Transformer quality inspection task scheduling method and system

Abstract

The present invention belongs to the technical field of detection of distribution transformers, and in particular, relates to a method and system for scheduling transformer quality detection tasks. The following steps are included: Step 1, modeling the detection items; Step 2, modeling the detection resources; Step 3, automatically allocating detection tasks; Step 4, automatically handling abnormal situations; Step 5, adjusting the detection items; Step 6, automatically arranging preparatory work; Step 7, performing statistics and optimization. The present invention can reduce idle resources, improve detection efficiency, greatly shorten the average detection time of each distribution transformer, and improve efficiency by 17%; it can also reduce the number of handling times, reduce costs, reduce the number of power-on and power-off times, extend the service life of related equipment, and save labor costs. The present invention is suitable for all kinds of large, medium and small distribution transformer detection institutions.

Description

Technical Field

[0001] The present invention belongs to the technical field of detection of distribution transformers, and in particular relates to a method and system for scheduling transformer quality detection tasks. Background Art

[0002] With the advancement of power grid construction, many new or replaced distribution transformers (hereinafter referred to as distribution transformers) are installed in various places, and the quality inspection of distribution transformers is an important link to ensure power supply reliability and power quality. The inspection process of distribution transformers is relatively complicated, with many inspection items, and the standards, equipment, processes, safety, etc. involved in each inspection item are different, and the skill requirements for inspection personnel are also different. Abnormal situations that affect the progress of the inspection process often occur.

[0003] At present, the dispatching of distribution transformer inspection tasks usually adopts the manual scheduling method, that is, a detailed inspection plan is formulated in advance, and equipment, sites, personnel and other resources are uniformly arranged to carry out inspections step by step. This method is simple and easy to implement, but it has major defects, mainly including two aspects:

[0004] First, there is a problem of low resource utilization efficiency.

[0005] Because the inspection process of distribution transformers is relatively complicated and there are many abnormal situations, it is difficult to accurately estimate the inspection time of the project. If a project is completed ahead of schedule, the relevant resources will be idle for a period of time. If the project is delayed, other samples will be queued and the resources of other projects will be idle, causing process confusion.

[0006] Second, there is the problem of being unable to handle emergencies flexibly.

[0007] If some samples need to be returned to the factory for rectification, or the testing process needs to be temporarily changed, or a certain sample needs to be processed urgently, the shifts must be rescheduled, which is time-consuming and laborious. Summary of the invention

[0008] In view of the deficiencies in the above-mentioned prior art, the present invention provides a transformer quality inspection task scheduling method and system, the purpose of which is to realize the inspection process of distribution transformers, adopt intelligent algorithms, automatically schedule samples, equipment, sites, personnel and other resources for the inspection process, and be able to handle emergencies at any time and automatically reallocate resources, so as to meet the professional requirements of distribution transformer inspection, avoid resource waste to the greatest extent, and improve the inspection efficiency.

[0009] The technical solution adopted by the present invention to achieve the above-mentioned purpose is:

[0010] The transformer quality detection task scheduling method includes the following steps:

[0011] Step 1: Model the test items;

[0012] Step 2: Model the detection resources;

[0013] Step 3: Automatically assign detection tasks;

[0014] Step 4: Automatically handle abnormal situations;

[0015] Step 5: Adjust the test items;

[0016] Step 6: Automatically arrange preparation work;

[0017] Step 7: Perform statistics and optimization.

[0018] Furthermore, the modeling of the inspection items is to establish a digital model of each inspection item according to the inspection process and specifications of the distribution transformer.

[0019] Furthermore, the detection resources include: detection equipment, venues, personnel, logistical tools, and power facility resources. Each resource is configured with a weighted coefficient to represent its importance to the detection project and indicate whether the resources can be temporarily deployed and whether they can be matched with each other.

[0020] Furthermore, the automatic allocation of detection tasks is to use an intelligent scheduling algorithm to automatically compile detection tasks for distribution transformers;

[0021] The intelligent scheduling algorithm is a system that uses parameters or variables of multiple dimensions and their weighted factors, comprehensively considers various factors, and performs weighted calculations to obtain the best task allocation solution;

[0022] The intelligent scheduling algorithm comprises the following steps:

[0023] Step 3.1 Automatically select the test items and mark various attributes according to the sample model and test type;

[0024] Step 3.2: automatically calculate the priority of the sample according to the test type and the nature of the sample sending unit, and integrate the sample priority into the project priority to generate a new project priority;

[0025] The specific algorithm is: if the sample priority is the highest level (deadline), the priority of all related projects will be set to the highest level (deadline); if the sample priority is the second level (urgent), the project priority will be increased by 33%; if the sample priority is the third level (urgent), the project priority will remain unchanged; if the sample priority is the lowest level (general), the priority of all related projects will be set to the lowest;

[0026] Step 3.3 loops through each test bench and each sample to calculate the optimal scheduling result;

[0027] Assume that the number of test benches is m, each test bench is marked as Ti, where i=1,2,...,m; the number of samples is n, the sample currently placed on the test bench Ti is Ti0, and each sample is marked as Yj, where j=1,2,...,n; use the loop traversal method to calculate the weight of deploying Yj to Ti, recorded as R(i,j);

[0028] The calculation method is as follows:

[0029] (1) If Yj->Ti can increase the number of projects with the highest priority, that is, allow the projects with the highest priority to start testing in advance, then set R to the maximum value of 100;

[0030] (2) The R value is preset to Q(Yj)-Q(Yi0), where Q(Yj) represents the weight of the test items of sample Yj on the test bench;

[0031] (3) If Yj->Ti, then add one more transport, subtract the transport weight from the R value, which can be optimized, and the initial value is 10; the basis for judging whether transport is needed is the value of j and i0, if the two are equal, then no transport is needed;

[0032] (3) If Yj->Ti, then add a power supply and power off, and subtract the power supply and power off weight from the R value, which can be optimized. The initial value is 20. Among them, the basis for judging whether power supply and power off is needed is the voltage and current parameters of the two samples before and after the scheduling. If the parameters are the same, continuous power supply can be provided.

[0033] (4) In the above calculation, it is also necessary to check the process specifications and mandatory inspection sequence specifications. If the specifications are violated, the R value is directly set to the minimum value of -100;

[0034] After obtaining all R values, select the largest and non-repeating n scheduling items to form the optimal scheduling solution.

[0035] Furthermore, the automatic handling of abnormal situations refers to automatically handling abnormal situations if they occur during the detection of distribution transformers, automatically finding the optimal path, and reallocating detection tasks;

[0036] The abnormal situations include: the need to return to the factory for rectification, the need for discussion and decision-making by the expert committee, and the temporary absence of inspection personnel with relevant skills. The specific situation is filled in the system, and the system starts the scheduling algorithm to reallocate resources;

[0037] Automatically find the optimal path and redistribute tasks, including the following steps:

[0038] Step (1) According to the actual situation, the abnormalities are divided into four categories: 1-situation feedback, 2-client rectification, 3-unqualified reporting, and 4-application for sample return;

[0039] Step (2) For Category 1 abnormality, the system does not start the rescheduling procedure, but only makes a record. Once Category 1 abnormality occurs twice in the same sample, it is automatically upgraded to Category 3 abnormality.

[0040] Step (3) For the second type of anomaly, the system retrieves the rectification records of the same client for the same type of anomaly and calculates the average rectification period. If the period is less than the set threshold, the initial value is 2 days, and there are no urgent samples among the samples to be inspected, the rescheduling procedure will not be started. Otherwise, the rescheduling procedure will be started.

[0041] Step (4) For category 3 and category 4 exceptions, the rescheduling procedure is started immediately.

[0042] Furthermore, the adjustment of the inspection items refers to adjusting the inspection items and modifying the sample priority before and during the inspection; after adjusting the items or modifying the priority, the scheduling system will automatically adjust the inspection order, while considering factors such as inspection quality, transportation cost, and power outage times, and combining all factors with their weighted factors to obtain the optimal result.

[0043] Furthermore, the automatic arrangement of the preparatory work means that after the detection task is generated, the scheduling system will automatically arrange the preparatory work at a specified time according to the settings.

[0044] Furthermore, the statistics and optimization refer to that after the sample testing is completed, the scheduling system will count the indicators of equipment idleness, number of transportation times, and number of power outages, and make horizontal and vertical comparisons to optimize the scheduling algorithm.

[0045] The transformer quality inspection task scheduling system adopts a single-server single-network architecture. The management and control platform interacts with the laboratory through switches. The scheduling system includes the following modules: data management module, real-time calculation module, human-computer interaction module and result notification module.

[0046] The execution order of the modules is:

[0047] (1) Execute the data management module and prepare basic data;

[0048] (2) Execute the real-time calculation module to calculate the transformer quality inspection task scheduling results;

[0049] (3) Execute the human-computer interaction module and confirm it by the user;

[0050] (4) Finally, the execution result notification module notifies the operator of the calculated task scheduling plan;

[0051] The hardware of the system is connected by a local area network;

[0052] The data management module is responsible for inputting and storing various archival data, test data, business processes, and historical records;

[0053] The real-time calculation module is responsible for calling the algorithm and calculating the scheduling result of the distribution transformer detection task;

[0054] The human-computer interaction module is responsible for human-computer interaction and human intervention in the scheduling process;

[0055] The result notification module uses an on-site indicator screen, a mobile client, etc. to feed back the dispatch results to on-site staff.

[0056] A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the transformer quality detection task scheduling method.

[0057] The present invention has the following beneficial effects and advantages:

[0058] The present invention provides a transformer quality inspection task scheduling method. The present invention uses an intelligent scheduling algorithm, adopts a multidimensional vector model and a machine learning algorithm, and can evaluate various indicators of the inspection results, such as inspection time, number of transports, number of power outages, etc., and automatically feeds back to the scheduling algorithm, adjusts relevant calculation parameters, and performs self-optimization.

[0059] The present invention is applicable to various large, medium and small distribution transformer detection institutions, and has achieved good results after trial use by the detection institutions. It mainly includes the following aspects:

[0060] (1) Reduce idle resources and improve detection efficiency. The average detection time for each distribution transformer was reduced from 12 working days to 10 working days, improving efficiency by 17%.

[0061] (2) Reduce the number of handling times and reduce costs. The average number of handling times for each distribution transformer has been reduced from 6 times to 5.5 times.

[0062] (3) Reduce the number of power on and off times. The average number of power on and off times for each distribution transformer has been reduced from 9 to 8 times, which can extend the service life of related equipment and save labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0064] Figure 1 It is a system architecture diagram of the present invention;

[0065] Figure 2 It is a flow chart for realizing the automatic dispatching system of the distribution transformer detection process of the present invention. DETAILED DESCRIPTION

[0066] In order to more clearly understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0067] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0068] Refer to the following Figure 1 and Figure 2 The technical solutions of some embodiments of the present invention are described.

[0069] Example 1

[0070] The present invention provides an embodiment, which is a transformer quality detection task scheduling method, such as Figure 2 As shown, Figure 2 It is a flow chart for realizing the automatic dispatching system of the distribution transformer detection process of the present invention.

[0071] The scheduling method of the present invention specifically comprises the following steps:

[0072] Step 1: Model the test items;

[0073] Specifically, a digital model of each inspection item is established based on the inspection process and specifications of the distribution transformer.

[0074] The inspection process and specification include the order information of the inspection items, such as which items must be carried out before the short-circuit test, which items must be carried out after the short-circuit test, which items must be carried out in order, which items can be carried out at any time, etc. Specifically, the inspection process, required equipment, required site, required personnel skills, average duration, shortest duration, abnormal conditions, abnormal probability, etc. The scheduling algorithm needs to use these parameters when calculating the optimal result.

[0075] Step 2: Model the detection resources;

[0076] The detection resources of distribution transformers include: detection equipment, sites, personnel, logistics tools, power supply facilities and other resources. When scheduling detection tasks, these resources must be fully considered to avoid resource conflicts and maximize resource idleness to improve efficiency. Each resource is configured with a weighted coefficient to indicate the importance of the detection project, and indicate whether the resources can be temporarily deployed and whether they can be matched with each other.

[0077] Step 3: Automatically assign detection tasks;

[0078] The automatic allocation of detection tasks specifically adopts an intelligent scheduling algorithm to automatically compile detection tasks for distribution transformers.

[0079] The intelligent scheduling algorithm is a system that uses parameters or variables of multiple dimensions and their weighted factors, and comprehensively considers various factors such as sample model, test type, nature of the sample delivery unit, current number of samples in inventory, laboratory status, use of testing equipment, maintenance plan of testing equipment, qualifications and other skills of relevant testing personnel, urgency of samples, etc., and performs weighted calculation to obtain the best task allocation plan.

[0080] The laboratory status specifically includes the number of samples being tested, etc.

[0081] The sample models include laminated core, amorphous, three-dimensional rolled core, high overload, dry type, etc.

[0082] The types of testing include state grid random inspection tests, provincial random inspection tests, type tests, commissioned tests, etc.

[0083] The nature of the unit includes the user unit, production unit, entrusting unit, management department, etc.

[0084] The specific process of the intelligent scheduling algorithm of the present invention includes the following steps:

[0085] Step 3.1 Automatically select the test items and mark various attributes based on the sample model and test type.

[0086] The various attributes include: whether it must be checked, whether it is destructive, whether it must be before or after a certain item, etc., and a priority is assigned to each item.

[0087] Step 3.2 automatically calculates the priority of the sample based on the test type and the nature of the sample sending unit, and integrates the sample priority into the project priority to generate a new project priority.

[0088] The specific algorithm is: if the sample priority is the highest level (deadline), the priority of all related projects will be set to the highest level (deadline); if the sample priority is the second level (urgent), the project priority will be increased by 33%; if the sample priority is the third level (expedited), the project priority will remain unchanged; if the sample priority is the lowest level (general), the priority of all related projects will be set to the lowest.

[0089] Step 3.3 loops through each test bench and each sample to calculate the optimal scheduling result.

[0090] Suppose the number of test benches is m, each test bench is marked as Ti (where i=1,2,...,m; the number of samples is n, the sample currently placed on the test bench Ti is Ti0, and each sample is marked as Yj (where j=1,2,...,n). The current problem is to solve "whether to allocate Yj to Ti", recorded as Yj->Ti (note that j and i are variables). The method adopted by this algorithm is to loop through and calculate the weight of allocating Yj to Ti, recorded as R(i,j). The specific calculation method is:

[0091] (1) If Yj->Ti can increase the number of items with the highest priority, that is, allow the items with the highest priority to start testing in advance, then set R to the maximum value of 100.

[0092] (2) The R value is preset to Q(Yj)-Q(Yi0), where Q(Yj) represents the weight of the test items performed on sample Yj on the test bench.

[0093] (3) If an additional transport is required after Yj->Ti, the transport weight (which can be optimized, with an initial value of 10) is subtracted from the R value. The basis for determining whether transport is required is the values ​​of j and i0. If the two are equal, no transport is required.

[0094] (3) If an additional power supply and power cut is required after Yj->Ti, the power supply and power cut weight (which can be optimized, with an initial value of 20) is subtracted from the R value. The basis for judging whether power supply and power cut is needed is the voltage and current parameters of the two samples before and after the scheduling. If the parameters are the same, continuous power supply can be provided without power supply and power cut operation.

[0095] (4) In the above calculation, it is also necessary to check the process specifications and mandatory test sequence specifications. If the specifications are violated, the R value is directly set to the minimum value of -100. The process specifications and mandatory test sequence specifications refer to the sample testing specifications formulated by the State Grid Corporation of China, which stipulate the order of some test items. For example, item A must be carried out before item B and cannot be carried out after item B.

[0096] After obtaining all R values, select the largest and non-repeating n scheduling items to form the optimal scheduling solution.

[0097] The intelligent scheduling algorithm adopts a multidimensional vector model and a machine learning algorithm, which can evaluate various indicators of the detection results, such as detection time, number of transports, number of power outages, etc., and automatically feed back to the scheduling algorithm to adjust relevant calculation parameters for self-optimization.

[0098] Step 4: Automatically handle abnormal situations;

[0099] If an abnormal situation occurs during the detection of the distribution transformer, the dispatching system and the dispatching method of the present invention can automatically process it, automatically find the optimal path, and reallocate the detection task.

[0100] The abnormal situations include: need to return to the factory for rectification, need for discussion and decision by the expert committee, temporary absence of testing personnel with relevant skills, etc. The specific situation can be filled in the system, and the system will start the scheduling algorithm to reallocate resources. Various factors will be considered during the reallocation, and under the premise of meeting the requirements of the testing process, the idle resources will be reduced as much as possible, and the number of handling and power outages will be reduced.

[0101] When searching for the optimal path, the following factors need to be considered comprehensively to obtain a weighted optimal value:

[0102] (1) The new task cannot conflict with the testing process, equipment function, site capacity, personnel skills, etc.;

[0103] (2) Avoid idle resources as much as possible and improve detection efficiency;

[0104] (3) Try to avoid repeatedly moving samples and repeatedly switching on and off power to save manpower and material costs.

[0105] When an exception occurs, the optimal path is automatically found and tasks are reallocated, which includes the following steps:

[0106] Step (1) First, according to the actual situation, the anomalies are divided into four categories: 1-situation feedback, 2-client rectification, 3-non-conformity reporting, and 4-application for sample return;

[0107] Step (2) For Category 1 abnormalities, the system does not start the rescheduling procedure, but only makes a record. Once Category 1 abnormalities occur twice in the same sample, it is automatically upgraded to Category 3 abnormalities.

[0108] Step (3) For the second type of anomaly, the system retrieves the rectification records of the same client for the same type of anomaly and calculates the average rectification period. If the period is less than the set threshold (the initial value is 2 days) and there are no urgent samples among the samples to be inspected, the rescheduling procedure will not be started. Otherwise, the rescheduling procedure will be started.

[0109] Step (4) For the third and fourth types of exceptions, the rescheduling procedure is started immediately. The algorithm of the rescheduling procedure is the same as the scheduling algorithm when allocating tasks.

[0110] Step 5: Adjust the test items;

[0111] Before and during the test, you can manually adjust the test items and modify the sample priority. After adjusting the items or modifying the priority, the scheduling system will automatically adjust the test order, taking into account factors such as test quality, handling costs, and power outage times, and combine all factors with their weighted factors to obtain the best results.

[0112] The manual adjustment of the test items is to manually adjust and intervene in the test tasks, such as temporarily changing the priority of the samples. The system sets the priority of the samples to multiple levels such as "general", "urgent", "extremely urgent", and "limited". Users can adjust the priority after obtaining authorization, and the system will automatically trigger the scheduling algorithm to reallocate the test tasks.

[0113] Step 6: Automatically arrange preparation work;

[0114] After the inspection task is generated, the scheduling system will automatically arrange the preparatory work at the specified time according to the settings to ensure the smooth progress of the inspection project.

[0115] The preparation work refers to the various preparations that need to be carried out in advance before the start of the testing project, including: transporting and handing over samples, arranging venues, preparing high-voltage power supplies, preparing safety isolation measures, etc. The system can automatically issue relevant notifications based on the task scheduling results, allowing relevant personnel to prepare in advance.

[0116] During the specific implementation, the preparation work to be done in advance includes: if the location of the sample needs to change, the system will automatically notify the logistics personnel 30 minutes before the start of the project to prepare to move the sample; if the test project requires high voltage electricity, the system will automatically notify the power supply management personnel 15 minutes before the start and after the end of the project to prepare to cut off the power supply; before conducting tests such as lightning strikes and short-circuit withstand capacity, safety warnings will be automatically issued to avoid safety hazards.

[0117] Step 7: Perform statistics and optimization.

[0118] After the sample testing is completed, the scheduling system will collect statistics on indicators such as equipment idleness, number of handling times, number of power outages, etc., and conduct horizontal and vertical comparisons to continuously optimize the scheduling algorithm.

[0119] In specific implementation, after the detection task is completed, the system will start the statistical evaluation program to count and compare various indicators in the sample detection process in order to optimize the relevant algorithms.

[0120] Example 2

[0121] The present invention further provides an embodiment, which is a transformer quality detection task scheduling system, such as Figure 1 As shown, Figure 1 It is a system architecture diagram of the present invention.

[0122] The dispatching system of the present invention adopts a single server single network architecture, and the management and control platform interacts with 10 laboratories through switches. The system of the present invention involves more than 200 testing equipment (pieces) and about 50 testing personnel.

[0123] The dispatching system of the present invention can perform more than 10 inspection items on the distribution transformer, including: insulation resistance measurement, voltage ratio measurement and connection group number verification, winding resistance measurement, external applied voltage withstand test, induced voltage withstand test, no-load current and no-load loss measurement, short-circuit impedance and load loss measurement, temperature rise test, sound level measurement, short-circuit withstand capacity test, lightning impulse test, partial discharge test, insulation heat resistance grade, overload capacity, insulating oil test and other inspection items.

[0124] The transformer quality inspection task scheduling system of the present invention comprises the following functional modules: a data management module, a real-time calculation module, a human-computer interaction module, and a result notification module.

[0125] The execution order of the modules is:

[0126] (1) Execute the data management module and prepare basic data;

[0127] (2) Execute the real-time calculation module to calculate the transformer quality inspection task scheduling results;

[0128] (3) Execute the human-computer interaction module and confirm it by the user;

[0129] (4) Finally, the execution result notification module notifies the staff of the calculated task scheduling plan.

[0130] The hardware of the system is connected by a local area network.

[0131] Among them, the data management module is responsible for inputting and storing various types of archival data, test data, business processes, historical records, etc.

[0132] The real-time calculation module is responsible for calling the algorithm and calculating the scheduling result of the distribution transformer detection task.

[0133] The human-computer interaction module is responsible for human-computer interaction and performs human intervention in the scheduling process.

[0134] The result notification module uses an on-site indicator screen, a mobile client, etc. to feed back the dispatch results to on-site staff.

[0135] Example 3

[0136] Based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the transformer quality detection task scheduling method described in Example 1 are implemented.

[0137] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0138] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0139] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0140] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A transformer quality inspection task scheduling method, characterized by: The following steps are involved: Step 1. Model the inspection items. According to the inspection process and specifications of the distribution transformer, establish a digital model for each inspection item; Step 2. Model the inspection resources; Step 3. Automatically assign inspection tasks. Use intelligent scheduling algorithms to automatically compile inspection tasks for distribution transformers. The intelligent scheduling algorithm is a system that uses parameters or variables of multiple dimensions and their weighting factors, comprehensively considers various factors, and performs weighted calculations to obtain the best task allocation plan; Step 4. Automatically handle abnormal situations. If abnormal situations occur during the inspection of distribution transformers, they will be automatically handled, the optimal path will be automatically found, and the inspection tasks will be reallocated; Step 5. Adjusting the test items means adjusting the test items and modifying the sample priority before and during the test. After modifying the sample priority, the scheduling system will automatically adjust the test order, taking into account the test quality, handling cost, and power outage times, and combining all factors with their weighted factors to obtain the best result. Step 6. Automatically arrange preparation work means that after the test task is generated, the scheduling system will automatically arrange the preparation work at the specified time according to the settings. Step 7. Perform statistics and optimization means that after the sample test is completed, the scheduling system will perform statistics on equipment idleness, handling times, and power outage times, and perform horizontal and vertical comparisons to optimize the scheduling algorithm. The intelligent scheduling algorithm includes: step 3.1 automatically selects the test items according to the sample model and the test type, and marks various attributes; step 3.2 automatically calculates the priority of the sample according to the test type and the nature of the sample delivery unit, and integrates the sample priority into the project priority to generate a new project priority; the specific algorithm is: if the deadline of the sample priority is the highest level, the deadline of the priority of the relevant projects is set to the highest level; if the sample priority is the second level of emergency, the project priority is increased by 33%; if the sample priority is the third level of emergency, the project priority remains unchanged; if the sample priority is the lowest level of general, the priority of the relevant projects is set to the lowest; step 3.3 loops through each test bench and each sample to calculate the optimal scheduling result; suppose the number of test benches is m, each test bench is marked as Ti, where i = 1, 2, ..., m; the number of samples is n, the sample currently placed on the test bench Ti is Ti0, and each sample is marked as Yj, where j = 1, 2, ..., n; the loop traversal method is used to calculate the weight of allocating Yj to Ti, recorded as R (i, j); the calculation method is as follows: (1) If after Yj->Ti, the number of the highest priority items can be increased, so that the highest priority items can be tested in advance, then R is set to the maximum value of 100; (2) The R value is preset to Q(Yj)-Q(Ti0), where Q(Yj) represents the weight of the test items of sample Yj on the test bench; (3) If after Yj->Ti, an additional transport is added, and the R value is subtracted from the transport weight for optimization, with the initial value of 10; the judgment basis for whether transport is needed is the values ​​of j and i0, such as If they are equal, no transportation is required; (4) If Yj->Ti, then add a power supply and power off, subtract the power supply and power off weight from the R value, and optimize it. The initial value is 20; Among them, the basis for judging whether power supply and power off is needed is the voltage and current parameters of the two samples before and after scheduling. If the parameters are the same, continuous power supply is provided; In the above calculation, it is also necessary to check the process specifications and mandatory inspection sequence specifications. If the specifications are violated, the R value is directly set to the minimum value -100; After obtaining all R values, select the largest and non-repeating n scheduling items to form the best scheduling plan.

2. The transformer quality detection task scheduling method according to claim 1 is characterized in that: The testing resources include: testing equipment, sites, personnel, logistical tools, and power facilities. Each resource is configured with a weighted coefficient to indicate its importance to the testing project and whether the resources can be temporarily deployed and whether they can be matched with each other.

3. The transformer quality detection task scheduling method according to claim 1 is characterized in that: The abnormal situations include: the need to return to the factory for rectification, the need for discussion and decision-making by the expert committee, and the temporary absence of inspection personnel with relevant skills. The specific situation is filled in the system, and the system starts the scheduling algorithm to reallocate resources; Automatically find the optimal path and redistribute tasks, including the following steps: Step (1) According to the actual situation, the abnormalities are divided into four categories: 1-situation feedback, 2-client rectification, 3-unqualified reporting, and 4-application for sample return; Step (2) For Class 1 abnormalities, the system does not start the rescheduling procedure, but only makes a record. Once Class 1 abnormalities occur twice in the same sample, it is automatically upgraded to Class 3 abnormalities. Step (3) For the second type of anomaly, the system retrieves the rectification records of the same client for the same type of anomaly and calculates the average rectification period. If the period is less than the set threshold, the initial value is 2 days, and there are no urgent samples among the samples to be inspected, the rescheduling procedure will not be started. Otherwise, the rescheduling procedure will be started. Step (4) For category 3 and category 4 exceptions, the rescheduling procedure is immediately initiated.

4. A transformer quality inspection task scheduling system, based on the transformer quality inspection task scheduling method according to claim 1, characterized in that: A single-server single-network architecture is adopted, and the management and control platform interacts with the laboratory through switches; the scheduling system includes the following modules: data management module, real-time calculation module, human-computer interaction module and result notification module; The execution order of the modules is: (1) Execute the data management module and prepare basic data; (2) Execute the real-time calculation module to calculate the transformer quality inspection task scheduling results; (3) Execute the human-computer interaction module and confirm it by the user; (4) Finally, the execution result notification module notifies the operator of the calculated task scheduling plan; The hardware of the system is connected by a local area network; The data management module is responsible for inputting and storing various archival data, test data, business processes, and historical records; The real-time calculation module is responsible for calling the algorithm and calculating the scheduling result of the distribution transformer detection task; The human-computer interaction module is responsible for human-computer interaction and human intervention in the scheduling process; The result notification module uses an on-site indicator screen and a mobile client to feed back the dispatch results to on-site staff.

5. A computer storage medium, characterized in that: The computer storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the transformer quality detection task scheduling method described in claims 1-3 are implemented.

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