Artificial intelligence-based power electromechanical equipment installation and modification intelligent detection system

By using intelligent partitioning and state segmentation processing, combined with multimodal data acquisition and real-time evaluation, the problems of adaptability and accuracy in power equipment detection have been solved, enabling early fault warning and personalized maintenance suggestions, thus improving detection efficiency and accuracy.

CN122361950APending Publication Date: 2026-07-10NINGBO ANXING ELECTRIC POWER CONSTRUCTION CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NINGBO ANXING ELECTRIC POWER CONSTRUCTION CO LTD
Filing Date
2026-04-14
Publication Date
2026-07-10

AI Technical Summary

Technical Problem

Existing power equipment testing methods cannot adaptively adjust testing strategies according to the equipment's operating stage and environmental conditions, cannot accurately monitor key components, have weak fault prediction capabilities, and have fixed testing standards that are difficult to adapt to different types of equipment and changing operating conditions.

Method used

The intelligent partitioning module divides the power equipment into core components, connecting components, and environmental monitoring areas, and deploys high-density, medium-density, and sparse sensor nodes respectively to collect multimodal data; the state segmentation processing module divides the equipment operation stages and establishes a normal state identification model; the equipment health index is evaluated in real time, and the detection frequency and accuracy are dynamically adjusted.

Benefits of technology

It achieves adaptability and accuracy in equipment detection, improves the timeliness of fault warning and detection efficiency, and can identify potential faults early and generate personalized maintenance suggestions.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses an intelligent detection system for power electromechanical equipment based on artificial intelligence, and particularly relates to the field of power equipment detection, and comprises an intelligent partition module, a data acquisition module, a state segmentation processing module, a real-time state evaluation module and a detection strategy optimization module. The application divides power equipment into core components, connecting components and environment monitoring areas, differentiates sensor nodes, and acquires multi-dimensional operation data. The application divides data subsets according to four stages of equipment starting, stable operation and the like, constructs normal state recognition models of each stage, compares real-time data with the models, recognizes abnormalities and evaluates risk grades, dynamically calculates equipment health indexes, predicts potential faults, adjusts thresholds in combination with equipment age and load rates, dynamically adjusts detection frequency, precision and standards, and generates individualized maintenance suggestions.
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