Research on a configurable method for fault diagnosis knowledge of machine tools and its application

Research on a configurable method for fault diagnosis knowledge of machine tools and its application Fault diagnosis is critical in PHM (Prognostics and Health Management) of machine tools due to its great significance in such efforts as prolonging lifespan, improving production efficiency, and reducing production costs. For machine tool manufacturers, a general fault diagnosis method and a software framework are needed to construct fault diagnosis systems for various machine tools and fault types, or the same type of machine tools under various life cycles, working conditions, and operating environments. A configurable method for fault diagnosis knowledge of machine tools (CMFDK-MT) is thus proposed in this paper. Firstly, an ontology-based fault diagnosis method for machine tools and an improved process of fault diagnosis with knowledge bases are introduced. Based on these, a framework of a knowledge-based configurable fault diagnosis platform for machine tools (KCFDP-MT) is designed. KCFDP-MT supports explicit knowledge representation with formal semantics, efficient knowledge utilization, and efficient integration of various fault diagnosis methods and technologies. Then, the configuration approaches for fault diagnosis activities, namely fault detection, identification, diagnosis, and solving, are studied respectively. The configuration and implementation methods of the KCFDP-MT framework are also presented. Finally, a prototype system is constructed for a CNC hobbing machine tool. Two cases of rolling bearing and gear based on signal processing are carried out to verify the effectiveness of the proposed method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Research on a configurable method for fault diagnosis knowledge of machine tools and its application

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London Ltd.
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-1268-z
Publisher site
See Article on Publisher Site

Abstract

Fault diagnosis is critical in PHM (Prognostics and Health Management) of machine tools due to its great significance in such efforts as prolonging lifespan, improving production efficiency, and reducing production costs. For machine tool manufacturers, a general fault diagnosis method and a software framework are needed to construct fault diagnosis systems for various machine tools and fault types, or the same type of machine tools under various life cycles, working conditions, and operating environments. A configurable method for fault diagnosis knowledge of machine tools (CMFDK-MT) is thus proposed in this paper. Firstly, an ontology-based fault diagnosis method for machine tools and an improved process of fault diagnosis with knowledge bases are introduced. Based on these, a framework of a knowledge-based configurable fault diagnosis platform for machine tools (KCFDP-MT) is designed. KCFDP-MT supports explicit knowledge representation with formal semantics, efficient knowledge utilization, and efficient integration of various fault diagnosis methods and technologies. Then, the configuration approaches for fault diagnosis activities, namely fault detection, identification, diagnosis, and solving, are studied respectively. The configuration and implementation methods of the KCFDP-MT framework are also presented. Finally, a prototype system is constructed for a CNC hobbing machine tool. Two cases of rolling bearing and gear based on signal processing are carried out to verify the effectiveness of the proposed method.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Nov 7, 2017

References

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