- Title
- Mobile agent based artificial immune system for machine condition monitoring
- Creator
- Hua, Xue-Liang; Gondal, Iqbal; Yaqub, Farrukh
- Date
- 2013
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/161437
- Identifier
- vital:12474
- Identifier
-
https://doi.org/10.1109/ICIEA.2013.6566349
- Abstract
- Machine condition monitoring is a process of continuously observing the status of a machine to ensure that proactive measures are taken to prevent damage due to abnormal operating conditions. Generally, industrial units such as mining, oil and gas etc, are located in geographically remote areas, so a large amount of data need to be acquired for fault diagnosis and prognosis remotely. To achieve this, certain resources such as stable communication network and adequate bandwidth are required. Furthermore, it is not always feasible to dispatch human resources simultaneously over large areas of operation to perform on-site maintenance. To overcome these issues, a mobile agent based system architecture is proposed for machine condition monitoring by imitating human immune system (ACMIS), which is also known as artificial immune system. The experiment results are presented to evaluate the performance of the proposed system in terms of fault detection accuracy and bandwidth allocation. Overall performance evaluation of the proposed framework suggests that our proposed scheme not only provides excellent fault detection accuracy but also a flexible and reliable machine condition monitoring system with reduced network and computational resources. Further our approach provides cost effective solution in building a practical machine condition monitoring system.
- Publisher
- IEEE
- Relation
- 2013 8th IEEE Conference on Industrial Electronics and Applications (ICIEA) p. 108-113
- Rights
- © 2013 IEEE
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0910 Manufacturing Engineering; 0913 Mechanical Engineering; Machine condition monitoring; Fault diagnosis; Mobile agent; Artificial immune system
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