In this final part, we discuss fault diagnosis methods that are based on historic process
knowledge. We also compare and evaluate the various methodologies reviewed in this …

The application of the wavelet transform for machine fault diagnostics has been developed
for last 10 years at a very rapid rate. A review on all of the literature is certainly not possible …

This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and …

Process monitoring plays an important role in chemical process safety management, and
fault diagnosis is a vital step of process monitoring. Among fault diagnosis researches …

Time series are recorded values of an interesting phenomenon such as stock prices,
household incomes, or patient heart rates over a period of time. Time series data mining …

Recently there has been significant development in the use of wavelet methods in various
data mining processes. However, there has been written no comprehensive survey …

Complex processes involve many process variables, and operators faced with the tasks of
monitoring, control, and diagnosis of these processes often find it difficult to effectively …

Modern computer-based control systems are able to collect a large amount of information,
display it to operators and store it in databases but the interpretation of the data and the …

In the signal processing domain, there has been growing interest in sparse coding with a
learned dictionary instead of a predefined one, which is advocated as an effective …

Data that represent complex and multivariate processes are well known to be multiscale due
to the variety of changes that could occur in a process with different localizations in time and …