An improved Multi-channels Information Fusion Model with multi-scale signals for fault diagnosis
international conference on big data(2021)
摘要
One of the challenges with Industrial artificial intelligence is that extracting features from signals collected from multiple sources of different components to train a more robust model. However, the acquisition of raw signals from complex mechanical systems shows a multi-rate sampling trend. To address the issue mentioned above, this paper presents a Multi-channels Information Fusion Model (MCIFM), which combines multisource learning into the basic CNN model. The results of Experiment 10 and the comprehensive comparative analysis of traditional CNN and traditional multi-source feature extractors show that this method can extract effective features from multi-rate sensors.
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关键词
CNN,STFT,Fault diagnosis,Feature learning,Multi-sensor feature fusion
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