Signal Processing and Artificial Intelligence Technology for High-End Equipment Fault Diagnosis

This Reprint presents the latest research progress of signal processing and artificial intelligence technologies for fault diagnosis of high-end mechanical equipment. It contains 13 original research papers, covering advanced dynamics modeling and mechanism analysis methods, novel signal processing...

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書誌詳細
フォーマット:	Online
言語:	英語
出版事項:	MDPI - Multidisciplinary Digital Publishing Institute 2026
主題:	data fusion axle box bearing fault diagnosis characteristic frequency bandpass filtering industrial collaborative robot anomaly detection trajectory change autoencoder dynamic time warping online monitoring dual-rotor system rotor unbalance assembly phase angle vibration amplitude aero-engines dynamic modeling aero-engine neural network vibration response fault detection LSTM auto-encoder self-attention mechanism rolling mill abnormal vibration monitoring and diagnosis multi-sensor information fusion multi-scale graph convolutional networks infrared thermography wind turbine blade deep learning defect detection object localization YOLO resonant frequencies autogram optimal demodulation frequency band bearing fault diagnosis rolling bearing convolutional neural network variational Bayesian inference decision-level fusion multi-task learning graph convolutional networks attention mechanism hydrodynamic bearing nonlinear dynamic coefficients oil film instability condition monitoring life prediction transformer dual-layer self-attention multi-scale convolution traction converter temperature sensor coupling fault diagnosis
オンライン･アクセス:	https://directory.doabooks.org/handle/20.500.12854/170645
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Signal Processing and Artificial Intelligence Technology for High-End Equipment Fault Diagnosis

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