Mechanical fault diagnosis based on digital image processing technology

Modern mechanical equipment continues to generate high productivity, at the same time, it has brought many new challenges and new problems. It is of great importance to detect and diagnose mechanical fault diagnosis in time and then provide alarm messages. Therefore, in this paper, we aim to propose a novel mechanical fault diagnosis with the digital image processing technology. Firstly, overall structure of mechanical equipment fault dynamic motion detection system is illustrated and the infrared image segmentation is the key part this system. Secondly, we convert the infrared image segmentation problem to a cluster problem and then, provide a novel immune neural network cluster algorithm. Finally, a representative region for a specific machinery condition is selected according to the largest dispersion degree criterion. Experimental results demonstrate that the proposed algorithm can detect mechanical faults with high accuracy. Copyright © 2019 Inderscience Enterprises Ltd.