期刊
MEASUREMENT
卷 207, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2022.112358
关键词
Tram; Condition monitoring; Gearbox fault diagnosis; Empirical mode decomposition; Decision tree; Machine -learning
The article presents the genesis of a method to diagnose a tram transmission based on acoustic signals from the track position. The influence of a damaged gearbox on acoustic phenomena near the tram line, specifically changes in psychoacoustic indicators, was demonstrated. Nonstationary acoustic signals were analyzed using empirical mode decomposition. The developed quantitative measure served as a classifier in decision trees. An effective tree was selected based on calculated diagnostic indicators, and an algorithm to diagnose the tram transmission without mounting equipment on the vehicle was developed.
The article presents the genesis of the work to develop a method of diagnosing a tram transmission from the track position using acoustic signals. Significant influence of the damaged gearbox on acoustic phenomena in the vicinity of a tram line was shown, especially visible changes in psychoacoustic indicators. Due to the nonstationary nature of the acoustic signals, analyses of the microphone matrix were carried out using the empirical mode decomposition. The developed quantitative measure of individual IMFs served as a classifier in decision trees. For the developed CART type decision trees, the indicators of the effectiveness of the diagnosis were calculated, i.e., the level of unnecessary repairs and the level of undetected damage. Based on these results, the most effective tree was selected, which was used to develop the final, not yet developed, algorithm to diagnose the tram transmission without the need to mount the equipment on the vehicle.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据