Smart Monitoring of Rotating Machinery for Industry 4.0
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Beschreibung
This book offers an overview of current methods for the intelligent monitoring of rotating machines. It describes the foundations of smart monitoring, guiding readers to develop appropriate machine learning and statistical models for answering important challenges, such as the management and analysis of a large volume of data. It also discusses real-world case studies, highlighting some practical issues and proposing solutions to them. The book offers extensive information on research trends, and innovative strategies to solve emerging, practical issues. It addresses both academics and professionals dealing with condition monitoring, and mechanical and production engineering issues, in the era of industry 4.0.
This book offers an overview of current methods for the intelligent monitoring of rotating machines. It describes the foundations of smart monitoring, guiding readers to develop appropriate machine learning and statistical models for answering important challenges, such as the management and analysis of a large volume of data. It also discusses real-world case studies, highlighting some practical issues and proposing solutions to them. The book offers extensive information on research trends, and innovative strategies to solve emerging, practical issues. It addresses both academics and professionals dealing with condition monitoring, and mechanical and production engineering issues, in the era of industry 4.0.
Reports on intelligent methods for condition monitoring of rotating machinery Presents strategies for managing large dataset in machine diagnostics Offers a good balance of theoretical and practical issues
Autor*in
Fakher Chaari
Themen in »Smart Monitoring of Rotating Machinery for Industry 4.0«
Smart health monitoring Canonical Variate Analysis Machine learning for condition monitoring Model Based Fault Diagnosis Algebraic estimator Damping failure analysis Gearbox monitoring Machinery in non-stationary operations Remaining useful life Rolling bearing fault Deep Learning for smart monitoring Probability density evolution Reliability analysis Rotating machine Bevel gear modelling