Intelligent Prognostics for Engineering Systems with Machine Learning Techniques
Mangey Ram editor Om Prakash Yadav editor Gunjan Soni editor Gaurav Kumar Badhotiya editor
Format:Hardback
Publisher:Taylor & Francis Ltd
Published:22nd Sep '23
Currently unavailable, and unfortunately no date known when it will be back
The text discusses the latest data-driven, physics-based, and hybrid approaches employed in each stage of industrial prognostics and reliability estimation. It will be a useful text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, electrical engineering, and computer science.
The book
- Discusses basic as well as advance research in the field of prognostics
- Explores integration of data collection, fault detection, degradation modeling and reliability prediction in one volume
- Covers prognostics and health management (PHM) of engineering systems
- Discusses latest approaches in the field of prognostics based on machine learning
The text deals with tools and techniques used to predict/ extrapolate/ forecast the process behavior, based on current health state assessment and future operating conditions with the help of Machine learning. It will serve as a useful reference text for senior undergraduate, graduate students, and academic researchers in areas such as industrial and production engineering, manufacturing science, electrical engineering, and computer science.
ISBN: 9781032054360
Dimensions: unknown
Weight: 453g
246 pages