Sensors Fault Diagnosis Trends and Applications

Fault diagnosis has always been a concern for industry. In general, diagnosis in complex systems requires the acquisition of information from sensors and the processing and extracting of required features for the classification or identification of faults. Therefore, fault diagnosis of sensors is cl...

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Médium:	Online
Jazyk:	angličtina
Vydáno:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Témata:	rolling bearing performance degradation hybrid kernel function krill herd algorithm SVR acoustic-based diagnosis gear fault diagnosis attention mechanism convolutional neural network stacked auto-encoder weighting strategy deep learning bearing fault diagnosis intelligent leak detection acoustic emission signals statistical parameters support vector machine wavelet denoising Shannon entropy adaptive noise reducer gaussian reference signal gearbox fault diagnosis one against on multiclass support vector machine varying rotational speed fault detection and diagnosis faults estimation actuator and sensor fault observer design Takagi-Sugeno fuzzy systems automotive perception sensor lidar fault detection fault isolation fault identification fault recovery fault diagnosis fault detection and isolation (FDIR) autonomous vehicle model predictive control path tracking control fault detection and isolation braking control nonlinear systems fault tolerant control iterative learning control neural networks cryptography wireless sensor networks machine learning scan-chain diagnosis artificial neural network NARX control valve decision tree signature matrix n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
On-line přístup:	ONIX_20220111_9783036510484_346
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ONIX_20220111_9783036510484_346

Sensors Fault Diagnosis Trends and Applications

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