AI赋能的工业设备智能化巡检维修方法及系统
The industrial equipment fault diagnosis method, which adaptively determines the sliding window length and weighting mechanism, solves the problems of high false alarm rate and false negative rate in the existing technology, and achieves high accuracy in detecting early faults, ensuring accurate determination of equipment status.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANDONG BLUEBIRD IND INTERNET CO LTD
- Filing Date
- 2026-05-09
- Publication Date
- 2026-07-17
AI Technical Summary
Existing industrial equipment fault diagnosis methods based on similarity matching algorithms have a high false alarm rate in complex industrial environments, are not sensitive to early faults, and cannot effectively distinguish between normal dynamic interference and real fault characteristics.
By acquiring the three-phase current sequence of the device motor, performing noise reduction and data conversion, adaptively determining the sliding window length, and combining second-order difference calculation and weighting mechanism, an anomaly detection mechanism is constructed to improve the sensitivity to early faults.
It effectively reduced the false alarm rate and the missed alarm rate, improved the detection rate of early faults, and ensured the accurate determination of equipment status.
Smart Images
Figure CN122160276B_ABST