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Proceedings of the International Conference on Technology Management and Innovation
Hao Xie
Hao Xie
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ASME Press
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Mechanical equipment, especially large scale equipment, has very complex failure mechanism, which is difficult to extract. Multiple concurrent failures are more and more widely happened. In cognizance of the complexity of concurrent fault diagnosis [8], this paper presents Unit concurrent Fault Diagnostic Systems based on Artificial Immune[9][10][11] and Evidence theory[1]. It uses the negative selection algorithm[2] which is derived from the self - non-self recognition mechanism to process the data. Moreover, we used the information fusion rules of Evidence theory, in order to make a more precise diagnostic result. The simulation results show that this method has high veracity ratio in multiple concurrent faults diagnosis.

I. Introduction
II. The Basic Principle
III. System Architecture of Concurrent Failure Based on Artificial Immune and Evidence Theory
IV. Simulation of Mimic-Fault Test Stand
V. Summary
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