CN108802576B - Subjective and objective integration assessment method for running state of oil-immersed capacitor bushing - Google Patents
Subjective and objective integration assessment method for running state of oil-immersed capacitor bushing Download PDFInfo
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Abstract
The invention belongs to the technical field of maintenance of the running state of power transmission and transformation equipment, and discloses a method for detecting the running state of an oil-immersed capacitor bushing, which comprises the steps of calculating the relative degradation degree of the running parameters of the oil-immersed capacitor bushing to obtain the relative degradation degree of each running parameter; the operation parameters comprise dielectric loss of an oil-immersed capacitor bushing to a ground screen, capacitance change rate, insulation resistance of the bushing end screen to the ground, and H in bushing oil2、C2H2Content and maintenance times; obtaining a first weight of each operation parameter by adopting an analytic hierarchy process; acquiring a second weight of each operation parameter by adopting an entropy weight method; integrating the first weight and the second weight by adopting a cuckoo algorithm to obtain a final weight; integrating the relative degradation degree of each operation parameter according to the final weight to obtain an evaluation value of the operation state of the oil-immersed capacitor bushing; the evaluation value obtained by the method is closer to the actual running state of the oil-immersed capacitor bushing, and the method has the advantages of comprehensive evaluation factors, clear quantification and strong operability.
Description
Technical Field
The invention belongs to the technical field of maintenance of the running state of power transmission and transformation equipment, and particularly relates to a method for detecting the running state of an oil-immersed capacitor bushing.
Background
The power transformer connects windings of different voltage classes into a line through bushings, and the bushings of different voltage classes are used for insulating a transformer oil tank. The bushing is a current-carrying element of the power transformer, and not only plays a role of insulation against the ground, but also plays a role of fixing the lead. In the case of an operating power transformer, an operating current flows through a lead wire in a bushing, so that once a short circuit occurs, the current is increased sharply and impacts the bushing, and in the severe case, the bushing is cracked to cause a serious accident. The power transformer bushing is one of the components in the power transformer accessory with a high probability of failure. The damage of the transformer bushing can often cause the explosion of the bushing and even cause the fire of the transformer, thus seriously affecting the safety of the power system. Therefore, the running state of the sleeve is accurately evaluated, the economic loss of the power system can be effectively avoided, and the potential safety hazard is reduced.
The existing method for evaluating and predicting the running state of the bushing only focuses on a certain influence factor influencing the running state of the bushing, cannot comprehensively reflect the change condition of the insulation state of the high-voltage bushing, and has a large one-sidedness in the evaluation and prediction result, regardless of the evaluation and prediction of the running state of the bushing based on the oil component of the bushing in the early stage or the evaluation and prediction of the running state of the bushing based on the fitting of the aging trend of the insulation paper in recent years.
One of the difficulties of the casing state evaluation technology is how to determine the parameter weight; the existing weight determination methods include subjective weighting method and objective weighting method. The subjective weighting method is a method for obtaining parameter weight by comparing and calculating parameters to be evaluated based on the experience of experts. The subjective weighting method mainly comprises the following steps: expert survey (Delphi) method, Analytic Hierarchy Process (AHP) method, preference ratio method, ring ratio scoring method, binomial coefficient method, comparison matrix method and importance ranking method. Objective weighting is a method of determining the weight of a parameter based on the difference in objective data for each scenario operating parameter value in order to avoid interference to the weighting artifacts due to the knowledge, experience and preferences of the decision maker or expert. The objective weighting method mainly comprises the following steps: principal component analysis, entropy weight, dispersion maximization, mean square deviation and multi-objective planning. The application of the subjective and objective weighting methods in parameter weight determination is thousands of years, the subjective weighting method embodies knowledge experience or preference of experts, and the objective weighting method utilizes objective mathematical reasoning. However, both the subjective and objective weighting methods have limitations, and the subjective weighting method has subjective randomness; the objective weighting method usually ignores subjective information of a decision maker, and is particularly suitable for the field of evaluation of the running condition of the casing pipe with high engineering practicability.
Disclosure of Invention
In view of the above defects or improvement requirements of the prior art, the present invention provides a method for detecting an operation state of an oil-immersed capacitive bushing, which aims to improve the accuracy of a prediction result of the operation state of the oil-immersed capacitive bushing.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for detecting an operation state of an oil-immersed capacitive bushing, including the steps of:
(1) obtaining the operation parameters of the oil-immersed capacitor bushing to be measured, including dielectric loss to the ground screen, capacitance change rate, insulation resistance of the bushing end screen to the ground, and H in the bushing oil2Gas content, C in casing oil2H2Gas content and maintenance frequency of the oil-immersed capacitor bushing;
(2) acquiring a relative degradation degree set formed by the relative degradation degrees of various operation parameters;
(3) obtaining an operation state detection value of the oil-immersed type capacitor bushing according to the relative degradation degree set and a corresponding operation parameter weight set obtained by an operation parameter weight model;
the method for obtaining the corresponding operation parameter weight by the operation parameter weight model comprises the following steps:
(a) determining a first weight of the operating parameter using an analytic hierarchy process;
(b) determining a second weight of the operating parameter by using an entropy weight method;
(c) and obtaining an optimal weighting coefficient by adopting a cuckoo algorithm, integrating the first weight and the second weight, enabling the weight obtained by integration to be as close as possible to the minimum value of an objective function of an operation parameter weight model constructed based on the minimum discrimination information principle, and obtaining the weight of each operation parameter to form an operation parameter weight set.
Preferably, the method for detecting the operation state of the integrated oil-immersed capacitor bushing is implemented,
the threshold value range of dielectric loss C2-1 of the ground end screen is [800, 2000 ]]Relative degree of deterioration thereof
The threshold value range of C2-2 of the capacitance change rate is [1.5, 2.0 ]]Relative degree of deterioration thereof
The threshold value range of C2-3 of insulation resistance of the bushing end shield to the ground is [30, 50%]Relative degree of deterioration thereof
H in casing oil2The threshold range of C2-4 for gas content is [0, 0.8%]Relative degree of deterioration thereof
In casing oil C2H2The threshold range of C2-5 for gas content is [0, 2%]Relative degree of deterioration thereof
The threshold value range of C2-6 of the maintenance times of the oil-immersed capacitor bushing is [0,2 ]]Relative degree of deterioration thereof
Preferably, in the method for detecting an operating state of an integrated oil-immersed capacitor bushing, step (a) includes the following substeps:
(a.1) establishing a priority relation matrix M representing three kinds of expert opinions by using a three-scale method1、M2、M3；
Priority relation matrix M ═ Mij)n×nThe general expression of (a) is:
satisfies the following conditions: m isij≥0；mij+mji＝1；mii0.5; wherein i is a row number and j is a column number;
(a.2) obtaining m for each value in the priority relation matricesijThe judgment value is obtained according to the expected value and a preset three-scale quantization table, and an integrated priority relation matrix M is obtained according to the judgment value;
(a.3) converting the priority relation matrix M obtained by integration into a fuzzy consistent matrix F:
(a.4) normalizing the sum of each row of elements of the fuzzy consistent matrix F to obtain the initial weight distribution corresponding to each parameter:
and (a.5) taking the initial weight distribution as an iteration initial value to carry out iteration to obtain the first weight of the operation parameter.
Preferably, in the method for detecting the operating state of the integrated oil-immersed capacitive bushing, step (a.5) includes the following substeps:
(a.5.1) determination of V0＝(v01,v02,…,v0n)T＝W＝(ω1,ω2,…,ωn)TAs an iteration initial value, iterating to obtain the (k +1) th iteration value Vk+1＝E*Vk(ii) a Wherein W refers to initial weight assignment; e is a reciprocal matrix obtained by converting the fuzzy consistent matrix F;
(a.5.2) obtaining the (k +1) th iteration value Vk+1The component max (V) having the largest absolute valuek+1)；
(a.5.3) performing precision calculation: if max (V)k+1)-max(Vk) < ε then max (V)k+1) As a main eigenvalue λmaxTo V pairk+1After normalization processing, obtaining final weight vector distribution D which is the first weight, and ending circulation; wherein epsilon is a preset calculation precision;
if max (V)k+1)-max(Vk) If is greater than epsilon, the k-th iteration value V iskAs a new iteration initial value, iteration is performed again, and the final weight distribution obtained by circulation is the first weight, wherein
Preferably, in the method for detecting an operating state of an integrated oil-immersed capacitor bushing, step (b) includes the following substeps:
(b.1) evaluating the operation parameters by using the selected expert opinions to form an evaluation matrix R:
(b.2) carrying out non-dimensionalization processing on the elements in the evaluation matrix R to obtain a matrix S:
(b.3) normalizing the matrix S obtained by the dimensionless processing to obtain a matrix S':
(b.4) calculating the entropy value and the difference coefficient of the operation parameters according to the matrix S' obtained by normalization:
and (b.5) obtaining the second weight of each operation parameter by adopting an objective entropy weight method calculation formula according to the entropy value and the difference coefficient of each operation parameter.
Preferably, in the method for detecting an operating state of an integrated oil-immersed capacitive bushing, step (c) includes the following substeps:
(c.1) integrating the first weight and the second weight to enable the integrated first weight and the integrated second weight to be as close to a target function of a constructed operation parameter weight model as possible;
wherein the objective function is
Wherein p refers to the number of the operating parameter,
(c.2) carrying out optimization calculation on the value of the weighting coefficient by adopting a cuckoo algorithm to obtain the weighting coefficient alpha which is most suitable for the target function;
(c.3) obtaining the final operating parameter weight λ ═ α ×, λ1+(1-α)*λ2；
Wherein λ is1Means that a first weight, λ, is integrated2Means integrating the second weight, alpha is a weighting coefficient, and alpha is more than 0 and less than 1.
Preferably, in the method for detecting an operating state of an integrated oil-filled capacitive bushing, a detected value HV ═ L λ of the operating state of the oil-filled capacitive bushing is obtainedT；
Wherein, λ is an operation parameter weight set, and L is an operation parameter relative degradation degree set.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) the invention provides a method for detecting the running state of an oil-immersed capacitor bushing, which respectively determines the weight of a running parameter by an analytic hierarchy process in a subjective weighting method and an entropy weighting method in an objective weighting method; integrating the determined main weight value and the determined objective weight value respectively by using an optimized Cuckoo Search (CS) algorithm to obtain a final weight; the method can reflect expert experience data and combine actual operation data of the bushing, so that a theoretical experience value of the weight can be reflected, and the weight ratio of each parameter can be objectively calculated, so that the evaluation value of the operation state of the oil-immersed capacitor bushing is closer to the actual operation state of the oil-immersed capacitor bushing;
(2) the method for detecting the running state of the oil-immersed capacitor sleeve has the advantages of comprehensive evaluation factors, clear quantification and strong operability, and can provide a visual evaluation result; the method can be combined into a large platform for on-line monitoring of the field device, provides auxiliary information for device fault diagnosis, and has strong practicability.
Drawings
Fig. 1 is an operation parameter system schematic diagram of an operation state of an oil-immersed capacitor bushing provided by an embodiment;
fig. 2 is a schematic flow chart of a method for detecting an operating state of an oil-immersed capacitive bushing according to an embodiment;
fig. 3 is a schematic flow chart of the cuckoo algorithm employed in the embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 1, the system of the operation parameters adopted in an embodiment of the method for detecting the operation state of the oil-immersed capacitor bushing provided by the present invention specifically includes dielectric loss to the end screen, capacitance change rate, insulation resistance of the end screen of the bushing to the ground, and H in the bushing oil2Gas content, C in casing oil2H2Maintenance times of gas content and oil-immersed type capacitor bushingAnd (4) counting.
Referring to fig. 2, a flow of the method for detecting the operation state of the oil-immersed capacitive bushing provided in the embodiment specifically includes the following steps:
(1) obtaining the operation parameters of the oil-immersed capacitor bushing to be measured, including dielectric loss to the ground screen, capacitance change rate, insulation resistance of the bushing end screen to the ground, and H in the bushing oil2Gas content, C in casing oil2H2Gas content and maintenance frequency of the oil-immersed capacitor bushing;
(2) acquiring a relative degradation degree set formed by the relative degradation degrees of various operation parameters;
(3) obtaining an operation state detection value of the oil-immersed type capacitor bushing according to the relative degradation degree set and a corresponding operation parameter weight set obtained by an operation parameter weight model;
wherein the step (3) comprises
(a) Obtaining a first weight of each operation parameter by adopting an analytic hierarchy process;
(b) acquiring a second weight of each operation parameter by adopting an entropy weight method;
(c) integrating the first weight and the second weight of each operation parameter by adopting an optimized cuckoo algorithm to obtain the final weight occupied by each operation parameter;
the adopted cuckoo algorithm has the basic idea that nest parasitic behaviors of cuckoos are effectively combined with Levy flight of birds or fruit flies; in the algorithm, the Levy flight can ensure that the algorithm has better global search performance, and can also ensure local search capability based on host nest discovery probability, so that the local search and the global search can be effectively combined, and the obtained solution accuracy is higher; the basic flow of the cuckoo algorithm is shown in fig. 3, and specifically as follows:
firstly, constructing an objective function: f (x), x ═ x1,…,xd)T；
② initializing population, generating n nest (solution) xi(i＝1,2,…,n)；
Judging whether the maximum iteration times or termination conditions are reached;
fourthly, when the termination condition is not met, performing circular calculation, and finding out the current optimal solution through local search and global search;
when the final condition is reached, outputting the current optimal solution as the final solution of the optimal value.
(d) And integrating the relative degradation degrees of the operation parameters according to the final weight to obtain an evaluation value of the operation state of the oil-immersed type capacitor bushing.
In the embodiment, the relative degradation degree is used for representing the degradation degree of the actual condition of the parameter compared with the fault condition, and the value of the relative degradation degree is between 0 and 1; reflecting the degradation degree of the parameter under the current condition according to different values;
for smaller and more optimal parameters, the relative degradation is calculated as:
for larger and more optimal parameters, the relative degradation is calculated as:
wherein, CiIs the current value of the parameter i; cmaxAn upper threshold value of a specified range for the i parameter; cminA lower threshold of the range is specified for the i parameter.
In an embodiment, the threshold range of the operating parameter C2-1 of the dielectric loss of the oil-immersed type capacitor bushing to the ground screen is [800, 2000%]Relative degree of deterioration thereof
The threshold value range of the capacitance change rate C2-2 is [1.5, 2.0 ]]Relative degree of deterioration thereof
The threshold range of the bushing end screen insulation resistance to ground C2-3 is [30, 50 ]]Relative degree of deterioration thereof
H in casing oil2The threshold range of the gas content C2-4 is [0, 0.8%]Relative degree of deterioration thereof
In casing oil C2H2The threshold range of the gas content C2-5 is [0, 2%]Relative degree of deterioration thereof
The threshold range of the maintenance frequency C2-6 of the oil-immersed capacitor bushing is [0,2 ]]Relative degree of deterioration thereof
Each operation parameter forms a relative degradation degree set L ═ Lc2-1lc2-2lc2-3lc2-4lc2-5lc2-6]。
In the examples, step (a) is specifically as follows:
the method for carrying out weight distribution on the 6 operation parameters of the oil-immersed capacitor bushing by adopting the subjective weighting method of the analytic hierarchy process specifically comprises the following steps:
(a.1) establishing a priority relation matrix M representing three kinds of expert opinions by using a three-scale method1、M2、M3(the examples are given for the purpose of illustration only, sinceAnd randomly generated):
priority relation matrix M ═ Mij)n×nSatisfies the following conditions:
element m of ith row and jth column in matrixij≥0；mij+mji＝1；mii＝0.5；
Table 1 below is a three-scale quantization table in the examples;
TABLE 1 quantization table by three-scale method
| mij | Comparison of degree of |
| 1 | Parameter i is more important than parameter j |
| 0.5 | Parameter i is as important as parameter j |
| 0 | Parameter j is more important than parameter i |
(a.2) integrating the priority relation matrixes, wherein the specific method comprises the following steps:
synthesizing multiple expert experiences to make mijThe method is closer to the actual situation; suppose there is k (k is more than or equal to 2) bit expert baseIn the three-scale method for mijThe judgment is as follows: m isij 1，mij 2，…，mij kThen the expected value of the decision is:
the final decision value is determined from the expected value as follows:
obtaining a final priority relation matrix M according to the final judgment value:
(a.3) converting the final priority relation matrix M into a fuzzy consistent matrix F:
(a.4) according to the fuzzy consistent matrix F, performing the following processing to obtain the initial weight distribution of the parameters:
first, the sum of each row of elements (not compared to itself) in the fuzzy consensus matrix F is found:
the sum of the elements (without diagonal elements) in the fuzzy consensus matrix F is then found:
wherein h isiIndicates the degree of importance of the parameter i relative to the overall parameter, for hiIs subjected to normalizationAnd acquiring weight distribution corresponding to each parameter:
obtaining initial weight distribution of the parameters according to the weight distribution corresponding to each parameter:
W＝(ω1,ω2,…,ωn)T(8)
in an embodiment, the resulting initial weight assignment W ═ 00.23060.26940.26940.23060]T
(a.5) calculating a final weight distribution according to the initial weight distribution, specifically as follows:
firstly, the fuzzy consistent matrix F is converted into a reciprocal matrix E ═ Eij)n×n：
Then, the initial weight distribution W is used as an iteration initial value V0And then further acquiring final weight distribution D with higher precision, wherein the specific method comprises the following steps:
let V0＝(v01,v02,…,v0n)T＝W＝(ω1,ω2,…,ωn)TAs an iteration initial value, V is obtained by the iteration formula (10)k+1Then, V is calculatedk+1The component max (V) having the largest absolute valuek+1)；
Vk+1＝E*Vk (10)
Finally, the precision calculation is carried out, if max (V)k+1)-max(Vk) < ε (ε is calculation accuracy, in this example ε is ≦ 0.001), then max (V)k+1) As a main eigenvalue λmaxTo V pairk+1Carrying out normalization processing to obtain final weight vector distribution D, and ending circulation;
if max (V)k+1)-max(Vk) If is greater than epsilon and does not meet the precision requirement, V is setkAs a new initial quantity, iteration is performed again, and the final weight assignment is obtained by looping, wherein
Obtaining a first set of weights lambda consisting of first weights for the operating parameters1；
λ1＝[0.1796 0.1519 0.1519 0.1519 0.1519 0.2128]。
In the examples, step (b) is specifically as follows:
the method for carrying out weight distribution on the 6 operation parameters of the oil-immersed capacitor bushing by adopting the entropy weight method which is an objective weighting method specifically comprises the following steps:
(b.1) evaluating the 6 operation parameters by using three selected expert opinions to form an evaluation matrix R of 6 x 2 orders:
(b.2) performing dimensionless processing on the numerical values in the evaluation matrix to obtain a matrix S:
(b.3) normalizing the matrix S obtained by the dimensionless process to obtain a matrix S':
(b.4) calculating the entropy value and the difference coefficient of each operation parameter:
H1＝0.9544；α1＝0.0456；
H2＝0.6307；α2＝0.3693；
H3＝0.9989；α3＝0.0011；
H4＝0.8669；α4＝0.1331；
H5＝0.8864；α5＝0.1136；
H6＝0.8559；α6＝0.1441；
wherein H1～H6Entropy, α, corresponding to 6 operating parameters, respectively1～α6Difference coefficients corresponding to 6 operating parameters, respectively;
(b.5) obtaining a second weight set composed of second weights of the operation parameters according to the entropy value and the difference coefficient of each operation parameter and an objective entropy weight calculation formula
λ2＝[0.0565 0.4577 0.0014 0.1650 0.1408 0.1786]。
The optimization integration of the first weight and the second weight by adopting an optimized cuckoo algorithm specifically comprises the following substeps:
(c.1) constructing the following objective function based on the principle of minimum discrimination information
Wherein p refers to the number of the operating parameter,
(c.2) integrating the first weight set and the second weight set to make the integrated function and the first weight and the second weight as close as possible,
obtaining the final weight lambda alpha lambda1+(1-α)*λ2(ii) a Wherein alpha is more than 0 and less than 1;
and (c.3) performing optimization calculation on the weighting coefficient alpha value by applying matlab and adopting a cuckoo algorithm to obtain the weighting coefficient alpha which is most suitable for the target function and is 0.5, and further obtaining the final weight lambda after integration.
In the embodiment, the operation condition detection value HV ═ L ×. λ of the oil-filled capacitive bushing is obtained according to the final weightT；
Wherein: HV is an operation condition detection value; l is a relative degradation degree set of the operation parameters; lambda is the final weight of the operating parameter; the value range of HV is 0-1, and the larger the HV value is, the better the health condition of the sleeve is.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (5)
1. The method for detecting the running state of the oil-immersed type capacitor bushing is characterized by comprising the following steps of:
(1) obtaining the operation parameters of the oil-immersed capacitor bushing to be measured, including dielectric loss to the ground screen, capacitance change rate, insulation resistance of the bushing end screen to the ground, and in the bushing oilH 2Gas content, in casing oilC 2 H 2Gas content and maintenance frequency of the oil-immersed capacitor bushing;
(2) acquiring a relative degradation degree set formed by the relative degradation degrees of various operation parameters;
(3) obtaining an operation state detection value of the oil-immersed type capacitor bushing according to the relative degradation degree set and a corresponding operation parameter weight set obtained by an operation parameter weight model;
the method for obtaining the corresponding operation parameter weight by the operation parameter weight model comprises the following steps:
(a) determining a first weight of the operating parameter using an analytic hierarchy process;
(b) determining a second weight of the operating parameter by using an entropy weight method;
(c) and obtaining an optimal weighting coefficient by adopting a cuckoo algorithm, integrating the first weight and the second weight, enabling the weight obtained by integration to be as close as possible to an objective function of the constructed operation parameter weight model, and obtaining the weight of each operation parameter to form an operation parameter weight set.
2. The method for detecting the operating state of the oil-filled capacitive bushing according to claim 1,
the threshold range of the dielectric loss C2-1 of the earth end screen is [800, 2000 ]]Relative degree of deterioration thereof
；
The threshold value range of the capacitance change rate C2-2 is [1.5, 2.0 ]]Relative degree of deterioration thereof
；
The threshold range of the bushing end screen insulation resistance to ground C2-3 is [30, 50 ]]Relative degree of deterioration thereof
；
In casing oilH 2The threshold range of the gas content C2-4 is [0, 0.8%]Relative degree of deterioration thereof
；
In casing oilC 2 H 2The threshold range of the gas content C2-5 is [0, 2%]Relative degree of deterioration thereof
；
The threshold range of the maintenance frequency C2-6 of the oil-immersed capacitor bushing is [0,2 ]]Relative degree of deterioration thereof
。
3. The oil-filled capacitive bushing operating state detection method according to claim 1 or 2, wherein step (a) comprises the following substeps:
(a.1) establishing a priority relation matrix representing three expert opinions by using a three-scale method;
(a.2) obtaining the expected value judged for each value in each priority relation matrix, obtaining the judgment value according to the expected value and a preset three-scale quantization table, and obtaining an integrated priority relation matrix according to the judgment valueM；
(a.3) integrating the obtained priority relation matrixMConversion to fuzzy consistent matrixF：
(a.4) on the fuzzy uniform matrixFNormalizing the sum of each row of elements to obtain the initial weight distribution corresponding to each parameter:
and (a.5) taking the initial weight distribution as an iteration initial value to carry out iteration to obtain a first weight of the operation parameter.
4. The oil-filled capacitive bushing operating state detection method according to claim 1 or 2, wherein step (b) comprises the following substeps:
(b.1) evaluating the operational parameters using the selected expert opinions to form an evaluation matrixR：
(b.2) evaluation matrix of pairsRThe elements in (1) are subjected to dimensionless processing to obtain a matrixS：
(b.3) matrix obtained by dimensionless processingSPerforming normalization processing to obtain matrixS’：
(b.4) matrix obtained from normalizationS’Calculating the entropy and difference coefficients of the operating parameters:
and (b.5) obtaining the second weight of each operation parameter by adopting an objective entropy weight method calculation formula according to the entropy value and the difference coefficient of each operation parameter.
5. The method for detecting the operating state of the oil-immersed capacitive bushing according to claim 1 or 2, wherein the oil is immersedRunning state detection value of capacitor bushing
；
Wherein,λrefers to a set of operating parameter weights,Lrefers to a set of operating parameters versus a degree of degradation.
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