CN115375156A - Composite insulator state evaluation method, system and computer equipment - Google Patents
Composite insulator state evaluation method, system and computer equipment Download PDFInfo
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Abstract
The embodiment of the invention provides a composite insulator state evaluation method, which comprises the following steps: determining a state quantity evaluation index of the composite insulator to form a state quantity evaluation index matrix; performing a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in a state quantity evaluation index matrix to obtain a rank matrix; obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value; according to the state quantity evaluation index weight value, obtaining a rank sum ratio estimation value and a probability unit of each evaluation object; determining a linear regression equation between the rank sum ratio estimation value of each evaluation object and the probability unit, and obtaining the rank sum ratio of each evaluation object according to the linear regression equation; and determining the state of the composite insulator according to the rank and the ratio of each evaluation object. The method of the embodiment of the invention integrates two methods of subjective weighting and objective weighting to determine the weight of the selected state quantity, so as to overcome the defect of adopting a single weighting method.
Description
Technical Field
The invention relates to the field of electric power, in particular to a composite insulator state evaluation method, a composite insulator state evaluation system, computer equipment and a computer readable storage medium.
Background
The silicon rubber composite insulator has the advantages of light weight, high mechanical strength, strong hydrophobicity and hydrophobic mobility, high pollution-resistant lightning voltage, simple manufacturing process, convenient maintenance and the like, can effectively inhibit the occurrence of pollution flashover accidents of a power grid after being used, and is widely applied at home and abroad. However, with the increase of the operating life, the composite insulator is inevitably affected by various environmental factors such as illumination, humidity, temperature difference, dirt and the like in the outdoor operation process for a long time, and the composite insulator is also affected by strong electric field and strong mechanical force, so that the composite insulator can be aged in different degrees. Therefore, in order to ensure safe and stable operation of the power system, it is necessary to perform evaluation of the aging state of the insulator.
The state evaluation of the composite insulator relates to multiple indexes and multiple levels, most of the research at home and abroad focuses on evaluating the pollution of the composite insulator at present, and a method for evaluating the overall state of the composite insulator is lacked.
How to evaluate the overall state of the composite insulator is a problem to be solved urgently at present.
Disclosure of Invention
The embodiment of the invention provides a composite insulator state evaluation method, which aims to solve the problem that the overall state of a composite insulator is not evaluated in the prior art. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
The embodiment of the invention provides a composite insulator state evaluation method, which comprises the following steps:
determining a state quantity evaluation index of the composite insulator to form a state quantity evaluation index matrix;
performing a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in a state quantity evaluation index matrix to obtain a rank matrix;
obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value;
obtaining rank and ratio estimation values and probability units of all evaluation objects according to the state quantity evaluation index weight values;
determining a linear regression equation between the rank sum ratio estimation value of each evaluation object and the probability unit, and obtaining the rank sum ratio of each evaluation object according to the linear regression equation;
and determining the state of the composite insulator according to the rank and the ratio of each evaluation object.
Optionally, the step of determining the subjective weight value includes:
assigning a subjective weight value to the state quantity evaluation index;
determining a judgment matrix according to the mutual importance degree between the state quantity evaluation indexes;
if the judgment matrix passes the consistency test, the subjective weight value is assigned reasonably, and if the judgment matrix does not pass the consistency test, the subjective weight value is adjusted.
Optionally, the step of determining the determination matrix according to the mutual importance degree between the state quantity evaluation indexes includes:
and determining the judgment matrix by a calibration method by comparing the mutual importance degrees of the state quantity evaluation indexes.
Optionally, the step of checking the consistency of the judgment matrix includes:
and when the consistency check index of the judgment matrix is smaller than the set threshold, the judgment matrix passes the consistency check.
Optionally, the step of adjusting the subjective weight value if the determination matrix fails the consistency check includes: and readjusting the mutual importance degree among the evaluation indexes until the judgment matrix passes the consistency test.
Optionally, the step of determining the objective weight value includes:
and determining an objective weight value according to the variation coefficient of each state quantity evaluation index.
Optionally, the objective weight value calculation formula is as follows:
in the formula: lambda [ alpha ] i Coefficient of variation, σ, representing the i-th state quantity evaluation index i A standard deviation indicating the i-th state quantity evaluation index,
represents the average of the i-th state quantity evaluation indexes,
and an objective weight value representing the ith state quantity evaluation index.
Optionally, the state quantity evaluation index weight value calculation formula is as follows:
in the formula: w i Represents the i-th state quantity evaluation index weight value, omega i The subjective weight value of the ith state quantity evaluation index is expressed,
and the objective weight value of the ith state quantity evaluation index is represented.
Optionally, the step of obtaining the rank sum ratio estimation value of each evaluation object according to the state quantity evaluation index weight value includes:
when the weight values of the state quantity evaluation indexes are the same, the rank sum ratio evaluation value delta of the evaluation object is calculated according to the following formula RSRi ：
In the formula: i =1,2,. ·, m; r ij The rank of the ith row and jth column element of the rank matrix R.
Optionally, the step of obtaining the rank sum ratio estimation value of each evaluation object according to the state quantity evaluation index weight value includes:
when the weighted values of the state quantity evaluation indexes are different, the rank sum ratio estimation value delta of the evaluation object is calculated according to the following formula WRSRi ：
In the formula: i =1,2,. Said, m; omega j Weight value of the jth evaluation index, ∑ ω j ＝1，R ij The rank of the ith row and jth column element.
Optionally, the probability unit is obtained by:
compiling a rank sum ratio estimation value frequency distribution table, taking the same values as a group, and listing frequency f and accumulated frequency sigma f of each group of rank sum ratio estimation values;
determining rank range R and average rank for each set of rank sum ratio estimates
Calculate the percentage of average rank
The last accumulated frequency is corrected according to 1-1/4 m;
p is to be i Conversion into probability unit P of i-th evaluation object robiti Probability unit P robiti By the followingThe formula is determined:
P robiti ＝u(p i )+5
in the formula: u (p) i ) Expressed as a percentage p i The corresponding standard normal dispersion.
Optionally, the step of determining a linear regression equation between the rank sum ratio estimation value and the probability unit of each evaluation object includes:
and determining a linear regression equation by taking the probability unit corresponding to the accumulated frequency as an independent variable and taking the rank sum ratio estimation value as a dependent variable.
Optionally, the linear regression equation is:
δ RSRi (or delta) WRSRi )＝a+b×P robiti
In the formula: delta RSRi Or delta WRSRi To evaluate the rank sum ratio estimate of the object, P robiti Is a probability unit, a and b are coefficients to be determined, and the coefficients are obtained when a linear regression equation is calculated by means of simulation software.
Optionally, the step of determining the state of the composite insulator according to the rank sum ratio of each evaluation object includes: and performing grading sequencing on each evaluation object according to the probability unit, and determining the state of the composite insulator according to the grading corresponding to the rank and the ratio of each evaluation object.
Optionally, the step of performing rank ordering on each evaluation object according to a probability unit includes:
determining the number of the grading;
and calculating a grading critical value by using the linear regression equation by using the probability unit critical value as an independent variable, and grading and sequencing each evaluation object.
The embodiment of the invention also provides a composite insulator state evaluation system, which comprises:
the state quantity evaluation index matrix module is used for determining state quantity evaluation indexes of the composite insulator and forming a state quantity evaluation index matrix;
the rank matrix module is used for carrying out a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in the state quantity evaluation index matrix to obtain a rank matrix;
the weight value module is used for obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value;
the rank sum ratio estimation value and probability unit module is used for estimating the index weight value according to the state quantity to obtain the rank sum ratio estimation value and the probability unit of each estimation object;
the system comprises a rank and ratio module, a probability unit and a probability unit, wherein the rank and ratio module is used for determining a linear regression equation between a rank and ratio estimation value and the probability unit of each evaluation object and obtaining the rank and ratio of each evaluation object according to the linear regression equation;
and the state determining module is used for determining the state of the composite insulator according to the rank and the ratio of each evaluation object.
The embodiment of the present invention further provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method according to any one of the above embodiments when executing the computer program.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method according to any of the above embodiments.
The technical scheme provided by the embodiment of the invention has the following beneficial effects:
according to the method, the state quantity evaluation index weighted value is obtained according to the subjective weighted value and the objective weighted value, the running state of the composite insulator is evaluated, and the defect of adopting a single weighting method is overcome; the method not only can evaluate the state of a single string of composite insulators, but also can comprehensively evaluate and sort the running states of a plurality of strings of composite insulators.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flow chart illustrating a composite insulator state assessment method according to an exemplary embodiment;
FIG. 2 is a schematic diagram of a composite insulator state assessment system shown in accordance with an exemplary embodiment;
FIG. 3 is a schematic diagram illustrating a composite insulator state assessment system in accordance with an exemplary embodiment;
FIG. 4 is a schematic diagram illustrating the structure of a computer device according to an example embodiment.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments herein to enable those skilled in the art to practice them. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the embodiments herein includes the full ambit of the claims, as well as all available equivalents of the claims. The terms "first," "second," and the like, herein are used solely to distinguish one element from another element without requiring or implying any actual such relationship or order between such elements. In practice, a first element can also be referred to as a second element, and vice versa. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such structure, apparatus, or device. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a structure, device, or apparatus that comprises the element. The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like herein, as used herein, are defined as orientations or positional relationships based on the orientation or positional relationship shown in the drawings, and are used for convenience in describing and simplifying the description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the present invention. In the description herein, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may include, for example, mechanical or electrical connections, and communication between two elements, and may include direct connection and indirect connection through intervening media, where the meaning of the terms is to be understood by those skilled in the art as appropriate.
Herein, the term "plurality" means two or more, unless otherwise specified.
Herein, the character "/" indicates that the preceding and following objects are in an "or" relationship. For example, A/B represents: a or B.
Herein, the term "and/or" is an associative relationship describing objects, meaning that three relationships may exist. For example, a and/or B, represents: a or B, or A and B.
The embodiments and features of the embodiments of the invention may be combined with each other without conflict.
Fig. 1 shows an embodiment of a composite insulator state evaluation method.
As shown in fig. 1, the present embodiment discloses a method for evaluating a state of a composite insulator, including the following steps:
the method comprises the following steps of S1, determining a state quantity evaluation index of the composite insulator to form a state quantity evaluation index matrix A;
s2, performing a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in the evaluation index matrix A to obtain a rank matrix R;
s3, obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value;
s4, obtaining rank and ratio estimated values and probability units of all the evaluation objects according to the state quantity evaluation index weight values;
s5, determining a linear regression equation between the rank sum ratio estimation value and the probability unit of each evaluation object, and obtaining the rank sum ratio of each evaluation object according to the linear regression equation;
and S6, determining the state of the composite insulator according to the rank and the ratio of each evaluation object.
The order of step S2 and step S3 in this embodiment may be reversed.
The state evaluation method for the composite insulator disclosed by the embodiment integrates two methods of subjective weight value assignment and objective weight value assignment, determines the state quantity evaluation index weight value, and can overcome the defect of adopting a single weighting method.
Optionally, in the step of determining the state quantity evaluation index of the composite insulator and forming the state quantity evaluation index matrix a, from three aspects of a preliminary test, an electrical test and a mechanical performance test, an index having a large influence on the operating state of the insulator is determined by using a principal component analysis method, and the state quantity evaluation index matrix a is formed. Specifically, the state quantity evaluation index of the composite insulator is selected according to one or more of the parameters of visual inspection, a hardness test, a hydrophobicity test, a sheathed water diffusion test, tracking and corrosion resistance, a stress corrosion test, a tear strength test, a tensile strength test, elongation at break, a rated mechanical load test, a mechanical failure load test, an operating life, a pollution test and an infrared temperature rise. Assuming that m evaluation objects (i.e., composite insulators) are provided, each evaluation object has n state quantity evaluation indexes, and the jth state quantity evaluation index of the ith evaluation object is represented as a ij Thus, the state quantity evaluation index matrix a = (a) is constructed ij ) m×n 。
For example, as shown in fig. 2, 14 state quantity evaluation indexes A1, A2 \8230 \ 8230 \ 8230a 14, I1, I2 \8230 \ 8230 \ 8230, I78 representing 78 evaluation targets were determined, and the state quantity evaluation indexes of the composite insulators are shown in table 1:
TABLE 1
| Index (es) | I1 | I2 | I3 | I4 | I5 | I6 | I7 | I8 | … | I78 |
| A1 | 1 | 0.4 | 0.8 | 0.8 | 1 | 1 | 1 | 0.5 | … | 1 |
| A2 | 73.25 | 60.375 | 65.625 | 71.625 | 65.125 | 66.25 | 65.375 | 67.625 | … | 67 |
| A3 | 3 | 3 | 3 | 3 | 3 | 3 | 2 | 3 | … | 4 |
| A4 | 98 | 92.5 | 155.5 | 87 | 112 | 99.5 | 98 | 140.5 | … | 99.5 |
| A5 | 2.58 | 5 | 3.53 | 3.4 | 0.6 | 3.21 | 0.42 | 3.49 | … | 0.66 |
| A6 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0.1 | … | 1 |
| A7 | 9.4 | 7.6 | 7.9 | 9.6 | 7.6 | 9.4 | 8.2 | 9.4 | … | 8.3 |
| A8 | 3.3 | 2.8 | 2.9 | 2.5 | 3.3 | 2.7 | 3.7 | 4 | … | 5.7 |
| A9 | 0.756 | 0.356 | 0.5 | 0.696 | 0.844 | 0.808 | 0.468 | 0.844 | … | 1.228 |
| |
100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | … | 120 |
| A11 | 151 | 163 | 161 | 147 | 156 | 126 | 148 | 152 | … | 143 |
| A12 | 13 | 14 | 15 | 20 | 14 | 12 | 14 | 24 | … | 11 |
| A13 | 0.9217 | 0.08026 | 0.1269 | 0.0829 | 0.16674 | 0.1013 | 0.161 | 0.10084 | … | 0.04686 |
| A14 | 0.7 | 0.1 | 0.7 | 0.7 | 0.2 | 0.7 | 2.3 | 0.8 | … | 0.933 |
Optionally, the step of performing a state quantity test on each evaluation object specifically includes: composite insulators of different manufacturers, different operation years and different operation environments are selected and inspected from power transmission lines in different areas, and one or more combinations of apparent state, hydrophobicity test, electrical performance test, mechanical performance test and other tests are respectively carried out on the selected and inspected composite insulators. Optionally, the apparent state is scored according to the standard JBT10945 for composite insulators. Alternatively, the hydrophobicity test is run according to standard DLT376 to obtain a HC (water jet fractionation) rating. Alternatively, the electrical performance test is performed according to standard GBT6553 and standard GBT 22079. Alternatively, the mechanical property test is performed according to standard GBT528 and standard GBT19519, and test results are obtained.
And if m evaluation objects are selected and each object has n evaluation indexes, each evaluation index has m evaluation objects, and the values of the corresponding evaluation objects of each evaluation index are sequenced and ranked to obtain the rank matrix R. Specifically, the order r of each evaluation index corresponding to each evaluation object is written in sequence for the state quantity evaluation index matrix a ij . The following principles should be followed in the process of ranking: the benefit type index (the larger the index value is, the better the index value is) adopts a mode of rank arrangement from small to large; the cost index (the smaller the index value, the better) is ranked from large to small. And the same data values of the evaluation indexes of the same state quantity are the same and the average rank is compiled. The rank matrix R = (R) can be obtained according to the above principle ij ) m×n 。
The rank matrix of the state quantity evaluation index shown in table 1 is shown by the following equation:
optionally, the step of determining the subjective weight value includes: giving subjective weight values to the state quantity evaluation indexes; determining a judgment matrix according to the mutual importance degree between the state quantity evaluation indexes, and determining an element E in the judgment matrix ij I.e. the importance of i to j; if the judgment matrix passes the consistency test, the subjective weight value is assigned reasonably, and if the judgment matrix does not pass the consistency test, the subjective weight value is adjusted.
Optionally, the step of assigning a subjective weight value to the state quantity evaluation index includes: and (4) selecting an analytic hierarchy process to endow the state quantity evaluation index with a subjective weight value.
Alternatively, the determination matrix E is determined according to the degree of mutual importance between the state quantity evaluation indexes ij Comprises the following steps: by comparing the mutual importance degree among n state quantity evaluation indexes, the judgment matrix E is realized by adopting a scaling method ij And (4) determining.
In order to verify the reasonableness of the structure of the judgment matrix, a consistency check is required, and optionally, the step of judging that the matrix passes the consistency check comprises the following steps: and when the consistency check index of the judgment matrix is smaller than the set threshold, the judgment matrix passes the consistency check. For example, when the consistency check index CR<When the value is 0.1, the judgment matrix is reasonable in structure through inspection. According to the constructed judgment matrix, the subjective weight value omega of each state quantity evaluation index can be calculated i . Specifically, the judgment matrix is normalized according to columns, then the normalized rows are added, each element in the vector obtained after addition is divided by the number n of the state quantity evaluation indexes to obtain a weight vector, and then the subjective weight value omega can be obtained i 。
Optionally, if the determination matrix fails the consistency check, the step of adjusting the subjective weight value includes: readjusting the mutual importance degree between the evaluation indexes to ensure that the importance degree between every two evaluation indexes accords with logic until the judgment matrix passes consistency test.
Optionally, the step of determining the objective weight value includes: and determining an objective weight value according to the variation coefficient of each state quantity evaluation index. In the embodiment of the invention, a variation coefficient method is selected to carry out objective weight value assignment on each state quantity evaluation index. The variation coefficient method fully utilizes the state information contained in each state quantity evaluation index to obtain objective weight value assignment. Because the dimension of each state quantity evaluation index is different in the state quantity evaluation index system, the variation coefficient of each state quantity evaluation index can be used for reflecting the differentiation degree of each state quantity evaluation index value.
Optionally, the objective weight value calculation formula is as follows:
in the formula: lambda [ alpha ] i Coefficient of variation, σ, representing the i-th state quantity evaluation index i Indicates the standard deviation of the i-th state quantity evaluation index,
represents the average of the i-th state quantity evaluation indexes,
an objective weight value representing the ith state quantity evaluation index.
In the embodiment of the invention, the combination of the subjective weight value and the objective weight value is adopted to weight each state quantity evaluation index, and the calculation formula of the state quantity evaluation index weight value is as follows:
in the formula: w i Indicating the i-th state quantity evaluationWeight of index, ω i The subjective weight value of the ith state quantity evaluation index is expressed,
and the objective weight value of the ith state quantity evaluation index is represented.
Optionally, the step of obtaining the rank and ratio estimation value of each evaluation object according to the state quantity evaluation index weight value includes:
when the weight values of the state quantity evaluation indexes are the same, the rank sum ratio evaluation value delta of the evaluation object is calculated according to the following formula RSRi ：
In the formula: i =1,2,. ·, m; r ij Is the rank of the ith row and jth column element of the rank matrix R.
Optionally, the step of obtaining the rank and ratio estimation value of each evaluation object according to the state quantity evaluation index weight value includes: when the weighted values of the various state quantity evaluation indexes are different, the rank sum ratio estimation value delta of the evaluation object is calculated according to the following formula WRSRi ：
In the formula: i =1,2,. Said, m; omega j Weight value of the jth evaluation index, ∑ ω j ＝1，R ij The rank of the ith row and jth column elements.
Optionally, the probability unit is obtained by: evaluating the rank sum ratio of the evaluation objects to estimate the value delta RSRi Or delta WRSRi Arranging the two groups into a row from small to large, taking the two groups with the same value as a group, and compiling a rank-sum ratio estimation value frequency distribution table; listing frequency f and accumulated frequency sigma f of each group of rank sum ratio estimated values; determining rank range R and average rank for each set of rank-sum ratio estimates
Calculating average rankPercentage of times
The last accumulated frequency is corrected according to 1-1/4 m; p is to be i Conversion into probability unit P of i-th evaluation object robiti Probability unit P robiti The determination is made by the following formula:
P robiti ＝u(p i )+5
in the formula: u (p) i ) Expressed as a percentage p i The corresponding standard normal dispersion. The corresponding relationship between the percentage of the average rank and the probability unit can be obtained by table lookup.
The frequency distribution table of rank-sum ratio estimation values obtained from the state quantity evaluation indexes shown in table 1 is shown in table 2:
TABLE 2
Optionally, the step of determining a linear regression equation between the rank sum ratio estimation value and the probability unit of each evaluation object includes: by the probability unit P corresponding to the cumulative frequency robiti As independent variable, estimate delta by rank-sum ratio RSRi Or delta WRSRi For the dependent variable, a linear regression equation is determined.
Optionally, the linear regression equation is:
δ RSRi (or delta) WRSRi )＝a+b×P robiti
In the formula: delta RSRi Or delta WRSRi To evaluate the rank sum ratio estimate of the object, P robiti Is a probability unit, a and b are coefficients to be determined, and the coefficients are obtained by calculating a linear regression equation by means of simulation software.
Optionally, the step of determining the state of the composite insulator according to the rank and the ratio of each evaluation object includes performing grading sequencing on each evaluation object according to the probability unit, and determining the state of the composite insulator according to the grading corresponding to the rank and the ratio of each evaluation object. Optionally, the step of performing rank ordering on each evaluation object according to the probability unit includes: determining the number of the grading; and calculating a grading critical value by using the probability unit critical value as an independent variable through a linear regression equation, and grading and sequencing each evaluation object.
In particular, according to the probability unit P robiti And (4) grading each evaluation object, wherein the variances of all grades are consistent and are the best grade, the grades are generally graded by 3-5 grades, and the probability unit critical value under the common grade condition can be obtained by table lookup. And after the grading number is determined, calculating the grading critical value by using the probability unit critical value as an independent variable through a linear regression equation, thereby realizing grading sequencing of the evaluation objects. In order to unify the evaluation results to the related regulations of the composite insulator as much as possible, the final results can be classified into four grades, that is, 3 probability unit critical values are determined, for example, the final results are classified into four grades of good, general, early warning and abnormal.
Optionally, the method of the embodiment of the present invention performs state evaluation on the composite insulator based on the WRSR model.
As shown in fig. 3, in another embodiment, there is also provided a composite insulator state evaluation system, including: a state quantity evaluation index matrix module 100, configured to determine a state quantity evaluation index of the composite insulator, and form a state quantity evaluation index matrix; the rank matrix module 200 is configured to perform a state quantity test on each evaluation object to obtain a rank of each evaluation object of each evaluation index in the state quantity evaluation index matrix, and obtain a rank matrix; a weight value module 300, configured to obtain a state quantity evaluation index weight value according to the subjective weight value and the objective weight value; a rank sum ratio estimation value and probability unit module 400, configured to obtain a rank sum ratio estimation value and a probability unit of each evaluation object according to the state quantity evaluation index weight value; the rank and ratio module 500 is configured to determine a linear regression equation between the rank and ratio estimation value of each evaluation object and the probability unit, and obtain the rank and ratio of each evaluation object according to the linear regression equation; and a state determining module 600, configured to determine a state of the composite insulator according to the rank and the ratio of each evaluation object.
The working principle of the composite insulator state evaluation system in this embodiment is the same as that of the composite insulator state evaluation method in each of the above embodiments, and details are not repeated here.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing static information and dynamic information data. The network interface of the computer device is used for communicating with an external terminal through a network connection. Which computer program is executed by a processor to carry out the steps in the above-described method embodiments.
Those skilled in the art will appreciate that the configuration shown in fig. 4 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing devices to which aspects of the present invention may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. Non-volatile memory may include Read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
The present invention is not limited to the structures that have been described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (18)
1. A composite insulator state evaluation method is characterized by comprising the following steps:
determining a state quantity evaluation index of the composite insulator to form a state quantity evaluation index matrix;
performing a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in a state quantity evaluation index matrix to obtain a rank matrix;
obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value;
according to the state quantity evaluation index weight value, obtaining a rank sum ratio estimation value and a probability unit of each evaluation object;
determining a linear regression equation between the rank sum ratio estimation value of each evaluation object and the probability unit, and obtaining the rank sum ratio of each evaluation object according to the linear regression equation;
and determining the state of the composite insulator according to the rank and the ratio of each evaluation object.
2. The method for evaluating the condition of a composite insulator according to claim 1,
the step of determining the subjective weight value comprises the following steps:
assigning a subjective weight value to the state quantity evaluation index;
determining a judgment matrix according to the mutual importance degree between the state quantity evaluation indexes;
if the judgment matrix passes the consistency test, the subjective weight value is assigned reasonably, and if the judgment matrix does not pass the consistency test, the subjective weight value is adjusted.
3. The method for evaluating the condition of a composite insulator according to claim 2,
the step of determining the judgment matrix according to the mutual importance degree between the state quantity evaluation indexes comprises the following steps:
and determining the judgment matrix by a calibration method by comparing the mutual importance degrees of the state quantity evaluation indexes.
4. The method of evaluating the state of a composite insulator according to claim 2,
the step of checking the consistency of the judgment matrix comprises the following steps:
and when the consistency check index of the judgment matrix is smaller than the set threshold, the judgment matrix passes the consistency check.
5. The method for evaluating the condition of a composite insulator according to claim 2,
if the judgment matrix does not pass the consistency test, the step of adjusting the subjective weight value comprises the following steps: and readjusting the mutual importance degree among the evaluation indexes until the judgment matrix passes the consistency test.
6. The method for evaluating the condition of a composite insulator according to claim 1,
the step of determining the objective weight value comprises:
and determining an objective weight value according to the variation coefficient of each state quantity evaluation index.
7. The method of evaluating the state of a composite insulator according to claim 6,
the objective weight value calculation formula is as follows:
in the formula: lambda i Coefficient of variation, σ, representing the i-th state quantity evaluation index i Indicates the standard deviation of the i-th state quantity evaluation index,
represents the average of the i-th state quantity evaluation indexes,
and an objective weight value representing the ith state quantity evaluation index.
8. The method of evaluating the state of a composite insulator according to claim 1,
the state quantity evaluation index weighted value calculation formula is as follows:
in the formula: w i Indicates the i-th state quantity evaluation index weight value, omega i The subjective weight value of the ith state quantity evaluation index is expressed,
represents the objective weight of the ith state quantity evaluation indexThe value is obtained.
9. The method for evaluating the state of a composite insulator according to claim 1, wherein the step of obtaining the rank sum ratio estimation value of each evaluation target according to the state quantity evaluation index weight value includes:
when the weight values of the state quantity evaluation indexes are the same, the rank sum ratio estimation value delta of the evaluation object is calculated according to the following formula RSRi ：
In the formula: i =1,2,. ·, m; r ij The rank of the ith row and jth column elements of the rank matrix R.
10. The method for evaluating the state of a composite insulator according to claim 1, wherein the step of obtaining the rank sum ratio estimation value of each evaluation target according to the state quantity evaluation index weight value includes:
when the weighted values of the various state quantity evaluation indexes are different, the rank sum ratio estimation value delta of the evaluation object is calculated according to the following formula WRSRi ：
In the formula: i =1,2,. ·, m; omega j Is the weighted value of the jth evaluation index, sigma omega j ＝1，R ij The rank of the ith row and jth column element.
11. The method for evaluating the state of a composite insulator according to claim 9 or 10, wherein the probability unit is obtained by:
compiling a rank sum ratio estimation value frequency distribution table, taking the same values as a group, and listing frequency f and accumulated frequency sigma f of each group of rank sum ratio estimation values;
determining rank order range R for each set of rank sum ratio estimatesAnd average order of rank
Calculate the percentage of average rank
The last accumulated frequency is corrected according to 1-1/4 m;
p is to be i Conversion into probability unit P of i-th evaluation object robiti Probability unit P robiti The determination is made by the following formula:
P robiti ＝u(p i )+5
in the formula: u (p) i ) Expressed as a percentage p i The corresponding standard normal dispersion.
12. The method for evaluating the state of a composite insulator according to claim 1, wherein the step of determining a linear regression equation between the rank sum ratio estimation value and the probability unit of each evaluation object comprises:
and determining a linear regression equation by taking the probability unit corresponding to the accumulated frequency as an independent variable and taking the rank sum ratio estimation value as a dependent variable.
13. The method of evaluating the condition of a composite insulator according to claim 12,
the linear regression equation is:
δ RSRi (or delta) WRSRi )＝a+b×P robiti
In the formula: delta RSRi Or delta WRSRi To evaluate the rank sum ratio estimate of the object, P robiti Is a probability unit, a and b are coefficients to be determined, and the coefficients are obtained by calculating a linear regression equation by means of simulation software.
14. The method of evaluating the state of a composite insulator according to claim 1,
the step of determining the state of the composite insulator according to the rank and the ratio of each evaluation object comprises the following steps: and performing grading sequencing on each evaluation object according to the probability unit, and determining the state of the composite insulator according to the grading corresponding to the rank and the ratio of each evaluation object.
15. The method for evaluating the condition of a composite insulator according to claim 14,
the step of performing grading and sequencing on each evaluation object according to the probability unit comprises the following steps:
determining the number of the grading;
and calculating a grading critical value through the linear regression equation by taking the probability unit critical value as an independent variable, and grading and sequencing each evaluation object.
16. A composite insulator condition assessment system, comprising:
the state quantity evaluation index matrix module is used for determining state quantity evaluation indexes of the composite insulator and forming a state quantity evaluation index matrix;
the rank matrix module is used for carrying out a state quantity test on each evaluation object to obtain the rank of each evaluation object of each evaluation index in the state quantity evaluation index matrix to obtain a rank matrix;
the weight value module is used for obtaining a state quantity evaluation index weight value according to the subjective weight value and the objective weight value;
the rank and ratio estimation value and probability unit module is used for estimating the index weight value according to the state quantity to obtain the rank and ratio estimation value and the probability unit of each estimation object;
the rank and ratio module is used for determining a linear regression equation between the rank and ratio estimation value of each evaluation object and the probability unit and obtaining the rank and ratio of each evaluation object according to the linear regression equation;
and the state determining module is used for determining the state of the composite insulator according to the rank and the ratio of each evaluation object.
17. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 15.
18. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 15.
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| CN116124903A (en) * | 2023-04-13 | 2023-05-16 | 广东电网有限责任公司揭阳供电局 | Defect early warning method, device, system, equipment and medium for insulator |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116124903A (en) * | 2023-04-13 | 2023-05-16 | 广东电网有限责任公司揭阳供电局 | Defect early warning method, device, system, equipment and medium for insulator |
| CN116124903B (en) * | 2023-04-13 | 2023-08-15 | 广东电网有限责任公司揭阳供电局 | Defect early warning method, device, system, equipment and medium for insulator |
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