LEADER 03579nam 2200805z- 450 001 9910557630403321 005 20210501 035 $a(CKB)5400000000045110 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68494 035 $a(oapen)doab68494 035 $a(EXLCZ)995400000000045110 100 $a20202105d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAlgorithms for Fault Detection and Diagnosis 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (130 p.) 311 08$a3-0365-0462-1 311 08$a3-0365-0463-X 330 $aDue to the increasing demand for security and reliability in manufacturing and mechatronic systems, early detection and diagnosis of faults are key points to reduce economic losses caused by unscheduled maintenance and downtimes, to increase safety, to prevent the endangerment of human beings involved in the process operations and to improve reliability and availability of autonomous systems. The development of algorithms for health monitoring and fault and anomaly detection, capable of the early detection, isolation, or even prediction of technical component malfunctioning, is becoming more and more crucial in this context. This Special Issue is devoted to new research efforts and results concerning recent advances and challenges in the application of "Algorithms for Fault Detection and Diagnosis", articulated over a wide range of sectors. The aim is to provide a collection of some of the current state-of-the-art algorithms within this context, together with new advanced theoretical solutions. 606 $aHistory of engineering and technology$2bicssc 610 $aadaptive template matching 610 $aamplitude-aware permutation entropy 610 $abattery faults 610 $abattery management system 610 $abattery safety 610 $acombined prediction 610 $adamage 610 $adigital image processing 610 $aedge detection 610 $afault diagnosis 610 $afault diagnostic algorithms 610 $afault prediction 610 $agenetic algorithm 610 $agray level co-occurrence matrix 610 $ainstantaneous angular speed 610 $aKalman filter 610 $aleast squares support vector machine 610 $alithium-ion battery 610 $amachine diagnostics 610 $amachine vision 610 $amisalignment 610 $amotion tracking 610 $amultiscale entropy 610 $amultivariate grey model 610 $aparametric template modeling 610 $aquantum genetic algorithm 610 $arandom forest 610 $areusable launch vehicle 610 $arolling bearings 610 $aself-organization map 610 $astructural health monitoring 610 $aSURVISHNO 2019 challenge 610 $athruster fault detection 610 $athruster valve failure 610 $avideo tachometer 615 7$aHistory of engineering and technology 700 $aFerracuti$b Francesco$4edt$01280545 702 $aFreddi$b Alessandro$4edt 702 $aMonteriù$b Andrea$4edt 702 $aFerracuti$b Francesco$4oth 702 $aFreddi$b Alessandro$4oth 702 $aMonteriù$b Andrea$4oth 906 $aBOOK 912 $a9910557630403321 996 $aAlgorithms for Fault Detection and Diagnosis$93017193 997 $aUNINA