Research on Health Stage Division of Switch Machine Based on Bray-Curtis Distance and Fisher Optimal Segmentation Method

In order to reasonably and accurately evaluate the health status of the switch machine, a health stage division method of switch machine combining Bray-Curtis distance and Fisher optimal segmentation is proposed. First, the power curve of switch machine is divided into five sections, and eight time-domain characteristic parameters of each section are extracted. Second, the characteristic parameters with the largest correlation between fifteen dimensions and state of the switch machine are selected by using the Holder coefficient method as the input of Bray-Curtis distance algorithm, using Bray-Curtis distance to calculate health index (HI), which represents health state of switch machine. Finally, HI curve is divided by Fisher optimal segmentation method, and the optimal number of health stages of switch machine is determined to be three, and HI interval and threshold of each health stage are obtained. The effectiveness of this method is verified by 4382 sets of on-site switch machine data experiments. The experimental results show that the health index curve calculated by Bray-Curtis distance can accurately represent the health status of the switch machine. Compared with Frechet distance and European distance, this method has better performance in tendency, robustness, and runtime. Combining with Fisher optimal segmentation method, it can reasonably and effectively divide the health stage of the switch machine, providing some support for the on-site judgment of the health status of the switch machine.