Circuit breaker health state assessment method and computer equipment

Abstract

The invention belongs to the technical field of circuit breakers, and particularly relates to a circuit breaker health state evaluation method and computer equipment. The method comprises the following steps: obtaining a measured value of each secondary index under each primary index reflecting the health state of the circuit breaker, and calculating a deterioration degree used for judging the aging degree of the measured value of the secondary index according to the measured value of each secondary index; constructing whitening weight functions of different grey classes of the second-level indexes, and substituting the degradation degrees of the second-level indexes into the whitening weight functions of different grey classes to obtain grey clustering coefficients of the second-level indexes; and obtaining an evaluation result of the health state of the circuit breaker according to the gray clustering coefficient of each secondary index and the weight corresponding to each primary index. The accuracy of the health state evaluation result of the circuit breaker is improved, the reliability of the circuit breaker is improved, faults are avoided, and normal operation of the circuit breaker is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of circuit breakers, and particularly relates to a method for evaluating the health status of a circuit breaker and a computer device. Background Art

[0002] The health status of a circuit breaker directly determines the reliability of the circuit breaker. Therefore, the evaluation of the health status of the circuit breaker is very important, and the evaluation result directly determines whether the circuit breaker can continue to be used. Higher evaluation accuracy can effectively improve the reliability of the circuit breaker, avoid faults, reduce power system downtime and operation and maintenance time, and at the same time maximize the service life of the circuit breaker and improve economic benefits.

[0003] However, there are many factors affecting the evaluation result of the health status of a circuit breaker, including the insulation characteristics, mechanical characteristics, electrical characteristics, and wear conditions of the circuit breaker. Each of these characteristics is affected by multiple secondary factors. In the prior art, when evaluating the health status of a circuit breaker, the influence of these secondary factors is often ignored, resulting in low evaluation accuracy of the health status of the circuit breaker, poor reliability of the circuit breaker, and affecting the normal operation of the power system. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for evaluating the health status of a circuit breaker and a computer device to solve the technical problem of low evaluation accuracy of the health status of a circuit breaker in the prior art, resulting in poor reliability of the circuit breaker.

[0005] To solve the above technical problem, the present invention provides a method for evaluating the health status of a circuit breaker, including the following steps:

[0006] Obtain the measured values of each secondary index under each primary index reflecting the health status of the circuit breaker, and calculate the deterioration degree for judging the aging degree of the measured value of the secondary index according to the measured values of each secondary index;

[0007] Construct the whitenization weight function of different grey classes of the secondary index, and substitute the deterioration degree of the secondary index into the whitenization weight function of different grey classes to obtain the grey clustering coefficient of the secondary index;

[0008] Obtain the evaluation result of the health status of the circuit breaker according to the grey clustering coefficient of each secondary index and the weight corresponding to each primary index.

[0009] The present invention is an exploratory invention. The present invention proposes a method for constructing a multi-level evaluation index for the health state of a circuit breaker, and then, based on the multi-level evaluation index, obtaining an evaluation method for the health state of the circuit breaker. Specifically, the degradation degree of a secondary index is calculated according to the measured value of the secondary index, and then a whitenization weight function for different grey classes of the secondary index is constructed, and the degradation degree is substituted into it to obtain the grey clustering coefficient of the secondary index. The grey clustering coefficient of the secondary index can reflect the health state of the secondary index. The evaluation result of the health state of the circuit breaker is obtained based on the grey clustering coefficient of the secondary index and the weight corresponding to the primary index. By constructing a multi-level architecture, the secondary indexes affecting the primary index are also incorporated into the calculation process, considering more comprehensively and in more detail, thereby improving the accuracy of the evaluation result of the health state of the circuit breaker, enhancing the reliability of the circuit breaker, avoiding failures, and ensuring the normal operation of the circuit breaker.

[0010] Further, the method for obtaining the evaluation result of the health state of the circuit breaker according to the grey clustering coefficients of each secondary index of each grey class and the weights corresponding to each primary index is as follows:

[0011] A grey clustering coefficient matrix of the secondary indexes is constructed according to the grey clustering coefficients of the secondary indexes, and the evaluation result of the health state of the circuit breaker is obtained by using the fuzzy comprehensive evaluation method based on the grey clustering coefficient matrix of the secondary indexes and the weight vector of the primary index.

[0012] Further, the following steps are also included:

[0013] The sum of the products of the grey clustering coefficients of all secondary indexes belonging to the same primary index and the corresponding weights is calculated to obtain the grey clustering coefficient of the primary index, and the evaluation result of the health state of each primary index is obtained according to the grey clustering coefficients of each primary index.

[0014] Further, the weight of the secondary index is a variable weight that changes with the set variable weight coefficient and is calculated based on the degradation degree of the secondary index and a constant weight that remains unchanged.

[0015] Further, the calculation method for calculating the variable weight of the secondary index according to the degradation degree of the secondary index and the constant weight is as follows:

[0016]

[0017] In the formula, W pl is the variable weight of the secondary index, W pl (0) is the constant weight of the secondary index, m pl is the degradation degree of the secondary index, λ is the variable weight coefficient, and n is the number of secondary indexes under the p-th primary index.

[0018] Further, the calculation method for the degradation degree of the secondary index is as follows:

[0019]

[0020] Wherein, m pl is the deterioration degree of the secondary index, M pl is the measured value of the secondary index, M a is the standard value of the secondary index; M b - is the lower limit of the critical value of the secondary index; M b + is the upper limit of the critical value of the secondary index.

[0021] Furthermore, the constant weight of the secondary index is obtained from the subjective weight of the secondary index obtained by using the subjective weighting method and the objective weight of the secondary index obtained by using the objective weighting method.

[0022] Furthermore, the method for obtaining the constant weight of the secondary index from the subjective weight and the objective weight of the secondary index is: using the combined weighting method to combine and weight the subjective weight and the objective weight to obtain the constant weight of the secondary index.

[0023] Furthermore, the primary indexes of the circuit breaker health state include one or more of opening wear, insulation characteristics, mechanical characteristics, and electrical characteristics; the secondary indexes of opening wear include one or more of relative electrical wear, cumulative opening times, and service life; the secondary indexes of insulation characteristics include one or more of gas pressure, micro water content in the arc extinguishing chamber, micro water content in other gas chambers, and primary circuit insulation to ground; mechanical characteristics include one or more of closing non-synchronization, opening non-synchronization, initial opening speed, and initial closing speed; the secondary indexes of electrical characteristics include at least one of opening coil resistance, closing coil resistance, minimum operating voltage of the opening coil, and minimum operating voltage of the closing coil.

[0024] To solve the above technical problems, the present invention also provides a computer device, including a processor, and the processor implements the method steps as described in the circuit breaker health state assessment method of the present invention when executing a computer program.

[0025] The present invention is an improved invention creation, and its beneficial effects are the same as those of the circuit breaker health state assessment method of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flowchart of the circuit breaker health state assessment method according to the method embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] A circuit breaker health status evaluation method and a computer device of the present invention construct a multi-level evaluation index for the circuit breaker health status indicators, and then obtain the evaluation method for the circuit breaker health status according to the multi-level evaluation index. Specifically, the deterioration degree is calculated according to the measured value of the secondary index, and then the whitenization weight function of different grey classes of the secondary index is constructed, and the deterioration degree is substituted into it to obtain the grey clustering coefficient of the secondary index. The grey clustering coefficient of the secondary index can reflect the health status of the secondary index. The health status evaluation result of the circuit breaker is obtained according to the grey clustering coefficient of the secondary index and the weight corresponding to the primary index. By constructing a multi-level architecture, the secondary indicators affecting the primary index are also incorporated into the calculation process, considering more comprehensively and in more detail, thereby improving the accuracy of the circuit breaker health status evaluation result, enhancing the reliability of the circuit breaker, avoiding failures, and ensuring the normal operation of the circuit breaker.

[0028] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0029] Method embodiment:

[0030] Since there are many characteristics affecting the health status of the circuit breaker, which are mainly divided into five categories: breaking wear, insulation characteristics, mechanical characteristics, electrical characteristics and basic characteristics, and each category includes more than one specific index. Based on this, in order to comprehensively consider the various health status evaluation indicators of the circuit breaker, the present invention proposes a circuit breaker health status evaluation method that considers all indicators at different levels. The specific method is as Figure 1 shown, and includes the following steps:

[0031] Step 1: Construct a circuit breaker health status evaluation index system.

[0032] Since the circuit breaker health status indicators can be divided into five categories: breaking wear, insulation characteristics, mechanical characteristics, electrical characteristics and basic characteristics. Therefore, in this embodiment, these five indicators are used as the primary indicators for the circuit breaker health status evaluation, and each primary indicator includes corresponding secondary indicators. The secondary indicators under each primary indicator in this embodiment are respectively: the breaking wear primary indicator includes three secondary indicators: relative electrical wear, cumulative breaking times and service life; the insulation characteristics primary indicator includes secondary indicators such as gas pressure, micro water content in the arc extinguishing chamber, micro water content in other gas chambers and primary circuit insulation to ground; the mechanical characteristics primary indicator includes secondary indicators such as closing non-synchronism, opening non-synchronism, initial opening speed and initial closing speed; the electrical characteristics primary indicator includes secondary indicators such as opening coil DC resistance, closing DC resistance, minimum operating voltage of the opening coil and minimum operating voltage of the closing coil; the basic situation primary indicator includes secondary indicators such as working environment, appearance and maintenance status.

[0033] Closing non-synchronization is divided into phase-to-phase closing non-synchronization and same-phase closing non-synchronization. Phase-to-phase closing non-synchronization refers to the time difference of contact of each phase contact, and same-phase closing non-synchronization refers to the time difference of contact of different break contacts within the same phase, which is expressed by time. The case of opening non-synchronization is the same.

[0034] As another implementation manner, the first-level indicators may also include one or more of breaking wear, insulation characteristics, mechanical characteristics, electrical characteristics, and basic characteristics, and the second-level indicators corresponding to the first-level indicators may also include one or more of all the indicators corresponding thereto.

[0035] Step 2: Calculate the grey clustering weights corresponding to each second-level indicator.

[0036] 1. Calculate the deterioration degree of the second-level indicator.

[0037] The deterioration degree of this second-level indicator is used to judge the aging degree of the measured value of the second-level indicator. Specifically, the calculation formula for the deterioration degree of the second-level indicator is:

[0038]

[0039] In the formula, m pl represents the relative deterioration degree of a certain second-level indicator, M pl represents the actual measured value of this second-level indicator, M a represents the standard value of the second-level indicator; M b - is the lower limit of the critical value of the second-level indicator; M b + is the upper limit of the critical value of the second-level indicator.

[0040] 2. Calculate the grey clustering coefficient of the second-level indicator according to the whitenization weight function of the variable weight of the second-level indicator.

[0041] The upper measure of the mixed center point triangular whitenization weight function is the weight function of grey class s, and the lower measure is the weight function of grey class 1. In this embodiment, the health state of the circuit breaker is divided into four evaluation levels: good, general, warning, and failure. s is equal to 4, corresponding to 4 grey scales. The expressions of the whitenization weight functions of the four grey scales are as follows:

[0042]

[0043] In the formula, f pl 1 、f pl 2 、f pl 3 and f pl 4 are the whitenization weight functions corresponding to the four levels of good, general, warning, and failure respectively, μ 1 、μ 2 、μ3 , μ 4 is the center point of the four grey classes.

[0044] According to the whitening weight function of the secondary index, the grey clustering coefficient of the secondary index can be obtained. The specific grey clustering coefficient of the secondary index is f pl k (m pl ), where p is the serial number of the primary index to which the secondary index belongs, l is the serial number of the secondary index in its belonging primary index, m pl is the deterioration degree of the secondary index, and f pl k is the k-th grey class whitening weight function of the secondary index, and k is the serial number of the grey class.

[0045] The specific method for determining the grey class k of the secondary index is as follows: According to the deterioration degree m pl of the secondary index, substitute it into the four whitening weight functions f pl 1 , f pl 2 , f pl 3 and f pl 4 respectively, and four values are obtained. Only one non-zero positive value exists among the four values. The grey class corresponding to the non-zero positive value is the grey class k of the secondary index. For example:

[0046] If m pl ∈[m 1 , μ 2 , then f pl 3 = 0, f pl 4 = 0, and there must be one positive value and one negative value among f pl 1 and f pl 2 . The positive value is f pl k (m pl )(k = 1 or 2). The grey class corresponding to the positive value is the grey class k of the grey clustering coefficient of the secondary index.

[0047] Step 3: Obtain the evaluation result of the circuit breaker health status according to the grey clustering coefficient of the secondary index and the weight of the primary index.

[0048] 1. Construct the grey clustering coefficient matrix of the secondary index according to the grey clustering coefficient of the secondary index.

[0049] Write the grey clustering coefficient of the l-th secondary index under the p-th primary index into the p-th row and l-th column of the matrix to obtain the grey clustering coefficient matrix of the secondary index.

[0050] 2. Use the fuzzy comprehensive evaluation method to obtain the breaker health state evaluation matrix according to the grey clustering coefficient matrix of the secondary index and the weight vector of the primary index, and solve to obtain the breaker health state evaluation result. The specific calculation method is as follows:

[0051] H 1 = G 1 ·W 1

[0052] H 1 is the breaker health state evaluation score, reflecting the breaker health state; W 1 is the weight vector of the primary index, G 1 is the grey clustering coefficient matrix of the secondary index, and · is the fuzzy operator.

[0053] Determine the health state of the entire breaker according to the breaker health state evaluation score. For example, if the score range is 0 - 1 point, then 0 - 0.25 corresponds to breaker failure, 0.26 - 0.5 points corresponds to breaker warning, 0.51 - 0.75 points corresponds to general breaker health state, and 0.76 - 1 point corresponds to good breaker health state.

[0054] Step Four: Calculate the evaluation results of each primary index of the breaker.

[0055] In this embodiment, in order to evaluate the health state of the breaker more reasonably and in detail, it is also possible to calculate the grey clustering coefficient of each primary index based on the grey clustering coefficient of the secondary index to obtain the evaluation results of each primary index. The specific steps are as follows:

[0056] 1. Calculate the variable weights of each secondary index.

[0057] In this embodiment, the weights corresponding to the secondary index include subjective weights and objective weights. The subjective weights are obtained through subjective weighting by the weighting method (subjective weighting method), and the objective weights are calculated and determined by the entropy weight method (objective weighting method). Then, the constant weights of the secondary index are calculated by the combined weighting method. Based on the constant weights of the secondary index and the degree of deterioration, the variable weights of the secondary index are calculated. The constant weights of the secondary index remain unchanged, and the variable weights change with the change of the variable weight coefficient. The specific calculation formula of the combined weighting method is as follows: The weight vector coefficient of the k-th weighting is ω k , then the vectors of different weighting methods are:

[0058] W = (ω 1 , ω 2 , ……, ω p )

[0059] In this embodiment, there are two weight assignment methods, namely subjective weight assignment and objective weight assignment. Therefore, the constant weight W determined by combined weight assignment pl (0) has the following calculation formula:

[0060] W pl (0) = ω 1 W pl (1) + ω 2 W pl (2)

[0061] In the formula, W pl (0) is the constant weight of the l-th secondary index under the p-th primary index, and W pl (1) is its subjective weight, ω 1 is the combined weight assignment weight of the subjective weight, and W pl (2) is its objective weight, and ω 2 is the combined weight assignment weight of the objective weight.

[0062] The constant weight vector of the secondary indexes under a primary index is:

[0063] W p (0) = [W p1 (0) , W p2 (0) ,......, W pn (0)

[0064] In the formula, W p (0) is the constant weight vector of the p-th primary index, and W p1 (0) , W p2 (0) ……W pn (0) are the constant weight vectors of the secondary indexes from the 1st to the nth under the p-th primary index respectively.

[0065] Combining the constant weight of the secondary index and the relative deterioration degree, the variable weight of the secondary index can be obtained. The specific calculation formula is as follows:

[0066]

[0067] In the formula, W pl is the variable weight of the secondary index, and W pl (0) ​is the constant weight of the secondary index, and λ is the variable weight coefficient. pl =1, we can pl It is approximately equal to 0.99999. p is the serial number of the first-level indicator to which the second-level indicator belongs, and l is the serial number of the second-level indicator in the first-level indicator to which it belongs.

[0068] 2. Calculate the health status of the primary indicators.

[0069] Sum the grey clustering coefficients of all secondary indicators of the same grey class and belonging to the same primary indicator to obtain the grey clustering coefficients of each grey class and each primary indicator. The specific calculation formula is as follows:

[0070]

[0071] In the formula, θ p is the grey clustering coefficient of the pth first-level indicator of the kth grey class, that is, the health status score of the first-level indicator, n is the number of second-level indicators under the pth first-level indicator, W pl Represents the variable weight of the secondary indicator.

[0072] According to θ p The calculation results of the circuit breaker's primary indicators are used to obtain the health status assessment results.

[0073] Computer equipment example:

[0074] A computer device of the present invention includes a processor, and the processor implements the steps of the circuit breaker health status assessment method as described in the method embodiment of the present invention when executing a computer program. The specific process, principle and beneficial effects of the method have been described in detail in the method embodiment, and will not be repeated in this embodiment.

[0075] The processor may be a microprocessor MCU, a programmable logic device FPGA or other processing device.

[0076] In summary, for a circuit breaker health status evaluation method and a computer device of the present invention, by constructing a multi-level architecture, the secondary indicators affecting the primary indicators are also incorporated into the calculation process, taking more comprehensive and detailed considerations, thereby improving the accuracy of the circuit breaker health status evaluation result, enhancing the reliability of the circuit breaker, avoiding faults, and ensuring the normal operation of the circuit breaker. Further, the present invention uses the fuzzy comprehensive evaluation method to obtain the circuit breaker health status evaluation result based on the grey clustering coefficient of the secondary indicators and the weights of the primary indicators, taking into account the problems of index fuzziness and randomness, improving the evaluation accuracy, and further ensuring the normal operation of the circuit breaker. Further, the present invention can not only obtain the circuit breaker overall health status evaluation result, but also calculate the health status evaluation result of each specific primary indicator. The evaluation result is more comprehensive and detailed, enhancing the reliability of the evaluation result, and targeted protection strategies can be adopted for different health statuses of the primary indicators to ensure the safe and reliable operation of the circuit breaker. Further, when calculating the health status of the primary indicators, the present invention adopts variable weights for the weights of the secondary indicators that change according to the magnitude of their deterioration degree and constant weights, which is more flexible and accurate compared to constant weights, improving the evaluation accuracy of the circuit breaker primary indicator health status.

Claims

1. A circuit breaker health status assessment method, characterized in that: The following steps are involved: Obtaining the measured values ​​of each secondary indicator under each primary indicator reflecting the health status of the circuit breaker, and calculating the degradation degree used to determine the aging degree of the secondary indicator measured value according to the measured values ​​of each secondary indicator; Construct the whitening weight function of different gray classes of the secondary index, substitute the degradation degree of the secondary index into the whitening weight function of different gray classes, and obtain the gray clustering coefficient of the secondary index; The evaluation result of the health status of the circuit breaker is obtained according to the grey clustering coefficient of each secondary indicator and the weight corresponding to each primary indicator.

2. The circuit breaker health status assessment method according to claim 1, characterized in that: According to the grey clustering coefficient of each secondary indicator of each grey class and the weight corresponding to each primary indicator, the method for obtaining the evaluation result of the health status of the circuit breaker is as follows: According to the grey clustering coefficient of each secondary indicator, the grey clustering coefficient matrix of the secondary indicator is constructed, and the health status assessment result of the circuit breaker is obtained according to the grey clustering coefficient matrix of the secondary indicator and the weight vector of the primary indicator using the fuzzy comprehensive evaluation method.

3. The circuit breaker health status assessment method according to claim 1, characterized in that: The following steps are also included: The grey clustering coefficient of the first-level indicator is obtained by summing the products of the grey clustering coefficients of all the second-level indicators belonging to the same first-level indicator and the corresponding weights, and the health status assessment results of each first-level indicator are obtained according to the grey clustering coefficients of each first-level indicator.

4. The circuit breaker health status assessment method according to claim 3, characterized in that: The weight of the secondary indicator is a variable weight that changes with the set variable weight coefficient and is calculated based on the degradation degree of the secondary indicator and a constant weight.

5. The circuit breaker health status assessment method according to claim 4, characterized in that: The calculation method of the variable weight of the secondary indicator based on the degradation degree and constant weight of the secondary indicator is as follows: Where W pl is the variable weight of the secondary index, W pl (0) is the constant weight of the secondary index, m pl is the degradation degree of the secondary indicator, λ is the variable weight coefficient, and n is the number of secondary indicators under the pth primary indicator.

6. The circuit breaker health status assessment method according to claim 1, characterized in that: The calculation method of the degradation degree of the secondary index is as follows: In the formula, m pl is the degradation degree of the secondary index, M pl is the measured value of the secondary indicator, M a is the standard value of the secondary indicator; M b - is the lower limit of the critical value of the secondary indicator; M b + It is the upper limit of the critical value of the secondary indicator.

7. The circuit breaker health status assessment method according to claim 4, characterized in that: The constant weight of the secondary indicator is obtained based on the subjective weight of the secondary indicator obtained using the subjective weighting method and the objective weight of the secondary indicator obtained using the objective weighting method.

8. The circuit breaker health status assessment method according to claim 7, characterized in that: The method for obtaining the constant weight of the secondary indicator based on the subjective weight and objective weight of the secondary indicator is: using the combined weighting method to weight the subjective weight and the objective weight to obtain the constant weight of the secondary indicator.

9. The circuit breaker health status assessment method according to any one of claims 1 to 8, characterized in that: The primary indicators of the health status of the circuit breaker include: one or more of breaking wear, insulation characteristics, mechanical characteristics and electrical characteristics; the secondary indicators of breaking wear include one or more of relative electrical wear, cumulative number of breaking times and service life; the secondary indicators of insulation characteristics include one or more of gas pressure, arc extinguishing chamber micro-water volume, other gas chamber micro-water volume and primary circuit to ground insulation; mechanical characteristics include one or more of different closing phases, different opening phases, just opening speed and just closing speed; the secondary indicators of electrical characteristics include at least one of the opening coil resistance, closing coil resistance, opening coil minimum operating voltage and closing coil minimum operating voltage.

10. A computer device comprising a processor, characterized in that: The processor implements the steps of the circuit breaker health status assessment method according to any one of claims 1 to 9 when executing the computer program.

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