Sensors Fault Diagnosis Trends and Applications

• Format: eBook
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Technology: general issues; acoustic emission signals; acoustic-based diagnosis; actuator and sensor fault; adaptive noise reducer; artificial neural network; attention mechanism; automotive; autonomous vehicle; bearing fault diagnosis; braking control; control valve; convolutional neural network; cryptography; decision tree; deep learning; fault detection; fault detection and diagnosis; fault detection and isolation; fault detection and isolation (FDIR); fault diagnosis; fault identification; fault isolation; fault recovery; fault tolerant control; faults estimation; gaussian reference signal; gear fault diagnosis; gearbox fault diagnosis; hybrid kernel function; intelligent leak detection; iterative learning control; krill herd algorithm; lidar; machine learning; model predictive control; n/a; NARX; neural networks; nonlinear systems; observer design; one against on multiclass support vector machine; path tracking control; perception sensor; performance degradation; rolling bearing; scan-chain diagnosis; Shannon entropy; signature matrix; stacked auto-encoder; statistical parameters; support vector machine; SVR; Takagi-Sugeno fuzzy systems; varying rotational speed; wavelet denoising; weighting strategy; wireless sensor networks
• Online Access: Open Access: DOAB: description of the publication; Open Access: DOAB, download 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 clearly important as faulty information from a sensor may lead to misleading conclusions about the whole system. As engineering systems grow in size and complexity, it becomes more and more important to diagnose faulty behavior before it can lead to total failure. In the light of above issues, this book is dedicated to trends and applications in modern-sensor fault diagnosis.