Sensors Fault Diagnosis Trends and Applications

• Kolejni autorzy: Witczak, Piotr (Redaktor)
• Format: Elektroniczne Rozdział
• Język: angielski
• Wydane: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Hasła przedmiotowe: Technology: general issues; 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
• Dostęp online: DOAB: download the publication; DOAB: description of the publication

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...