A method and system for evaluating oil-immersed transformer quality

Abstract

The present invention belongs to the technical field of transformers, and provides a method and system for evaluating the quality of an oil-immersed transformer, comprising the following steps: obtaining an evaluation index system for the quality level of the oil-immersed transformer; constructing a judgment matrix based on the obtained evaluation index system, and calculating the weight of the judgment matrix; performing subjective weighting and normalization processing on the evaluation index system to obtain a comprehensive variable weight; and realizing the quality evaluation of the oil-immersed transformer according to a membership function and the comprehensive variable weight.

Description

Technical Field

[0001] The present invention belongs to the technical field of transformers, and in particular relates to a quality assessment method and system for oil-immersed transformers. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] With the continuous development of my country's power grid and the continuous expansion of the power market, oil-immersed transformers have been increasingly widely used in the entire power system due to their unique advantages. In the evaluation of the quality level and operating conditions of transformers, regular maintenance, electrical tests, power outage preventive tests, and oil chromatography analysis have been used for a long time. This series of tests has corresponding standards, but can only reflect whether the indicators in a certain test meet the standards. At present, domestic and foreign research also focuses on static, quantitative evaluation and analysis methods based on some indicators.

[0004] In the quality assessment of oil-immersed transformers, the analysis of test data is an indispensable link. In the existing technology, an evaluation database is constructed using test data, and each indicator is qualified according to the relevant standards and evaluation guidelines of the State Grid, but the correlation between various types of data is not deeply explored, and there is no comprehensive evaluation model; the weight of each indicator of the evaluation object is assigned by combined weighting, and the weight values ​​of the two weighting methods are not considered in the fusion, and the advantages of the two weighting methods are not fully combined; the anti-entropy weight method is used for evaluation, which optimizes the indicator polarization problem caused by the sensitivity of the difference of the entropy value method; the ideal solution is used to sort the evaluation objects, which has a certain reference value, but there is no obvious division of the power quality level; the different influence degrees of each indicator are considered, but there is a certain subjectivity, and the objectivity of the data is not fully utilized. Summary of the invention

[0005] In order to solve the above problems, the present invention proposes a method and system for evaluating the quality of oil-immersed transformers. From a global and systematic perspective, the method and system fully consider the influence of various indicators of the transformer, the extreme values ​​of the indicator data, the distribution of the data, and the overall deterioration. When weighting each evaluation indicator, the evaluation needs and purpose are considered, and the objective information of the data itself is fully utilized. The subjective and objective information are fully and effectively combined to construct a quality inspection and evaluation model for oil-immersed transformers to realize the evaluation of transformer quality.

[0006] According to some embodiments, a first solution of the present disclosure provides a method for evaluating the quality of an oil-immersed transformer, which adopts the following technical solution:

[0007] A method for evaluating the quality of an oil-immersed transformer comprises the following steps:

[0008] Obtain an evaluation index system for the quality level of oil-immersed transformers;

[0009] Constructing a judgment matrix based on the obtained evaluation index system, and calculating the weight of the judgment matrix;

[0010] Subjectively weighting the evaluation index system and normalizing it to obtain a comprehensive variable weight;

[0011] According to the membership function and the comprehensive variable weight, the quality assessment of the oil-immersed transformer is realized.

[0012] As a further technical limitation, in the process of obtaining the evaluation index system for the quality level of the oil-immersed transformer, the state parameters of the oil-immersed transformer are collected from four perspectives: the operating reliability, operating conditions, inherent electrical characteristics and historical environmental information of the oil-immersed transformer, and the evaluation index of the quality level of the oil-immersed transformer is determined; after obtaining the evaluation index system for the quality level of the oil-immersed transformer, the health status of the transformer is graded according to the evaluation index of the oil-immersed transformer.

[0013] Furthermore, the evaluation index system for the quality level of the oil-immersed transformer includes a target layer, a criterion layer and an indicator layer; the target layer is the quality level of the oil-immersed transformer, the criterion layer is the evaluation sub-items of the oil-immersed transformer, and the indicator layer is the evaluation indicators of the oil-immersed transformer.

[0014] Furthermore, according to the transformer hierarchy structure determined by the evaluation index system of the oil-immersed transformer, each element and the lower-layer elements dominated by the element constitute a subdomain, and all elements in the subdomain constitute the judgment matrix.

[0015] As a further technical limitation, the linear combination in the combined weighting method is used to calculate the comprehensive variable weight.

[0016] As a further technical limitation, the membership function adopts a semi-trapezoidal membership function.

[0017] Furthermore, in the process of the oil-immersed transformer quality assessment, the evaluation matrix and the fuzzy comprehensive evaluation set are calculated based on the membership function, and the comprehensive score of the oil-immersed transformer is calculated in combination with the comprehensive variable weight to achieve the quality assessment of the oil-immersed transformer.

[0018] According to some embodiments, a second solution of the present disclosure provides an oil-immersed transformer quality assessment system, which adopts the following technical solution:

[0019] A quality assessment system for an oil-immersed transformer, comprising:

[0020] An acquisition module is configured to acquire an evaluation index system of a quality level of an oil-immersed transformer;

[0021] A calculation module is configured to construct a judgment matrix based on the acquired evaluation index system, calculate the weight of the judgment matrix; perform subjective weighting and normalization processing on the evaluation index system to obtain a comprehensive variable weight;

[0022] The evaluation module is configured to implement quality evaluation of the oil-immersed transformer according to the membership function and the comprehensive variable weight.

[0023] According to some embodiments, a third solution of the present disclosure provides a computer-readable storage medium, which adopts the following technical solution:

[0024] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps in the oil-immersed transformer quality assessment method as described in the first aspect of the present disclosure.

[0025] According to some embodiments, a fourth solution of the present disclosure provides an electronic device, which adopts the following technical solution:

[0026] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the oil-immersed transformer quality assessment method as described in the first aspect of the present disclosure are implemented.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention uses the analytic hierarchy process and the anti-entropy weight method to conduct quantitative and qualitative analysis on the test data and actual detection conditions of the oil-immersed transformer, and performs subjective and objective weighting and correction to obtain the comprehensive variable weight of each indicator; combined with the correlation coefficient, the importance ranking and internal correlation of each evaluation indicator of the oil-immersed transformer are obtained, and according to the detection sequence of first performing non-destructive test and then performing destructive test, according to the comprehensive weight and the degree of correlation, the corresponding tests and indicators are detected in sequence to see if they are normal, which effectively reduces the detection time and the workload of the front-line maintenance personnel, and verifies the accuracy of the established oil-immersed transformer quality evaluation method; the analytic hierarchy process based on the comprehensive variable weight and the correlation coefficient for the quality evaluation of the oil-immersed transformer can reflect the correlation between the various indicators in the oil-immersed transformer to a certain extent, and also ensures the effectiveness of the quality evaluation of the oil-immersed transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure.

[0030] Figure 1 is a flow chart of the oil-immersed transformer quality assessment method in the first embodiment of the present disclosure;

[0031] Figure 2 is a schematic diagram of the oil-immersed transformer quality assessment index system in the first embodiment of the present disclosure;

[0032] Figure 3 It is a structural block diagram of the oil-immersed transformer quality assessment system in the second embodiment of the present disclosure. DETAILED DESCRIPTION

[0033] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be noted that the following detailed descriptions are all illustrative and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0035] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0036] In the absence of conflict, the embodiments in the present disclosure and the features in the embodiments may be combined with each other.

[0037] Embodiment 1

[0038] Embodiment 1 of the present disclosure introduces a method for evaluating the quality of an oil-immersed transformer.

[0039] like Figure 1 The oil-immersed transformer quality assessment method shown in the figure assesses the quality of the oil-immersed transformer based on the hierarchical analysis method with comprehensive variable weights and the correlation coefficient. First, the various influencing factors of the oil-immersed transformer are analyzed to determine the evaluation index system. The hierarchical analysis method is used for subjective weighting, with reference to expert experience and relevant standards and evaluation guidelines for the quality of various materials of the State Grid. The anti-entropy weight method is then used to conduct quantitative and qualitative analysis of the test data and actual detection conditions of the oil-immersed transformer for objective weighting. A comprehensive variable weight is obtained by correcting the weights of the two methods, and then combined with the correlation coefficient to obtain the importance ranking of each evaluation index of the oil-immersed transformer and the internal correlation relationship. Finally, the quality level of the oil-immersed transformer is evaluated according to the established fuzzy evaluation method.

[0040] As one or more implementation methods, since there are many factors affecting the operation of distribution transformers and the degree of correlation between each factor is different, there is great uncertainty and ambiguity. Therefore, it is extremely important to establish quality evaluation indicators for oil-immersed transformers and the entire evaluation system.

[0041] Determine the evaluation metric set

[0042] In order to comprehensively, systematically, objectively and truly characterize the quality level of oil-immersed transformers, the opinions of experts and on-site operation and maintenance personnel were solicited. This embodiment selected 16 state parameters as evaluation indicators of the quality level of oil-immersed transformers from four perspectives: operating reliability, operating conditions, inherent electrical characteristics and historical environmental information of oil-immersed transformers. These parameters include real-time detection data, test data, historical operation and maintenance information and environmental information.

[0043] The system is divided into three levels. The top target layer is the oil-immersed transformer quality level X, which is decomposed into four evaluation sub-items in the middle criterion layer: X = (X 1 ,X 2 ,X 3 ,X 4 ), each sub-item contains 4 evaluation indicators, forming the bottom indicator layer. 11 , Externally applied pressure test X 12 And fault repair record X 43 are qualitative indicators, and the remaining 13 are quantitative indicators. The final evaluation indicator system is as follows: Figure 2 shown.

[0044] Evaluation level classification

[0045] In the oil-immersed transformer evaluation index system, the health status of the transformer must be graded. In this embodiment, based on the actual situation and the grade classification in relevant literature, the quality level of the oil-immersed transformer is divided into four grades: good, qualified, abnormal, and unqualified. Let the evaluation grade set U = {U 1 ,U 2 ,U 3 ,U 4}. 1 That is "good", which means the overall quality of the transformer is good and can operate safely and stably; U 2 "Qualified" means that the overall performance of the transformer has slightly decreased, but it can still ensure safe and stable operation; U 3 "Abnormal" indicates that the transformer is in poor quality and has certain operating risks, and should be regularly inspected and maintained; U 4If the value is “unqualified”, it means that the transformer has been damaged, some indicators can no longer meet national standards, and safe operation cannot be guaranteed, so it needs to be repaired immediately.

[0046] As one or more implementation methods, the quality level of oil-immersed transformers not only affects their own service life, but also affects the operational safety and stability of the entire power system. The quality assessment of distribution transformers needs to describe their specific working conditions and health levels as accurately as possible, and the weight of the oil-immersed transformer quality assessment index directly determines the accuracy of the final result. Therefore, the selection of the index weighting method is also extremely critical.

[0047] Determining subjective constant weights using the analytic hierarchy process

[0048] The basis for establishing the relative importance judgment matrix between factors Figure 2 In the hierarchical structure determined by the evaluation system, each element and the lower-level elements dominated by it constitute a subdomain, and all the elements in it will construct several judgment matrices.

[0049] The significance of constructing a matrix is ​​to quantitatively analyze the relative importance of all sub-layer elements dominated by upper-layer elements. In this embodiment, the judgment matrix D is constructed by the 1-9 ratio scaling method, as shown in Table 1 below.

[0050] Table 1 1-9 Proportional Scaling Method

[0051]

[0052] Note: ① The scale for reverse comparison is the reciprocal of the initial scale; ② Even values ​​are the medians of adjacent discriminations.

[0053] According to matrix theory, the weight of each dimension corresponds to the maximum characteristic root λ of the judgment matrix D max The eigenvector of is normalized and recorded as A.

[0054] DA=λ max A (1)

[0055] Among them, the elements of A are the ranking weights of the relative importance of elements in the same level relative to a factor in the upper level. This process is called hierarchical single sorting.

[0056] At this time, it is also necessary to perform a consistency check on the matrix D, namely:

[0057] f CI =(λ max -n)(n-1) (2)

[0058] Introducing random consistency index f RI Measuring consistency indexf CI , f RIDetermined by the matrix order n, the order in this embodiment is 4, so f RI = 0.9. Define the consistency ratio f CR is the ratio of the two, which is:

[0059] f CR =f CI f RI (3)

[0060] When f CR When <0.1, it means that the matrix D passes the consistency test.

[0061] In order to calculate the weight of each bottom layer indicator relative to the target layer, a total ranking is required. 1 , X 2 , …, X m The sorting of the target layer X is recorded as a 1 , a 2 , …, a m ; n factors in the indicator layer correspond to X in the criterion layer i The hierarchical order of 1j , b 2j , …, b nj (where j = 1, 2, ..., m).

[0062] Then the weight of the indicator layer to the target layer, that is, the subjective constant weight, is:

[0063]

[0064] The consistency ratio f of the total sort CR for:

[0065]

[0066] Similarly, when f CR When <0.1, it means that the total sorting passes the consistency test.

[0067] Anti-entropy weight method determines objective variable weights

[0068] Entropy reflects the degree of disorder of the system. Specifically, it reflects the discreteness and uncertainty of the data at the indicator level. The entropy method is an objective weighting method based on data-driven. This embodiment uses the anti-entropy weight method to correct the problem that the entropy method is not sensitive enough to the difference of indicators. The greater the data difference of the indicator, the greater the anti-entropy.

[0069] In this embodiment, the index characteristics selected for the quality assessment of oil-immersed transformers are divided into qualitative and quantitative types. For quantitative indicators, their data have a certain value; for qualitative indicators, their values ​​are assigned according to the test results, with "1" for qualified and "0" for otherwise. This embodiment first normalizes the selected indicators.

[0070] For m indicators and n corresponding data, then a ij is the data of the jth sample of the i-th element in the indicator layer (i=1,…,m; j=1,…,n). For indicators with optimal specific values, the standardization process is as follows:

[0071]

[0072] Among them, a ov is the optimal value for this indicator.

[0073] The larger the index data is, the better the test condition is, which is called the benefit index (positive index), such as insulation resistance, etc. The standardization process is as follows:

[0074]

[0075] The smaller the index data is, the better the test situation is, which is called a cost index (negative index), such as temperature rise, etc. The standardization process is as follows:

[0076]

[0077] First, the evaluation matrix C is established based on the normalized data. The dimension is determined by the index. After calculating the proportion of data in each index, the entropy of the index can be obtained as:

[0078]

[0079] Then the corrected anti-entropy is:

[0080]

[0081] The final weight is:

[0082]

[0083] When the indicator data changes, the data-driven weights will also change accordingly.

[0084] Determine the composite variable weight

[0085] In the existing technology, most studies on the evaluation of transformer quality level only select subjective weights or objective weights of a single indicator, or simply fit the two, which will lead to deviations in the final evaluation results. The most commonly used combination weighting method is linear combination, as shown below:

[0086] Z i =αW i +(1-α)H i (12)

[0087] However, in the process of linear combination, the determination of the coefficients of the two weights is still a subjective process. To avoid the above problem, this embodiment considers using a method of mutual correction of subjective and objective weights to determine the final comprehensive weight.

[0088] Define the maximum value of the subjective weight in each evaluation index as w max , the minimum value is w min The calculation of subjective correction objective weight is as follows:

[0089] 1) If Hi <w min , then the comprehensive weight of this indicator Zi=w min , the comprehensive weights of the remaining indicators are:

[0090]

[0091] 2) If Hi∈[w min , w max ], then Zi=Hi.

[0092] 3) If Hi <w max , then the comprehensive weight of this indicator Zi=w max , the comprehensive weights of the remaining indicators are:

[0093]

[0094] Among them k=i+1,i+2,…,n.

[0095] The comprehensive weight of objective correction of subjective is the proportional coefficient of entropy as the weight of conventional linear combination, as follows:

[0096] Z i =e i 'W i +(1-e i ')H i (15)

[0097] The specific selection method of the above two correction methods is to compare the fluctuation of the selected indicator data with the similarity of the subjective weight. If the fluctuation of the indicator data is greater, then choose the subjective correction of the objective weight; otherwise, choose the objective correction of the subjective weight, and finally get the comprehensive variable weight of each indicator.

[0098] Index importance ranking and correlation

[0099] In order to explore the correlation between multiple indicators, this embodiment aims to explore the correlation between multiple indicator data. The Person correlation coefficient can be used to measure the correlation between two variables. Therefore, the person correlation coefficient can be used to explore the correlation between multiple indicators. The formula is:

[0100]

[0101] Among them, r is the person correlation coefficient between the two test indicators, X and Y are the test indicators respectively, and k is the indicator data group sequence. The value range of r is [-1, 1]. Usually, when r is between 0.00 and ±0.30, the correlation between the two indicators is unrelated, when r is between ±0.3 and 0.5, the correlation between the two indicators is slightly correlated, when r is between ±0.50 and ±0.80, the correlation between the two indicators is significantly correlated, and when r is between ±0.80 and ±1.00, the correlation between the two indicators is highly correlated; in this embodiment, the correlation between multiple indicators is slightly correlated and above, indicating that there is correlation between the two indicators. After calculating that there is a certain correlation between multiple indicators, in the later detection of oil-immersed transformers, the top items can be tested first according to the comprehensive weight of each indicator and the ranking of the indicators and test items associated with it, which can greatly improve the efficiency of equipment detection.

[0102] Establishing a quality assessment model for oil-immersed transformers

[0103] This embodiment uses the membership function to classify the quality evaluation level of the oil-immersed transformer. The entire model combines the comprehensive variable weight with the fuzzy comprehensive evaluation matrix calculated by the membership function, and finally calculates the quality level of the oil-immersed transformer to be tested. This embodiment uses a membership function combined with a semi-trapezoidal and ridge-shaped form, and its expression is:

[0104]

[0105]

[0106]

[0107]

[0108] Substituting the standardized index into the membership function, the resulting evaluation matrix is:

[0109] R n =[u n1 ,u n2 ,u n3 ,u n4 ] (twenty one)

[0110] Among them, n is the four levels in the criterion layer, namely X 1 ,X 2 ,X 3 ,X 4 . From this, we can get the fuzzy comprehensive evaluation set B of the target layer as:

[0111] Bn =W n R n =[b 1 ,b 2 ,b 3 ,b 4 ] (twenty two)

[0112] Among them, W n is the comprehensive variable weight of each indicator in each criterion layer, and the obtained set is substituted into formula (23) to calculate the comprehensive score:

[0113]

[0114] The relationship between the corresponding U value and the transformer quality grade is shown in Table 2:

[0115] Table 2 Correspondence between U and quality level

[0116]

[0117] When the U value is in [1,2], the oil-immersed transformer is in a normal state, that is, qualified; when the U value is in the rest range, the oil-immersed transformer is in an abnormal or unqualified state.

[0118] To ensure reliability, the data in this embodiment are all derived from relevant tests and actual detection data of the oil-immersed transformer by the power grid.

[0119] According to relevant national technical standards, considering the common fault types of transformers and the corresponding fault probability, and soliciting the opinions of front-line operation and maintenance personnel and experts, the corresponding judgment matrix D is constructed as follows:

[0120]

[0121] Further get its maximum characteristic root λ maX =4.118, and the corresponding eigenvector A = [0.112, 0.625, 0.212, 0.051] T , its consistency ratio f CR =0.043<0.1, the consistency test passed.

[0122] Similarly, we can get {X i1 ,X i2 ,X i3 ,X i4}The maximum eigenvalue λ of the judgment matrix about Xi i and the corresponding eigenvector B i (i=1,2,3,4), respectively:

[0123] B 1=[0.333, 0.334, 0.167, 0.166] T ,λ 1 =4,f CR =0<0.1, consistency test passed;

[0124] B 2 =[0.441, 0.051, 0.289, 0.219] T ,λ 2 =4.106, f CR =0.039<0.1, the consistency test passed;

[0125] B 3 =[0.109, 0.351, 0.351, 0.189] T ,λ 3 =4.01,f CR =0.003<0.1, the consistency test passed;

[0126] B 4 =[0.113, 0.113, 0.535, 0.239] T ,λ 4 =4.01, f CR =0.003<0.1, the consistency test passed. Then the subjective constant weight obtained by the hierarchical analysis method is:

[0127]

[0128] Substituting the data into the variable objective weights based on the data-driven anti-entropy weight method is:

[0129]

[0130] After comparing the two weights, the subjective correction objective weight method is selected to obtain the matrix Z of the comprehensive variable weights of each indicator:

[0131]

[0132] Combining the comprehensive variable weight with the correlation coefficient, the correlation of each indicator can be obtained as shown in Table 3:

[0133] Table 3 Correlation between indicators

[0134]

[0135] In the quality inspection of oil-immersed transformers, if the inspection sequence is to conduct non-destructive tests first and then destructive tests, the corresponding tests and indicators can be inspected in sequence according to the comprehensive weights and the degree of relevance to see if they are normal.

[0136] According to the results of sorting the indicators by their relevance in Table 3, according to the principle of conducting non-destructive tests first and then destructive tests, the temperature rise (X 21 ), and then detect the related test, namely the winding resistance test (X 33 ), no-load current and loss measurement (X 23 ), short circuit impedance and loss measurement (X 24 ), when any of the top inspection items fails, it can be directly determined that the transformer is in a fault state, which greatly reduces the detection time and the workload of front-line maintenance personnel.

[0137] After the standardized test data is inserted into the membership function to obtain the fuzzy comprehensive evaluation set of the target layer, combined with the comprehensive variable weights, the quality grades of the six oil-immersed transformers to be tested are obtained as shown in Table 4:

[0138] Table 4 Results of the quality classification of 6 transformers

[0139]

[0140] Among them, the quality levels of 5 transformers were between good and qualified, and the quality of 1 transformer was abnormal, which was consistent with the actual test results of the original data.

[0141] This embodiment uses the analytic hierarchy process and the anti-entropy weight method to perform quantitative and qualitative analysis on the test data and actual detection conditions of the oil-immersed transformer, and performs subjective and objective weighting and correction to obtain the comprehensive variable weight of each indicator; combined with the correlation coefficient, the importance ranking and internal correlation of each evaluation indicator of the oil-immersed transformer are obtained, and the corresponding tests and indicators are tested in sequence according to the detection sequence of first performing non-destructive tests and then performing destructive tests, according to the comprehensive weights and the degree of correlation, to determine whether they are normal, which effectively reduces the detection time and the workload of front-line maintenance personnel, and verifies the accuracy of the established oil-immersed transformer quality evaluation method; the analytic hierarchy process based on comprehensive variable weights and correlation coefficients for oil-immersed transformer quality evaluation can reflect the correlation between the various indicators in the oil-immersed transformer to a certain extent, and also ensures the effectiveness of the oil-immersed transformer quality evaluation.

[0142] Embodiment 2

[0143] Embodiment 2 of the present disclosure introduces a quality assessment system for an oil-immersed transformer.

[0144] like Figure 3 The oil-immersed transformer quality assessment system shown includes:

[0145] An acquisition module is configured to acquire an evaluation index system of a quality level of an oil-immersed transformer;

[0146] A calculation module is configured to construct a judgment matrix based on the acquired evaluation index system, calculate the weight of the judgment matrix; perform subjective weighting and normalization processing on the evaluation index system to obtain a comprehensive variable weight;

[0147] The evaluation module is configured to implement quality evaluation of the oil-immersed transformer according to the membership function and the comprehensive variable weight.

[0148] The detailed steps are the same as those of the oil-immersed transformer quality assessment method provided in Example 1 and will not be repeated here.

[0149] Embodiment 3

[0150] A third embodiment of the present disclosure provides a computer-readable storage medium.

[0151] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps in the oil-immersed transformer quality assessment method as described in the first embodiment of the present disclosure.

[0152] The detailed steps are the same as those of the oil-immersed transformer quality assessment method provided in Example 1 and will not be repeated here.

[0153] Embodiment 4

[0154] A fourth embodiment of the present disclosure provides an electronic device.

[0155] An electronic device comprises a memory, a processor and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the oil-immersed transformer quality assessment method as described in the first embodiment of the present disclosure are implemented.

[0156] The detailed steps are the same as those of the oil-immersed transformer quality assessment method provided in Example 1 and will not be repeated here.

[0157] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. A method for evaluating the quality of an oil-immersed transformer, characterized in that: The following steps are involved: Obtain an evaluation index system for the quality level of oil-immersed transformers; The evaluation index system of the oil-immersed transformer quality level includes a target layer, a criterion layer and an indicator layer; the target layer is the quality level of the oil-immersed transformer, the criterion layer is the evaluation sub-item of the oil-immersed transformer, and the indicator layer is the evaluation index of the oil-immersed transformer; Calculate the weight of each bottom layer indicator relative to the target layer for total ranking; Criteria layer m Factors X 1, X 2, ..., X m For the target layer X The sorting of a 1, a 2, ..., a m ; Indicator layer n Factors in the criteria layer X i The hierarchical order of b 1j , b 2j , … , b nj , j =1,2, … , m ; The weight of the indicator layer to the target layer is: The consistency ratio of the total sort is: The Person correlation coefficient is used to explore the correlation between multiple indicators. The formula is: in, r is the person correlation coefficient between the two test indicators, X , Y are the test indicators respectively, k is the indicator data set sequence; Constructing a judgment matrix based on the obtained evaluation index system, and calculating the weight of the judgment matrix; Subjectively weighting the evaluation index system and normalizing it to obtain a comprehensive variable weight; According to the membership function and the comprehensive variable weight, the quality assessment of the oil-immersed transformer is realized.

2. A method for evaluating the quality of an oil-immersed transformer as claimed in claim 1, characterized in that: In the process of obtaining the evaluation index system for the quality level of the oil-immersed transformer, the state parameters of the oil-immersed transformer are collected from four perspectives: the operating reliability, operating conditions, inherent electrical characteristics and historical environmental information of the oil-immersed transformer, and the evaluation index of the quality level of the oil-immersed transformer is determined; after obtaining the evaluation index system for the quality level of the oil-immersed transformer, the health status of the transformer is graded according to the evaluation index of the oil-immersed transformer.

3. A method for evaluating the quality of an oil-immersed transformer as claimed in claim 1, characterized in that: According to the transformer hierarchy structure determined by the evaluation index system of the oil-immersed transformer, each element and the lower-layer elements dominated by the element form a subdomain, and all elements in the subdomain constitute the judgment matrix.

4. A method for evaluating the quality of an oil-immersed transformer as claimed in claim 1, characterized in that: The linear combination in the combined weighting method is used to calculate the comprehensive variable weight.

5. A method for evaluating the quality of an oil-immersed transformer as claimed in claim 1, characterized in that: The membership function adopts a semi-trapezoidal membership function.

6. A method for evaluating the quality of an oil-immersed transformer as claimed in claim 5, characterized in that: In the process of the oil-immersed transformer quality assessment, the evaluation matrix and the fuzzy comprehensive evaluation set are calculated based on the membership function, and the comprehensive score of the oil-immersed transformer is calculated in combination with the comprehensive variable weight to achieve the quality assessment of the oil-immersed transformer.

7. A quality assessment system for oil-immersed transformers, characterized in that: include: An acquisition module is configured to acquire an evaluation index system of a quality level of an oil-immersed transformer; The evaluation index system of the oil-immersed transformer quality level includes a target layer, a criterion layer and an indicator layer; the target layer is the quality level of the oil-immersed transformer, the criterion layer is the evaluation sub-item of the oil-immersed transformer, and the indicator layer is the evaluation index of the oil-immersed transformer; Calculate the weight of each bottom layer indicator relative to the target layer for total ranking; Criteria layer m Factors X 1, X 2, ..., X m For the target layer X The sorting of a 1, a 2, ..., a m ; Indicator layer n Factors in the criteria layer X i The hierarchical order of b 1j , b 2j , … , b nj , j =1,2, … , m ; The weight of the indicator layer to the target layer is: The consistency ratio of the total sort is: The Person correlation coefficient is used to explore the correlation between multiple indicators. The formula is: in, r is the person correlation coefficient between the two test indicators, X , Y They are the test indicators respectively. k is the indicator data set sequence; A calculation module is configured to construct a judgment matrix based on the acquired evaluation index system, calculate the weight of the judgment matrix; perform subjective weighting and normalization processing on the evaluation index system to obtain a comprehensive variable weight; The evaluation module is configured to implement quality evaluation of the oil-immersed transformer according to the membership function and the comprehensive variable weight.

8. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps in the oil-immersed transformer quality assessment method according to any one of claims 1 to 6 are implemented.

9. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the oil-immersed transformer quality assessment method according to any one of claims 1 to 6 are implemented.

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