CN-121979129-A - Air-ground collaborative inspection decision-making method and system for direct current and extra-high voltage transformer substation

CN121979129ACN 121979129 ACN121979129 ACN 121979129ACN-121979129-A

Abstract

The application relates to a method and a system for making a decision on the collaborative night and space inspection of a direct current and extra-high voltage transformer substation, which relate to the technical field of transformer substation inspection and comprise the steps of collecting daily inspection tasks; the method comprises the steps of responding to a daily inspection task to inspect a transformer substation to generate inspection initial data and data source equipment, inputting the inspection initial data and the corresponding data source equipment into an edge calculation module to analyze so as to determine abnormal confidence, judging whether the abnormal confidence is not smaller than a confidence threshold, if not, continuing inspecting the transformer substation in response to the daily inspection task to generate the inspection initial data, if so, acquiring abnormal detection equipment corresponding to the abnormal confidence, determining check detection equipment according to the abnormal detection equipment, controlling the check detection equipment to assist the abnormal detection equipment to perform collaborative check so as to generate check detection data, and analyzing the check detection data so as to determine equipment early warning signals. The application has the effect of improving the timeliness of the inspection response.

Inventors

LIANG CHUAN
LI YANG
LI HONGYAN

Assignees

浙江天铂云科光电股份有限公司

Dates

Publication Date: 20260505
Application Date: 20251226

Claims (9)

1. The space-ground collaborative inspection decision-making method for the direct current and extra-high voltage transformer substation is characterized by comprising the following steps of: Collecting a daily inspection task; the method comprises the steps that a preset unmanned aerial vehicle, a preset robot dog and a preset fixed device carry out inspection on a preset transformer substation in response to a daily inspection task so as to generate inspection initial data and corresponding data source equipment; inputting the inspection initial data and the corresponding data source equipment into a preset edge calculation module for analysis so as to determine abnormal confidence; judging whether the abnormal confidence coefficient is not smaller than a preset confidence coefficient threshold value; If not, the unmanned aerial vehicle, the machine dog and the fixed equipment continue to carry out inspection on the transformer substation in response to the daily inspection task so as to generate inspection initial data; If yes, acquiring an abnormality detection device corresponding to the abnormality confidence, and determining a rechecking detection device according to the abnormality detection device; controlling the review detection equipment to assist the abnormality detection equipment to carry out collaborative review so as to generate review detection data; And analyzing the recheck detection data to determine the equipment early warning signal.
2. The method for collaborative space-time patrol decision-making of direct current and extra-high voltage transformer stations according to claim 1, wherein the step of inputting patrol initial data and corresponding data source equipment into a preset edge calculation module for analysis to determine abnormal confidence comprises: Searching corresponding equipment abnormal characteristic weights in a preset equipment abnormal characteristic weight relation according to the inspection initial data and the corresponding data source equipment; searching a corresponding data maximum value and a corresponding data minimum value in a preset data threshold relation according to the inspection initial data; judging whether the inspection initial data meets the requirement of a data minimum value or not; if not, removing the inspection initial data; If yes, analyzing the inspection initial data, the equipment abnormal characteristic weight, the data maximum value and the data minimum value to determine the abnormal confidence.
3. The method for collaborative space-time patrol decision-making of direct current and extra-high voltage transformer stations according to claim 2, wherein the step of analyzing patrol initial data, equipment anomaly characteristic weights, data maxima and data minima to determine anomaly confidence comprises: Normalizing the inspection initial data according to the data maximum value and the data minimum value to generate abnormal characteristic offset degree; weighting and summing the abnormal characteristic offset degree according to the abnormal characteristic weight of the equipment to generate initial confidence coefficient; Searching a corresponding equipment reliability coefficient in a preset equipment reliability coefficient relation according to the data source equipment; and correcting the initial confidence coefficient according to the equipment reliability coefficient to generate an abnormal confidence coefficient.
4. The air-ground collaborative inspection decision-making method for direct current and extra-high voltage substations according to claim 1, wherein the step of controlling the review detection device to assist the anomaly detection device in collaborative review to generate review detection data comprises: Collecting the position of an abnormal device and the position of a rechecking device of a rechecking detection device; searching a corresponding rechecking data type and a collaborative rechecking position in a preset data rechecking corresponding relation according to the initial data and the abnormal equipment position; Controlling the rechecking detection equipment to move from the rechecking equipment position to the collaborative rechecking position; controlling a rechecking detection device to detect the collaborative rechecking position according to the rechecking data type so as to generate collaborative rechecking data; Associating the inspection initiation data with the collaborative review data to generate review detection data.
5. The method for collaborative space-time patrol decision-making for direct current and extra-high voltage transformer substations according to claim 4, wherein the step of controlling the movement of the rechecking detection device from the rechecking device position to the collaborative rechecking position comprises: Analyzing the rechecking equipment position and the collaborative rechecking position according to a preset path planning algorithm to determine a basic moving path; collecting a dynamic grid map of a basic moving path; Extracting dynamic obstacle positions from a preset substation grid map according to the dynamic grid map; Screening the dynamic obstacle positions according to the basic moving path and a preset obstacle influence radius to generate influence obstacle positions; Analyzing the influence obstacle position and the basic moving path to determine an optimized moving path; and controlling the rechecking detection equipment to move from the rechecking equipment position to the collaborative rechecking position according to the optimized moving path.
6. The method for collaborative space-time patrol decision-making for direct current and extra-high voltage substations according to claim 5, wherein the step of analyzing the impact obstacle location and the basic movement path to determine an optimized movement path comprises: Extracting an influence path position from the basic moving path according to the influence obstacle position; calculating the influence obstacle position and the influence path position according to a preset influence direction model to generate an influence direction vector; calculating the influence obstacle position and the influence path position according to a preset influence distance model so as to generate an obstacle influence distance; collecting equipment support coefficients; correcting the influence direction vector and the obstacle influence distance according to the equipment support coefficient to generate a position optimization vector; and optimizing the influence path positions in the basic moving path according to the position optimization vector to generate an optimized moving path.
7. The method for collaborative space-time patrol decision-making for direct current and extra-high voltage substations according to claim 1, wherein the step of analyzing the rechecked detection data to determine the equipment early warning signal comprises: Analyzing the rechecking detection data to determine rechecking confidence; Searching a corresponding equipment early warning level in a preset confidence level relation according to the rechecking confidence level; searching a corresponding treatment strategy in a preset treatment knowledge graph according to the rechecking confidence coefficient and the rechecking detection data; associating the device pre-warning level with a treatment policy to generate a device pre-warning signal.
8. The method for collaborative space-time patrol decision-making for direct current and extra-high voltage substations according to claim 7, wherein the step of analyzing the rechecking detection data to determine rechecking confidence comprises: determining unmanned aerial vehicle rechecking data, machine dog rechecking data and fixed equipment rechecking data according to the rechecking detection data; Respectively analyzing unmanned aerial vehicle rechecking data, machine dog rechecking data and fixed equipment rechecking data to determine unmanned aerial vehicle confidence, machine dog confidence and fixed equipment confidence; acquiring an unmanned plane reliability coefficient of the unmanned plane, a robot dog reliability coefficient of a robot dog and a fixing device reliability coefficient of a fixing device; and carrying out weighted voting on the unmanned plane confidence coefficient, the robot dog confidence coefficient and the fixed equipment confidence coefficient according to the unmanned plane reliability coefficient, the robot dog reliability coefficient and the fixed equipment reliability coefficient so as to generate a rechecking confidence coefficient.
9. A DC and extra-high voltage transformer station space-earth collaborative inspection decision-making system is characterized by comprising: The acquisition module is used for acquiring daily inspection tasks and abnormal detection equipment; a memory for storing a program of the air-ground collaborative patrol decision-making method of the direct current and extra-high voltage transformer substation according to any one of claims 1 to 8; The processor, the program in the memory can be loaded and executed by the processor and implement the method for collaborative space-time patrol and inspection decision-making of the direct current and extra-high voltage transformer substation according to any one of claims 1 to 8.

Description

Air-ground collaborative inspection decision-making method and system for direct current and extra-high voltage transformer substation Technical Field The application relates to the technical field of substation inspection, in particular to an air-ground collaborative inspection decision-making method and system for a direct current and extra-high voltage substation. Background Direct current and extra-high voltage substations are core hubs of modern smart power grids, bear key tasks of long-distance, large-capacity and high-efficiency power transmission, and with the construction of novel power systems, the requirements of the substations on safe, reliable, intelligent and efficient operation and maintenance are increasingly improved. In the related technology, the 'space-world' collaborative inspection is an important technical support for intelligent operation and maintenance of direct current and extra-high voltage substations, unmanned aerial vehicle, quadruped robot dogs, fixed high-definition eagle eyes and other equipment are adopted to inspect the substations, data generated by inspection are uploaded to a data integration platform to carry out multi-source data fusion, multi-source data characteristics are identified through an equipment health model to determine whether defects occur in the equipment, and a treatment scheme is determined according to a knowledge graph and the equipment defects to be recommended. Aiming at the related technology, the current ' space-sky ' and ground ' collaborative inspection intelligent is data collaborative, but the behavior collaborative among inspection equipment is lacking, for example, when an eye of a fixed Gao Qingying finds an abnormal condition, abnormal data can be only transmitted to a data integration platform for data analysis, and an unmanned plane and a machine dog cannot check in time, so that inspection response is lagged, and further improvement space is provided. Disclosure of Invention In order to improve the timeliness of the patrol response, the application provides an air-ground collaborative patrol decision method and system for a direct current and extra-high voltage transformer substation. In a first aspect, the application provides an air-ground collaborative inspection decision method for a direct current and extra-high voltage transformer substation, which adopts the following technical scheme: A method for making a decision on the collaborative night and sky inspection of a direct current and extra-high voltage transformer station comprises the following steps: Collecting a daily inspection task; the method comprises the steps that a preset unmanned aerial vehicle, a preset robot dog and a preset fixed device carry out inspection on a preset transformer substation in response to a daily inspection task so as to generate inspection initial data and corresponding data source equipment; inputting the inspection initial data and the corresponding data source equipment into a preset edge calculation module for analysis so as to determine abnormal confidence; judging whether the abnormal confidence coefficient is not smaller than a preset confidence coefficient threshold value; If not, the unmanned aerial vehicle, the machine dog and the fixed equipment continue to carry out inspection on the transformer substation in response to the daily inspection task so as to generate inspection initial data; If yes, acquiring an abnormality detection device corresponding to the abnormality confidence, and determining a rechecking detection device according to the abnormality detection device; controlling the review detection equipment to assist the abnormality detection equipment to carry out collaborative review so as to generate review detection data; And analyzing the recheck detection data to determine the equipment early warning signal. Optionally, inputting the inspection initial data and the corresponding data source device into a preset edge calculation module for analysis, so as to determine the abnormal confidence level, wherein the step of determining the abnormal confidence level comprises the following steps: Searching corresponding equipment abnormal characteristic weights in a preset equipment abnormal characteristic weight relation according to the inspection initial data and the corresponding data source equipment; searching a corresponding data maximum value and a corresponding data minimum value in a preset data threshold relation according to the inspection initial data; judging whether the inspection initial data meets the requirement of a data minimum value or not; if not, removing the inspection initial data; If yes, analyzing the inspection initial data, the equipment abnormal characteristic weight, the data maximum value and the data minimum value to determine the abnormal confidence. Optionally, the step of analyzing the inspection initial data, the equipment abnormal feature weight, the data maximum value and the data minim