CN113065755B - Medium-low voltage fuse model selection method, device, equipment and medium - Google Patents
Medium-low voltage fuse model selection method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a medium for selecting models of medium and low voltage fuses, which are used for constructing performance evaluation indexes of the medium and low voltage fuses and acquiring performance evaluation index data; calculating the weight of the performance evaluation index according to the obtained judgment matrix of the performance evaluation index; weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight to obtain weighted index data; respectively calculating Euclidean distances between the weighted index data and the maximum and minimum weighted index data of the low-voltage fuses in each model to obtain a first distance error and a second distance error of the low-voltage fuses in each model; the performance score of the medium-low voltage fuses in each model is calculated based on the first distance error and the second distance error, the model of the optimal medium-low voltage fuse is further determined, and the technical problems that the fuse is impacted by peak current for a long time, the performance is poor and burning loss is further caused due to the fact that the performance parameters of the fuse in the prior art are not matched with practical application and the model selection is not matched are solved.
Description
Technical Field
The application relates to the technical field of fuses, in particular to a method, a device, equipment and a medium for selecting models of medium and low voltage fuses.
Background
The fuse is a traditional circuit protection device, and is widely applied to a power system due to the characteristics of simple structure, low price and high reliability. In recent years, fuse failure accidents frequently occur, and the main reason is that performance parameters are not matched with practical application and selection type, so that the fuse is impacted by peak current for a long time, the performance is poor, and further burning loss is caused. Therefore, establishing a performance evaluation system for the medium and low voltage fuse and optimizing the fuse type selection are technical problems that need to be solved urgently by the technical personnel in the field.
Disclosure of Invention
The application provides a method, a device, equipment and a medium for selecting models of medium and low voltage fuses, which are used for solving the technical problems that in the prior art, the performance parameters of the fuses are not accordant with practical application and the models are not matched, so that the fuses are impacted by peak current for a long time, the performance is poor, and further burning loss is caused.
In view of this, the first aspect of the present application provides a method for selecting a model of a medium-low voltage fuse, including:
constructing a performance evaluation index of the medium and low voltage fuse, and acquiring performance evaluation index data of the medium and low voltage fuses of various models;
acquiring a judgment matrix of the performance evaluation index, and calculating the weight of the performance evaluation index based on the judgment matrix;
weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain weighted index data of the low-voltage fuses in each model;
calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model;
and calculating to obtain the performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance score.
Optionally, the method further includes:
and carrying out standardized processing on the performance evaluation index data of the medium and low voltage fuses of various types.
Optionally, the method further includes:
calculating consistency ratio according to the maximum characteristic root of the judgment matrix;
when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective;
and when the consistency ratio is larger than or equal to the preset threshold value, adjusting the judgment matrix.
Optionally, the calculating, based on the first distance error and the second distance error, a performance score of the low-voltage fuse in each model includes:
calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model;
and calculating the ratio of the second distance error of the low-voltage fuses in each model to the corresponding distance error sum to obtain the performance score of the low-voltage fuses in each model.
The second aspect of the present application provides a medium and low voltage fuse model selection device, including:
the building unit is used for building performance evaluation indexes of the medium and low voltage fuses and acquiring performance evaluation index data of the medium and low voltage fuses in various models;
a first calculation unit configured to acquire a determination matrix of the performance evaluation index and calculate a weight of the performance evaluation index based on the determination matrix;
the weighting unit is used for weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain the weighted index data of the low-voltage fuses in each model;
the second calculation unit is used for calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model;
and the third calculation unit is used for calculating the performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance score.
Optionally, the method further includes:
and the processing unit is used for carrying out standardized processing on the performance evaluation index data of the medium and low voltage fuses of various types.
Optionally, the method further includes: a determination unit configured to:
calculating a consistency ratio according to the maximum characteristic root of the judgment matrix;
when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective;
and when the consistency ratio is greater than or equal to the preset threshold value, adjusting the judgment matrix.
Optionally, the third calculating unit is specifically configured to:
calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model;
calculating the ratio of the second distance error of each type of low-voltage fuse to the corresponding distance error sum to obtain the performance score of each type of low-voltage fuse;
and determining the model of the optimal medium and low voltage fuse according to the performance score.
A third aspect of the present application provides a medium and low voltage fuse model selection device, the device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute any one of the methods for selecting a model of a medium-low voltage fuse described in the first aspect according to instructions in the program code.
A fourth aspect of the present application provides a computer-readable storage medium for storing program code for executing the medium-and low-voltage fuse model selection method of any one of the first aspects.
According to the technical scheme, the method has the following advantages:
the application provides a method for selecting models of medium and low voltage fuses, which comprises the following steps: constructing performance evaluation indexes of the medium and low voltage fuses, and acquiring performance evaluation index data of the medium and low voltage fuses of various types; acquiring a judgment matrix of the performance evaluation index, and calculating the weight of the performance evaluation index based on the judgment matrix; weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain the weighted index data of the low-voltage fuses in each model; calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-and-medium voltage fuses of each model to obtain a first distance error of the low-and-medium voltage fuses of each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-and-medium voltage fuses of each model to obtain a second distance error of the low-and-medium voltage fuses of each model; and calculating to obtain the performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance score.
According to the method, after the performance evaluation indexes of the medium-low voltage fuses are established, the judgment matrixes of the performance evaluation indexes are obtained, corresponding weights are further obtained, then the performance evaluation index data of the medium-low voltage fuses of various types are weighted according to the weights, the weighted index data are obtained, after the first distance error between the weighted index data and the maximum weighted index data and the second distance error between the weighted index data and the minimum weighted index data are determined, the performance score of the medium-low voltage fuses of various types is calculated, finally the optimal type of the medium-low voltage fuses is determined through the performance score, and the technical problems that the fuse is impacted by peak current for a long time, the performance is poor and burning loss is caused due to the fact that the fuse performance parameters in the prior art are not matched with actual application and the types are not matched are solved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a method for selecting a model of a medium-low voltage fuse according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram illustrating performance influencing factors of a medium-low voltage fuse according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of performance evaluation indexes of a medium-and-low voltage fuse provided in an embodiment of the present application;
fig. 4 is a schematic structural diagram of a medium-low voltage fuse model selection device according to an embodiment of the present application.
Detailed Description
The application provides a method, a device, equipment and a medium for selecting models of medium and low voltage fuses, which are used for solving the technical problems that in the prior art, the performance parameters of the fuses are not accordant with practical application and the models are not matched, so that the fuses are impacted by peak current for a long time, the performance is poor, and further burning loss is caused.
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
For easy understanding, referring to fig. 1, an embodiment of a method for selecting a model of a medium-low voltage fuse provided by the present application includes:
Establishing an evaluation index system is an important content of fuse performance evaluation work. The performance evaluation index of the fuse can accurately and clearly reflect the working state and the operation condition of the fuse. Therefore, a comprehensive index system needs to be established by carefully screening and following the systematic, scientific and objective principles, so that the reliability of the evaluation result can be ensured. The specific index construction method comprises the following steps:
(1) The goal of the evaluation is made clear. The evaluation target is defined first, and the evaluation range is drawn out, so that the evaluation index can be further refined. The evaluation target of the embodiment of the present application is the performance of the fuse.
(2) The hierarchical structure for determining the evaluation index is generally divided into a primary evaluation index and a secondary evaluation index.
(3) And (5) initially selecting evaluation indexes. The technical data provided by each fuse manufacturer is collected, and combined with the analysis of the operation performance of the fuse, the selectable indexes are listed, and the influence factors of the operation performance of the fuse can be referred to fig. 2.
(4) And determining an evaluation index. And analyzing each index, screening according to a construction principle of the evaluation index, and finally determining each evaluation index.
(5) And (5) constructing an evaluation index system. Classifying the determined indexes, quantizing qualitative indexes, and normalizing all indexes.
The method comprises the steps of screening performance evaluation indexes of the fuse by adopting a layering method, dividing the performance influence factors of the fuse into three first-level indexes, and selecting second-level indexes under the first-level indexes. The hierarchy of the initial selection index is shown in table 1.
TABLE 1 Primary selection index System
In the actual quantification process, the initial selection index system can be properly simplified according to parameters which can be provided by a manufacturer and the actual requirements of use, and important performance evaluation indexes are reserved. The performance evaluation indexes after screening in the examples of the present application are shown in fig. 3.
The performance evaluation index data of the low-voltage fuse in each model is obtained, and a corresponding index data matrix R = { R } can be generated ij } m×n The matrix has m evaluation objects (namely m types of medium and low voltage fuses) in total, and n individual performance evaluation index data. The performance evaluation indexes are divided into benefit indexes and cost indexes, wherein the benefit indexes refer to indexes with better numerical values, and the cost indexes refer to indexes with better numerical values. Since the unit and order of magnitude of each performance evaluation index data are greatly different from each other, the performance evaluation index data r needs to be set ij Carrying out normalization processing to obtain the normalized evaluation index data x ij The process of carrying out standardized processing on the performance evaluation index data of the medium and low voltage fuses of various types is as follows:
for the benefit type index:
for cost-type indices:
and 102, acquiring a judgment matrix of the performance evaluation index, and calculating the weight of the performance evaluation index based on the judgment matrix.
According to the situation of the evaluation object, the complex problem is decomposed into a plurality of different components, and the different components are divided into different groups according to different attributes or conditions to form a hierarchical structure, as shown in fig. 3.
For each performance evaluation index in the same layer, a pairwise comparison method is adopted to obtain a judgment matrix A = (c) according to the comparison degree of 1-9 ij ) m×n Reference may be made to table 2. The judgment matrix is a positive and inverse matrix and satisfies the following conditions:
c ij ＝1/c ji ；
c ii ＝1；
TABLE 2 judgment Scale and meanings
| Scale c ij | Scale Properties |
| 1 | The importance of the factors is the same |
| 3 | Factor i is slightly more important than factor j |
| 5 | Factor i is more important than factor j |
| 7 | The importance of the factor i is obviously stronger than that of the factor j |
| 9 | The factor i is absolutely stronger than the importance of the factor j |
| 2,4,6,8 | Factor i is more important than factor j by the adjacent median |
| 1,1/2，…，1/9 | The importance of the two factors is opposite to that of the above |
Solving a characteristic equation of the judgment matrix, solving a maximum characteristic value of the matrix and a corresponding characteristic vector thereof, and carrying out normalization processing on the characteristic vector to obtain a weight vector W = { W = of the index ij } m×n 。
Further, consistency check is carried out on the judgment matrix, and specifically, consistency ratio is calculated according to the maximum characteristic root of the judgment matrix; when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective; and when the consistency ratio is larger than or equal to a preset threshold value, adjusting the judgment matrix. The consistency ratio CR is calculated as:
where CI is the sample mean value, λ max In order to determine the maximum eigenvalue of the matrix, RI is an average random consistency index value, which can be obtained by looking up a table in table 3. When the consistency ratio CR is less than 0.1, judging that the matrix meets the consistency, and judging that the weight is effective; otherwise, adjusting the judgment matrix.
TABLE 3 average consistency index
And 103, weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain the weighted index data of the low-voltage fuses in each model.
Corresponding performance evaluation is performed according to the weight of each performance evaluation indexWeighting the price index data to obtain weighted index data Z = { Z ] of the low-voltage fuses in each type ij } m×n Namely:
z ij ＝w ij x ij 。
and 104, calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model.
Determining maximum value Z of weighted index data of same attribute + (Ideal solution) and minimum value Z - (negative ideal solution), there are:
calculating the maximum value Z of the low-voltage fuse and the weighting index data in each model + (i.e., maximum weighted index data) and minimum value Z - The Euclidean distance (i.e. the minimum weighted index data) to obtain a first distance error
And a second distance error
Namely:
and 105, calculating to obtain the performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance score.
Calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model; calculating the ratio of the second distance error of the low-voltage fuses in each model to the sum of the corresponding distance errors to obtain the performance score P of the low-voltage fuses in each model i . Namely:
and then sorting according to the performance scores of the low-voltage fuses in various models to determine the optimal performance score, and further determining the model of the optimal low-voltage fuse in the various models. Performance score P i The larger, the first distance error
The smaller the size is, the more ideal the type i medium and low voltage fuse is, the maximum performance score corresponds to the optimal medium and low voltage fuse, the type of which is the optimal type, namely the type to be selected finally.
In the embodiment of the application, after the performance evaluation indexes of the medium-low voltage fuses are established, the judgment matrixes of the performance evaluation indexes are obtained, corresponding weights are further obtained, then the performance evaluation index data of the medium-low voltage fuses of various types are weighted according to the weights, the weighted index data are obtained, after the first distance error between the weighted index data and the maximum weighted index data and the second distance error between the weighted index data and the minimum weighted index data are determined, the performance score of the medium-low voltage fuses of various types is calculated, finally the optimal type of the medium-low voltage fuses is determined through the performance score, and the technical problems that the fuse is impacted by peak current for a long time, the performance is poor and burning loss is caused due to the fact that the fuse performance parameters in the prior art are not matched with actual application and the types are not matched are solved.
The above is an embodiment of a method for selecting a model of a medium-low voltage fuse provided by the present application, and the following is an embodiment of a device for selecting a model of a medium-low voltage fuse provided by the present application.
Referring to fig. 4, an embodiment of the present invention provides a device for selecting a model of a medium-low voltage fuse, including:
the building unit is used for building performance evaluation indexes of the medium and low voltage fuses and acquiring performance evaluation index data of the medium and low voltage fuses in various models;
a first calculation unit configured to acquire a determination matrix of the performance evaluation index and calculate a weight of the performance evaluation index based on the determination matrix;
the weighting unit is used for weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain the weighted index data of the low-voltage fuses in each model;
the second calculation unit is used for calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model;
and the third calculating unit is used for calculating the performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance score.
As a further improvement, the method further comprises the following steps:
and the processing unit is used for carrying out standardized processing on the performance evaluation index data of the medium and low voltage fuses of various types.
As a further improvement, the method also comprises the following steps: a determination unit configured to:
calculating a consistency ratio according to the maximum characteristic root of the judgment matrix;
when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective;
and when the consistency ratio is greater than or equal to a preset threshold value, adjusting the judgment matrix.
As a further improvement, the third computing unit is specifically configured to:
calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model;
calculating the ratio of the second distance error of each type of medium-low voltage fuse to the corresponding distance error sum to obtain the performance score of each type of medium-low voltage fuse;
and determining the model of the optimal medium and low voltage fuse according to the performance score.
In the embodiment of the application, after the performance evaluation indexes of the low-voltage fuses are established, the judgment matrix of each performance evaluation index is obtained, corresponding weights are further obtained, then the performance evaluation index data of the low-voltage fuses in each model are weighted according to the weights, the weighted index data are obtained, after the first distance error between each weighted index data and the maximum weighted index data and the second distance error between each weighted index data and the minimum weighted index data are determined, the performance score of the low-voltage fuses in each model is calculated, and finally the model of the optimal low-voltage fuse in each model is determined through the performance score.
The embodiment of the application also provides a device for selecting the model of the medium-low voltage fuse, which comprises a processor and a memory;
the memory is used for storing the program codes and transmitting the program codes to the processor;
the processor is configured to execute the medium and low voltage fuse model selection method in the foregoing method embodiment according to instructions in the program code.
The embodiment of the application also provides a computer-readable storage medium, which is used for storing program codes, and the program codes are used for executing the medium-low voltage fuse model selection method in the method embodiment.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for executing all or part of the steps of the method described in the embodiments of the present application through a computer device (which may be a personal computer, a server, or a network device). And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (8)
1. A method for selecting the model of a medium-low voltage fuse is characterized by comprising the following steps:
constructing performance evaluation indexes of the medium and low voltage fuses, and acquiring performance evaluation index data of the medium and low voltage fuses of various types;
acquiring a judgment matrix of the performance evaluation index, and calculating the weight of the performance evaluation index based on the judgment matrix;
weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain weighted index data of the low-voltage fuses in each model;
calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model;
calculating to obtain a performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse in each model according to the performance score;
calculating the weight of the performance evaluation index based on the judgment matrix, wherein the calculating comprises solving a characteristic equation of the judgment matrix to obtain a characteristic vector of the judgment matrix, and performing normalization processing on the characteristic vector to obtain the weight of the performance evaluation index;
calculating to obtain a performance score of the low-voltage fuse in each model based on the first distance error and the second distance error, wherein the performance score comprises: calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model; and calculating the ratio of the second distance error of the low-voltage fuses in each model to the corresponding distance error sum to obtain the performance score of the low-voltage fuses in each model.
2. The medium and low voltage fuse model selection method of claim 1, further comprising:
and (4) carrying out standardized processing on the performance evaluation index data of the low-voltage fuses in various types.
3. The medium and low voltage fuse model selection method of claim 1, further comprising:
calculating consistency ratio according to the maximum characteristic root of the judgment matrix;
when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective;
and when the consistency ratio is larger than or equal to the preset threshold value, adjusting the judgment matrix.
4. A medium and low voltage fuse model selection device, comprising:
the building unit is used for building performance evaluation indexes of the medium and low voltage fuses and obtaining performance evaluation index data of the medium and low voltage fuses in various types;
a first calculation unit configured to acquire a determination matrix of the performance evaluation index and calculate a weight of the performance evaluation index based on the determination matrix;
the weighting unit is used for weighting the performance evaluation index data of the low-voltage fuses in each model according to the weight of the performance evaluation index to obtain the weighted index data of the low-voltage fuses in each model;
the second calculation unit is used for calculating the Euclidean distance between the weighted index data and the maximum weighted index data of the low-voltage fuses in each model to obtain a first distance error of the low-voltage fuses in each model, and calculating the Euclidean distance between the weighted index data and the minimum weighted index data of the low-voltage fuses in each model to obtain a second distance error of the low-voltage fuses in each model;
the third calculation unit is used for calculating performance scores of the low-voltage fuses in all models based on the first distance error and the second distance error, and determining the model of the optimal low-voltage fuse according to the performance scores;
the first calculating unit is specifically configured to solve a feature equation of the determination matrix to obtain a feature vector of the determination matrix, and perform normalization processing on the feature vector to obtain a weight of the performance evaluation index;
the third computing unit is specifically configured to: calculating the sum of the first distance error and the second distance error of the low-voltage fuses in each model to obtain the sum of the distance errors of the low-voltage fuses in each model; calculating the ratio of the second distance error of each type of low-voltage fuse to the corresponding distance error sum to obtain the performance score of each type of low-voltage fuse; and determining the model of the optimal medium and low voltage fuse according to the performance score.
5. The medium-and low-voltage fuse model selection device according to claim 4, further comprising:
and the processing unit is used for carrying out standardized processing on the performance evaluation index data of the low-voltage fuses in various types.
6. The medium-and low-voltage fuse model selection device according to claim 4, further comprising: a determination unit configured to:
calculating consistency ratio according to the maximum characteristic root of the judgment matrix;
when the consistency ratio is smaller than a preset threshold value, judging that the weight is effective;
and when the consistency ratio is larger than or equal to the preset threshold value, adjusting the judgment matrix.
7. A medium and low voltage fuse model selection device, the device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the medium and low voltage fuse model selection method of any one of claims 1-3 according to instructions in the program code.
8. A computer-readable storage medium characterized in that the computer-readable storage medium stores program code for executing the medium-and low-voltage fuse model selection method of any one of claims 1 to 3.
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| JP2005166462A (en) * | 2003-12-03 | 2005-06-23 | Soundtech:Kk | Fuse, method of mounting fuse on automobile, and automobile mounting fuse |
| CN107634499A (en) * | 2017-09-28 | 2018-01-26 | 广东电网有限责任公司东莞供电局 | A kind of double protection on-load switch fuse combined electric apparatus and circuit structure |
| CN109472001A (en) * | 2018-11-02 | 2019-03-15 | 广东电网有限责任公司 | A kind of superiority and inferiority appraisal procedure of scheme, superiority and inferiority assessment system and relevant apparatus |
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| US20180284756A1 (en) * | 2016-05-09 | 2018-10-04 | StrongForce IoT Portfolio 2016, LLC | Methods and systems for adaption of data collection under anomalous conditions in an internet of things mining environment |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005166462A (en) * | 2003-12-03 | 2005-06-23 | Soundtech:Kk | Fuse, method of mounting fuse on automobile, and automobile mounting fuse |
| CN107634499A (en) * | 2017-09-28 | 2018-01-26 | 广东电网有限责任公司东莞供电局 | A kind of double protection on-load switch fuse combined electric apparatus and circuit structure |
| CN109472001A (en) * | 2018-11-02 | 2019-03-15 | 广东电网有限责任公司 | A kind of superiority and inferiority appraisal procedure of scheme, superiority and inferiority assessment system and relevant apparatus |
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