CN114254951A - Power grid equipment arrival sampling inspection method based on digitization technology - Google Patents
Power grid equipment arrival sampling inspection method based on digitization technology Download PDFInfo
- Publication number
- CN114254951A CN114254951A CN202111615474.3A CN202111615474A CN114254951A CN 114254951 A CN114254951 A CN 114254951A CN 202111615474 A CN202111615474 A CN 202111615474A CN 114254951 A CN114254951 A CN 114254951A
- Authority
- CN
- China
- Prior art keywords
- product
- type
- products
- historical
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention relates to the technical field of spot check of power grid equipment, in particular to a power grid equipment arrival spot check method based on a digitization technology, which comprises the following steps: the method comprises the steps of obtaining product information of each type of product in a plurality of products, and constructing an information matrix of each type of product according to the product information; screening out a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix; acquiring a historical spot check record of each type of product, and counting the historical qualification rate of each type of product in each spot check according to the historical spot check record; constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product; and selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the sampling inspection index corresponding to each type of products. The invention can improve the precision and efficiency of product sampling inspection.
Description
Technical Field
The invention relates to the technical field of spot check of power grid equipment, in particular to a power grid equipment arrival spot check method based on a digitization technology.
Background
The quality of the power grid equipment is an important aspect influencing the stable operation and reliability of the power grid. In recent years, the manufacturing industry of power equipment in China is rapidly developed, market competition is strong, most of the equipment has seriously surplus capacity due to low technical threshold, and partial enterprises have low cost, so that the design margin is reduced, the phenomena of material substitution, twice filling, small filling and the like occur, and the quality risk of the power grid equipment is increased. Meanwhile, the uneven management level of the power grid equipment manufacturer is also an important reason for the low quality of the power grid equipment. Therefore, in order to ensure quality, the purchased goods need to be subjected to a delivery inspection.
Most of the current product random inspection methods perform random inspection on a certain proportion of the quantity in a certain batch of equipment according to a set performance index, but when the types of products in the batch are various, different types of products contain different functional characteristics, the focused performance of each type of different products is different, and the random inspection of the set performance index can not realize accurate performance detection on the different types of products; meanwhile, the qualification rates of different products are often inconsistent, and the sampling inspection with a fixed proportion wastes sampling inspection resources, so that the sampling inspection efficiency is low.
Disclosure of Invention
The invention provides a method and a device for sampling and inspecting the arrival of power grid equipment based on a digital technology and a computer readable storage medium, and mainly aims to solve the problems of low accuracy and low efficiency in sampling and inspecting products.
In order to achieve the above object, the present invention provides a method for checking the arrival of a power grid device based on a digitization technology, which comprises:
the method comprises the steps of obtaining product information of each type of product in a plurality of products, and constructing an information matrix of each type of product according to the product information;
screening out a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix;
acquiring a historical spot check record of each type of product, and counting the historical qualification rate of each type of product in each spot check according to the historical spot check record;
constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product;
and selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the sampling inspection index corresponding to each type of products.
Optionally, the constructing an information matrix of each type of product according to the product information includes:
selecting product information corresponding to one type of products in the plurality of products one by one as target information;
performing word segmentation processing on the target information to obtain information word segmentation;
respectively calculating the similarity of each information participle and a plurality of preset feature entries, and selecting the information participle with the similarity larger than a preset similarity threshold value as a product feature participle;
and constructing the information matrix by utilizing the product characteristic word segmentation.
Optionally, constructing the information matrix by using the product feature segmentation includes:
converting the product feature segmentation into word vectors;
and writing the word vector into a pre-constructed blank matrix to obtain the information matrix.
Optionally, the screening out the spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix includes:
selecting one type of products in the plurality of products one by one as target type products;
respectively calculating a distance value between the target class product corresponding information matrix and each performance index in a plurality of preset performance indexes;
and selecting the performance index of which the distance value is smaller than a preset distance threshold value as a spot check index corresponding to the target class product.
Optionally, the respectively calculating a distance value between the target category product corresponding information matrix and each of a plurality of preset performance indexes includes:
respectively calculating the distance value between the corresponding information matrix of the target class product and each performance index in a plurality of preset performance indexes by using the following distance value algorithm:
wherein D is the distance value, xkAnd y is the information matrix corresponding to the target class product, wherein the k individual performance index is the plurality of preset performance indexes.
Optionally, the counting the historical yield of each type of product at each spot check according to the historical spot check record includes:
counting the total number of the spot checks of each type of products in the historical spot check record at each spot check;
counting the qualified quantity of the spot checks of each type of products in the historical spot check record during each spot check;
and dividing the qualified quantity of the random inspection of each type of products by the qualified quantity of the random inspection of each type of products in each random inspection to obtain the historical qualified rate of each type of products in each random inspection.
Optionally, the constructing a fitting function of the historical yield corresponding to each type of product includes:
counting the sampling inspection time of each type of product in the historical sampling inspection record during each sampling inspection;
mapping the sampling inspection time and the historical qualification rate to a pre-constructed coordinate system to obtain a qualification rate coordinate of each type of product in each sampling inspection;
calculating a fitting coordinate of each qualified rate coordinate by using a preset initial function;
calculating a difference value between the fitting coordinate and the qualified rate coordinate;
judging whether the difference value is smaller than a preset difference threshold value or not;
when the difference value is larger than or equal to the preset difference threshold value, adjusting the parameters of the initial function according to the difference value, and returning to the step of calculating the difference value between the fitting coordinate and the qualified rate coordinate;
and when the difference value is smaller than the preset difference threshold value, determining that the initial function at the moment is a fitting function.
According to the embodiment of the invention, an information matrix is constructed according to the product information of different types of products, and the information matrix is utilized to pertinently screen out the performance indexes of the response of each type of products, so that the product is pertinently sampled and inspected according to the performance indexes corresponding to each type of products, and the precision of the product sampling and inspection is improved; meanwhile, the historical spot-check records of each type of products are analyzed, the current qualification rate of each type of products is estimated, products with preset quantity are selected according to the current qualification rate corresponding to each type of products for spot-check, the spot-check of all types of products according to a fixed proportion is avoided, and the overall spot-check efficiency is improved. Therefore, the method, the device, the electronic equipment and the computer readable storage medium for the power grid equipment delivery spot check based on the digitization technology can solve the problems of low accuracy and efficiency in product spot check.
Drawings
Fig. 1 is a schematic flowchart of a method for checking a delivery of a power grid device based on a digitization technique according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a process for calculating a matching value according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating selection of a second user representation according to an embodiment of the present invention;
FIG. 4 is a functional block diagram of a product spot check device based on information screening according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device for implementing the grid device arrival spot inspection method based on the digitization technology according to an embodiment of the present invention.
The objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a power grid equipment arrival sampling inspection method based on a digital technology. The execution subject of the grid equipment arrival sampling inspection method based on the digital technology includes, but is not limited to, at least one of electronic equipment, such as a server, a terminal, and the like, which can be configured to execute the method provided by the embodiment of the present application. In other words, the grid device arrival spot check method based on the digitization technology can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides basic cloud computing services such as a cloud service, a cloud database, cloud computing, a cloud function, cloud storage, a Network service, cloud communication, a middleware service, a domain name service, a security service, a Content Delivery Network (CDN), a big data and artificial intelligence platform, and the like.
Referring to fig. 1, a schematic flow chart of a method for checking a delivery of a power grid device based on a digitization technique according to an embodiment of the present invention is shown. In this embodiment, the method for checking the arrival of the power grid equipment based on the digitization technology includes:
s1, obtaining product information of each type of products in the plurality of products, and constructing an information matrix of each type of products according to the product information.
In an embodiment of the present invention, the product information may be provided in advance by a supplier of each of the plurality of products.
In detail, the product information includes information such as a product name, a product function, a product use condition, a product applicable group, and the like.
In one practical application scenario of the invention, because each different product type includes different functional characteristics, and the performance of each different product type which needs to be paid attention to is different, in order to improve the accuracy of the spot check on the different product types, the product information of each product type can be analyzed respectively, so that the targeted spot check on each product type can be realized according to the analysis result in the following process, and the accuracy of the spot check is improved.
In an embodiment of the present invention, the product information may be analyzed to construct an information matrix that may identify each of the plurality of products.
In detail, feature extraction and semantic analysis can be respectively performed on the product information of each type of product, and then an information matrix corresponding to the product information of each type of product is generated according to the analysis result.
In the embodiment of the present invention, referring to fig. 2, the constructing an information matrix of each type of product according to the product information includes:
s21, selecting the product information corresponding to one type of the products one by one as target information;
s22, performing word segmentation processing on the target information to obtain information word segmentation;
s23, respectively calculating the similarity between each information participle and a plurality of preset feature entries, and selecting the information participle with the similarity larger than a preset similarity threshold value as a product feature participle;
and S24, constructing the information matrix by utilizing the product characteristic word segmentation.
In the embodiment of the application, the target information is split into the information participles, and each information participle is analyzed and processed independently, so that the occupation of calculation during analysis can be reduced, and the analysis efficiency is improved.
Specifically, when performing word segmentation processing on the target information, the embodiment of the present invention may search the target information in a preset standard dictionary according to different lengths, and collect contents that can be searched in the standard dictionary into information words, where the standard dictionary includes a plurality of standard words.
Furthermore, in the embodiment of the application, the similarity between each information participle and a plurality of preset feature entries can be respectively calculated by utilizing algorithms with similarity calculation functions, such as a euclidean distance algorithm, a cosine distance algorithm and the like, so that the information participles with the similarity greater than a preset similarity threshold value are selected as product feature participles, and the participles possibly used for representing target information in the information participles are screened out according to the similarity, which is favorable for improving the accuracy of the screened product feature participles.
Further, in order to facilitate subsequent analysis of the screened product feature participles, the product feature participles may be converted into word vectors.
In detail, the word vector of each word in the product feature segmentation can be queried from a preset word vector table, and the word vectors are spliced into the word vector of the product feature segmentation according to the sequence of each word in the product feature segmentation, wherein the word vector table comprises a plurality of words, and the word vectors corresponding to each word can be retrieved in the word vector table by searching each word of the product feature segmentation to obtain the word vector corresponding to each word, and the word vectors are spliced into the word vector of the product feature segmentation according to the sequence of each word in the product feature segmentation, wherein the word vector table is similar to the standard dictionary and is a pre-constructed data table comprising the word vectors corresponding to a plurality of single words.
For example, the product feature segmentation includes three characters of "teenagers", the three characters are respectively queried in the character vector table, a character vector corresponding to the "teenager" character is { a }, a character vector corresponding to the "few" character is { B }, and a character vector corresponding to the "year" character is { C }, and then the three character vectors can be spliced into the word vector of the information segmentation according to the sequence of the three characters in the product feature segmentation of "teenagers": { ABC }.
In other embodiments of the present application, the product feature word segmentation may be converted into word vectors by using word2vec models, NLP (Natural Language Processing) models, bert models, and other models having a word vector conversion function.
In the embodiment of the present application, constructing the information matrix by using the product feature segmentation includes:
converting the product feature segmentation into word vectors;
and writing the word vector into a pre-constructed blank matrix to obtain the information matrix.
Specifically, the blank matrix, that is, a matrix whose elements are all 0, may be created by a B-zeros (m, n) function in an R language library.
In the embodiment of the present application, the word vectors may be filled into the blank matrix one by one in a row vector manner, so as to obtain an information matrix including the word vectors.
And S2, screening the corresponding sampling inspection indexes of each type of products from a plurality of preset performance indexes according to the information matrix.
In the embodiment of the invention, the performance indexes include but are not limited to product specification indexes, use frequency indexes, product anti-interference capacity indexes and the like.
In one practical application scenario of the invention, each type of product corresponds to a large number of performance indexes, if the same set of performance indexes are adopted for all types of products for sampling inspection, the result of sampling inspection is not accurate enough, and when the performance indexes are excessive, the efficiency of sampling inspection is low, therefore, the sampling inspection indexes corresponding to each type of products can be screened out from a plurality of preset performance indexes according to the information matrix, the number of indexes is reduced, the sampling inspection efficiency is improved, meanwhile, the targeted index sampling inspection of different types of products is realized, and the accuracy of sampling inspection is improved.
In the embodiment of the present invention, referring to fig. 3, the screening out the spot check index corresponding to each type of product from the plurality of preset performance indexes according to the information matrix includes:
s31, selecting one type of products in the multiple products one by one as target type products;
s32, respectively calculating the distance value between the corresponding information matrix of the target type product and each performance index in a plurality of preset performance indexes;
and S33, selecting the performance index of which the distance value is smaller than a preset distance threshold value as a spot check index corresponding to the target class product.
In detail, the calculating the distance value between the target category product corresponding information matrix and each performance index of a plurality of preset performance indexes includes:
respectively calculating the distance value between the corresponding information matrix of the target class product and each performance index in a plurality of preset performance indexes by using the following distance value algorithm:
wherein D is the distance value, xkAnd y is the information matrix corresponding to the target class product, wherein the k individual performance index is the plurality of preset performance indexes.
In other embodiments of the present invention, the distance value between the information matrix corresponding to the target type product and each of the plurality of preset performance indexes may be calculated by using an algorithm having a distance value calculation function, such as a cosine distance algorithm, an euclidean distance algorithm, or the like.
And S3, acquiring the historical sampling inspection record of each type of product, and counting the historical qualification rate of each type of product in each sampling inspection according to the historical sampling inspection record.
In the embodiment of the invention, the historical spot check record comprises data such as time, spot check quantity, qualified quantity and the like of each spot check of each type of products in historical time.
In detail, the historical snapshot record can be crawled from a predetermined data storage area using a computer sentence with data crawling function (e.g., java sentence, python sentence, etc.), wherein the data storage area includes, but is not limited to, a database, a network cache.
In an embodiment of the present invention, the counting the historical yield of each product in each sampling according to the historical sampling record includes:
counting the total number of the spot checks of each type of products in the historical spot check record at each spot check;
counting the qualified quantity of the spot checks of each type of products in the historical spot check record during each spot check;
and dividing the qualified quantity of the random inspection of each type of products by the qualified quantity of the random inspection of each type of products in each random inspection to obtain the historical qualified rate of each type of products in each random inspection.
In the embodiment of the invention, because various products of different types exist, if the products of each type are subjected to the sampling inspection with uniform quantity, the waste of sampling inspection resources can be caused for the products with higher qualification rate, and the conditions of missing inspection, less inspection and the like can occur for the products with lower qualification rate, so that the sampling inspection result is inaccurate, therefore, the historical qualification rate of each type of products in each sampling inspection can be counted according to the historical sampling inspection record, and further, the subsequent targeted sampling inspection can be performed on the products of each type according to the historical qualification rate, so that the precision of the sampling inspection is improved.
S4, constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product.
In one practical application scenario of the invention, since the historical qualification rate corresponding to each product is obtained by analyzing the historical spot-check record of each product, the historical qualification rate can only represent the qualification rate performance of each product when the product is spot-checked in the history, and if the historical qualification rate is directly used for performing spot-check analysis on the existing product, the spot-check result is inaccurate.
Therefore, a fitting function of the historical qualification rate corresponding to each type of product can be established through the historical qualification rate, and the current qualification rate of each type of product can be obtained through analysis according to the fitting function, so that the current qualification rate can be conveniently utilized for carrying out random inspection on each type of product in the follow-up process, and the precision of the product random inspection is improved.
In an embodiment of the present invention, the constructing a fitting function of the historical yield corresponding to each type of product includes:
counting the sampling inspection time of each type of product in the historical sampling inspection record during each sampling inspection;
mapping the sampling inspection time and the historical qualification rate to a pre-constructed coordinate system to obtain a qualification rate coordinate of each type of product in each sampling inspection;
calculating a fitting coordinate of each qualified rate coordinate by using a preset initial function;
calculating a difference value between the fitting coordinate and the qualified rate coordinate;
judging whether the difference value is smaller than a preset difference threshold value or not;
when the difference value is larger than or equal to the preset difference threshold value, adjusting the parameters of the initial function according to the difference value, and returning to the step of calculating the difference value between the fitting coordinate and the qualified rate coordinate;
and when the difference value is smaller than the preset difference threshold value, determining that the initial function at the moment is a fitting function.
In detail, the historical qualification rate can be mapped into a pre-constructed coordinate system by using the spot check time as a dependent variable and the historical qualification rate as an independent variable, for example, if the historical qualification rate is t and the spot check time is m, the historical qualification rate and the spot check time can be mapped into the pre-constructed coordinate system to obtain a qualification rate coordinate (m, t).
For example, the preset initial function may be y ═ f (x, a), where y is a value of a dependent variable (historical yield) in the coordinate system, x is a value of an independent variable (sampling time) in the coordinate system, and a is a preset parameter to be adjusted.
Specifically, the abscissa or ordinate of all the qualification rate coordinates can be substituted into the initial function, so as to obtain a fitting coordinate corresponding to each qualification rate coordinate by using the initial function, and further obtain a difference value between the coordinates by calculating according to the qualification rate coordinates and the fitting coordinate.
In an embodiment of the present invention, the calculating a difference value between the fitting coordinate and the yield coordinate includes:
calculating a difference value between the fitting coordinate and the yield coordinate using a difference algorithm as follows:
wherein D is the difference value, N is the number of the qualification rate coordinates, aiAbscissa of the ith yield coordinate, biAs the abscissa of the i-th fitted coordinate, ciIs the ordinate of the i-th pass coordinate, diIs the ordinate of the i-th fitted coordinate.
When the difference value is greater than or equal to a preset difference threshold value, it can be determined that the fitting effect of the initial function on the qualification rate coordinates is poor, a preset optimization function (such as a Foundation Toolbox function, a Quick Fit function and the like) can be used for adjusting the parameters of the initial function according to the difference value, the preset initial function is returned to be used for calculating the fitting coordinates of each qualification rate coordinate, the difference value is recalculated until the difference value is less than the preset difference threshold value, and the initial function at the moment is determined to be the fitting function.
Further, the analyzing according to the fitting function to obtain the current yield of each type of product includes:
the current percent of pass of each type of product is obtained by utilizing the fitting function analysis as follows:
Q＝F(M)
wherein Q is the current qualification rate, F is the fitting function, and M is the current time.
And S5, selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the spot inspection indexes corresponding to each type of products.
In the embodiment of the invention, the product to be detected can be selected from each product in the plurality of products according to the current qualification rate, and the performance of the product to be detected is further tested by using the spot-check index corresponding to each product.
In the embodiment of the present invention, the selecting a product to be detected from each of the plurality of products according to the current yield includes:
selecting one type of products in the plurality of products one by one as target type products;
calculating the product between the current qualification rate corresponding to the target type product and the quantity of the target type product to obtain the quantity of the products to be selected;
and randomly selecting the products with the quantity of the products to be selected from the target class products as the products to be detected.
For example, there are class a products, class B products, and class C products, where the number of class a products is 100, the number of class B products is 200, and the number of class C products is 1000; and the current qualification rate of the products of class A is 90%, the current qualification rate of the products of class B is 80%, the current qualification rate of the products of class C is 95%, then 100 (1-90%) is selected from the products of class A to 10 products, 200 (1-80%) is selected from the products of class B to 40 products, 1000 (1-95%) is selected from the products of class C to 50 products, and the performance indexes corresponding to the products of class A are respectively utilized to carry out performance inspection on the 10 products selected from the products of class A; respectively utilizing the performance indexes corresponding to the B-class products to carry out performance inspection on 40 products selected from the B-class products; and respectively utilizing the performance indexes corresponding to the C-class products to carry out performance inspection on 50 products selected from the C-class products.
According to the embodiment of the invention, an information matrix is constructed according to the product information of different types of products, and the information matrix is utilized to pertinently screen out the performance indexes of the response of each type of products, so that the product is pertinently sampled and inspected according to the performance indexes corresponding to each type of products, and the precision of the product sampling and inspection is improved; meanwhile, the historical spot-check records of each type of products are analyzed, the current qualification rate of each type of products is estimated, products with preset quantity are selected according to the current qualification rate corresponding to each type of products for spot-check, the spot-check of all types of products according to a fixed proportion is avoided, and the overall spot-check efficiency is improved. Therefore, the method for the selective inspection of the arrival of the power grid equipment based on the digital technology can solve the problems of low accuracy and low efficiency in the selective inspection of products.
Fig. 4 is a functional block diagram of a product spot check device based on information screening according to an embodiment of the present invention.
The product selective examination device 100 based on information screening according to the present invention can be installed in an electronic device. According to the implemented functions, the product spot check device 100 based on information screening may include a matrix construction module 101, an index screening module 102, a record analysis module 103, a function analysis module 104, and a performance detection module 105. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the matrix construction module 101 is configured to obtain product information of each type of product in a plurality of products, and construct an information matrix of each type of product according to the product information;
the index screening module 102 is configured to screen a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix;
the record analysis module 103 is configured to obtain a historical sampling inspection record of each type of product, and count a historical qualification rate of each type of product in each sampling inspection according to the historical sampling inspection record;
the function analysis module 104 is configured to construct a fitting function of the historical qualification rate corresponding to each type of product, and analyze the fitting function to obtain the current qualification rate of each type of product;
the performance detection module 105 is configured to select a product to be detected from each of the plurality of products according to the current qualification rate, and perform performance inspection on the product to be detected by using a spot-check index corresponding to each product.
In detail, when used, each module in the product spot inspection device 100 based on information screening according to the embodiment of the present invention adopts the same technical means as the grid equipment to item spot inspection method based on the digital technology described in fig. 1 to fig. 3, and can produce the same technical effect, which is not described herein again.
Fig. 5 is a schematic structural diagram of an electronic device for implementing a grid device arrival spot check method based on a digitization technique according to an embodiment of the present invention.
The electronic device 1 may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may further include a computer program, such as a product spot check program based on information screening, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules (for example, executing a product sampling program based on information screening, etc.) stored in the memory 11 and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in the electronic device and various types of data, such as codes of a product spot check program based on information screening, but also temporarily store data that has been output or will be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Only electronic devices having components are shown, and those skilled in the art will appreciate that the structures shown in the figures do not constitute limitations on the electronic devices, and may include fewer or more components than shown, or some components in combination, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The product spot check program based on information filtering stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when running in the processor 10, can realize:
the method comprises the steps of obtaining product information of each type of product in a plurality of products, and constructing an information matrix of each type of product according to the product information;
screening out a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix;
acquiring a historical spot check record of each type of product, and counting the historical qualification rate of each type of product in each spot check according to the historical spot check record;
constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product;
and selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the sampling inspection index corresponding to each type of products.
Specifically, the specific implementation method of the instruction by the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to the drawings, which is not described herein again.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
the method comprises the steps of obtaining product information of each type of product in a plurality of products, and constructing an information matrix of each type of product according to the product information;
screening out a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix;
acquiring a historical spot check record of each type of product, and counting the historical qualification rate of each type of product in each spot check according to the historical spot check record;
constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product;
and selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the sampling inspection index corresponding to each type of products.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules 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 modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention 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 can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (7)
1. A power grid equipment arrival sampling inspection method based on a digitization technology is characterized by comprising the following steps:
the method comprises the steps of obtaining product information of each type of product in a plurality of products, and constructing an information matrix of each type of product according to the product information;
screening out a spot check index corresponding to each type of product from a plurality of preset performance indexes according to the information matrix;
acquiring a historical spot check record of each type of product, and counting the historical qualification rate of each type of product in each spot check according to the historical spot check record;
constructing a fitting function of the historical qualification rate corresponding to each type of product, and analyzing according to the fitting function to obtain the current qualification rate of each type of product;
and selecting a product to be detected from each type of products in the plurality of products according to the current qualification rate, and performing performance inspection on the product to be detected by using the sampling inspection index corresponding to each type of products.
2. The grid equipment arrival spot inspection method based on the digitization technology as claimed in claim 1, wherein the constructing of the information matrix of each type of product according to the product information comprises:
selecting product information corresponding to one type of products in the plurality of products one by one as target information;
performing word segmentation processing on the target information to obtain information word segmentation;
respectively calculating the similarity of each information participle and a plurality of preset feature entries, and selecting the information participle with the similarity larger than a preset similarity threshold value as a product feature participle;
and constructing the information matrix by utilizing the product characteristic word segmentation.
3. The grid equipment arrival sampling inspection method based on the digitization technology as claimed in claim 2, wherein the construction of the information matrix by using the product feature participles comprises:
converting the product feature segmentation into word vectors;
and writing the word vector into a pre-constructed blank matrix to obtain the information matrix.
4. The method for inspecting the arrival of the electric network equipment in the goods based on the digitization technology as claimed in claim 1, wherein the step of screening out the corresponding inspection index of each type of products from a plurality of preset performance indexes according to the information matrix comprises the steps of:
selecting one type of products in the plurality of products one by one as target type products;
respectively calculating a distance value between the target class product corresponding information matrix and each performance index in a plurality of preset performance indexes;
and selecting the performance index of which the distance value is smaller than a preset distance threshold value as a spot check index corresponding to the target class product.
5. The grid equipment to goods sampling method based on the digitization technology as claimed in claim 4, wherein the calculating the distance value between the target category product correspondence information matrix and each performance index of a plurality of preset performance indexes comprises:
respectively calculating the distance value between the corresponding information matrix of the target class product and each performance index in a plurality of preset performance indexes by using the following distance value algorithm:
wherein D is the distance value, xkAnd y is the information matrix corresponding to the target class product, wherein the k individual performance index is the plurality of preset performance indexes.
6. The grid equipment to goods sampling method based on the digitization technology as claimed in any one of claims 1 to 5, wherein the statistics of the historical qualification rate of each type of product at each sampling time according to the historical sampling records comprises:
counting the total number of the spot checks of each type of products in the historical spot check record at each spot check;
counting the qualified quantity of the spot checks of each type of products in the historical spot check record during each spot check;
and dividing the qualified quantity of the random inspection of each type of products by the qualified quantity of the random inspection of each type of products in each random inspection to obtain the historical qualified rate of each type of products in each random inspection.
7. The grid equipment to item spot inspection method based on the digitization technology as claimed in claim 6, wherein the constructing a fitting function of the historical yield corresponding to each type of product comprises:
counting the sampling inspection time of each type of product in the historical sampling inspection record during each sampling inspection;
mapping the sampling inspection time and the historical qualification rate to a pre-constructed coordinate system to obtain a qualification rate coordinate of each type of product in each sampling inspection;
calculating a fitting coordinate of each qualified rate coordinate by using a preset initial function;
calculating a difference value between the fitting coordinate and the qualified rate coordinate;
judging whether the difference value is smaller than a preset difference threshold value or not;
when the difference value is larger than or equal to the preset difference threshold value, adjusting the parameters of the initial function according to the difference value, and returning to the step of calculating the difference value between the fitting coordinate and the qualified rate coordinate;
and when the difference value is smaller than the preset difference threshold value, determining that the initial function at the moment is a fitting function.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111615474.3A CN114254951A (en) | 2021-12-27 | 2021-12-27 | Power grid equipment arrival sampling inspection method based on digitization technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111615474.3A CN114254951A (en) | 2021-12-27 | 2021-12-27 | Power grid equipment arrival sampling inspection method based on digitization technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114254951A true CN114254951A (en) | 2022-03-29 |
Family
ID=80798242
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111615474.3A Pending CN114254951A (en) | 2021-12-27 | 2021-12-27 | Power grid equipment arrival sampling inspection method based on digitization technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114254951A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991223A (en) * | 2015-07-27 | 2015-10-21 | 国网重庆市电力公司电力科学研究院 | Watt-hour meter state assessment index selection and quantization method |
| CN110807082A (en) * | 2018-08-01 | 2020-02-18 | 北京京东尚科信息技术有限公司 | Quality spot check item determination method, system, electronic device and readable storage medium |
| CN110826855A (en) * | 2019-10-09 | 2020-02-21 | 广州供电局有限公司 | Method and system for testing network access performance of intelligent power distribution room state monitoring sensor |
| CN111598410A (en) * | 2020-04-24 | 2020-08-28 | Oppo（重庆）智能科技有限公司 | Product spot check method and device, computer readable medium and terminal equipment |
| CN111797913A (en) * | 2020-06-23 | 2020-10-20 | 国网湖北省电力有限公司电力科学研究院 | Bayesian-based power grid distribution network key material minimum spot inspection cost calculation method |
| CN112101819A (en) * | 2020-10-28 | 2020-12-18 | 平安国际智慧城市科技股份有限公司 | Food risk prediction method, device, equipment and storage medium |
| WO2021174919A1 (en) * | 2020-03-06 | 2021-09-10 | 平安科技（深圳）有限公司 | Method and apparatus for analysis and matching of resume data information, electronic device, and medium |
-
2021
- 2021-12-27 CN CN202111615474.3A patent/CN114254951A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991223A (en) * | 2015-07-27 | 2015-10-21 | 国网重庆市电力公司电力科学研究院 | Watt-hour meter state assessment index selection and quantization method |
| CN110807082A (en) * | 2018-08-01 | 2020-02-18 | 北京京东尚科信息技术有限公司 | Quality spot check item determination method, system, electronic device and readable storage medium |
| CN110826855A (en) * | 2019-10-09 | 2020-02-21 | 广州供电局有限公司 | Method and system for testing network access performance of intelligent power distribution room state monitoring sensor |
| WO2021174919A1 (en) * | 2020-03-06 | 2021-09-10 | 平安科技（深圳）有限公司 | Method and apparatus for analysis and matching of resume data information, electronic device, and medium |
| CN111598410A (en) * | 2020-04-24 | 2020-08-28 | Oppo（重庆）智能科技有限公司 | Product spot check method and device, computer readable medium and terminal equipment |
| CN111797913A (en) * | 2020-06-23 | 2020-10-20 | 国网湖北省电力有限公司电力科学研究院 | Bayesian-based power grid distribution network key material minimum spot inspection cost calculation method |
| CN112101819A (en) * | 2020-10-28 | 2020-12-18 | 平安国际智慧城市科技股份有限公司 | Food risk prediction method, device, equipment and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| 代洲: "基于组合赋权和模糊综合评判的电网企业物资品控体系综合能效评价", 《华南理工大学学报(自然科学版)》 * |
| 曹喆岫: "基于数据挖掘的T产品质量评价研究", 《中国优秀博硕士学位论文全文数据库(硕士)经济与管理科学辑》 * |
| 李有铖: "供应商分级分类管理策略研究", 《中国设备工程》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112883190A (en) | Text classification method and device, electronic equipment and storage medium | |
| CN112613569A (en) | Image recognition method, and training method and device of image classification model | |
| CN115081025A (en) | Sensitive data management method and device based on digital middlebox and electronic equipment | |
| CN114612194A (en) | Product recommendation method and device, electronic equipment and storage medium | |
| CN113516417A (en) | Service evaluation method and device based on intelligent modeling, electronic equipment and medium | |
| CN116485220A (en) | Staff performance assessment method and device, electronic equipment and storage medium | |
| CN114862140A (en) | Behavior analysis-based potential evaluation method, device, equipment and storage medium | |
| CN113742069A (en) | Capacity prediction method and device based on artificial intelligence and storage medium | |
| CN112948705A (en) | Intelligent matching method, device and medium based on policy big data | |
| CN116303677A (en) | Measurement method, device, equipment and storage medium based on data distribution balance degree | |
| CN115641186A (en) | Intelligent analysis method, device and equipment for preference of live broadcast product and storage medium | |
| CN114518993A (en) | System performance monitoring method, device, equipment and medium based on business characteristics | |
| CN111652281B (en) | Information data classification method, device and readable storage medium | |
| CN114254951A (en) | Power grid equipment arrival sampling inspection method based on digitization technology | |
| CN114780688A (en) | Text quality inspection method, device and equipment based on rule matching and storage medium | |
| CN115062200A (en) | User behavior mining method and system based on artificial intelligence | |
| CN114840631A (en) | Spatial text query method and device, electronic equipment and storage medium | |
| CN113806492A (en) | Record generation method, device and equipment based on semantic recognition and storage medium | |
| CN113505117A (en) | Data quality evaluation method, device, equipment and medium based on data indexes | |
| CN112052310A (en) | Information acquisition method, device, equipment and storage medium based on big data | |
| CN113268614A (en) | Label system updating method and device, electronic equipment and readable storage medium | |
| CN111383050A (en) | Product data integration and analysis method, device and computer readable storage medium | |
| CN115225489B (en) | Dynamic control method for queue service flow threshold, electronic equipment and storage medium | |
| CN111309623B (en) | Coordinate class data classification test method and device | |
| CN114689975B (en) | Harmonic current-based product testing method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20220329 |