CN116187838A - Quality evaluation method, system and device for power equipment and storage medium - Google Patents
Quality evaluation method, system and device for power equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a quality evaluation method system, a device and a storage medium of power equipment, wherein the method comprises the following steps: acquiring detection data of the power equipment, and constructing a detection data set based on the detection data; preprocessing the detection data set to obtain a quality data set; normalizing the quality data set to obtain a normalized data set; constructing a judgment matrix for the quality data set by adopting an analytic hierarchy process, and setting a weight coefficient set according to the judgment matrix; calculating power equipment according to the weight coefficient set and the standard data set to obtain diversity; clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain clustering results; determining a quality evaluation result of the power equipment according to the clustering result; the invention can fully mine the detection data information, reasonably and finely evaluate the quality of the power equipment, and save manpower and material resources.
Description
Technical Field
The invention relates to a quality evaluation method, a system, a device and a storage medium of power equipment, and belongs to the technical field of power systems.
Background
In the aspect of the power grid equipment quality evaluation method at present, technicians often evaluate equipment quality according to detection reports of equipment test experiments. However, from the technical and data point of view, the device detection report only provides an option of whether the device is qualified, and the information in the detection data cannot be fully mined, so that the quality of the power grid device cannot be refined and classified. In addition, the number of power grid equipment is numerous, and a large amount of manpower and material resources are consumed by the quality evaluation of the equipment by means of detection reports, so that high manpower cost is brought to enterprises.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides a quality evaluation method, a system, a device and a storage medium for power equipment, which can fully mine detection data information, reasonably and finely evaluate the quality of the power equipment and save manpower and material resources.
In order to achieve the above purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the present invention provides a quality assessment method for an electrical device, including:
acquiring detection data of the power equipment, and constructing a detection data set based on the detection data;
preprocessing the detection data set to obtain a quality data set;
normalizing the quality data set to obtain a normalized data set;
constructing a judgment matrix for the quality data set by adopting an analytic hierarchy process, and setting a weight coefficient set according to the judgment matrix;
calculating power equipment according to the weight coefficient set and the standard data set to obtain diversity;
clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain clustering results;
and determining a quality evaluation result of the power equipment according to the clustering result.
Preferably, the detection data set is R:
R＝{R 1 ，R 2 ，...R i ...，R I }
wherein R is i The detection data of the ith power equipment is obtained, wherein I is the number of the power equipment;
R i ＝{r i_1 ，r i_2 ，...r i_n ...，r i_N }
wherein r is i_n Is the value of the nth detection index of the ith power equipment.
Preferably, the pretreatment includes:
calculating a preprocessed numerical value according to the threshold value and the numerical value of each detection index:
x i_n ＝|r i_n -th n |
in th n For the nth detection fingerTarget threshold value, x i_n R is _in Values after pretreatment;
constructing a quality data set according to the preprocessed numerical value:
the mass dataset X is:
X＝{X 1 ，X 2 ，...X i ...，X I }
wherein X is i Quality data for the i-th power device:
X i ＝{x i_1 ，x i_2 ，...x i_n ...，x i_N }。
preferably, the normalizing includes:
in the method, in the process of the invention,
respectively the maximum value and the minimum value of the nth detection index of the ith power equipment,
is x i_n Normalized values;
building a normative dataset according to the normalized numerical values:
canonical dataset X * The method comprises the following steps:
in the method, in the process of the invention,
specification data for the ith power device:
preferably, the power device obtaining set S is:
S＝{S 1 ，S 2 ，...S i ...，S I }
wherein S is i Score for the ith power device:
in the formula, row is to sum the matrix according to rows, gamma is a weight coefficient, and gamma= { gamma 1 ，γ 2 ，...γ n ...，γ N }。
Preferably, the clustering the power equipment score sets by adopting a K-Means clustering algorithm comprises:
determining a quality assessment rating of k=1, 2;
randomly selecting K elements from the power equipment acquisition set S as initial clustering centers;
calculating Euclidean distance between each element in the power equipment obtaining set S and each clustering center, and distributing each element to the clustering center with the smallest Euclidean distance to generate a clustering cluster; calculating the mass centers of all the clustering clusters, taking the mass centers as clustering centers, repeating the current steps until the mass centers are converged, and outputting the final clustering clusters.
Preferably, the determining the quality evaluation result of the power equipment according to the clustering result includes:
and determining a quality evaluation grade k of each cluster, and taking the quality evaluation grade k as a quality evaluation result of the power equipment corresponding to each element in each cluster.
In a second aspect, the present invention provides a quality assessment system for an electrical device, the system comprising:
the data acquisition module is used for acquiring detection data of the power equipment and constructing a detection data set based on the detection data;
the preprocessing module is used for preprocessing the detection data set to obtain a quality data set;
the normalization module is used for normalizing the quality data set to obtain a normalized data set;
the weight acquisition module is used for constructing a judgment matrix for the quality data set by adopting a hierarchical analysis method, and setting a weight coefficient set according to the judgment matrix;
the score calculation module is used for calculating the power equipment to obtain the diversity according to the weight coefficient set and the standard data set;
the score clustering module is used for clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain a clustering result;
and the quality evaluation module is used for determining the quality evaluation result of the power equipment according to the clustering result.
In a third aspect, the present invention provides a quality assessment apparatus for an electrical device, including a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method described above.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method.
Compared with the prior art, the invention has the beneficial effects that:
the quality evaluation method, the system, the device and the storage medium for the power equipment provided by the invention solve the problems that the expert experience is excessively relied on, the labor cost is high, the quality evaluation result is not fine and the like based on the combination of the analytic hierarchy process and the K-Means clustering algorithm. Firstly, preprocessing original detection data by utilizing a detection report of power equipment to enable the data to contain equipment quality information, and eliminating influences of different detection indexes with different dimensions by normalization; then, using analytic hierarchy process, in combination with expert experience, a quantitative weight of each index is given, and a score of quality evaluation of each device is given. And finally, based on the obtained score vector, the score information is mined by using a K-Means algorithm, and the quality evaluation result of each sample is given, so that manpower and material resources are greatly saved.
Drawings
Fig. 1 is a flowchart of a quality evaluation method of an electrical device according to a first embodiment of the present invention;
fig. 2 is a flowchart of clustering using a K-Means clustering algorithm according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Embodiment one:
as shown in fig. 1, the present invention provides a quality assessment method for an electrical device, including the following steps:
1. acquiring detection data of the power equipment, and constructing a detection data set based on the detection data;
the detection dataset is R:
R＝{R 1 ，R 2 ，...R i ...，R I }
wherein R is i The detection data of the ith power equipment is obtained, wherein I is the number of the power equipment;
R i ＝{r i_1 ，r i_2 ，...r i_n ...，r i_N }
wherein r is i_n Is the value of the nth detection index of the ith power equipment.
Taking an alternating current lightning arrester as an example, the detection indexes of the alternating current lightning arrester are shown in table 1;
table 1:
2. preprocessing the detection data set to obtain a quality data set;
the pretreatment comprises the following steps:
calculating a preprocessed numerical value according to the threshold value and the numerical value of each detection index:
x i_n ＝|r i_n -th n |
in th n Is the threshold value of the nth detection index, x i_n R is i_n Values after pretreatment;
constructing a quality data set according to the preprocessed numerical value:
the mass dataset X is:
X＝{X 1 ，X 2 ，...X i ...，X I }
wherein X is i Quality data for the i-th power device:
X i ＝{x i_1 ，x i_2 ，...x i_n ...，x i_N }
3. normalizing the quality data set to obtain a normalized data set;
normalization includes:
in the method, in the process of the invention,
respectively the maximum value and the minimum value of the nth detection index of the ith power equipment,
is x i_n Normalized values;
building a normative dataset according to the normalized numerical values:
canonical dataset X * The method comprises the following steps:
in the method, in the process of the invention,
specification data for the ith power device: />
4. Constructing a judgment matrix for the quality data set by adopting an analytic hierarchy process, and setting a weight coefficient set according to the judgment matrix; the judgment matrix is shown in table 1, and the weight coefficient can be directly set according to expert experience.
Table 1:
5. calculating power equipment according to the weight coefficient set and the standard data set to obtain diversity;
the power equipment obtaining set S is as follows:
S＝{S 1 ，S 2 ，...S i ...，S I }
wherein S is i Score for the ith power device:
in the formula, row is to sum the matrix according to rows, gamma is a weight coefficient, and gamma= { gamma 1 ，γ 2 ，...γ n ...，γ N }。
6. Clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain clustering results;
as shown in fig. 2, the clustering process includes:
determining a quality assessment rating of k=1, 2, …, K;
randomly selecting K elements from the power equipment acquisition set S as initial clustering centers;
calculating Euclidean distance between each element in the power equipment obtaining set S and each clustering center, and distributing each element to the clustering center with the smallest Euclidean distance to generate a clustering cluster; calculating the mass centers of all the clustering clusters, taking the mass centers as clustering centers, repeating the current steps until the mass centers are converged, and outputting the final clustering clusters.
7. Determining a quality evaluation result of the power equipment according to the clustering result;
the method specifically comprises the following steps: and determining a quality evaluation grade k of each cluster, and taking the quality evaluation grade k as a quality evaluation result of the power equipment corresponding to each element in each cluster.
Embodiment two:
the embodiment of the invention provides a quality evaluation system of power equipment, which comprises:
the data acquisition module is used for acquiring detection data of the power equipment and constructing a detection data set based on the detection data;
the preprocessing module is used for preprocessing the detection data set to obtain a quality data set;
the normalization module is used for normalizing the quality data set to obtain a normalized data set;
the weight acquisition module is used for constructing a judgment matrix for the quality data set by adopting a hierarchical analysis method, and setting a weight coefficient set according to the judgment matrix;
the score calculation module is used for calculating the power equipment to obtain the diversity according to the weight coefficient set and the standard data set;
the score clustering module is used for clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain a clustering result;
and the quality evaluation module is used for determining the quality evaluation result of the power equipment according to the clustering result.
Embodiment III:
based on the first embodiment, the embodiment of the invention provides a quality evaluation device of power equipment, which comprises a processor and a storage medium;
the storage medium is used for storing instructions;
the processor is operative to perform the steps of the method described above in accordance with the instructions.
Embodiment four:
based on the first embodiment, the embodiment of the present invention provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the above method.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. A quality assessment method of an electrical device, comprising:
acquiring detection data of the power equipment, and constructing a detection data set based on the detection data;
preprocessing the detection data set to obtain a quality data set;
normalizing the quality data set to obtain a normalized data set;
constructing a judgment matrix for the quality data set by adopting an analytic hierarchy process, and setting a weight coefficient set according to the judgment matrix;
calculating power equipment according to the weight coefficient set and the standard data set to obtain diversity;
clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain clustering results;
and determining a quality evaluation result of the power equipment according to the clustering result.
2. The method for evaluating the quality of an electrical device according to claim 1, wherein the detection data set is R:
R＝{R 1 ,R 2 ,…R i …,R I }
wherein R is i The detection data of the ith power equipment is obtained, wherein I is the number of the power equipment;
R i ＝{r i_1 ,r i_2 ,…r i_n …,r i_N }
wherein r is i_n Is the value of the nth detection index of the ith power equipment.
3. A method of evaluating the quality of an electrical device according to claim 2, wherein the preprocessing comprises:
calculating a preprocessed numerical value according to the threshold value and the numerical value of each detection index:
x i_n ＝|r i_n -th n |
in th n Is the threshold value of the nth detection index, x i_n R is i_n Values after pretreatment;
constructing a quality data set according to the preprocessed numerical value:
the mass dataset X is:
X＝{X 1 ,X 2 ,…X i …,X I }
wherein X is i Quality data for the i-th power device:
X i ＝{x i_1 ,x i_2 ,…x i_n …,x i_N }。
4. a method of quality assessment of electrical equipment according to claim 3, wherein said normalizing comprises:
in the method, in the process of the invention,
maximum value and minimum value of n-th detection index of i-th electric power equipment, respectively,/->
Is x i_n Normalized values;
building a normative dataset according to the normalized numerical values:
canonical dataset X * The method comprises the following steps:
in the method, in the process of the invention,
specification data for the ith power device:
5. the method for evaluating the quality of an electrical device according to claim 4, wherein the set of power device gains S is:
S＝{S 1 ,S 2 ,…S i …,S I }
wherein S is i Score for the ith power device:
in the formula, row is to sum the matrix according to rows, gamma is a weight coefficient, and gamma= { gamma 1 ,γ 2 ,…γ n …,γ N }。
6. The method for evaluating the quality of a power device according to claim 5, wherein the clustering the power device score sets using a K-Means clustering algorithm comprises:
determining a quality assessment rating of k=1, 2, …, K;
randomly selecting K elements from the power equipment acquisition set S as initial clustering centers;
calculating Euclidean distance between each element in the power equipment obtaining set S and each clustering center, and distributing each element to the clustering center with the smallest Euclidean distance to generate a clustering cluster; calculating the mass centers of all the clustering clusters, taking the mass centers as clustering centers, repeating the current steps until the mass centers are converged, and outputting the final clustering clusters.
7. The method for evaluating the quality of an electrical device according to claim 6, wherein determining the quality evaluation result of the electrical device according to the clustering result comprises:
and determining a quality evaluation grade k of each cluster, and taking the quality evaluation grade k as a quality evaluation result of the power equipment corresponding to each element in each cluster.
8. A quality assessment system for an electrical device, the system comprising:
the data acquisition module is used for acquiring detection data of the power equipment and constructing a detection data set based on the detection data;
the preprocessing module is used for preprocessing the detection data set to obtain a quality data set;
the normalization module is used for normalizing the quality data set to obtain a normalized data set;
the weight acquisition module is used for constructing a judgment matrix for the quality data set by adopting a hierarchical analysis method, and setting a weight coefficient set according to the judgment matrix;
the score calculation module is used for calculating the power equipment to obtain the diversity according to the weight coefficient set and the standard data set;
the score clustering module is used for clustering the power equipment score sets by adopting a K-Means clustering algorithm to obtain a clustering result;
and the quality evaluation module is used for determining the quality evaluation result of the power equipment according to the clustering result.
9. A quality evaluation device of an electric power device, which is characterized by comprising a processor and a storage medium;
the storage medium is used for storing instructions;
the processor being operative according to the instructions to perform the steps of the method according to any one of claims 1-7.
10. Computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236805A (en) * | 2023-11-16 | 2023-12-15 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
| CN117579704A (en) * | 2024-01-15 | 2024-02-20 | 深圳市检验检疫科学研究院 | Detection data acquisition method and system based on Internet of things |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117236805A (en) * | 2023-11-16 | 2023-12-15 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
| CN117236805B (en) * | 2023-11-16 | 2024-02-02 | 北京国电通网络技术有限公司 | Power equipment control method, device, electronic equipment and computer readable medium |
| CN117579704A (en) * | 2024-01-15 | 2024-02-20 | 深圳市检验检疫科学研究院 | Detection data acquisition method and system based on Internet of things |
| CN117579704B (en) * | 2024-01-15 | 2024-04-12 | 深圳市检验检疫科学研究院 | Detection data acquisition method and system based on Internet of things |
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