Electric power inspection scheduling method and system based on artificial intelligence

Abstract

The invention discloses a power inspection scheduling method based on artificial intelligence, and the method comprises the following steps: S1, building an artificial intelligence scheduling model, obtaining an inspection region in charge of a power inspection team, extracting the parameter data of power equipment in the inspection region, and planning the route of an inspection robot; s2, information input: inputting information of maintenance technicians, and loading items responsible for the maintenance technicians; s3, carrying out detection planning, carrying out operation fault prediction analysis on the power equipment according to historical parameter data, enabling the inspection robot to move according to a set route, carrying out one-by-one troubleshooting, carrying out the independent detection of a certain node, and controlling the inspection robot to reach a predicted maintenance node of a maintenance point; and S4, fault judgment: the inspection robot carries out online troubleshooting. According to the invention, professionals are correspondingly called for on-site maintenance, one-to-one correspondence between problems and technicians is realized, the processing speed of the problems occurring in inspection is effectively improved, and the efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent scheduling, and particularly to a power inspection scheduling method and system based on artificial intelligence. Background Art

[0002] Power lines are the main framework of the power grid, and their operation requires safety and reliability. Therefore, the inspection and maintenance of transmission lines have become the basic work to ensure the reliable power supply of the power grid. Currently, the formation of power line inspections is generally that the person in charge of the power supply work area issues tasks for the lines to be inspected, and the scheduling of inspection vehicles is based on years of work experience, with strong randomness. In the realistic background of complex power grid geographical structure relationships and expanding inspection areas, it is often difficult to achieve high-efficiency response.

[0003] The existing power inspection vehicle scheduling methods have the following problems: The scheduling method lacks data basis or is completely based on the subjective judgment of operators during scheduling, resulting in long waiting times for power inspection vehicles during peak power inspection times, causing inspection personnel to be unable to reach the inspection equipment on time, that is, people do not reach the equipment on time, a failure occurs, and the processing progress is not fast enough, and its efficiency needs to be improved. Summary of the Invention

[0004] Based on the technical problems existing in the background art, the present invention proposes a power inspection scheduling method and system based on artificial intelligence.

[0005] A power inspection scheduling method based on artificial intelligence proposed by the present invention includes the following steps:

[0006] S1: Establish an artificial intelligence scheduling model, obtain the inspection area responsible for by the power inspection team, extract the parameter data of power equipment in the inspection area at the same time, and plan the route of the inspection robot;

[0007] S2: Information entry, enter the information of maintenance technicians and load the projects responsible for by the maintenance personnel;

[0008] S3: Detection planning, conduct operation fault prediction and analysis on power equipment according to historical parameter data, the inspection robot moves according to the set route, conducts one-by-one inspections, and for a certain node that needs to be inspected separately, control the inspection robot to reach the predicted inspection node of the maintenance point;

[0009] S4: Fault judgment, the inspection robot conducts on-line inspections, the fault levels are divided into low, medium, and high, and conduct fault judgment and analysis, automatically transfer out the maintenance personnel responsible for the problem, and upload it to the dispatching desk;

[0010] S5: Location maintenance, according to the data uploaded by the robot, the system automatically calls the responsible technicians, displays the fault content on the display screen, and correspondingly calls professional personnel to conduct on-site repairs;

[0011] S6: Data is stored in the database. Technicians conduct on-site repairs and make online records, retaining videos.

[0012] S7: Technical evaluation. According to parameter comparison, evaluate the technical capabilities of technicians.

[0013] Preferably, the parameters include whether arriving at the scene on time, with an evaluation proportion of 20%; whether the repair is completed smoothly and the completion time, with an evaluation proportion of 50%; whether it is standardized, including operations and attire, with an evaluation proportion of 20%; whether the on-site environment is kept clean, with an evaluation proportion of 10%.

[0014] Preferably, the technician information includes identity information, the responsible area, and the proficient fields.

[0015] Preferably, the display screen shows the fault content, including the pictures taken and uploaded by the inspection robot, the information of the technician responsible for this fault, and the set time period to reach the target point.

[0016] Preferably, the content of the online record includes technician information, fault problems, the time to solve the problems, and the time to reach the target point.

[0017] A system for implementing an artificial intelligence-based power inspection scheduling method, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it realizes the steps of the power inspection vehicle scheduling method based on the artificial intelligence algorithm as described in any one of claims 1-4.

[0018] Preferably, both the memory and the processor are electrically connected to the inspection robot.

[0019] Preferably, the memory is used for information entry and data storage loading.

[0020] The beneficial effects in the present invention are as follows:

[0021] 1. The inspection robot conducts online troubleshooting, makes fault judgment and analysis, automatically retrieves the responsible repair personnel for the problem, uploads it to the dispatching desk. According to the data uploaded by the robot, the system automatically calls the responsible technician, and shows the fault content on the display screen, and correspondingly calls professional personnel to conduct on-site repairs, realizing a one-to-one correspondence between problems and technicians, effectively improving the processing speed of problems occurring during the inspection and improving efficiency.

[0022] 2. Technicians conduct on-site repairs, make online records, retain videos, and conduct subsequent technical evaluations. According to parameter comparison, evaluate the technical capabilities of technicians. Based on whether arriving at the scene on time, solving problems, and the degree of problem solution, it is used for subsequent professional title evaluation and performance distribution. Description of the Drawings

[0023] Figure 1 Flowchart of a power inspection and scheduling method based on artificial intelligence proposed by the present invention;

[0024] Figure 2 Connection of a power inspection and scheduling system based on artificial intelligence proposed by the present invention;

[0025] Figure 3 Evaluation method diagram of the present invention. Detailed Implementation Modes

[0026] Next, in combination with the drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0027] Refer to Figures 1-3 , a power inspection and scheduling method based on artificial intelligence, including the following steps:

[0028] S1: Establish an artificial intelligence scheduling model, obtain the inspection areas responsible for the power inspection team, and at the same time extract the parameter data of the power equipment in the inspection areas, and plan the routes of the inspection robots;

[0029] S2: Information entry, enter the information of the maintenance technicians, and load the projects responsible for the maintenance personnel;

[0030] S3: Detection planning, conduct predictive analysis of the operation faults of the power equipment according to the historical parameter data, the inspection robots move according to the set routes, conduct one-by-one inspections, and for a certain node that needs to be detected separately, control the inspection robot to reach the predicted inspection node of the maintenance point;

[0031] S4: Fault judgment, the inspection robot conducts on-line inspections, the fault levels are divided into low, medium, and high, and conduct fault judgment analysis, automatically call out the maintenance personnel responsible for the problem, and upload it to the dispatching desk;

[0032] S5: Location maintenance, according to the data uploaded by the robot, the system automatically calls the responsible technicians, and displays the fault content on the display screen, and calls the professional personnel correspondingly for on-site maintenance;

[0033] S6: Data storage, the technicians conduct on-site maintenance, make on-line records, and retain videos;

[0034] S7: Technical evaluation, evaluate the technical capabilities of the technicians according to parameter comparison.

[0035] In the present invention, the parameters include whether arriving at the site on time, with an evaluation proportion of 20%; whether the repair is successfully completed and the completion time, with an evaluation proportion of 50%; whether it is standardized, including operations and clothing, with an evaluation proportion of 20%; and whether the on-site environment is kept clean, with an evaluation proportion of 10%.

[0036] In the present invention, the technician information includes identity information, the responsible area, and the area of expertise.

[0037] In the present invention, the display screen shows the fault content, including the pictures taken and uploaded by the inspection robot, the technician information responsible for this fault, and the set time period for reaching the target point.

[0038] In the present invention, the content recorded online includes technician information, fault problems, the time to solve the problems, and the time to reach the target point.

[0039] A system for implementing a power inspection scheduling method based on artificial intelligence includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it realizes the steps of the power inspection vehicle scheduling method based on the artificial intelligence algorithm as described in any one of claims 1 - 4.

[0040] In the present invention, both the memory and the processor are electrically connected to the inspection robot.

[0041] In the present invention, the memory is used for information entry and data storage loading.

[0042] In the present invention, the inspection robot conducts online troubleshooting, performs fault judgment and analysis, automatically retrieves the maintenance personnel responsible for the problem, uploads it to the dispatching desk. According to the data uploaded by the robot, the system automatically calls the responsible technician, and shows the fault content on the display screen, and correspondingly calls professional personnel to conduct on-site repairs, realizing a one-to-one correspondence between problems and technicians, effectively improving the processing speed of problems occurring during inspection and improving efficiency;

[0043] Furthermore, the technician conducts on-site repairs, makes online records, retains videos, and conducts subsequent technical evaluations. According to parameter comparison, the technical ability of the technician is evaluated. Based on whether arriving at the site on time, solving the problem, and the degree of problem solution, it is used for subsequent professional title evaluation and performance distribution.

[0044] The above is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. An artificial intelligence-based power inspection and dispatching method, characterized in that: The following steps are involved: S1: Establish an artificial intelligence dispatching model to obtain the inspection area that the power inspection team is responsible for, extract parameter data of power equipment in the inspection area, and plan the route of the inspection robot; S2: Information entry, enter the maintenance technician information and load the projects that the maintenance technician is responsible for; S3: Inspection planning: predict and analyze the operation failure of power equipment based on historical parameter data. The inspection robot moves along the set route and conducts inspections one by one. If a certain node needs to be inspected separately, the inspection robot is controlled to arrive at the predicted maintenance node of the maintenance point. S4: Fault judgment: the inspection robot conducts online troubleshooting, classifies the fault level into low, medium, and high, and performs fault judgment and analysis, automatically calls out the responsible maintenance personnel for the problem, and uploads it to the dispatching station; S5: Positioning and maintenance: Based on the data uploaded by the robot, the system automatically calls the responsible technician and displays the fault content on the display screen. The corresponding professional personnel are called to perform maintenance on site. S6: Data is stored in the database, and technicians conduct on-site maintenance, record it online, and keep the video; S7: Technical evaluation, evaluating the technical capabilities of technicians based on parameter comparison.

2. According to the artificial intelligence-based power inspection and dispatching method of claim 1, it is characterized in that: The parameters include whether the on-site arrival is on time, accounting for 20% of the evaluation; whether the repair is completed smoothly and on time, accounting for 50% of the evaluation; whether the operation is standardized, including operation and dress, accounting for 20% of the evaluation; whether the on-site environment is kept clean, accounting for 10% of the evaluation.

3. The power inspection and dispatching method based on artificial intelligence according to claim 1 is characterized in that: The technical personnel information includes identity information, areas of responsibility and areas of expertise.

4. The power inspection and dispatching method based on artificial intelligence according to claim 1 is characterized in that: The display screen displays the fault content, including the pictures taken and uploaded by the inspection robot, the information of the technician responsible for the fault, and the time period set to reach the target point.

5. The power inspection and dispatching method based on artificial intelligence according to claim 1 is characterized in that: The content of the online record includes technician information, fault problem, time of solving the problem and time of arriving at the target point.

6. A system for implementing an artificial intelligence-based power inspection and dispatching method, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the artificial intelligence-based power inspection and dispatching method as described in any one of claims 1 to 4 are implemented.

7. The power inspection and dispatching system based on artificial intelligence according to claim 5 is characterized in that: The memory and the processor are both electrically connected to the inspection robot.

8. The power inspection and dispatching system based on artificial intelligence according to claim 5 is characterized in that: The memory is used for information entry and data loading into the database.

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