04224nam 2200865z- 450 991056646080332120220506(CKB)5680000000037773(oapen)https://directory.doabooks.org/handle/20.500.12854/81086(oapen)doab81086(EXLCZ)99568000000003777320202205d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierInformation Theory and Its Application in Machine Condition MonitoringBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (194 p.)3-0365-3208-0 3-0365-3209-9 Condition monitoring of machinery is one of the most important aspects of many modern industries. With the rapid advancement of science and technology, machines are becoming increasingly complex. Moreover, an exponential increase of demand is leading an increasing requirement of machine output. As a result, in most modern industries, machines have to work for 24 hours a day. All these factors are leading to the deterioration of machine health in a higher rate than before. Breakdown of the key components of a machine such as bearing, gearbox or rollers can cause a catastrophic effect both in terms of financial and human costs. In this perspective, it is important not only to detect the fault at its earliest point of inception but necessary to design the overall monitoring process, such as fault classification, fault severity assessment and remaining useful life (RUL) prediction for better planning of the maintenance schedule. Information theory is one of the pioneer contributions of modern science that has evolved into various forms and algorithms over time. Due to its ability to address the non-linearity and non-stationarity of machine health deterioration, it has become a popular choice among researchers. Information theory is an effective technique for extracting features of machines under different health conditions. In this context, this book discusses the potential applications, research results and latest developments of information theory-based condition monitoring of machineries.History of engineering and technologybicsscTechnology: general issuesbicsscadaptive particle swarm optimization (APSO)anomaly detectionbearingcombined fault diagnosiscubic spline interpolation envelopeD-S evidence theorydeep learningdomain adaptationempirical wavelet transformfault detectionfault diagnosisgearboxgrey wolf optimizerHuffman-multi-scale entropy (HMSE)improved artificial bee colony algorithminformation fusionJS divergencekernel density estimationlow pass FIR filterLSSVMmachine visionmisalignmentMobileNetV3multi-source heterogeneous fusionn/aoptimal bandwidthpartial transferpeak extractionrail surface defect detectionrotating machinerysatellite momentum wheelsignal interceptionsubdomainsupport vector machinesupport vector machine (SVM)transfer learningwind turbinesYOLOv4History of engineering and technologyTechnology: general issuesLi Yongboedt1295517Gu FengshouedtLiang XihuiedtLi YongboothGu FengshouothLiang XihuiothBOOK9910566460803321Information Theory and Its Application in Machine Condition Monitoring3023565UNINA