Machinery Fault Diagnosis Based on Feature Level Fuzzy Integral Data Fusion Techniques

Xiaofeng, Liu, Ma, Lin, & Mathew, Joseph (2006) Machinery Fault Diagnosis Based on Feature Level Fuzzy Integral Data Fusion Techniques. In IEEE International Conference on Industrial Informatics, 2006, Aug 2006, Singapore.

View at publisher


Fuzzy methods for machinery fault diagnosis are able to classify fault patterns in a non-dichotomous way thereby imitating the way humans process vague information. As an outgrowth of classical set and measure theory, fuzzy measure and fuzzy integral theory has the ability to infer the importance of each criterion and represent certain interactions among them. Based on fuzzy measure and fuzzy integral theory, a novel feature level direct fuzzy data fusion approach for machinery fault diagnosis is presented. Fuzzy analysis method was used to obtain the membership values of each feature for each fault class. The Choquet fuzzy integral data fusion method was employed to produce the diagnostic result using different features. Current and vibration signals from electrical motors were used to validate the method. Results showed that the proposed feature level fuzzy measure and fuzzy integral fusion approach performed very well for electrical motor fault diagnosis.

Impact and interest:

9 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

647 since deposited on 12 Sep 2007
52 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 9458
Item Type: Conference Paper
Refereed: Yes
DOI: 10.1109/INDIN.2006.275689
ISBN: 0780397002
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Copyright Owner: Copyright 2006 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 12 Sep 2007 00:00
Last Modified: 11 Oct 2012 01:06

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page