Artificial intelligent system for integrated wear debris analysis and vibration analysis in machine condition monitoring

振动和磨粒分析是机械维修和故障诊断的两种主要状态监测技术。然而，它们只能诊断出不到50%的故障。将对这两种技术的相关性进行一系列的实验和理论研究。该项目将整合包括3D显微镜、神经网络和专家系统在内的先进技术，基于这两种状态监测技术的相互依存和相互独立的作用，开发一种人工智能系统。成功的结果将改善维护计划，减少人工参与，并将为工程行业带来显著的经济效益。

Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. However, they can diagnose less than 50% of faults. A series of experimental and theoretical studies on the correlation of the two techniques will be conducted. This project will integrate advanced technologies including 3D microscopy, neural networks and expert systems to develop an artificial intelligent system based on the dependent and independent roles of the two condition monitoring techniques. Successful outcomes will result in an improved maintenance program and reduction in human involvement, and will provide significant economic benefit to engineering industries.