Remote intelligent inspection method and system for transformer substation

Through the Zhongzhiji similarity measurement calculation method, the problems of inaccurate equipment identification results and low patrol efficiency in the remote intelligent inspection system of the substation were solved, and higher identification accuracy and efficiency were achieved, and data security and system robustness were improved.

CN119741514APending Publication Date: 2025-04-01上海许继电气有限公司 +1
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Patent Information

Application Number
CN202411831580.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-12
Publication Date
2025-04-01

AI Technical Summary

Technical Problem

The existing remote intelligent inspection system of substations has problems such as inaccurate equipment identification results, low patrol efficiency, poor data security and low equipment identification accuracy in bad weather.

Method used

The Zhongzhikan similarity metric calculation method is used to convert the substation equipment image acquired in real time with the equipment image in normal state, and perform similarity calculations to determine the equipment status. This method uses the uncertain membership degree of Zhongzhikong to enhance the important features of the device image, reducing the impact of feature uncertainty on the recognition results.

Benefits of technology

It improves the accuracy of inspection results and inspection efficiency, avoids the risk of information leakage, reduces system operation costs, and maintains high robustness in adverse weather conditions.

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Abstract

The invention relates to a remote intelligent substation inspection method and system, and belongs to the technical field of substation inspection. The method comprises the following steps: carrying out median set similarity measurement calculation on a transformer substation equipment image obtained in real time and a normal equipment image of corresponding equipment in a normal state, if a similarity measurement value obtained through median set similarity measurement calculation is greater than or equal to a set threshold value, determining that the equipment state is normal, otherwise, determining that the equipment state is abnormal. According to the method, the device image of the substation device in the to-be-judged state and the normal device image when the device is in the normal state are subjected to neutrosophy set similarity measurement calculation, and after the images are converted into the neutrosophy set, the important features of the device image can be enhanced by using the specific uncertain membership degree of the neutrosophy set; the influence of feature uncertainty on the identification result is reduced, the problem that the equipment identification result is inaccurate due to external uncertain factors of the image is overcome, the accuracy of the inspection result is effectively improved, and the inspection efficiency is improved.
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