1st Edition
by Asoke K. Nandi (Author), Hosameldin Ahmed (Author)
Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring
Clear
and concise throughout, this accessible book is the first to be wholly
devoted to the field of condition monitoring for rotating machines using
vibration signals. It covers various feature extraction, feature
selection, and classification methods as well as their applications to
machine vibration datasets. It also presents new methods including
machine learning and compressive sampling, which help to improve safety,
reliability, and performance.
Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines
starts by introducing readers to Vibration Analysis Techniques and
Machine Condition Monitoring (MCM). It then offers readers sections
covering: Rotating Machine Condition Monitoring using Learning
Algorithms; Classification Algorithms; and New Fault Diagnosis
Frameworks designed for MCM. Readers will learn signal processing in the
time-frequency domain, methods for linear subspace learning, and the
basic principles of the learning method Artificial Neural Network (ANN).
They will also discover recent trends of deep learning in the field of
machine condition monitoring, new feature learning frameworks based on
compressive sampling, subspace learning techniques for machine condition
monitoring, and much more.
- Covers the fundamental as well
as the state-of-the-art approaches to machine condition
monitoring―guiding readers from the basics of rotating machines to the
generation of knowledge using vibration signals
- Provides new
methods, including machine learning and compressive sampling, which
offer significant improvements in accuracy with reduced computational
costs
- Features learning algorithms that can be used for fault diagnosis and prognosis
- Includes previously and recently developed dimensionality reduction techniques and classification algorithms
Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.
