Intelligent sampling inspection method based on equipment life cycle

Abstract

The invention relates to an intelligent sampling inspection method and device based on an equipment life cycle, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring equipment full life cycle quality information and supplier information of power equipment materials; according to the equipment full life cycle quality information and the supplier information, carrying out differential analysis on to-be-sampled materials in the power equipment materials, and determining a differential detection score of the to-be-sampled materials; according to the differentiation detection score of the to-be-sampled material, outputting a differentiation detection scheme for the to-be-sampled material and a corresponding dynamic sampling plan; and determining a detection mechanism identifier and a test item identifier according to the differentiated detection scheme, and creating a target sampling inspection task according to the detection mechanism identifier, the test item identifier and the dynamic sampling inspection plan. By adopting the method, the intelligent degree of carrying out quality sampling inspection on the electrical equipment materials can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power equipment detection, and in particular to an intelligent sampling method, device, computer equipment, computer-readable storage medium and computer program product based on the equipment life cycle. Background Art

[0002] As the main demand side of power equipment, power grid companies should actively use the intelligent sampling model based on the full life cycle of equipment and the classification results of suppliers to promote the quality improvement of power equipment manufacturing. On the premise of fully considering the actual technical status and development needs of various types of power equipment manufacturing industries, it is necessary to use the advantages of power grid companies to drive the overall digital transformation of upstream and downstream, strengthen digital management of the supply chain and resource sharing of the industrial chain, promote common application scenarios, and serve the transformation and upgrading of the entire industry and improve governance capabilities.

[0003] In the process of quality inspection of power equipment and materials, traditional technology often conducts random inspections on power equipment and materials in a fixed manner, which lacks flexibility and cannot be adaptively adjusted according to the actual conditions of the power equipment and materials.

[0004] Therefore, there is a problem in the traditional technology that the quality sampling inspection of power equipment and materials is not intelligent enough. Summary of the invention

[0005] Based on this, it is necessary to provide an intelligent sampling method, device, computer equipment, computer-readable storage medium and computer program product based on the equipment life cycle, which can improve the intelligence of quality sampling of power equipment and materials in response to the above technical problems.

[0006] In a first aspect, the present application provides an intelligent sampling inspection method based on a device life cycle, the method comprising:

[0007] Obtaining equipment quality information and supplier information throughout the life cycle of power equipment and materials; the equipment quality information throughout the life cycle includes equipment quality information at multiple different stages of the power equipment's life cycle;

[0008] According to the equipment life cycle quality information and the supplier information, a differentiated analysis is performed on the materials to be sampled among the power equipment materials to determine the differentiated detection scores of the materials to be sampled;

[0009] Outputting a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan according to the differentiated detection scores of the materials to be inspected;

[0010] According to the differentiated detection scheme, the detection agency identifier and the test item identifier are determined, and a target sampling task is created based on the detection agency identifier, the test item identifier and the dynamic sampling plan; the target sampling task is used to be pushed to the sampling agency that matches the detection agency identifier to instruct the sampling agency to test the materials to be sampled.

[0011] In one embodiment, outputting a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan according to the differentiated detection scores of the materials to be inspected includes:

[0012] Obtaining a plurality of preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes and corresponding dynamic sampling plans;

[0013] Determining a target score range within which the differential detection score falls among the plurality of candidate score ranges;

[0014] The differentiated detection scheme corresponding to the target score range and the corresponding dynamic sampling plan are used as the differentiated detection scheme for the materials to be sampled and the corresponding dynamic sampling plan.

[0015] In one embodiment, after the step of outputting the differentiated detection scheme for the material to be sampled and the corresponding dynamic sampling plan, the method further includes:

[0016] Displaying a sampling inspection plan adjustment page of the dynamic sampling inspection plan;

[0017] In response to an adjustment operation implemented through the sampling inspection plan adjustment page, obtaining sampling inspection plan parameters newly inputted by the adjustment operation;

[0018] Generate a new dynamic sampling plan based on the sampling plan parameters.

[0019] In one embodiment, performing a differentiated analysis on the materials to be sampled among the power equipment materials based on the equipment life cycle quality information and the supplier information to determine the differentiated detection scores of the materials to be sampled includes:

[0020] According to the equipment life cycle quality information and the supplier information, query the evaluation dimension data corresponding to the supplier of the materials to be sampled under at least two evaluation dimensions; the evaluation dimensions at least include the number of daily operation failures within a preset time, the severity of the problem event, historical test results, the number of internal quality problem notifications, and the exposure scope of external quality reports;

[0021] Mapping the evaluation dimension data under each of the evaluation dimensions into a weighted score corresponding to each of the evaluation dimensions;

[0022] The weighted scores corresponding to the evaluation dimensions are integrated to obtain the differentiated detection scores of the materials to be inspected.

[0023] In one embodiment, the method further comprises:

[0024] In response to meeting the task push time indicated by the dynamic sampling plan, the target sampling task is pushed to the sampling agency that matches the testing agency identifier; the sampling agency is used to test the materials to be sampled according to the test items that match the test item identifier;

[0025] The material inspection results for the materials to be inspected sent back by the inspection agency are displayed, and the quality information of the equipment throughout its life cycle is updated based on the material inspection results.

[0026] In one embodiment, the equipment quality information includes external quality information and internal quality information; the external quality information is the equipment quality information of the category of the materials to be sampled or the supplier of the materials to be sampled obtained through the external environment; the internal quality information includes problem events, daily operation failures and historical test results reported by the category of the materials to be sampled or the supplier of the materials to be sampled within the organization.

[0027] In a second aspect, the present application also provides an intelligent sampling device based on the equipment life cycle, the device comprising:

[0028] An acquisition module is used to acquire equipment quality information and supplier information of power equipment materials throughout their life cycle; the equipment quality information throughout its life cycle includes equipment quality information of multiple different links in the entire life cycle of the power equipment;

[0029] A differential analysis module, used to perform differential analysis on the materials to be sampled among the power equipment materials according to the equipment life cycle quality information and the supplier information, and determine the differential detection scores of the materials to be sampled;

[0030] An output module, used to output a differentiated detection scheme for the materials to be sampled and a corresponding dynamic sampling plan according to the differentiated detection scores of the materials to be sampled;

[0031] A creation module is used to determine the testing agency identifier and the test item identifier according to the differentiated testing scheme, and to create a target sampling task according to the testing agency identifier, the test item identifier and the dynamic sampling plan; the target sampling task is used to be pushed to the sampling agency that matches the testing agency identifier to instruct the sampling agency to test the materials to be sampled.

[0032] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0033] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0034] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0035] The above-mentioned intelligent sampling inspection method, device, computer equipment, computer-readable storage medium and computer program product based on the equipment life cycle obtain the equipment quality information and supplier information of the power equipment materials throughout the life cycle; the equipment quality information throughout the life cycle includes the equipment quality information of multiple different links in the whole life cycle of the power equipment; and based on the equipment quality information and supplier information throughout the life cycle, the materials to be sampled in the power equipment materials are subjected to differential analysis to determine the differentiated detection scores of the materials to be sampled; then, based on the differentiated detection scores of the materials to be sampled, a differentiated detection scheme for the materials to be sampled and a corresponding dynamic sampling inspection plan are output; and by A differentiated testing plan determines the testing agency identification and the test item identification, and creates a target sampling task based on the testing agency identification, the test item identification and the dynamic sampling plan; the target sampling task is used to be pushed to the sampling agency that matches the testing agency identification to instruct the sampling agency to test the materials to be sampled; in this way, it is possible to flexibly and individually determine a differentiated testing plan suitable for the actual quality of the materials to be sampled based on the equipment life cycle quality information and supplier information of the power equipment and materials, thereby improving the efficiency of the sampling of power equipment and materials, thereby achieving an improvement in the intelligence level of quality sampling of power equipment and materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0037] FIG1 is a diagram of an application environment based on an intelligent sampling method in one embodiment;

[0038] FIG2 is a schematic diagram of a process flow based on an intelligent sampling method in one embodiment;

[0039] FIG3 is a schematic diagram of a flow chart of an intelligent sampling method in another embodiment;

[0040] FIG4 is a block diagram of a smart sampling device in one embodiment;

[0041] FIG5 is a diagram showing the internal structure of a computer device in one embodiment;

[0042] FIG6 is a schematic diagram of another intelligent sampling model in an embodiment. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0044] The intelligent sampling method based on the device life cycle provided in the embodiment of the present application can be applied in the application environment shown in FIG1 . In which, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers.

[0045] The terminal 102 obtains the equipment life cycle quality information and supplier information of the power equipment materials from the server 104; the equipment life cycle quality information includes equipment quality information of multiple different links in the whole life cycle of the power equipment; the terminal 102 performs a differentiated analysis on the materials to be inspected in the power equipment materials based on the equipment life cycle quality information and supplier information, and determines the differentiated detection scores of the materials to be inspected; the terminal 102 outputs a differentiated detection scheme for the materials to be inspected, and a corresponding dynamic inspection plan based on the differentiated detection scores of the materials to be inspected; the terminal 102 determines the inspection agency identification and the test item identification based on the differentiated detection scheme, and creates a target inspection task based on the inspection agency identification, the test item identification and the dynamic inspection plan; the target inspection task is used to be pushed to the inspection agency that matches the inspection agency identification, so as to instruct the inspection agency to inspect the materials to be inspected.

[0046] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, etc. The server 104 may be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0047] In an exemplary embodiment, as shown in FIG2 , a smart sampling method based on the device life cycle is provided, and the method is applied to the terminal 102 in FIG1 as an example for explanation, including the following steps S202 to S208 . Among them:

[0048] Step S202, obtaining equipment life cycle quality information and supplier information of power equipment materials; equipment life cycle quality information includes equipment quality information of multiple different links in the life cycle of power equipment. Specifically, the multiple different links include planning, design, demand, selection, production, testing, transportation, installation, operation, maintenance, and overhaul.

[0049] Among them, equipment quality information includes external quality information and internal quality information; external quality information is the equipment quality information of the categories of materials to be inspected or the suppliers of materials to be inspected obtained through the external environment; internal quality information includes problem events, daily operation failures and historical test results reported by the categories of materials to be inspected or the suppliers of materials to be inspected within the organization.

[0050] Among them, the equipment's full life cycle quality information also includes information related to supplier performance and operation and maintenance; supplier information refers to supplier classification and grading results and supplier evaluation results.

[0051] In a specific implementation, for the power equipment and materials to be quality inspected, the terminal can obtain the equipment quality information and supplier information of the power equipment and materials throughout their life cycle from the server.

[0052] Step S204: Perform differential analysis on the materials to be sampled among the power equipment materials based on the equipment's full life cycle quality information and supplier information to determine the differentiated detection scores of the materials to be sampled.

[0053] In the specific implementation, the terminal can conduct differentiated analysis on the materials to be inspected among the power equipment materials based on the quality information of the equipment throughout its life cycle and the supplier information, and determine the differentiated inspection scores of the materials to be inspected.

[0054] Optionally, based on the equipment's full life cycle quality information and supplier information, a differentiated analysis is performed on the materials to be inspected among the power equipment materials to determine the differentiated inspection scores of the materials to be inspected, including: based on the equipment's full life cycle quality information and supplier information, querying the evaluation dimension data corresponding to at least two evaluation dimensions of the supplier providing the materials to be inspected; the evaluation dimensions include at least the number of daily operation failures within a preset time, the severity of problem events, historical inspection results, the number of internal quality problem notifications, and the scope of external quality report exposure; mapping the evaluation dimension data under each evaluation dimension into a weighted score corresponding to each evaluation dimension; and integrating the weighted scores corresponding to each evaluation dimension to obtain the differentiated inspection scores of the materials to be inspected.

[0055] In specific implementation, the terminal can query the evaluation dimension data corresponding to at least two evaluation dimensions of the supplier of the materials to be sampled based on the equipment's full life cycle quality information and supplier information; the evaluation dimensions at least include the number of daily operation failures within a preset time, the severity of the problem event, historical test results, the number of internal quality problem notifications, and the scope of external quality report exposure. For example, the terminal can obtain the number of daily operation failures, the severity of the problem event, historical test results, the number of internal quality problem notifications, and the scope of external quality report exposure of the supplier of the materials to be sampled in the past N years.

[0056] Then, the terminal can map the evaluation dimension data under each evaluation dimension to the weighted score corresponding to each evaluation dimension. In actual applications, each evaluation dimension has multiple rating levels. The higher the rating, the higher the weighted score of the evaluation dimension; the higher the weighted score, the more serious the quality problem of the evaluation dimension.

[0057] In actual applications, each evaluation dimension can have at least three rating levels, including level 1, level 2 and level 3; among which, the weighted score corresponding to level 1 is 1; the weighted score corresponding to level 2 is 2; and the weighted score corresponding to level 3 is 3.

[0058] For example, if the number of daily operation failures in the past N years is 1, the rating level is determined to be 1; if the number of daily operation failures is 2-4, the rating level is determined to be 2; if the number of daily operation failures is 5 or more or there is a family defect, the rating level is determined to be 3;

[0059] If the severity of the problem events in the past N years is moderate, the rating level is determined to be 1; if the severity of the problem events is major, the rating level is determined to be 2; if the severity of the problem events is severe, the rating level is determined to be 3;

[0060] If the historical inspection results in the past N years show that Class C defects occurred within 1-4 times, the rating level is determined to be 1; if the historical inspection results show that Class A or B defects occurred 1-2 times or Class C defects occurred 5 times or more, the rating level is determined to be 2; if the historical inspection results show that Class A or B defects occurred 3 times or more, the rating level is determined to be 3.

[0061] If the number of internal quality problem reports in the past N years is 1, the rating level is determined to be 1; if the number of internal quality problem reports is 2-4 times, the rating level is determined to be 2; if the number of internal quality problem reports is 5 times or more, the rating level is determined to be 3.

[0062] If the external quality report exposure scope in the past N years is local or enterprise reports, the rating level is determined to be 1; if the external quality report exposure scope is industry reports, the rating level is determined to be 2; if the external quality report exposure scope is national media reports, the rating level is determined to be 3.

[0063] In actual applications, the terminal can obtain a differential analysis table, as shown in Table 1, and use the differential analysis table to quickly map the evaluation dimension data under each evaluation dimension to the weighted score corresponding to each evaluation dimension.

[0064] Table 1

[0065]

[0066] Then, the terminal integrates the weighted scores corresponding to each evaluation dimension to obtain the differentiated detection scores of the materials to be inspected. Specifically, the terminal can add the weighted scores corresponding to each evaluation dimension to obtain the differentiated detection scores of the materials to be inspected.

[0067] Step S206: output a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan according to the differentiated detection scores of the materials to be inspected.

[0068] In the specific implementation, the terminal can sample the differentiated detection scores of materials, output differentiated detection plans for the materials to be sampled, and the corresponding dynamic sampling plan.

[0069] Optionally, based on the differentiated detection scores of the materials to be inspected, a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan are output, including: obtaining a plurality of preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes, and corresponding dynamic inspection plans; determining a target score range within which the differentiated detection score falls in the plurality of candidate score ranges; and using the differentiated detection scheme corresponding to the target score range, and the corresponding dynamic inspection plan, as the differentiated detection scheme for the materials to be inspected, and the corresponding dynamic inspection plan.

[0070] Specifically, the terminal can obtain multiple preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes and corresponding dynamic sampling plans.

[0071] For example, the candidate score range A is that the differentiated detection score is less than 3 points. The differentiated detection plan corresponding to the candidate score range A is included in the routine arrival sampling, and the dynamic sampling plan corresponding to the candidate score range A is to add 1 batch in the current year; the candidate score range B is that the differentiated detection score is greater than or equal to 3 points and less than 5 points. The differentiated detection plan corresponding to the candidate score range B is included in the technical specification level inspection, and the dynamic sampling plan corresponding to the candidate score range B is to add 1 batch in the current year if no level 3 problems occur; the candidate score range C is that the differentiated detection score is greater than or equal to 5, and the differentiated detection plan corresponding to the candidate score range C is included in the special inspection (if necessary, design non-routine test plans and conduct analytical testing), and test comparison is conducted by more than 2 testing institutions; the dynamic sampling plan corresponding to the candidate score range C is to add 2 batches in the current year.

[0072] Optionally, after outputting the differentiated inspection scheme for the materials to be inspected and the corresponding dynamic inspection plan, the method also includes: displaying the inspection plan adjustment page of the dynamic inspection plan; in response to the adjustment operation implemented through the inspection plan adjustment page, obtaining the inspection plan parameters newly input by the adjustment operation; and generating a new dynamic inspection plan based on the inspection plan parameters.

[0073] In the specific implementation, the terminal can dynamically select the sampling plan on the sampling plan adjustment page; the sampling plan adjustment page displays the output of the differentiated detection scheme for the materials to be sampled, and the corresponding dynamic sampling plan; the sampling plan adjustment page also provides an adjustment entry for the dynamic sampling plan for the materials to be sampled; the user's adjustment operation on the dynamic sampling plan is obtained through the adjustment entry; the terminal can respond to the adjustment operation implemented through the sampling plan adjustment page, and obtain the sampling plan parameters newly input by the adjustment operation; the terminal then generates a new dynamic sampling plan based on the sampling plan parameters. For example, the dynamic sampling plan output by the terminal for the material A to be sampled is to add 1 batch in the current year if no level 3 problem occurs; the user can adjust the dynamic sampling plan output for the material A to be sampled to add 2 batches in the current year through the sampling plan adjustment page.

[0074] Step S208, determining the inspection agency identification and the test item identification according to the differentiated inspection scheme, and creating a target inspection task according to the inspection agency identification, the test item identification and the dynamic inspection plan.

[0075] Among them, the target sampling task is used to be pushed to the sampling agency that matches the inspection agency identification to instruct the sampling agency to inspect the materials to be sampled.

[0076] In the specific implementation, the terminal can determine the inspection agency identification and the test item identification according to the differentiated inspection scheme, and create a target sampling task according to the inspection agency identification, the test item identification and the dynamic sampling plan. Then, the terminal can push the target sampling task to the sampling agency that matches the inspection agency identification to instruct the sampling agency to test the materials to be sampled according to the test items that match the test item identification.

[0077] Optionally, the above method also includes: in response to meeting the task push time indicated by the dynamic sampling plan, pushing the target sampling task to the sampling agency that matches the testing agency identifier; the sampling agency is used to test the materials to be sampled according to the test items that match the test item identifier; displaying the material inspection results for the materials to be sampled sent back by the sampling agency, and updating the equipment's full life cycle quality information based on the material inspection results.

[0078] In a specific implementation, the terminal can determine the task push time for the target sampling task according to the dynamic sampling plan; the terminal can push the target sampling task to the sampling agency that matches the detection agency identifier in response to the trigger condition of satisfying the task push time; specifically, the terminal can send the target sampling task to the computer device configured by the sampling agency that matches the detection agency identifier, and promptly instruct the sampling agency to test the materials to be sampled according to the test items that match the test item identifier, and obtain the material test results of the materials to be sampled. The computer device configured by the sampling agency can transmit the material test results of the materials to be sampled back to the terminal; the terminal can display the material test results for the materials to be sampled returned by the sampling agency, and update the equipment's full life cycle quality information based on the material test results.

[0079] In the above-mentioned intelligent sampling inspection method based on the equipment life cycle, the equipment quality information and supplier information of the power equipment and materials throughout the life cycle are obtained; the equipment quality information throughout the life cycle includes equipment quality information of multiple different links in the whole life cycle of the power equipment; and according to the equipment quality information and supplier information throughout the life cycle, the materials to be sampled in the power equipment and materials are subjected to differential analysis to determine the differentiated detection scores of the materials to be sampled; then, according to the differentiated detection scores of the materials to be sampled, a differentiated detection scheme for the materials to be sampled and a corresponding dynamic sampling inspection plan are output; and according to the differentiated detection scheme, the detection agency identification and the test item identification are determined, and a target sampling inspection task is created according to the detection agency identification, the test item identification and the dynamic sampling inspection plan; the target sampling inspection task is used to be pushed to the sampling inspection agency matching the detection agency identification to instruct the sampling inspection agency to inspect the materials to be sampled; in this way, it is possible to flexibly and individually determine the differentiated detection scheme suitable for the actual quality of the materials to be sampled based on the equipment quality information and supplier information throughout the life cycle of the power equipment and materials, and the corresponding dynamic sampling inspection plan, so as to improve the efficiency of the sampling inspection of the power equipment and materials, thereby realizing the improvement of the intelligence level of the quality sampling inspection of the power equipment and materials.

[0080] In another embodiment, as shown in FIG. 3 , a smart sampling method based on a device life cycle is provided, which is described by taking the method applied to the terminal 102 in FIG. 1 as an example, and includes the following steps:

[0081] Step S302, obtaining equipment quality information and supplier information of power equipment materials throughout their life cycle.

[0082] Step S304, based on the equipment life cycle quality information and supplier information, query the evaluation dimension data corresponding to the supplier of the materials to be sampled under at least two evaluation dimensions.

[0083] Step S306, mapping the evaluation dimension data under each evaluation dimension into a weighted score corresponding to each evaluation dimension, integrating the weighted scores corresponding to each evaluation dimension, and obtaining a differentiated detection score for the materials to be sampled.

[0084] Step S308, obtaining a plurality of preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes and corresponding dynamic sampling plans.

[0085] Step S310 , determining a target score range into which the differential detection score falls among multiple candidate score ranges.

[0086] Step S312: Use the differentiated detection scheme corresponding to the target score range and the corresponding dynamic sampling plan as the differentiated detection scheme for the materials to be sampled and the corresponding dynamic sampling plan.

[0087] Step S314, displaying the sampling plan adjustment page of the dynamic sampling plan.

[0088] Step S316, in response to the adjustment operation implemented through the sampling plan adjustment page, the sampling plan parameters newly input by the adjustment operation are obtained, and a new dynamic sampling plan is generated according to the sampling plan parameters.

[0089] Step S318, according to the differentiated detection scheme, determine the detection agency identification and the test item identification, and create a target sampling task according to the detection agency identification, the test item identification and the dynamic sampling plan.

[0090] Step S320, in response to satisfying the task push time indicated by the dynamic sampling plan, push the target sampling task to the sampling agency that matches the testing agency identifier; the sampling agency is used to test the materials to be sampled according to the test items that match the test item identifier.

[0091] Step S322: Display the material inspection results for the materials to be inspected sent back by the inspection agency, and update the equipment life cycle quality information based on the material inspection results.

[0092] It should be noted that the specific limitations of the above steps can be found in the specific limitations of an intelligent sampling method based on the equipment life cycle mentioned above, which will not be repeated here.

[0093] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0094] Based on the same inventive concept, the embodiment of the present application also provides an intelligent sampling device based on the equipment life cycle for implementing the intelligent sampling method based on the equipment life cycle involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more intelligent sampling devices based on the equipment life cycle provided below can refer to the limitations of the intelligent sampling method based on the equipment life cycle above, and will not be repeated here.

[0095] In an exemplary embodiment, as shown in FIG4 , a smart sampling device based on the equipment life cycle is provided, comprising:

[0096] The acquisition module 410 is used to acquire equipment quality information and supplier information of power equipment materials throughout their life cycle; the equipment quality information throughout their life cycle includes equipment quality information of multiple different links in the entire life cycle of the power equipment;

[0097] The differential analysis module 420 is used to perform differential analysis on the materials to be sampled in the power equipment materials according to the equipment life cycle quality information and the supplier information, and determine the differential detection scores of the materials to be sampled;

[0098] The output module 430 is used to output a differentiated detection scheme for the materials to be sampled and a corresponding dynamic sampling plan according to the differentiated detection scores of the materials to be sampled;

[0099] A creation module 440 is used to determine the testing agency identifier and the test item identifier according to the differentiated testing scheme, and to create a target sampling task according to the testing agency identifier, the test item identifier and the dynamic sampling plan; the target sampling task is used to be pushed to a sampling agency that matches the testing agency identifier to instruct the sampling agency to test the materials to be sampled.

[0100] In one embodiment, the output module 430 is specifically used to obtain a plurality of preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes, and corresponding dynamic sampling plans; determine a target score range within which the differentiated detection score falls in the plurality of candidate score ranges; and use the differentiated detection scheme corresponding to the target score range, and the corresponding dynamic sampling plan, as the differentiated detection scheme for the materials to be inspected, and the corresponding dynamic sampling plan.

[0101] In one embodiment, the device is also used to display a sampling plan adjustment page of the dynamic sampling plan; in response to an adjustment operation implemented through the sampling plan adjustment page, obtain the sampling plan parameters newly input by the adjustment operation; and generate a new dynamic sampling plan based on the sampling plan parameters.

[0102] In one embodiment, the differential analysis module 420 is specifically used to query the evaluation dimension data corresponding to the supplier of the materials to be inspected under at least two evaluation dimensions based on the equipment's full life cycle quality information and the supplier information; the evaluation dimensions include at least the number of daily operation failures within a preset time, the severity of problem events, historical test results, the number of internal quality problem notifications, and the scope of external quality report exposure; the evaluation dimension data under each evaluation dimension is mapped into a weighted score corresponding to each evaluation dimension; the weighted scores corresponding to each evaluation dimension are integrated to obtain the differentiated detection score of the materials to be inspected.

[0103] In one of the embodiments, the device is also used to push the target sampling task to the sampling agency that matches the testing agency identifier in response to the task push time that meets the dynamic sampling plan indication; the sampling agency is used to test the materials to be sampled according to the test items that match the test item identifier; display the material inspection results for the materials to be sampled sent back by the sampling agency, and update the equipment's full life cycle quality information based on the material inspection results.

[0104] In one embodiment, the equipment quality information includes external quality information and internal quality information; the external quality information is the equipment quality information of the category of the materials to be sampled or the supplier of the materials to be sampled obtained through the external environment; the internal quality information includes problem events, daily operation failures and historical test results reported by the category of the materials to be sampled or the supplier of the materials to be sampled within the organization.

[0105] Each module in the above-mentioned intelligent sampling device based on the equipment life cycle can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0106] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG5. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner may be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, an intelligent sampling method based on the life cycle of the device is implemented. The display unit of the computer device is used to form a visually visible picture, which may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0107] Those skilled in the art will understand that the structure shown in FIG. 5 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0108] To facilitate understanding by those skilled in the art, FIG6 exemplarily provides a schematic diagram of another intelligent sampling model; wherein the intelligent sampling model is used to obtain equipment quality information and supplier information of power equipment materials throughout their entire life cycle. The equipment life cycle quality information includes external quality problem notifications, contract performance / quality problem events, daily operation failures, and historical test results; based on the equipment life cycle quality information and supplier information, differentiated analysis is performed on the materials to be sampled in the power equipment materials to determine the differentiated test scores of the materials to be sampled; based on the differentiated test scores of the materials to be sampled, a differentiated test plan for the materials to be sampled and a corresponding dynamic test plan are output; based on the differentiated test plan, the test agency identification and test item identification are determined, and a target test task is created based on the test agency identification, test item identification and dynamic test plan; the target test task is used to be pushed to the test agency that matches the test agency identification to instruct the test agency to test the materials to be sampled; in response to the task push time that meets the dynamic test plan indication, the target test task is pushed to the test agency that matches the test agency identification; the test agency is used to test the materials to be sampled according to the test items that match the test item identification; the material test results for the materials to be sampled sent back by the test agency are displayed, and the historical test results in the equipment life cycle quality information are updated according to the material test results.

[0109] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above-mentioned intelligent sampling method based on the device life cycle. The steps of the intelligent sampling method based on the device life cycle here can be the steps of the intelligent sampling method based on the device life cycle in each of the above-mentioned embodiments.

[0110] In one embodiment, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the processor executes the steps of the above-mentioned intelligent sampling method based on the device life cycle. Here, the steps of the intelligent sampling method based on the device life cycle can be the steps of the intelligent sampling method based on the device life cycle in each of the above-mentioned embodiments.

[0111] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the processor executes the steps of the above-mentioned intelligent sampling method based on the device life cycle. Here, the steps of the intelligent sampling method based on the device life cycle can be the steps of the intelligent sampling method based on the device life cycle in each of the above-mentioned embodiments.

[0112] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0113] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magneto resistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0114] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0115] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An intelligent sampling inspection method based on the equipment life cycle, characterized in that: The method comprises: Obtaining equipment quality information and supplier information throughout the life cycle of power equipment and materials; the equipment quality information throughout the life cycle includes equipment quality information at multiple different stages of the power equipment's life cycle; According to the equipment life cycle quality information and the supplier information, a differentiated analysis is performed on the materials to be sampled among the power equipment materials to determine the differentiated detection scores of the materials to be sampled; Outputting a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan according to the differentiated detection scores of the materials to be inspected; According to the differentiated detection scheme, the detection agency identifier and the test item identifier are determined, and a target sampling task is created based on the detection agency identifier, the test item identifier and the dynamic sampling plan; the target sampling task is used to be pushed to the sampling agency that matches the detection agency identifier to instruct the sampling agency to test the materials to be sampled.

2. The method according to claim 1, characterized in that Outputting a differentiated detection scheme for the materials to be inspected and a corresponding dynamic inspection plan according to the differentiated detection scores of the materials to be inspected includes: Obtaining a plurality of preset candidate score ranges; different candidate score ranges correspond to different differentiated detection schemes and corresponding dynamic sampling plans; Determining a target score range within which the differential detection score falls among the plurality of candidate score ranges; The differentiated detection scheme corresponding to the target score range and the corresponding dynamic sampling plan are used as the differentiated detection scheme for the materials to be sampled and the corresponding dynamic sampling plan.

3. The method according to claim 1, characterized in that After the step of outputting the differentiated detection scheme for the materials to be sampled and the corresponding dynamic sampling plan, the method further includes: Displaying a sampling inspection plan adjustment page of the dynamic sampling inspection plan; In response to an adjustment operation implemented through the sampling inspection plan adjustment page, obtaining sampling inspection plan parameters newly inputted by the adjustment operation; Generate a new dynamic sampling plan based on the sampling plan parameters.

4. The method according to claim 1, characterized in that: The step of performing a differentiated analysis on the materials to be sampled among the power equipment materials based on the equipment life cycle quality information and the supplier information to determine the differentiated detection scores of the materials to be sampled includes: According to the equipment life cycle quality information and the supplier information, query the evaluation dimension data corresponding to the supplier of the materials to be sampled under at least two evaluation dimensions; the evaluation dimensions at least include the number of daily operation failures within a preset time, the severity of the problem event, historical test results, the number of internal quality problem notifications, and the exposure scope of external quality reports; Mapping the evaluation dimension data under each of the evaluation dimensions into a weighted score corresponding to each of the evaluation dimensions; The weighted scores corresponding to the evaluation dimensions are integrated to obtain the differentiated detection scores of the materials to be inspected.

5. The method according to claim 1, characterized in that The method further comprises: In response to meeting the task push time indicated by the dynamic sampling plan, the target sampling task is pushed to the sampling agency that matches the testing agency identifier; the sampling agency is used to test the materials to be sampled according to the test items that match the test item identifier; The material inspection results for the materials to be inspected sent back by the inspection agency are displayed, and the quality information of the equipment throughout its life cycle is updated based on the material inspection results.

6. The method according to any one of claims 1 to 5, characterized in that: The equipment quality information includes external quality information and internal quality information; the external quality information is the equipment quality information of the category of the materials to be sampled or the supplier of the materials to be sampled obtained through the external environment; the internal quality information includes the problem events, daily operation failures and historical test results reported by the category of the materials to be sampled or the supplier of the materials to be sampled within the organization.

7. An intelligent sampling inspection device based on the equipment life cycle, characterized in that: The device comprises: An acquisition module is used to acquire equipment quality information and supplier information of power equipment materials throughout their life cycle; the equipment quality information throughout its life cycle includes equipment quality information of multiple different links in the entire life cycle of the power equipment; A differential analysis module, used to perform differential analysis on the materials to be sampled among the power equipment materials according to the equipment life cycle quality information and the supplier information, and determine the differential detection scores of the materials to be sampled; An output module, used to output a differentiated detection scheme for the materials to be sampled and a corresponding dynamic sampling plan according to the differentiated detection scores of the materials to be sampled; A creation module is used to determine the testing agency identifier and the test item identifier according to the differentiated testing scheme, and to create a target sampling task according to the testing agency identifier, the test item identifier and the dynamic sampling plan; the target sampling task is used to be pushed to the sampling agency that matches the testing agency identifier to instruct the sampling agency to test the materials to be sampled.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images