Sensors Fault Diagnosis Trends and Applications
Witczak, Piotr
Sensors Fault Diagnosis Trends and Applications - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (236 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1049-1 9783036510484 9783036510491
10.3390/books978-3-0365-1049-1 doi
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
Sensors Fault Diagnosis Trends and Applications - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (236 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1049-1 9783036510484 9783036510491
10.3390/books978-3-0365-1049-1 doi
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