equation parameters (a1, a2). If a1 exceeds the upper limit, it is judged as a equipment load performance failure; if a1 exceeds the lower limit, it is judged as a monitoring system abnormality; if a2 exceeds the upper limit, it is judged as an abnormal equipment environmental condition; if a2 exceeds the lower limit, it is judged as equipment environmental condition optimization.

6. The method for diagnosing the temperature rise load performance index characteristics of electric power equipment according to claim 1, characterized in that: The temperature rise load performance index characteristic parameter change trend diagnosis step comprises the following steps: The change trend of the characteristic parameters is calculated by taking the derivative of the function of the characteristic equation parameters with respect to time to obtain the change trend of the characteristic parameters. The formula is: Calculate and plot a1 separately ′ (t), a2 ′ (t), a3 ′ (t) Trend lines over time; Diagnosis of the changing trend of characteristic parameters, if a1 ′ (t) exceeds the upper limit, it is judged as a potential risk of equipment load performance; if a1 ′ (t) exceeds the lower limit, the monitoring system is judged to be abnormal; when the heat dissipation conditions of the equipment change, a2(t) will shift in trend. ′ (t) exceeds the upper limit, it is judged that the equipment environment conditions are optimized; if a2 ′ If (t) exceeds the lower limit, it is judged that the equipment environment condition has deteriorated.

7. An electronic device, characterized in that include: processor; Memory; And a program, wherein the program is stored in the memory and configured to be executed by a processor, and the program includes instructions for executing the method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to perform the method according to any one of claims 1 to 6.

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