LEADER 01397nas 2200445-a 450 001 996212726503316 005 20221206233909.0 011 $a1347-5800 035 $a(OCoLC)52415442 035 $a(CKB)954925454932 035 $a(CONSER)--2008247648 035 $a(DE-599)ZDB2106630-9 035 $a(EXLCZ)99954925454932 100 $a20030611a19689999 s-- - 101 0 $aeng 135 $aurmnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aActa histochemica et cytochemica$b[e-journal] $eofficial journal of the Japan Society of Histochemistry and Cytochemistry 210 $aKyoto, Japan $cJapan Society of Histochemistry and Cytochemistry 300 $aRefereed/Peer-reviewed 311 $a0044-5991 606 $aHistochemistry 606 $aHistochemistry$vPeriodicals 606 $aCytochemistry$vPeriodicals 606 $aCytochemistry$2fast$3(OCoLC)fst00886240 606 $aHistochemistry$2fast$3(OCoLC)fst00957658 608 $aPeriodicals.$2fast 615 0$aHistochemistry. 615 0$aHistochemistry 615 0$aCytochemistry 615 7$aCytochemistry. 615 7$aHistochemistry. 676 $a591.8/05 712 02$aNihon Soshiki Saibo? Kagakukai. 906 $aJOURNAL 912 $a996212726503316 996 $aActa histochemica et cytochemica$92085439 997 $aUNISA LEADER 04317nam 2201189z- 450 001 9910619469103321 005 20221025 010 $a3-0365-5174-3 035 $a(CKB)5670000000391583 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93169 035 $a(oapen)doab93169 035 $a(EXLCZ)995670000000391583 100 $a20202210d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDeep Learning-Based Machinery Fault Diagnostics 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (290 p.) 311 08$a3-0365-5173-5 330 $aThis book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aabnormal case removal 610 $aalumina concentration 610 $aaluminum reduction process 610 $aanti-noise 610 $aattention mechanism 610 $aautonomous underwater vehicle 610 $aauxiliary model 610 $aBayesian network 610 $abearing fault detection 610 $abelief rule base 610 $acanonical correlation analysis 610 $acanonical variate analysis 610 $acase-based reasoning 610 $aconvolution fusion 610 $aconvolutional neural network 610 $adata augmentation 610 $adata-driven 610 $adeep residual network 610 $adistributed predictive control 610 $adisturbance detection 610 $adynamic autoregressive latent variables model 610 $adynamics 610 $aevent-triggered control 610 $aevidential reasoning 610 $aevidential reasoning rule 610 $afault detection 610 $afault diagnosis 610 $afault tolerant control 610 $afilter 610 $aflywheel fault diagnosis 610 $afractional-order calculus theory 610 $afuzzy fault tree analysis 610 $agated recurrent unit 610 $agearbox fault diagnosis 610 $ahammerstein output-error systems 610 $ahigh-speed trains 610 $ainformation transformation 610 $aintelligent fault diagnosis 610 $ainterval type-2 Takagi-Sugeno fuzzy model 610 $ajust-in-time learning 610 $ak-nearest neighbor analysis 610 $alocal outlier factor 610 $aLSSVM 610 $amulti-innovation identification theory 610 $an/a 610 $anonlinear networked systems 610 $aocean currents 610 $aoperational optimization 610 $aparameter optimization 610 $apower transmission system 610 $aprocess monitoring 610 $aPSO 610 $arobust optimization 610 $asintering process 610 $aspatiotemporal feature fusion 610 $astacked pruning sparse denoising autoencoder 610 $astate identification 610 $astatistical local analysis 610 $asubspace identification 610 $asystem modelling 610 $athruster fault diagnostics 610 $avariable time lag 610 $awavelet mutation 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aChen$b Hongtian$4edt$01063057 702 $aZhong$b Kai$4edt 702 $aRan$b Guangtao$4edt 702 $aCheng$b Chao$4edt 702 $aChen$b Hongtian$4oth 702 $aZhong$b Kai$4oth 702 $aRan$b Guangtao$4oth 702 $aCheng$b Chao$4oth 906 $aBOOK 912 $a9910619469103321 996 $aDeep Learning-Based Machinery Fault Diagnostics$93013732 997 $aUNINA