Open access peer-reviewed chapter

Fault Diagnosis and Health Assessment for Rotating Machinery Based on Kernel Density Estimation and Kullback-Leibler Divergence

By Yu Liu, Chen-Yao Yan and Fan Zhang

Submitted: May 2nd 2016Reviewed: December 27th 2016Published: May 31st 2017

DOI: 10.5772/67360

Downloaded: 331

© 2017 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite and reference

Link to this chapter Copy to clipboard

Cite this chapter Copy to clipboard

Yu Liu, Chen-Yao Yan and Fan Zhang (May 31st 2017). Fault Diagnosis and Health Assessment for Rotating Machinery Based on Kernel Density Estimation and Kullback-Leibler Divergence, Fault Diagnosis and Detection Mustafa Demetgul, IntechOpen, DOI: 10.5772/67360. Available from:

Embed this chapter on your site Copy to clipboard

<iframe src="http://www.intechopen.com/embed/fault-diagnosis-and-detection/fault-diagnosis-and-health-assessment-for-rotating-machinery-based-on-kernel-density-estimation-and-" />

Embed this code snippet in the HTML of your website to show this chapter

chapter statistics

331total chapter downloads

More statistics for editors and authors

Login to your personal dashboard for more detailed statistics on your publications.

Access personal reporting

Related Content

This Book

Next chapter

Dynamics-Based Vibration Signal Modeling for Tooth Fault Diagnosis of Planetary Gearboxes

By Xihui Liang, Ming J. Zuo and Wenhua Chen

Related Book

First chapter

Control Designs for Linear Systems Using State-Derivative Feedback

By Rodrigo Cardim, Marcelo C. M. Teixeira, Edvaldo Assuncao and Flavio A. Faria

We are IntechOpen, the world's leading publisher of Open Access books. Built by scientists, for scientists. Our readership spans scientists, professors, researchers, librarians, and students, as well as business professionals. We share our knowledge and peer-reveiwed research papers with libraries, scientific and engineering societies, and also work with corporate R&D departments and government entities.

+3,550 Open Access Books

+57,400 Citations in Web of Science

+108,500 IntechOpen Authors and Academic Editors

+560,000 Unique visitors per month

More about us