LEADER 03784nam 2200997z- 450 001 9910557506603321 005 20231214132842.0 035 $a(CKB)5400000000044490 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76611 035 $a(EXLCZ)995400000000044490 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSensors Fault Diagnosis Trends and Applications 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (236 p.) 311 $a3-0365-1048-6 311 $a3-0365-1049-4 330 $aFault 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. 606 $aTechnology: general issues$2bicssc 610 $arolling bearing 610 $aperformance degradation 610 $ahybrid kernel function 610 $akrill herd algorithm 610 $aSVR 610 $aacoustic-based diagnosis 610 $agear fault diagnosis 610 $aattention mechanism 610 $aconvolutional neural network 610 $astacked auto-encoder 610 $aweighting strategy 610 $adeep learning 610 $abearing fault diagnosis 610 $aintelligent leak detection 610 $aacoustic emission signals 610 $astatistical parameters 610 $asupport vector machine 610 $awavelet denoising 610 $aShannon entropy 610 $aadaptive noise reducer 610 $agaussian reference signal 610 $agearbox fault diagnosis 610 $aone against on multiclass support vector machine 610 $avarying rotational speed 610 $afault detection and diagnosis 610 $afaults estimation 610 $aactuator and sensor fault 610 $aobserver design 610 $aTakagi-Sugeno fuzzy systems 610 $aautomotive 610 $aperception sensor 610 $alidar 610 $afault detection 610 $afault isolation 610 $afault identification 610 $afault recovery 610 $afault diagnosis 610 $afault detection and isolation (FDIR) 610 $aautonomous vehicle 610 $amodel predictive control 610 $apath tracking control 610 $afault detection and isolation 610 $abraking control 610 $anonlinear systems 610 $afault tolerant control 610 $aiterative learning control 610 $aneural networks 610 $acryptography 610 $awireless sensor networks 610 $amachine learning 610 $ascan-chain diagnosis 610 $aartificial neural network 610 $aNARX 610 $acontrol valve 610 $adecision tree 610 $asignature matrix 615 7$aTechnology: general issues 700 $aWitczak$b Piotr$4edt$01322282 702 $aWitczak$b Piotr$4oth 906 $aBOOK 912 $a9910557506603321 996 $aSensors Fault Diagnosis Trends and Applications$93034754 997 $aUNINA