Fuzzy classifier with automatic rule generation for fault diagnosis of hydraulic brake system using statistical features
by R. Jegadeeshwaran; V. Sugumaran
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 1, No. 3, 2015

Abstract: This study focuses on the condition monitoring of a hydraulic brake system using vibration signal through a machine learning approach. The machine learning approach has three main steps: feature extraction, feature selection and feature classification. Statistical features were used for the fault diagnosis of hydraulic brake system. Through a feature extraction technique, descriptive statistical features were extracted from the acquired vibration signals. C4.5 decision tree algorithm was used for selecting best features that will distinguish the fault conditions of the brake from given train samples. For feature classification, fuzzy logic was used as a classifier. A necessary rule set was formed automatically by using decision tree algorithm. The generated rule set is fed to fuzzy classifier. The procedure to build fuzzy classifier is also explained and the results were discussed.

Online publication date: Tue, 16-Jun-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Fuzzy Computation and Modelling (IJFCM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com