Intelligent sensing inspection system and method for transformer substation

Abstract

The invention discloses an intelligent sensing inspection system and method for a transformer substation, and relates to the technical field of electric power system inspection. The system comprises an edge end data acquisition and analysis subsystem, a station end management subsystem and a cloud artificial intelligence subsystem, the edge end data acquisition and analysis subsystem is used for acquiring target inspection data based on an inspection task and performing edge analysis on the target inspection data based on an artificial intelligence model to obtain an inspection analysis result; the station end management subsystem is used for generating and issuing an inspection task, managing inspection related data and generating an original sample set for training and optimizing an artificial intelligence model; and the cloud artificial intelligence subsystem is used for training and optimizing an artificial intelligence model according to the original sample set and issuing the artificial intelligence model. By multiplexing existing equipment of the transformer substation and deploying intelligent equipment, intelligent and automatic inspection of the transformer substation is realized, the manual operation and maintenance cost is saved, and high-quality operation and maintenance are realized.

Description

technical field [0001] The invention relates to the technical field of power system inspection, in particular to an intelligent perception inspection system and method for a substation. Background technique [0002] With the rapid development of the power grid, the number of substations and substation equipment has doubled, and the inspection workload of the power grid is also increasing. With the optimization and upgrading of the power system and the continuous improvement of safety awareness, new requirements have also been put forward for the addition of inspection tasks and safety improvement of power inspection. At present, the inspection work of each substation is usually carried out by manual inspection and traditional single inspection equipment. However, neither of these two requirements are well suited to inspection needs. [0003] The manual inspection method is to set up professional inspection personnel and inspection equipment required by the professional ins...

AI Technical Summary

Problems solved by technology

There are the following deficiencies: large demand for personnel, labor-intensive inspections; high reliance on personnel experience, and difficulty in judging the reliability of inspection results; there is also a contradiction between the shortage of inspection personnel and the increase in inspection tasks, which does not meet the real-time requirements of inspections

[0004] The traditional single inspection equipment method relies on a single type of inspection equipment. The inspection equipment acquires equipment data through the acquisition terminal according to the set trajectory, and transmits it to the background management system for manual data analysis. However, there are also the following deficiencies: inspection data processing The system only processes the data of a single type of inspection equipment, and data coordination and interaction between multiple types of inspection equipment cannot be carried out; a single type of inspection equipment is easily affected by the surrounding environment and peripheral equipment, resulting in serious damage to the power system. The analysis of the inspection results of the inspection objects is not in place; the intelligence level of the inspection equipment is insufficient, and it needs to rely on the back-end system to complete all data processing, which is highly dependent on the stability of the wireless network and the security of data transmission

The same type of inspection equipment needs to be processed by different inspection data processing systems. Once the type of inspection equipment changes, it is necessary to increase or delete the inspection data processing system accordingly, which is cumbersome to operate

[0007] (2) Insufficient front-end analysis capabilities and low real-time performance

The existing inspection equipment needs to rely on the back-end system to complete all data processing, the network bandwidth requirements and network stability are high, and it does not have real-time processing capabilities

[0008] (3) Detection and recognition algorithm is weak in robustness

The detection algorithm cannot shield the influence of magnetic field noise on the collected data, and cannot well guarantee the reliability of the analysis results of the back-end system

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