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Information Theory and Its Application in Machine Condition Monitoring

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...

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Formaat: Online
Taal:Engels
Gepubliceerd in: MDPI - Multidisciplinary Digital Publishing Institute 2022
Onderwerpen:
fault detection
deep learning
transfer learning
anomaly detection
bearing
wind turbines
misalignment
fault diagnosis
information fusion
improved artificial bee colony algorithm
LSSVM
D–S evidence theory
optimal bandwidth
kernel density estimation
JS divergence
domain adaptation
partial transfer
subdomain
rotating machinery
gearbox
signal interception
peak extraction
cubic spline interpolation envelope
combined fault diagnosis
empirical wavelet transform
grey wolf optimizer
low pass FIR filter
support vector machine
satellite momentum wheel
Huffman-multi-scale entropy (HMSE)
support vector machine (SVM)
adaptive particle swarm optimization (APSO)
rail surface defect detection
machine vision
YOLOv4
MobileNetV3
multi-source heterogeneous fusion
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Online toegang:ONIX_20220506_9783036532080_152
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Samenvatting: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.

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