Elevator emergency stop people trapping fault detection method based on multi-model fusion
A fault detection and multi-model technology, applied in elevators, transportation and packaging, etc., can solve the problems of difficult data collection, a large number of single-chip microcomputers, and high cost of use, so as to improve training and learning efficiency and judgment accuracy, data quality optimization, low cost effect
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[0043] combine figure 1 and figure 2 As shown, according to an embodiment of the present invention, a multi-model fusion-based fault detection method for elevator emergency stop and trapped people of the present invention includes:
[0044] S1. Acceleration data, audio data and image data in the elevator car are collected respectively during the operation of the elevator;
[0045] S2. Perform data preprocessing on the acceleration data and the audio data, and extract the acceleration features in the acceleration data and the audio features in the audio data respectively;
[0046] S3. Perform abnormal acceleration detection based on acceleration features and obtain abnormal acceleration detection results, and perform abnormal sound detection based on audio features and obtain abnormal sound detection results;
[0047] S4. Fusing the abnormal acceleration detection result and the abnormal sound detection result, and judging whether to generate an emergency stop fault alarm fo...
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