CN109409629B - Acquisition terminal manufacturer evaluation method based on multi-attribute decision model - Google Patents
Acquisition terminal manufacturer evaluation method based on multi-attribute decision model Download PDFInfo
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Abstract
The invention discloses an evaluation method of an acquisition terminal manufacturer based on a multi-attribute decision model, which relates to an evaluation method, and comprises the following steps: acquiring original data to obtain an evaluation index; calculating each evaluation index value, constructing an evaluation index matrix, and forming a decision matrix; calculating index value information entropy and spearman grade correlation coefficient, determining objective weight of a quality evaluation index, and carrying out weighting treatment on the decision matrix to obtain an evaluation matrix of the acquisition terminal equipment provider; calculating positive ideal solutions and negative ideal solutions of the acquisition terminal equipment suppliers, and calculating Euclidean distances from each acquisition terminal equipment supplier to the positive ideal point vectors and the negative ideal point vectors; and calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider according to the high-low degree. The technical scheme provides objective and scientific basis for the operation and maintenance of the power consumption information acquisition system and the quality evaluation and supervision of the acquisition terminal equipment for the power grid company.
Description
Technical Field
The invention relates to the field of power systems, in particular to an evaluation method of an acquisition terminal manufacturer based on a multi-attribute decision model.
Background
With the gradual deepening application of the construction of the electricity consumption information acquisition system, the acquisition terminal, the intelligent ammeter, the acquisition communication channel, the acquisition operation and maintenance team and other acquisition related resources are gradually expanded in the scale of each province company, the quality of the acquisition terminal is taken as a core component part of the electricity consumption information acquisition system, the acquisition success rate, the recall success rate and the remote setting success rate of the electricity consumption information of a user are directly influenced by the quality of the acquisition terminal, the electricity fee settlement of a power supply unit is further influenced, and a great amount of manpower and material resources are wasted in recent years for operation and maintenance caused by faults of the acquisition terminal. The quality evaluation of the acquisition terminal is one of important means for guaranteeing and improving the electricity consumption information acquisition service, a quality evaluation model of the acquisition terminal is constructed to comprehensively evaluate the quality of the acquisition terminal, the quality evaluation model can be used as evaluation of the acquisition terminal bid, suppliers can be further supervised to improve the equipment quality and after-sales service, and the investment of operation and maintenance manpower and material resources is reduced.
The existing method generally keeps the operation quality evaluation of the acquisition terminal on the basis of some simple assessment indexes, is similar to the acquisition rate and the online rate, lacks the support of actual operation various data, and cannot be trusted. Therefore, the quality evaluation index system of the acquisition terminal is not comprehensive enough, the evaluation model and method are not perfect enough, scientific and reasonable quantitative evaluation on the quality of the acquisition terminal is lacked, and scientific and reasonable evaluation support is not provided for marketing metering and material management well.
Disclosure of Invention
The technical problems to be solved and the technical task to be put forward in the invention are to perfect and improve the prior art scheme, and provide an evaluation method for the acquisition terminal manufacturer based on a multi-attribute decision model, so as to achieve the purpose of scientifically and reasonably quantitatively evaluating the quality of the acquisition terminal. For this purpose, the present invention adopts the following technical scheme.
The acquisition terminal manufacturer evaluation method based on the multi-attribute decision model is characterized by comprising the following steps of:
1) Acquiring the original data of the acquisition terminal equipment in each batch and region, and selecting a plurality of evaluation indexes for measuring the quality of the acquisition terminal equipment according to the operation monitoring big data of the acquisition terminal equipment: the evaluation indexes comprise load acquisition availability, data acquisition integrity, average fault-free working time, acquisition abnormal alarm times, operation fault rate and online rate;
2) Calculating each evaluation index value of the acquisition terminal equipment, and constructing an index matrix; performing standardization processing on the index matrix to form a decision matrix;
3) Calculating the information entropy of the evaluation index values of each item of the acquisition terminal equipment and the correlation coefficient of the Spekerman grade, determining the objective weight of the quality evaluation index according to the CRITIC method, and carrying out weighting treatment on the decision matrix according to the objective weight to obtain an acquisition terminal equipment provider evaluation matrix;
4) According to the evaluation matrix, calculating an ideal solution of the acquisition terminal equipment suppliers, wherein the ideal solution comprises a positive ideal solution and a negative ideal solution, and calculating Euclidean distances from each acquisition terminal equipment supplier to a positive ideal point vector and a negative ideal point vector;
5) And calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider according to the high-low degree.
As a preferable technical means: in step 1), the load acquisition availability is:
wherein: q represents the total batch number of the acquisition terminal equipment produced by the supplier, L represents the total area number of equipment installation of a certain batch, and N ij 、E ij And e ij Respectively representing the number of the ith batch of equipment in the jth installation area, the total load acquisition amount and the load acquisition amount available to the evaluation system after bad data are removed; omega SAMP,j Is a correction factor for representing the influence of non-quality factors in the jth region on the load acquisition availability, wherein omega is not less than 0 SAMP,j Is less than or equal to 1
The data acquisition integrity rate is as follows:
wherein: psi phi type ij Andrespectively representing theoretical data quantity to be acquired and actual data quantity to be acquired of the acquisition terminal equipment of the ith batch in the jth installation area, omega INT,j Is a correction factor for representing that the non-quality factors in the jth region influence the data acquisition integrity, and is more than or equal to 0 and less than or equal to omega INT,j Is less than or equal to 1 and is%>
The average fault-free operating time is:
wherein: n (N) j Is the number of acquisition terminal devices in the j-th installation area,T F,jk is the time, omega, from the initial operation of the kth device in the jth installation area when the kth device fails for the first time MTBF,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault-free working time, wherein omega is not less than 0 MTBF,j Is less than or equal to 1
The sum of the times of the abnormal alarm information is as follows:
wherein:and->The number of serious abnormal alarms, the number of general abnormal alarms and the number of slight abnormal alarms of the product of the ith batch in the jth installation area are respectively represented;
the operation failure rate is as follows:
wherein: t (T) rate,jk And T stop,jk The nominal operation time and the fault shutdown time of the kth acquisition terminal equipment in the jth installation area are respectively omega FAULT,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault shutdown, wherein omega is not less than 0 FAULT,j Is less than or equal to 1
The online rate is defined as:
wherein: b ij And B ij Respectively representing the number of the acquisition terminal devices of the ith batch in the jth installation area and the total number of the acquisition terminal devices actually installed, omega ONLINE,j Is a correction factor for representing the influence of non-quality factors on the linear rate in the jth region, wherein omega is not less than 0 ONLINE,j Is less than or equal to 1
As a preferable technical means: when calculating the entropy of each evaluation index value information of the acquisition terminal equipment in the step 3), the entropy weight is as follows:
wherein:r ij decision matrix element for evaluating a problem, +.>And assume that when f ij When=0, f ij ln f ij =0; m is the number of evaluation indexes, and N is the number of schemes to be evaluated; w (w) i Entropy weight of i index is represented, w is more than or equal to 0 i ≤1，/>
When the spearman grade correlation coefficient of each item of the acquisition terminal equipment is calculated, the spearman grade correlation coefficient calculation formula is as follows:
wherein:for sorting value vector +.>And->Is a covariance of (2); />And->Respectively are the rank value vectorsAnd->Standard deviation of (2); />And->Respectively are sorting value vectors->And->Is the average value of (2); />Andis a two-column variable with N elements,the ith variable value is z ij And z ik (1.ltoreq.i.ltoreq.N), where j.epsilon. {1,2, M, k e {1,2,., M; />And->Are respectively->And->Is a vector of ordered values, wherein->And->Z respectively ij And z ik At->And->Is a ranking value of (2); ρ ik Representing the spearman rank correlation coefficient, ρ, between the jth and kth indices j An overall kendel correlation coefficient representing the jth index and other indexes;
the objective weight calculation formula is:
wherein: c (C) j An objective weight representing the j-th index.
As a preferable technical means: in step 2), the index matrix is:
wherein: r is (r) ij Index value representing index j corresponding to acquisition terminal equipment i, N being the number of acquisition terminal equipment suppliers and N PM For the number of the acquisition terminal devices, M is the number of evaluation indexes for measuring the quality of the acquisition terminal devices of the suppliers, i is {1, 2.. The number of the acquisition terminal devices is N PM E {1,2,. }, M }; wherein M is equal to 6;
the calculation formula of the standardized treatment of the cost index is as follows:
the calculation formula of the benefit index standardization processing is as follows:
the decision matrix calculation formula of each index corresponding to each provider is as follows:
y”＝(y” kj ) N×M
wherein:Ω k representing a collection of acquisition terminal devices belonging to the production of vendor k.
As a preferable technical means: in step 4), an ideal solution to the acquisition terminal equipment vendor assessment problem is calculatedAnd anti-ideal solution->Wherein->j∈{1,2,...,M}。
As a preferable technical means: in step 4)Calculating Euclidean distance between supplier of acquisition terminal equipment and ideal solution and anti-ideal solution respectivelyAnd->The formula of (2) is:
wherein:the ith row of the matrix Z is evaluated for the weighted acquisition terminal equipment provider.
As a preferable technical means: in step 5), calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider sequentially from high to low, wherein the corresponding calculation formula is as follows:
wherein: c (C) i The relative approximation degree of each acquisition terminal equipment provider and the ideal solution is adopted, and the quality grade of each acquisition terminal equipment provider can be determined from high to low in sequence.
The beneficial effects are that: the technical scheme can be used for considering the correlation between indexes, can reasonably evaluate the operation quality of the acquisition terminal equipment, and can provide scientific and reasonable evaluation support for material management and marketing measurement professional departments. The quality evaluation index system of the acquisition terminal is comprehensive, the evaluation model and the method are perfect, scientific and reasonable quantitative evaluation can be made on the quality of the acquisition terminal, and scientific and reasonable evaluation support can be provided for marketing metering and material management. The method can provide objective and scientific basis for the operation and maintenance of the power consumption information acquisition system and the quality evaluation and supervision of the acquisition terminal equipment for the power grid company.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
For better understanding of the objects, technical solutions and technical effects of the present invention, the present invention will be further explained below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart of an evaluation method of an acquisition terminal manufacturer of a multi-attribute decision model according to an embodiment, including the following steps:
s10, acquiring the original data of the acquisition terminal equipment in each batch and region, comprehensively considering the operation monitoring big data of the acquisition terminal equipment, and providing 6 evaluation indexes for measuring the quality of the acquisition terminal equipment: load acquisition availability, data acquisition integrity, average fault-free working time, acquisition abnormal alarm times, operation fault rate and online rate.
In one embodiment:
when the acquisition terminal equipment acquires the related data of the load, bad data can be generated due to factors such as current, voltage mutation and electromagnetic interference, so that unusable data is firstly removed before the load acquisition data enters an evaluation system, and usable acquisition data is left for quality evaluation. The more data available, the more stable the acquisition of the acquisition terminal device, the better the quality. The load acquisition availability may be:
wherein: q represents the total batch number of the acquisition terminal equipment produced by the supplier, L represents the total area number of equipment installation of a certain batch, and N ij 、E ij And e ij Respectively representing the number and total load of the ith batch of equipment in the jth installation areaAnd evaluating the available load acquisition amount of the system after the bad data are removed. Omega SAMP,j Is a correction factor for representing the influence of non-quality factors in the jth region on the load acquisition availability, wherein omega is not less than 0 SAMP,j Is less than or equal to 1
The actual acquisition terminal device may not acquire data at a certain moment or within a certain period of time when acquiring various data, that is, the data acquisition is incomplete, which may cause the metering system to generate corresponding metering errors. Therefore, the more complete the data acquisition, the more accurate the metering result of the acquisition terminal device. The data acquisition integrity rate may be:
wherein: psi phi type ij Andrespectively representing theoretical data quantity to be acquired and actual data quantity to be acquired of the acquisition terminal equipment of the ith batch in the jth installation area, omega INT,j Is a correction factor for representing that the non-quality factors in the jth region influence the data acquisition integrity, and is more than or equal to 0 and less than or equal to omega INT,j Is less than or equal to 1 and is%>
The average fault-free working time refers to the average time that the acquisition terminal equipment can normally run before the first fault occurs. This is an important parameter for measuring the reliability of the acquisition terminal device, the longer the mean time to failure, the higher the reliability of the acquisition terminal device. Considering the installation area and other factors, the average fault-free working time can be as follows:
wherein: n (N) j The number of the acquisition terminal devices in the j-th installation area is T F,jk Is the time, omega, from the initial operation of the kth device in the jth installation area when the kth device fails for the first time MTBF,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault-free working time, wherein omega is not less than 0 MTBF,j Is less than or equal to 1
When the acquisition terminal equipment operates, more abnormal alarm information often appears, wherein the abnormal alarm information related to acquisition faults is mainly divided into the following 3 categories: severe anomalies (including terminal crashes, power failures, data errors, etc.), general anomalies (including terminal clock errors, communication module failures, terminal software version anomalies, 485 port failures, etc.), and minor anomalies (terminal task errors, communication parameter errors). The sum of the times of the abnormal alarm information is as follows:
wherein:and->The number of serious abnormal alarms, the number of general abnormal alarms and the number of slight abnormal alarms of the ith batch of products in the jth installation area are respectively indicated.
The factory provides its nominal life hour number when gathering terminal equipment when dispatching from the factory, gathers the condition that terminal equipment probably goes on running after the fault has been reset or overhauld by oneself in actual operation. When the fault occurs, the acquisition terminal equipment stops working, the longer the downtime is, the larger the metering deviation is caused, and the worse the quality is in comprehensive evaluation. The operation failure rate may be:
wherein: t (T) rate,jk And T stop,jk The nominal operation time and the fault shutdown time of the kth acquisition terminal equipment in the jth installation area are respectively omega FAULT,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault shutdown, wherein omega is not less than 0 FAULT,j Is less than or equal to 1
S20, calculating each index value of the acquisition terminal equipment, and constructing an index matrix; performing standardization processing on the index matrix to form a decision matrix;
in one embodiment, the index matrix may be:
wherein: r is (r) ij Index value representing index j corresponding to acquisition terminal equipment i, N being the number of acquisition terminal equipment suppliers and N PM For the number of the acquisition terminal devices, M is the number of evaluation indexes for measuring the quality of the acquisition terminal devices of the suppliers, i is {1, 2.. The number of the acquisition terminal devices is N PM E {1,2,..m }. Where M is equal to 6.
Because the dimensions of the evaluation indexes of the acquisition terminal devices are different, the index values are not comparable, and the number of the running acquisition terminal devices of different suppliers is different. In order to make the index values have a certain comparability and more reasonably evaluate the suppliers, dimensionless processing or standardization processing is required to be performed on the original values of all the indexes under all the acquisition terminal devices, and then the index values of the acquisition terminal devices of the same supplier after the standardization processing are averaged to represent the quality index of the acquisition terminal device of the supplier. In addition, the indexes can be classified into cost type and benefit type 2 types, wherein the larger the value of the cost type index is, the worse the value of the benefit type index is, and the smaller the value of the benefit type index is, the worse the value of the benefit type index is. Therefore, the following dimensionless or standardized processing needs to be adopted for the 2 types of indexes of the cost type and the benefit type, respectively.
The cost index standardization processing method can be as follows:
the benefit index standardization processing method can be as follows:
the decision matrix of each index corresponding to each provider may be:
y”＝(y” kj ) N×M
wherein:Ω k representing a collection of acquisition terminal devices belonging to the production of vendor k.
S30, calculating index value information entropy and spearman grade correlation coefficients of each item of the acquisition terminal equipment, determining objective weights of quality assessment indexes according to a CRITIC method, and carrying out weighting processing on decision matrixes according to the objective weights to obtain acquisition terminal equipment provider assessment matrixes;
the CRITIC method is an objective weighting method of an index weight in a multi-attribute decision problem, and the method is used for determining the objective weight of an evaluation index based on the difference degree of the evaluation index and the correlation between the evaluation indexes. The entropy and the spearman grade correlation coefficient are adopted to measure the value difference of different evaluation objects (namely the contrast strength of the evaluation index) and the conflict between the evaluation indexes. The entropy weight may be:
wherein:r ij decision matrix element for evaluating a problem, +.>And assume that when f ij When=0, f ij ln f ij =0; m is the number of evaluation indexes, and N is the number of schemes to be evaluated; w (w) i Entropy weight of i index is represented, w is more than or equal to 0 i ≤1，/>
The spearman's rank correlation coefficient is a correlation coefficient that statistically reflects the degree of correlation of two sets of rank variables. The requirements of the spearman grade correlation coefficient on the data conditions are not strict, so long as the observed values of the two variables are paired grade rating materials or grade materials obtained by converting continuous variable observed materials, the spearman grade correlation can be used for research no matter the overall distribution form of the two variables and the size of sample capacity. The spearman scale correlation coefficient may include:
wherein:for sorting value vector +.>And->Is a covariance of (2); />And->Respectively are the rank value vectorsAnd->Standard deviation of (2); />And->Respectively are sorting value vectors->And->Is a mean value of (c). />Andis a two-column variable with N elements, and the ith variable value is z respectively ij And z ik (1.ltoreq.i.ltoreq.N), where j.epsilon. {1,2, M, k e {1,2,., M; />And->Are respectively->And->Is a vector of ordered values, wherein->And->Z respectively ij And z ik At->And->Is included. ρ ik Representing the spearman rank correlation coefficient, ρ, between the jth and kth indices j The integral Kendell correlation coefficient of the j-th index and other indexes is represented.
When the spearman grade correlation coefficient of the index j is 1, the index and other indexes are shown to have consistent grade correlation; and when the spearman scale correlation coefficient is 0, the index and other indexes are independent.
From the above, it can be seen that entropy and spearman scale correlation coefficients can be used to measure the contrast intensity of the evaluation index and the conflict between the evaluation indexes, respectively, and thus the overall entropy and spearman scale correlation coefficients can be used to determine the objective weights of the respective indexes, which can be:
wherein: c (C) j An objective weight representing the j-th index.
S40, calculating positive ideal solutions and negative ideal solutions of the acquisition terminal equipment suppliers according to the evaluation matrix, and calculating Euclidean distances from each acquisition terminal equipment supplier to the positive ideal point vector and the negative ideal point vector;
in one embodiment, the ideal solution of the acquisition terminal equipment provider assessment problem can be determined asThe anti-ideal solution can be determined as +.>Wherein-> j∈{1,2,...,M}。
Euclidean distance between the provider of the acquisition terminal equipment and ideal solution and anti-ideal solutionAnd->The method comprises the following steps:
wherein:the ith row of the matrix Z is evaluated for the weighted acquisition terminal equipment provider.
S50, calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider according to the high-to-low ratio
In one embodiment, the relative approximations of the respective acquisition terminal device suppliers to the ideal solutions may be:
wherein C is i The relative approximation degree of each acquisition terminal equipment provider and the ideal solution is adopted, and the quality grade of each acquisition terminal equipment provider can be determined from high to low in sequence.
For further understanding of the present invention, the actual application of the present invention will be explained by taking the example of collecting terminal equipment data in a region governed by the Ningbo power supply company of Zhejiang power company in the national network. The original data set has 11565 pieces of data, 11312 pieces of data are available after data cleaning, 17 collection terminal equipment suppliers to be evaluated are provided, a plurality of equipment batches are arranged under each supplier, and all equipment batches are 58 batches. The quality assessment matrix of the acquisition terminal device of each supplier after normalization is given in table 1.
Table 1 standardized quality evaluation index value of acquisition terminal equipment
Firstly, calculating the numerical value of each index of a provider of the acquisition terminal equipment according to the definition of each index, so as to form an index matrix for comprehensively evaluating the problem of the acquisition terminal equipment, and then carrying out standardized processing on the index matrix; then, the entropy, entropy weight, spearman scale correlation coefficient, and objective comprehensive weight of each index were calculated from the definitions of entropy, entropy weight, and spearman scale correlation coefficient, respectively, and the results are shown in table 2.
TABLE 2 entropy, entropy weight, correlation coefficient and comprehensive weight of each index
As can be seen from table 2: the average fault-free working time index has the smallest entropy, the value of the index is 0.8944, which indicates that the value difference of each supplier on the index is largest, so the entropy weight of the index is largest (the value is 0.3980), namely the index provides more useful information for the comprehensive quality assessment of the supplier, and the proportion of the index in the comprehensive quality assessment of the supplier is larger; the data acquisition integrity index has the greatest entropy, the value of which is 0.9763, which indicates that the value difference of each provider on the index is the smallest, so the entropy weight of the index is the smallest (the value is 0.0893), namely the index provides less useful information for the comprehensive quality assessment of the provider, and the specific gravity of the index in the comprehensive quality assessment of the provider is smaller. Furthermore, it can be seen from table 2 that: the acquired abnormal alarm frequency index has the smallest spearman grade correlation coefficient, and the value of the index is 0.1247, which indicates that the correlation between the index and other indexes is the smallest, namely the degree of coincidence between useful information provided by the index and other indexes is not large, so that the index has a larger proportion in the comprehensive importance evaluation of the node; the average fault-free operating time index has the largest spearman rank correlation coefficient, and the value of the index is 0.2218, which indicates that the index has larger correlation with other indexes, and the provided useful information has larger coincidence degree, so that the index has smaller proportion in the comprehensive importance evaluation of the nodes. The definition of 6 indexes shows that the index of the acquisition abnormal alarm times is basically irrelevant to 2 indexes of average fault-free working time and operation fault rate, has a certain relation with the 2 indexes of load acquisition availability and data acquisition integrity rate, but has weak relevance, and the calculated spearman grade correlation coefficient of the index is minimum, so that the correlation is identical with the actual correlation of the index; the average fault-free working time is very relevant to the 3 indexes of the load acquisition availability, the data acquisition integrity and the operation fault rate, and the value of the spearman class correlation coefficient of the index is calculated to be the largest, so that the average fault-free working time is also consistent with the actual correlation of the index. After the entropy weight and the spearman class correlation coefficient are integrated, the comprehensive objective weights of 6 indexes can be obtained as follows: 0.1569, 0.0865, 0.3783, 0.0974, 0.1809 and 0.0999. From this it can be seen that: after synthesis, the average fault-free working time index has the largest weight, and the acquired abnormal alarm frequency index has the smallest weight; after the correlation of the indexes is considered, the objective comprehensive weight of the average fault-free working time index is smaller than the entropy weight without the correlation, and the acquired abnormal alarm frequency index is larger than the entropy weight without the correlation.
Then, the ideal solution and the anti-ideal solution of the quality evaluation problem of the acquisition terminal equipment of the suppliers are calculated, the Euclidean distance between each supplier and the ideal solution and the Euclidean distance between each supplier and the anti-ideal solution are obtained, the relative approximation degree between each supplier and the ideal solution is calculated on the basis, and the result is shown in the table 3. As can be seen from table 3: the first 10 suppliers with the best operation quality of the acquisition terminal equipment are respectively: 10. 9, 6, 5, 11, 7, 4, 13, 14 and 16, wherein the quality of operation of the acquisition terminal device produced by supplier 10 is optimal and the quality of operation of the acquisition terminal device produced by supplier 9 is optimal.
Table 3 quality assessment results of vendor-collected terminal devices based on the method of the present invention
The result shows that the method provided by the invention can be used for considering the correlation between indexes, can reasonably evaluate the operation quality of the acquisition terminal equipment, and can provide scientific and reasonable evaluation support for material management and marketing metering professional departments.
Claims (2)
1. The acquisition terminal manufacturer evaluation method based on the multi-attribute decision model is characterized by comprising the following steps of:
1) Acquiring the original data of the acquisition terminal equipment in each batch and region, and selecting a plurality of evaluation indexes for measuring the quality of the acquisition terminal equipment according to the operation monitoring big data of the acquisition terminal equipment: the evaluation indexes comprise load acquisition availability, data acquisition integrity, average fault-free working time, acquisition abnormal alarm times, operation fault rate and online rate;
the linear definition calculation formula is:
wherein: q represents the total batch number produced by the supplier of the acquisition terminal equipment, L represents the total area number of equipment installation of a certain batch, and b ij And B ij Respectively representing the number of the acquisition terminal devices of the ith batch in the jth installation area and the total number of the acquisition terminal devices actually installed, omega ONLINE,j Is a correction factor for representing the influence of non-quality factors on the linear rate in the jth region, wherein omega is not less than 0 ONLINE,j Is less than or equal to 1
2) Calculating each evaluation index value of the acquisition terminal equipment, and constructing an index matrix; performing standardization processing on the index matrix to form a decision matrix;
3) Calculating the information entropy of the evaluation index values of each item of the acquisition terminal equipment and the correlation coefficient of the Spekerman grade, determining the objective weight of the quality evaluation index according to the CRITIC method, and carrying out weighting treatment on the decision matrix according to the objective weight to obtain an acquisition terminal equipment provider evaluation matrix;
when the entropy of the evaluation index value information of each item of the acquisition terminal equipment is calculated, the entropy weight calculation formula is as follows:
wherein:r ij decision matrix element for evaluating a problem, +.>And assume that when f ij When=0, f ij ln f ij =0; m is the number of evaluation indexes, and N is the number of schemes to be evaluated; w (w) i Entropy weight of i index is represented, w is more than or equal to 0 i ≤1，
When the spearman grade correlation coefficient of each item of the acquisition terminal equipment is calculated, the spearman grade correlation coefficient calculation formula is as follows:
wherein:for sorting value vector +.>And->Is a covariance of (2); />And->Respectively are sorting value vectors->And->Standard deviation of (2); />And->Respectively are sorting value vectors->And->Is the average value of (2); />Andis a two-column variable with N elements, and the ith variable value is z respectively ij And z ik (1.ltoreq.i.ltoreq.N), where j.epsilon. {1,2, M, k e {1,2,., M; />And->Are respectively->And->Is a vector of ordered values, wherein->And->Z respectively ij And z ik At->And->Is a ranking value of (2); ρ ik Representing the spearman rank correlation coefficient, ρ, between the jth and kth indices j An overall kendel correlation coefficient representing the jth index and other indexes;
the objective weight calculation formula is:
wherein: c (C) j Objective weight representing the j-th index;
4) According to the evaluation matrix, calculating an ideal solution of the acquisition terminal equipment suppliers, wherein the ideal solution comprises a positive ideal solution and a negative ideal solution, and calculating Euclidean distances from each acquisition terminal equipment supplier to a positive ideal point vector and a negative ideal point vector;
calculating an ideal solution to an acquisition terminal equipment vendor assessment problemAnd anti-ideal solutionWherein->
Calculating Euclidean distance between supplier of acquisition terminal equipment and ideal solution and anti-ideal solution respectivelyAnd->The calculation formula of (2) is as follows:
wherein:evaluating the ith row of the matrix Z for the weighted acquisition terminal equipment provider;
5) Calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider according to the high-low degree;
calculating the relative approximation degree of each acquisition terminal equipment provider and the ideal solution, and determining the quality grade of each acquisition terminal equipment provider sequentially from high to low, wherein the corresponding calculation formula is as follows:
wherein: c (C) i The relative approximation degree of each acquisition terminal equipment provider and the ideal solution is adopted, and the quality grade of each acquisition terminal equipment provider can be determined from high to low in sequence.
2. The method for evaluating a collection terminal manufacturer based on a multi-attribute decision model according to claim 1, wherein in step 1), a load collection availability calculation formula is:
wherein: n (N) ij 、E ij And e ij Respectively representing the number of the ith batch of equipment in the jth installation area, the total load acquisition amount and the load acquisition amount available to the evaluation system after bad data are removed; omega SAMP,j Is a correction factor for representing the influence of non-quality factors in the jth region on the load acquisition availability, wherein omega is not less than 0 SAMP,j Is less than or equal to 1
The calculation formula of the data acquisition integrity rate is as follows:
wherein: psi phi type ij Andrespectively representing theoretical data quantity to be acquired and actual data quantity to be acquired of the acquisition terminal equipment of the ith batch in the jth installation area, omega INT,j Is a correction factor for representing that the non-quality factors in the jth region influence the data acquisition integrity, and is more than or equal to 0 and less than or equal to omega INT,j Is less than or equal to 1 and is%>
The average fault-free working time calculation formula is as follows:
wherein: n (N) j The number of the acquisition terminal devices in the j-th installation area is T F,jk Is the j thThe time, omega, of initial operation of the kth device in the installation area from the time of first failure MTBF,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault-free working time, wherein omega is not less than 0 MTBF,j Is less than or equal to 1
The sum of the times of the abnormal alarm information is calculated as follows:
wherein:and->The number of serious abnormal alarms, the number of general abnormal alarms and the number of slight abnormal alarms of the product of the ith batch in the jth installation area are respectively represented;
the operation failure rate calculation formula is:
wherein: t (T) rate,jk And T stop,jk The nominal operation time and the fault shutdown time of the kth acquisition terminal equipment in the jth installation area are respectively omega FAULT,j Is a correction factor for representing the influence of non-quality factors of the jth region on the fault shutdown, wherein omega is not less than 0 FAULT,j Is less than or equal to 1
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