Circuit breaker contact electrical life evaluation method based on dynamic resistance and fuzzy logic

Abstract

The invention relates to the technical field of circuit breakers, in particular to a circuit breaker contact electrical life evaluation method based on dynamic resistance and fuzzy logic. The system comprises a dynamic resistance measurement system which fuses dynamic resistance measurement characteristics and breaker body parameters; taking Q3 values of main contact resistance Rm and arc contact resistance Ra extracted by box diagram analysis as main input variables, and setting at least one fuzzy membership function for each group of Rm and Ra values; five language input variables, namely low (L), medium-low (ML), medium (M), medium-high (MH) and high (H), are set in the system; considering that the contact aging degree and the contact resistance value are in a linear relation, the system adopts a linear function to represent a mapping relation between input and output and weight distribution of a maximum interval; the membership function overlapping degree among all the linguistic variables is set to be 50%. The method has the advantages of being independent of large-scale data, higher in adaptability and capable of rapidly judging the aging state of the arc extinguish chamber of the circuit breaker.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breakers, in particular to a method for judging the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic. Background Art

[0002] In existing circuit breaker condition assessment technology, static resistance measurement is often used to determine the degree of aging of main contacts. With the increase in computing power and the development of machine learning algorithms, a variety of circuit breaker aging assessment methods based on big data and label training have emerged. While these methods can accurately predict electrical lifespan, they generally rely on large amounts of labeled data, resulting in high costs and poor generalization capabilities.

[0003] When evaluating circuit breaker status using static resistance measurements, only the aging of the main contacts can be analyzed, making it difficult to obtain key parameters of the arc contact points. This results in incomplete and inaccurate evaluation results. While intelligent evaluation methods based on machine learning and large amounts of labeled data can achieve relatively accurate judgments of circuit breaker electrical lifespan, these methods place extremely high demands on data size and labeling quality, require significant human effort and time for data processing, consume significant computing resources, and lack generalizability in practical applications, making them difficult to effectively promote on-site.

[0004] Dynamic resistance measurement technology, as a means of acquiring electrical characteristics throughout the entire process, does not rely on large-scale data and is more adaptable. Therefore, based on an in-depth analysis of dynamic resistance measurement technology, this application combines box plot analysis with fuzzy logic algorithms to propose a method for evaluating the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic. Summary of the Invention

[0005] The purpose of the present invention is to address the above-mentioned shortcomings and provide a circuit breaker contact electrical life evaluation method based on dynamic resistance measurement and fuzzy logic that does not rely on large-scale data and has stronger adaptability.

[0006] The technical solution of the present invention is: a method for judging the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic, including a dynamic resistance measurement system that integrates dynamic resistance measurement characteristics and circuit breaker body parameters; a main contact resistance R extracted by box plot analysis m and arc contact resistance R a The Q3 value is the main input variable, and for each group of R m and R a At least one fuzzy membership function is set for each value; a total of five language input variables are set in the system, namely low (L), medium-low (ML), medium (M), medium-high (MH) and high (H); considering that the degree of contact aging is linearly related to the contact resistance value, the system uses a linear function to represent the mapping relationship between input and output and the weight distribution of the maximum interval; the overlap of the membership functions between all language variables is set to 50%.

[0007] The dynamic resistance measurement system consists of a 12V / 220Ah stationary battery used as a current source and a resistor made of Cr-Al-Fe composite material to limit the test current from the battery. To measure the voltage and current signals in the circuit breaker, a two-channel digital oscilloscope was used. The current signal comes from a current shunt and a DC-DC analog voltage sensor. The voltage probe is fed into oscilloscope channel 1. The voltage signal obtained at the circuit breaker terminals is sent to oscilloscope channel 2 via a second 200MHz / 300V voltage probe.

[0008] The above scheme also includes:

[0009] The main contact resistance R m The formula for calculating the average value of is as follows:

[0010]

[0011] The dynamic resistance R(t) is calculated as follows, where V(t) is the voltage probe measurement value and I(t) is the current shunt measurement value:

[0012]

[0013] The five language input variables low (L), medium-low (ML), medium (M), medium-high (MH) and high (H) refer to the minimum value, maximum value, first quartile (Q1), second quartile (Q2) and third quartile (Q3) of the data set; the third quartile (Q3) is selected as the key input parameter of the decision-making tool.

[0014] The exposure aging levels construct five language output variables, which are defined as follows: low aging (DL-L), low to moderate aging (DL-ML), moderate aging (DL-M), moderate to high aging (DL-MH), and high aging (DL-H).

[0015] The advantages of the present invention are: it is found that by analyzing the mutation characteristics in the dynamic resistance data, a large number of label training processes can be effectively replaced, while reducing data dependence and improving evaluation efficiency and accuracy, and rapid judgment of the aging status of the circuit breaker arc extinguishing chamber can be achieved in actual application scenarios where there is a lack of large-scale training samples.

[0016] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a block diagram of the dynamic resistance measurement system in the present invention.

[0018] Figure 2It is a typical structural block diagram of the box diagram in the present invention.

[0019] Figure 3 R in the present invention m Graph of a linguistic variable function.

[0020] Figure 4 R in the present invention a Graph of a linguistic variable function.

[0021] Figure 5 It is the language output variable graph of DL in the present invention.

[0022] Figure 6 Dynamic resistance measurement curve of circuit breaker A in the present invention.

[0023] Figure 7 Dynamic resistance measurement curve of circuit breakers B and C in the present invention.

[0024] Figure 8 The contact resistance box diagram of the circuit breaker in the present invention - (a) R of circuit breaker A m Box diagram, (b) R of circuit breaker A a Box plot.

[0025] Figure 9 The contact resistance box diagram of the circuit breaker in the present invention - (c) R of circuit breakers B and C m Box diagram, (d) R of circuit breakers B and C a Box plot. DETAILED DESCRIPTION

[0026] See also Figure 1-9 , a method for evaluating the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic, this application uses dynamic resistance measurement (Dynamic Resistance Measurements, DRM) technology for data acquisition, and develops a system such as Figure 1 As shown, the system includes a 12V / 220Ah stationary battery used as a current source and a resistor made of Cr-Al-Fe composite material to limit the test current from the battery. A two-channel digital oscilloscope is used to measure the voltage and current signals in the circuit breaker. The current signal comes from a current shunt (500A / 60mV) and a DC-DC analog voltage sensor (0-60mV / 0-5V). The voltage probe is fed into oscilloscope channel 1. The voltage signal obtained at the circuit breaker terminals is sent to oscilloscope channel 2 via a second 200MHz / 300V voltage probe.

[0027] The dynamic resistance R(t) is calculated as follows, where V(t) is the voltage probe measurement value and I(t) is the current shunt measurement value.

[0028]

[0029] To evaluate the contact condition, 10 dynamic resistance tests were performed on each circuit breaker electrode. The parameters of each dynamic resistance curve were extracted: the main contact resistance R m and arc contact resistance R a Subsequently, the obtained data set was analyzed and the box plot was used to determine the representative R of each contact point. m and R a The best value of the main contact resistance R m The formula for calculating the average value of is as follows:

[0030]

[0031] The box plot is defined by the following five statistics: the minimum value, maximum value, first quartile (Q1), second quartile (median, Q2), and third quartile (Q3) of the data set. Its typical structure is shown in the figure. The box plot also introduces several key characteristic parameters: interquartile range (IQR), maximum value (UL), minimum value (LL), and outliers. The interquartile range is the difference between the third quartile and the first quartile (Q3-Q1), which is used to measure the degree of dispersion of the data. The upper and lower limit formulas are as follows:

[0032]

[0033] Samples outside these ranges are considered outliers. Outliers indicate errors in data measurement or recording and reflect potential abnormal behavior in the data set. Figure 2 .

[0034] Boxplot analysis is applied to the R of each circuit breaker m and R a The third quartile (Q3) was selected as the key input parameter for the decision-making tool because it represents the majority of the measured data and ensures that decisions are based on the overall behavior of the data. In addition, changes in the median and interquartile range can be used to indicate potential faults in the circuit breaker poles. For highly degraded contacts, corrosion may change their contact geometry; during the opening and closing process, mechanical defects may also cause micro-separation, resulting in an increase in shielding resistance and thus an increase in the IQR value. Therefore, IQR can be used as an effective indicator to measure the degree of aging of mechanical contacts and assist in diagnosing potential abnormalities in circuit breakers.

[0035] The fuzzy logic circuit breaker status assessment system focuses on integrating dynamic resistance measurement characteristics and circuit breaker body parameters. The system uses box plot analysis to extract the main contact resistance R m and arc contact resistance R aThe Q3 value is the main input variable, and for each group of R m and R a At least one fuzzy membership function is set for each value. Five language input variables are set in the system, namely low (L), medium-low (ML), medium (M), medium-high (MH) and high (H). Considering that the contact aging degree is linearly related to the contact resistance value, the system uses a linear function to represent the mapping relationship between input and output and the weight distribution of the maximum interval. The overlap of the membership functions between all language variables is set to 50%, Figure 3 and Figure 4 The membership function distribution corresponding to each linguistic variable is shown respectively.

[0036] To quantify the degree of aging, five language output variables were constructed and defined as follows: low degree of aging (DL-L), low to moderate degree of aging (DL-ML), moderate degree of aging (DL-M), moderate to high degree of aging (DL-MH), and high degree of aging (DL-H). Figure 5 A graphical representation of the membership functions of the output variables is shown.

[0037] In order to comprehensively consider the operating conditions of the circuit breaker and the importance of the aging degree of each contact part, R m and R a Assign weight W m and W a , and both are set to a constant value of 1. The inference process uses the Max-Min method, and the output defuzzification method is the Mean of Maximum (MoM) method. The definition of DL is detailed in Table 1.

[0038] Table 1 System reasoning logic

[0039]

[0040] The proposed assessment method can quantitatively analyze the aging of circuit breaker contacts even with limited data. By identifying representative dynamic resistance characteristics using box plots and combining them with a fuzzy logic analysis model, it can effectively identify the operating status of the contacts. The results are consistent with traditional methods and actual observations, validating the feasibility and engineering application value of this method.

[0041] To further verify the effectiveness of the method, relevant experiments are carried out based on actual circuit breaker samples, as follows.

[0042] One medium voltage circuit breaker and two high voltage circuit breakers were used as experimental samples, and the sample specifications were:

[0043] (1) Circuit breaker A: 5000A / 12.5kV / 50kA

[0044] (2) Circuit breaker B: 2500A / 40.5kV / 80kA

[0045] (3) Circuit breaker C: 2500A / 40.5kV / 80kA

[0046] At the rated contact opening and closing speed, a 300A test current was applied to obtain the dynamic resistance measurement curve. Figure 6 and Figure 7 It is the dynamic resistance curve obtained from the test of each circuit breaker.

[0047] Summarize Figure 6 and Figure 7 The results of the dynamic resistance test for each contact point were obtained, and the data set was extracted for box plot analysis. Figure 8 、 Figure 9 Box plots for each contact point of CB-A and CB-B are shown.

[0048] Figure 8 、 Figure 9 The block diagram demonstrates a method for handling abnormal data, using the median or third quartile (Q3) as an indicator of contact degradation. Visual inspection of contact aging by experimenters further confirms the correlation between the Q3 value and contact degradation. For highly degraded contacts, corrosion processes may alter the contact geometry. During opening and closing operations, mechanical defects may cause micro-separation of the contacts, resulting in shielding resistance values and larger IQR values. Therefore, IQR can be used as an indicator for analyzing mechanical strength.

[0049] In order to estimate the aging degree of each contact part, R m and R a Table 2 shows the reference range of language input variables (R m1 ,…,R m5 ,R a1 ,…,R a5 ) is a specific setting in the fuzzy system.

[0050] Table 2 R of circuit breakers A, B, and C m and R a scope

[0051]

[0052] Main contact resistance R extracted from box plot analysis m and arc contact resistance R a The Q3 value of the main input variable is used to estimate the aging degree using the fuzzy logic system. Table 3 lists the R values of each sample obtained by box plot analysis. m and R avalue, and the aging level of the fuzzy analysis.

[0053] Table 3 DRM curve parameters and aging levels of circuit breaker contacts CB-A1, CB-A2, CB-A3, CB-B1, CB-B2, and CB-B3

[0054]

[0055] Using this method, the aging levels of the circuit breaker contacts were 32%, 52%, 100%, 30%, 81%, and 100%, respectively, which are consistent with the results of visual inspection after the experiment. In summary, the proposed method can effectively determine the aging degree of circuit breaker contacts using a small amount of data.

[0056] The above description is only a specific embodiment of the present invention, and various examples do not limit the essential content of the present invention.

Claims

1. A method for evaluating the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic, characterized by: Including dynamic resistance measurement system, which integrates dynamic resistance measurement characteristics and circuit breaker body parameters; the main contact resistance R extracted by box plot analysis m and arc contact resistance R a The Q3 value is the main input variable, and for each group of R m and R a At least one fuzzy membership function is set for each value; a total of five language input variables are set in the system, namely low (L), medium-low (ML), medium (M), medium-high (MH) and high (H); considering that the contact aging degree is linearly related to the contact resistance value, the system uses a linear function to represent the mapping relationship between input and output and the weight distribution of the maximum interval; the overlap of the membership functions between all language variables is set to 50%; The dynamic resistance measurement system consists of a 12V / 220Ah stationary battery used as a current source and a resistor made of Cr-Al-Fe composite material to limit the test current from the battery. To measure the voltage and current signals in the circuit breaker, a two-channel digital oscilloscope was used. The current signal comes from a current shunt and a DC-DC analog voltage sensor. The voltage probe is fed into oscilloscope channel 1. The voltage signal obtained at the circuit breaker terminals is sent to oscilloscope channel 2 via a second 200MHz / 300V voltage probe.

2. The method for judging the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic according to claim 1, characterized in that The main contact resistance R m The formula for calculating the average value of is as follows: The dynamic resistance R(t) is calculated as follows, where V(t) is the voltage probe measurement value and I(t) is the current shunt measurement value:

3. The method for judging the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic according to claim 1 or 2, characterized in that The five language input variables low (L), medium-low (ML), medium (M), medium-high (MH) and high (H) refer to the minimum value, maximum value, first quartile (Q1), second quartile (Q2) and third quartile (Q3) of the data set; the third quartile (Q3) is selected as the key input parameter of the decision-making tool.

4. The method for judging the electrical life of circuit breaker contacts based on dynamic resistance and fuzzy logic according to claim 3, characterized in that The exposure aging levels construct five language output variables, which are defined as follows: low aging (DL-L), low to moderate aging (DL-ML), moderate aging (DL-M), moderate to high aging (DL-MH), and high aging (DL-H).

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