Power equipment status diagnosis method, electronic equipment, and storage medium based on temperature rise load performance

Abstract

The present invention provides a method for diagnosing the state of an electric power equipment based on temperature rise load performance, comprising the steps of: physical mathematical modeling, calculating the temperature rise load performance index of the equipment, judging the fault state of the equipment, defining the characteristics of the temperature rise load performance index of the equipment, diagnosing the characteristic surface shift diagram of the temperature rise load performance index, diagnosing the characteristic parameters of the temperature rise load performance index, and diagnosing the change trend of the characteristic parameters of the temperature rise load performance index. The present invention relates to an electronic device and a storage medium for executing the above method. The present invention applies a load current and temperature relationship model to the monitoring and diagnosis of electric power equipment, which greatly promotes the development of the state monitoring and diagnosis technology of electric power equipment, improves the accuracy and reliability of the monitoring and diagnosis of electric power equipment, and solves the inherent problems existing in the state monitoring and diagnosis of electric power equipment. It 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.

Description

Technical Field

[0001] The present invention relates to the technical field of online monitoring of electric power equipment, and in particular to an electric power equipment state diagnosis method based on temperature rise load performance, 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 status of power equipment based on temperature rise load performance, which can effectively solve the inherent problems existing in the status monitoring and diagnosis of power equipment. It 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 the state of an electric power device based on temperature rise load performance, comprising the following steps:

[0006] Physical mathematical modeling: Based on the analysis of current-induced heating and heat dissipation processes, a mathematical model of load current and temperature of power equipment is established;

[0007] Calculating the equipment temperature rise load performance index, and calculating the equipment temperature rise load performance index according to the load current and temperature mathematical model of the power equipment;

[0008] Determine the equipment fault state, and determine the equipment fault state according to the magnitude and trend of the temperature rise load performance index of the equipment shifting over time or the three-phase deviation of the temperature rise load performance index of the equipment or the temperature rise load ratio between phases;

[0009] 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;

[0010] 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;

[0011] 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;

[0012] 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 status according to the allowable deviation range.

[0013] Furthermore, the mathematical model of load current and temperature of the power equipment is:

[0014]

[0015] make: but

[0016] Where Q(t) is the total heating power of the monitored circuit, R is the total resistance of the monitored circuit, I(t) is the steady-state load current of the monitored circuit, T1(t) is the temperature of the monitored part, T0(t) is the ambient temperature of the monitored equipment, ΔT(t) is the temperature rise of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environmental reference point, and K Rλ is the coefficient of the load current and temperature relationship model, which is called the equipment temperature rise load performance index of the monitored part;

[0017] In the step of calculating the equipment temperature rise load performance index, the equipment temperature rise load performance index is magnified by a fixed multiple.

[0018] Furthermore, the determination of the equipment fault state according to the magnitude and trend of the deviation of the equipment temperature rise load performance index over time is specifically as follows: the process data of the change of the equipment temperature rise load performance index over time is plotted in a two-dimensional plane coordinate graph with time as the horizontal axis, and connected to form a trend curve, and the equipment fault state is determined according to the magnitude and trend of the deviation of the equipment temperature rise load performance index in the trend graph.

[0019] Further, the determination of the equipment fault state according to the three-phase deviation of the equipment temperature rise load performance index is specifically as follows: calculating the three-phase deviation of the equipment temperature rise load performance index, and determining whether the three-phase deviation of the equipment temperature rise load performance index is within the allowable range, if so, it means that there is no abnormality in the equipment, otherwise, it means that an abnormality occurs in a certain item of the equipment;

[0020] When judging the equipment fault state according to the three-phase deviation of the equipment temperature rise load performance index, the data of the three phases of the equipment are sampled at the same time and compared and calculated; the calculation formula of the three-phase deviation of the equipment temperature rise load performance index is:

[0021]

[0022] K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t))

[0023] K Rλ (t)ave=average(K Rλ a(t),K Rλ b(t),K Rλ c(t))

[0024] If ε(t) is not within the allowable range, it is determined that an abnormality has occurred in an item of the equipment.

[0025] Furthermore, the phase-to-phase temperature rise load ratio calculation formula is:

[0026]

[0027] Wherein, Ta(t), Tb(t) are the temperatures of the monitored parts of any two phases among the three phases of the equipment; ΔTa(t), ΔTb(t) are the temperature rises of the monitored parts of any two phases among the three phases of the equipment; Ia(t), Ib(t) are the current values ​​of any two phases among the three phases of the equipment; d ab (t) is the temperature rise load ratio between any two phases of the three phases of the equipment;

[0028] The extreme value method is used to simplify the phase-to-phase temperature rise load ratio calculation formula:

[0029]

[0030] T max (t) = max(T a (t),T b (t),T c (t))

[0031] T min (t) = min(T a (t),T b (t),T c (t))

[0032] I max (t) = max(I a (t),I b (t),I c (t))

[0033] I min (t) = min(I a (t),I b (t),I c (t))

[0034] Where, d(t) is the temperature rise load ratio between the phases of the equipment; T max (t) Take the maximum temperature among the three phases ABC; T min (t) Take the minimum temperature among the three phases ABC; I max (t) Take the maximum current among the three phases ABC; I min (t) Take the minimum current value among the three phases ABC; M is the magnification factor;

[0035] When the d(t) value deviates from K Rλ When it is out of the allowable range, it means that an abnormal situation has occurred in one of the three phases of the equipment.

[0036] Furthermore, the characteristic equation of the equipment temperature rise load performance index is:

[0037] K Rλ =a1T1+a2T0+a3

[0038] T1∈[273.15,393.15]K,T0∈[273.15,353.15]K

[0039] 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.

[0040] Furthermore, the temperature rise load performance index characteristic surface shift diagram diagnosis step includes the following steps:

[0041] 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;

[0042] 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.

[0043] 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 threshold. The upper boundary threshold surface equation is:

[0044] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=10.1

[0045] The equation of the lower boundary threshold surface is:

[0046] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=4.1;

[0047] Result diagnosis: if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state; 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; if it exceeds the upper boundary, it is judged that the temperature rise load performance of the equipment is abnormal; if it exceeds the lower boundary, it is judged that the monitoring system is abnormal.

[0048] Furthermore, the temperature rise load performance index characteristic parameter diagnosis step includes the following steps:

[0049] 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;

[0050] Threshold diagnosis of characteristic parameters: set the allowable range of characteristic equation parameters (a1, a2). If a1 exceeds the upper limit, it is judged as a load performance failure of the equipment; if a1 exceeds the lower limit, it is judged as an abnormality of the monitoring system; if a2 exceeds the upper limit, it is judged as an abnormality of the equipment environment; if a2 exceeds the lower limit, it is judged as optimization of the equipment environment;

[0051] The temperature rise load performance index characteristic parameter change trend diagnosis step comprises the following steps:

[0052] 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:

[0053]

[0054] Calculate and draw the trend lines of a1′(t), a2′(t), and a3′(t) over time respectively;

[0055] 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.

[0056] 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 power equipment status diagnosis method based on temperature rise load performance.

[0057] A computer-readable storage medium stores a computer program, wherein the computer program is executed by a processor to diagnose a power equipment status based on temperature rise load performance.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The present invention provides a method for diagnosing the state of an electric equipment based on temperature rise load performance, comprising the steps of: physical mathematical modeling, calculating the temperature rise load performance index of the equipment, judging the fault state of the equipment, defining the characteristics of the temperature rise load performance index of the equipment, diagnosing the characteristic surface transition diagram of the temperature rise load performance index, diagnosing the characteristic parameters of the temperature rise load performance index, and diagnosing the change trend of the characteristic parameters of the temperature rise load performance index. The present invention relates to an electronic device and a storage medium for executing the method for diagnosing the state of an electric equipment based on temperature rise load performance. The present invention realizes the real-time perception, analysis diagnosis and evaluation prediction of the operating state of the electric equipment through various sensor technologies, wide area communication technologies and information processing technologies. The load current and temperature relationship model is applied to the monitoring and diagnosis of the electric equipment, which greatly promotes the development of the monitoring and diagnosis technology of the state of the electric equipment, improves the accuracy and reliability of the monitoring and diagnosis of the electric equipment, and solves the inherent problems existing in the monitoring and diagnosis of the state of the electric equipment. It is an important means to realize the state maintenance management of the electric equipment and improve the lean level of the power production and operation management. And further designed and formulated fault diagnosis indicators are used to judge the operating state, fault state, health state, and hidden danger warning of the equipment, so as to achieve alarm, pre-warning, and comprehensive diagnosis in case of trouble.

[0060] 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

[0061] 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:

[0062] Figure 1 It is a flow chart of the power equipment status diagnosis method based on temperature rise load performance of the present invention;

[0063] Figure 2 It is the temperature rise load performance index transition diagram of the present invention;

[0064] Figure 3 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

[0065] 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.

[0066] Power equipment status diagnosis method based on temperature rise load performance, such as Figure 1 As shown, the method includes two parts: a method for diagnosing the temperature rise load performance index of electric equipment and a method for diagnosing the characteristics of the temperature rise load performance index of electric equipment. The method for diagnosing the temperature rise load performance index of electric equipment includes the following steps:

[0067] Physical mathematical modeling, based on the analysis of current heating and heat dissipation process, establish the mathematical model of load current and temperature of power equipment; under the static conditions of the system, the model equation is:

[0068]

[0069] make: but

[0070] Where Q(t) is the total heating power of the monitored circuit, R is the total resistance of the monitored circuit, I(t) is the steady-state load current of the monitored circuit, T1(t) is the temperature of the monitored part, T0(t) is the ambient temperature of the monitored equipment, ΔT(t) is the temperature rise of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environmental reference point, and K Rλ It is the coefficient of the load current and temperature relationship model, and is called the equipment temperature rise load performance index of the monitored part.

[0071] The physical meaning of equipment temperature rise load performance indicators:

[0072] R is the total resistance of the measured loop, which is divided into two parts: conductor resistance and contact resistance. Conductor resistance increases with the increase of temperature, which is approximately linear; contact resistance can be divided into contraction resistance and surface film resistance. Contact resistance is affected by many factors, such as contact form, contact pressure, contact surface finish, chemical corrosion, electrochemical corrosion, thermal cycle aging, material properties, critical voltage and current action, etc., which causes contact resistance to show nonlinear changes under certain critical influencing factors. However, for long-term stable working conditions, contact resistance is a stable value. The contact resistance value in the thermal steady state of the equipment can be used to indicate the performance of the electrical connection.

[0073] Theoretical analysis and experience show that the change in contact resistance at electrical connection points is likely to conform to the distribution law of the "bathtub curve" known in the field of equipment management, that is, in the early and late stages of equipment commissioning, the contact resistance is large, in the normal trial period, the contact resistance is small, and in the early stages of late failures, the contact resistance shows a trend of gradually increasing rapidly. Contact resistance is one of the main physical factors for judging the temperature rise load performance status of power equipment. Therefore, in the diagnostic method, by seeking or designing a physical indicator that is equivalent or proportional to the contact resistance as a diagnostic criterion, the quality and aging degree of the electrical connection performance of the equipment can be judged. Load current and temperature relationship model coefficient KRλ It is proportional to the total resistance R of the circuit under test and is designed as the equipment temperature rise load performance indicator of the monitored part.

[0074] λ is the heat dissipation coefficient between the monitored part and the environmental reference point, which is generally unrelated to the temperature rise load performance and operating status of the equipment itself. λ is related to the structure of the sensor and the environment in which it is located. The heat dissipation process of the heating part is divided into three ways: heat conduction, air convection, and heat radiation. The heat dissipation coefficient of the heat conduction process is related to the conductor material and the dielectric material, and is roughly close to a linear relationship; the air convection heat dissipation process is positively correlated with the air temperature; the heat radiation heat dissipation process is positively correlated with the conductor temperature and negatively correlated with the ambient temperature. The relevant experimental results show that λ increases with the increase of the conductor temperature, which is close to a linear relationship.

[0075] From the temperature rise load relationship model, it can be seen that K Rλ The value represents the temperature rise per unit current squared, and is also an indicator that directly reflects the temperature rise load performance of the equipment. The larger the value, the lower the load performance.

[0076] Calculate the equipment temperature rise load performance index. Under normal conditions, according to the mathematical model of load current and temperature of power equipment (system static conditions), the formula for calculating the equipment temperature rise load performance index is:

[0077] Standard unit: K / A 2 ×10 5

[0078] Since the square of the current is used as the denominator, the magnitude of the performance index is very small, and the equipment temperature rise load performance index is magnified by a fixed multiple, which is 10 in this embodiment. 5 times, convenient for calculation and diagnosis.

[0079] Determine the equipment fault status according to the magnitude and trend of the equipment temperature rise load performance index deviation over time or the three-phase deviation of the equipment temperature rise load performance index or the phase-to-phase temperature rise load ratio.

[0080] In one embodiment, if Figure 2 As shown, the equipment temperature rise load performance index K is calculated Rλ , K Rλ The process data that changes over time is plotted in a two-dimensional plane coordinate graph with time as the horizontal axis, and connected into a trend curve. Ideally, it is a fluctuating horizontal line, and the data distribution probability conforms to the normal distribution. It is suitable for analysis and diagnosis using SPC tools. Management and control can be performed through the Xbar-R (mean range chart) in the SPC tool.

[0081] When the equipment fails (contact resistance mutation, local overheating, partial discharge, heat dissipation structure mutation, etc.), K Rλ (t) will shift. Rλ (t) The magnitude and trend of the generated deviation are used to determine the equipment failure status.

[0082] In one embodiment, for a normal three-phase power equipment, when the three-phase monitoring points are the same, the sensors are the same, and the distances are close, it can be considered that the temperature rise load performance factors are similar: λa≈λb≈λc, Ra≈Rb≈Rc, then K Rλ a≈K Rλ b≈K Rλ c. And usually, at the same time, the three phases of the equipment have similar loads and similar temperature rises. From the equipment temperature rise load performance index algorithm, it can be concluded that the three phases have similar equipment temperature rise load performance indexes.

[0083] Sampling data from the three phases of the equipment at the same time and performing comparative calculations can effectively reduce measurement deviations caused by the system in the dynamic process and increase the reliability and accuracy of the diagnostic conclusions.

[0084] The calculation formula for the three-phase deviation of the equipment temperature rise load performance index is:

[0085]

[0086] K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t)), K Rλ (t)max takes the maximum value among the three phases ABC;

[0087] K Rλ (t)ave=average(K Rλ a(t),K Rλ b(t),K Rλ c(t)), K Rλ (t)ave takes the average value of the three phases ABC.

[0088] Set the three-phase deviation tolerance of the equipment temperature rise load performance and make status diagnosis. In an ideal situation, ε(t)≈0; when ε(t) is large, it means that an abnormality has occurred in one phase of the equipment. In this embodiment, the three-phase deviation tolerance of the equipment temperature rise load performance and the diagnostic criteria are as follows:

[0089]

[0090]

[0091] In one embodiment, when the three-phase monitoring points of the equipment are the same, the sensors are the same, the distances are close, and synchronous sampling is performed, the ambient temperature is almost the same, then the collection and calculation of the ambient temperature can be avoided in the comparative calculation, simplifying the optimization calculation process and optimizing the diagnosis results. The calculation formula for the phase-to-phase temperature rise load ratio is:

[0092]

[0093] And according to mathematical derivation, in an ideal situation, we have: ab (t) = K Rλ

[0094] Wherein, Ta(t), Tb(t) are the temperatures of the monitored parts of any two phases among the three phases of the equipment; ΔTa(t), ΔTb(t) are the temperature rises of the monitored parts of any two phases among the three phases of the equipment; Ia(t), Ib(t) are the current values ​​of any two phases among the three phases of the equipment; d ab (t) is the temperature rise load ratio between any two phases of the three phases of the equipment.

[0095] In engineering applications, the temperature rise load ratio between any two phases of the three phases of the equipment can be calculated and then diagnosed. The extreme value method can be used to simplify the calculation formula:

[0096]

[0097] T max (t) = max(T a (t),T b (t),T c (t))

[0098] T min (t) = min(T a (t),T b (t),T c (t))

[0099] I max (t) = max(I a (t),I b (t),I c (t))

[0100] I min (t) = min(I a (t),I b (t),I c (t))

[0101] Where, d(t) is the temperature rise load ratio between the phases of the equipment; T max (t) Take the maximum temperature among the three phases ABC; T min(t) Take the minimum temperature among the three phases ABC; I max (t) Take the maximum current among the three phases ABC; I min (t) Take the minimum current value among the three phases ABC; M is the amplification factor.

[0102] The algorithm conditions are: (1) T max (t) and I max (t), T min (t) and I min (t) must be the same phase. If not, no calculation is performed and d(t) = -1 is directly set, which means the diagnosis result is "equipment failure alarm" state; (2) Value restriction condition: |I max (t)-I min (t)|>>0, preferably, requires: |I max (t)-I min (t)|≥100A. If |I max (t)-I min (t)|<100A, indicating that the load difference between phases is too small and is not suitable for diagnosis using this method. Directly setting d(t)=0 means that this method cannot be used for diagnosis or the diagnosis result is: "equipment is normal".

[0103] Set the three-phase deviation tolerance range of the equipment temperature rise load performance to make status diagnosis. In an ideal situation, we have: d(t) = K Rλ ; When d(t) deviates greatly from kRλ, it means that an abnormal situation has occurred in one of the three phases of the equipment.

[0104] The permissible range and diagnostic criteria for the three-phase deviation of the equipment temperature rise load performance are as follows:

[0105] Equipment phase-to-phase temperature rise load ratio d(t) range Failure level <![CDATA[|d(t)-K Rλ |≥35%K Rλ ]]> Call the police <![CDATA[25%K Rλ ≤|d(t)-K Rλ |<35%K Rλ ]]> Early Warning <![CDATA[15%K Rλ ≤|d(t)-K Rλ |<25%K Rλ ]]> focus on <![CDATA[|d(t)-K Rλ |<15%K Rλ ]]> normal

[0106] The method for diagnosing the characteristic of temperature rise load performance index of power equipment includes the following steps:

[0107] 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.

[0108] 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.

[0109] For specific sensors and monitoring locations, the linear equation of correlation is called the characteristic equation of the equipment temperature rise load performance index:

[0110] K Rλ =a1T1+a2T0+a3

[0111] T1∈[273.15,393.15]K,T0∈[273.15,353.15]K

[0112] 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.

[0113] 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 3 As shown, the following steps are included:

[0114] 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;

[0115] 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.

[0116] 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.

[0117] The upper boundary threshold surface equation is:

[0118] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=10.1

[0119] The equation of the lower boundary threshold surface is:

[0120] K Rλ =a1T1+a2T0+a3, a1=0.034, a2=-0.027, a3=4.1.

[0121] 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.

[0122] Result diagnosis, if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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:

[0128] 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:

[0129] a1=[a1(t1),a1(t2),…,a1(t n )

[0130] a2=[a2(t1),a2(t2),…,a2(t n )

[0131] 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.

[0132] 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 obtained by numerical fitting method 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 calculation.

[0133] 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 excess 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 equipment environmental conditions optimization (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).

[0134] When the equipment temperature rise load performance 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. ′ (t), a2 ′ The size of (t) can be used to determine the trend of changes in the temperature rise load performance of electrical equipment. When a hidden danger occurs in the equipment (failure has not occurred yet), a1(t) and a2(t) will show trend changes. Because a3 plays the role of baseline value adjustment in the characteristic function, parameter trend analysis is not required.

[0135] 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:

[0136] 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:

[0137]

[0138] Calculate and draw the trend lines of a1′(t), a2′(t), and a3′(t) over time respectively;

[0139] 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.).

[0140] 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.

[0141] 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.

[0142] An electronic device includes: 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 power equipment status diagnosis method based on temperature rise load performance.

[0143] A computer-readable storage medium stores a computer program, and the computer program is executed by a processor to diagnose the state of an electric power device based on temperature rise load performance.

[0144] The present invention provides a method for diagnosing the state of an electric equipment based on temperature rise load performance, comprising the steps of: physical mathematical modeling, calculating the temperature rise load performance index of the equipment, judging the fault state of the equipment, defining the characteristics of the temperature rise load performance index of the equipment, diagnosing the characteristic surface transition diagram of the temperature rise load performance index, diagnosing the characteristic parameters of the temperature rise load performance index, and diagnosing the change trend of the characteristic parameters of the temperature rise load performance index. The present invention relates to an electronic device and a storage medium for executing the method for diagnosing the state of an electric equipment based on temperature rise load performance. The present invention realizes the real-time perception, analysis diagnosis and evaluation prediction of the operating state of the electric equipment through various sensor technologies, wide area communication technologies and information processing technologies. The load current and temperature relationship model is applied to the monitoring and diagnosis of the electric equipment, which greatly promotes the development of the monitoring and diagnosis technology of the state of the electric equipment, improves the accuracy and reliability of the monitoring and diagnosis of the electric equipment, and solves the inherent problems existing in the monitoring and diagnosis of the state of the electric equipment. It is an important means to realize the state maintenance management of the electric equipment and improve the lean level of the power production and operation management. And further designed and formulated fault diagnosis indicators are used to judge the operating state, fault state, health state, and hidden danger warning of the equipment, so as to achieve alarm, pre-warning, and comprehensive diagnosis in case of trouble.

[0145] 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 state of power equipment based on temperature rise load performance, characterized in that: The following steps are involved: S1, physical mathematical modeling: Based on the analysis of the heating and heat dissipation process of current, a mathematical model of load current and temperature of power equipment is established. The specific model is as follows; Q(t)=RI(t) 2 =λΔT(t),ΔT(t)=T1(t)-T0(t), make: but Where Q(t) is the total heating power of the monitored circuit, R is the total resistance of the monitored circuit, I(t) is the steady-state load current of the monitored circuit, T1(t) is the temperature of the monitored part, T0(t) is the ambient temperature of the monitored equipment, ΔT(t) is the temperature rise of the monitored part, λ is the heat dissipation coefficient between the monitored part and the environmental reference point, and K Rλ is the coefficient of the load current and temperature relationship model, which is called the equipment temperature rise load performance index of the monitored part; in the step of calculating the equipment temperature rise load performance index, the equipment temperature rise load performance index is magnified by a fixed multiple; the model accurately describes the quantitative relationship between the load current and the equipment temperature; S2, calculating the equipment temperature rise load performance index: using the mathematical model established in step S1, the equipment temperature rise load performance index is calculated to quantify the temperature rise load performance of the power equipment; S3, preliminarily judging the equipment fault state: according to the magnitude and trend of the deviation of the equipment temperature rise load performance index over time, or the three-phase deviation of the equipment temperature rise load performance index, or the phase-to-phase temperature rise load ratio, a preliminary equipment fault state judgment is made within a set threshold range; S4, define the characteristics of the equipment temperature rise load performance index: mathematically fit the functional relationship between the equipment temperature rise load performance index value and the conductor temperature and ambient temperature to obtain the equipment temperature rise load performance index characteristic equation. For specific sensors and monitoring locations, this characteristic equation is a linear equation: <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, 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. S5, temperature rise load performance index characteristic surface transition diagram diagnosis: calculate characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, draw a three-dimensional characteristic surface, and superimpose multiple three-dimensional characteristic surfaces at different time points to form a three-dimensional characteristic distribution space, set a characteristic allowable space domain in the space, and judge the equipment fault state by comparing the relationship between the actual characteristic distribution and the characteristic allowable space domain; S6, temperature rise load performance index characteristic parameter diagnosis: calculating characteristic equation parameters through the equipment temperature rise load performance index characteristic equation, and setting the allowable range of these parameters, and further judging the equipment fault state by monitoring whether the characteristic equation parameters exceed the allowable range; S7, temperature rise load performance index characteristic parameter change trend diagnosis: calculate the change trend of the characteristic equation parameters, and set the allowable deviation range of the change trend, and dynamically judge the equipment fault status by monitoring whether the change trend of the characteristic equation parameters exceeds the allowable deviation range.

2. The method for diagnosing the state of electric power equipment based on temperature rise load performance according to claim 1, characterized in that: According to the amplitude and trend of the deviation of the equipment temperature rise load performance index over time, a preliminary judgment on the equipment fault state is made. Specifically, the process data of the change of the equipment temperature rise load performance index over time is plotted in a two-dimensional plane coordinate graph with time as the horizontal axis, and connected into a trend curve. According to the amplitude and trend of the deviation of the equipment temperature rise load performance index in the trend graph, the equipment fault state is judged.

3. The method for diagnosing the state of electric equipment based on temperature rise load performance according to claim 1, characterized in that: According to the three-phase deviation of the equipment temperature rise load performance index, a preliminary equipment fault status judgment is made, specifically: the three-phase deviation of the equipment temperature rise load performance is calculated, and whether the three-phase deviation of the equipment temperature rise load performance index is within the allowable range, if yes, it means that there is no abnormality in the equipment, otherwise, it means that an abnormality has occurred in a certain item of the equipment; When judging the equipment fault state according to the three-phase deviation of the equipment temperature rise load performance index, the data of the three phases of the equipment are sampled at the same time and compared and calculated; the calculation formula of the three-phase deviation of the equipment temperature rise load performance index is: K Rλ (t)max=max(K Rλ a(t),K Rλ b(t),K Rλ c(t)) K Rλ (t)ave=average(K Rλ a(t),K Rλ b(t),K Rλ c(t)) If ε(t) is not within the permissible range, it is determined that an abnormality has occurred in an item of the equipment; Among them, ε(t) is the three-phase deviation of the equipment temperature rise load performance index, K Rλ (t)max is the maximum value of the three-phase equipment temperature rise load performance index, K Rλ (t)ave is the three-phase average value of the equipment temperature rise load performance index.

4. The method for diagnosing the state of electric equipment based on temperature rise load performance according to claim 1, characterized in that: According to the phase-to-phase temperature rise load ratio, make a preliminary judgment on the equipment fault status, specifically: The calculation formula of phase-to-phase temperature rise load ratio is: Wherein, Ta(t), Tb(t) are the temperatures of the monitored parts of any two phases among the three phases of the equipment; ΔTa(t), ΔTb(t) are the temperature rises of the monitored parts of any two phases among the three phases of the equipment; Ia(t), Ib(t) are the current values ​​of any two phases among the three phases of the equipment; d ab (t) is the temperature rise load ratio between any two phases of the three phases of the equipment; The extreme value method is used to simplify the phase-to-phase temperature rise load ratio calculation formula: T max (t)=max(T a (t),T b (t),T c (t)) T min (t)=min(T a (t),T b (t),T c (t)) I max (t)=max(I a (t),I b (t),I c (t)) I min (t)=min(I a (t),I b (t),I c (t)) Where, d(t) is the temperature rise load ratio between the phases of the equipment; T max (t) Take the maximum temperature among the three phases ABC; T min (t) Take the minimum temperature among the three phases ABC; I max (t) Take the maximum current among the three phases ABC; I min (t) Take the minimum current value among the three phases ABC; M is the magnification factor; When the d(t) value deviates from K Rλ When it is out of the allowable range, it means that an abnormal situation has occurred in one of the three phases of the equipment.

5. The method for diagnosing the state of electric equipment based on temperature rise load performance according to claim 1, characterized in that: The step S5, temperature rise load performance index characteristic surface shift diagram diagnosis step, is specifically: 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 threshold. 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 Result diagnosis: if the three-dimensional characteristic surface exceeds the characteristic allowable space domain, it is an abnormal state; for a specific K Rλ , using the upper boundary threshold surface equation and the lower boundary threshold surface equation, calculate the corresponding boundary threshold according to the monitoring data for diagnosis; If it exceeds the upper boundary, it is judged 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.

6. The method for diagnosing the state of electric equipment based on temperature rise load performance according to claim 1, characterized in that: The S6, temperature rise load performance index characteristic parameter diagnosis, is specifically: 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: set the allowable range of characteristic equation parameters (a1, a2). If a1 exceeds the upper limit, it is judged as a load performance failure of the equipment; if a1 exceeds the lower limit, it is judged as an abnormality of the monitoring system; if a2 exceeds the upper limit, it is judged as an abnormality of the equipment environment; if a2 exceeds the lower limit, it is judged as optimization of the equipment environment; S7, temperature rise load performance index characteristic parameter change trend diagnosis, specifically: 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) If it 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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