Acoustic emission rub-impact location algorithm for rotating machinery based on cluster analysis

Because the characteristics of rotating machinery determine that it may encounter rub-impact faults during operation and is not easy to stop for maintenance, the rub-impact positioning of rotating machinery is an urgent problem to be solved. To solve this problem, this paper proposed a parameter location method based on acoustic emission signal characteristics, and used an improved clustering algorithm to optimize the location results. This method can monitor the running of rotating machinery and accurately locate the source of rub-impact. The experimental results showed that compared with the TDOA location algorithm, the proposed method can more effectively separate the collision sources, and the improved clustering algorithm ran faster.