Time–frequency processing of track irregularities in high-speed train. (January 2016)

• Record Type: Journal Article
• Authors: Ning, Jing; Lin, Jianhui; Zhang, Bing
• Is Part Of: Mechanical systems and signal processing. Volume 66/67(2016)
• Page Start: 339
• Page End: 348
• Publication Date: 2016-01
• Subjects: Axle box acceleration -- Time–frequency distribution -- Detection -- Rail irregularities; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.04.031
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: Track irregularities are the main source of vehicle vibration. With the increase in the speed, the track irregularities have become a more significant issue of concerned. The axle box acceleration signals can be obtained for analyzing the track irregularities, but the signals are usually non-stationary and signal processing results are not normally satisfied with the ordinary way. Thus, time–frequency distribution analysis is proposed to use in this study. To minimize the cross-terms, a new method based on Empirical Mode Decomposition (EMD) and Cohen׳s class distribution has been developed and advanced. This approach has been tested with three typical simulation signals and then applied to analyze the track irregularities. The result is consistent with the result from track inspection cars. This indicates this new algorithm is suitable for analyzing the track irregularities. It can be applied in rail irregularity measurement to compensate some shortages of the track inspection cars. Highlights: A method based on EMD and Cohen class distribution was advanced. The method was applied to measure track irregularities via high speed train signals. This method could compensate some shortage for track inspection car.