作者
Mohamad‐Ali Mortada, Soumaya Yacout, Aouni Lakis
发表日期
2011/10/25
期刊
Journal of Quality in Maintenance Engineering
卷号
17
期号
4
页码范围
371-397
出版商
Emerald Group Publishing Limited
简介
Purpose
–
The purpose of this paper is to test the applicability and the performance of an approach called logical analysis of data (LAD) on the detection of faults in rotating machinery using vibration signals.
Design/methodology/approach
–
LAD is a supervised learning data mining technique that relies on finding patterns in a binary database to generate decision functions. The hypothesis is that a LAD‐based decision model can be used as an effective tool for automatic detection of faults in rolling element bearings. A novel Multiple Integer Linear Programming approach is used to generate patterns for the LAD decision model. Frequency and time‐based features are extracted from rotor bearing vibration signals and are pre‐processed to be suitable for use with LAD.
Findings
–
The results show good classification accuracy with both time and frequency features.
Practical implications
–
The diagnostic tool …
学术搜索中的文章
MA Mortada, S Yacout, A Lakis - Journal of Quality in Maintenance Engineering, 2011