Purpose–In this paper,a high-frequency radar test system was used to collect the data of clean ballast bed and fouled ballast bed of ballasted tracks,respectively,for a quantitative evaluation of the condition of rai...Purpose–In this paper,a high-frequency radar test system was used to collect the data of clean ballast bed and fouled ballast bed of ballasted tracks,respectively,for a quantitative evaluation of the condition of railway ballast bed.Design/methodology/approach–Based on original radar signals,the time–frequency characteristics of radar signals were analyzed,five ballast bed condition characteristic indexes were proposed,including the frequency domain integral area,scanning area,number of intersections with the time axis,number of timedomain inflection points and amplitude envelope obtained by Hilbert transform,and the effectiveness and sensitivity of the indexes were analyzed.Findings–The thickness of ballast bed tested at the sleep bottom by high-frequency radar is up to 55 cm,which meets the requirements of ballast bed detection.Compared with clean ballast bed,the values of the five indexes of fouled ballast bed are larger,and the five indexes could effectively show the condition of the ballast bed.The computational efficiency of amplitude envelope obtained by Hilbert transform is 140 s$km1,and the computational efficiency of other indexes is 5 s$km1.The amplitude envelopes obtained by Hilbert transform in the subgrade sections and tunnel sections are the most sensitive,followed by scanning area.The number of intersections with the time axis in the bridge sections was the most sensitive,followed by the scanning area.The scanning area can adapt to different substructures such as subgrade,bridges and tunnels,with high comprehensive sensitivity.Originality/value–The research can provide appropriate characteristic indexes from the high-frequency radar original signal to quantitatively evaluate ballast bed condition under different substructures.展开更多
基金funded by the National Key R&Dprogram of China[Grant No.2022YFB2603302]the Science and Technology Research and Development Program of China State Railway Group Co.,Ltd[Grant No.K2022G015]the Fund Project of China Academy of Railway Sciences Corporation Limited[Grant No.2022YJ305].
文摘Purpose–In this paper,a high-frequency radar test system was used to collect the data of clean ballast bed and fouled ballast bed of ballasted tracks,respectively,for a quantitative evaluation of the condition of railway ballast bed.Design/methodology/approach–Based on original radar signals,the time–frequency characteristics of radar signals were analyzed,five ballast bed condition characteristic indexes were proposed,including the frequency domain integral area,scanning area,number of intersections with the time axis,number of timedomain inflection points and amplitude envelope obtained by Hilbert transform,and the effectiveness and sensitivity of the indexes were analyzed.Findings–The thickness of ballast bed tested at the sleep bottom by high-frequency radar is up to 55 cm,which meets the requirements of ballast bed detection.Compared with clean ballast bed,the values of the five indexes of fouled ballast bed are larger,and the five indexes could effectively show the condition of the ballast bed.The computational efficiency of amplitude envelope obtained by Hilbert transform is 140 s$km1,and the computational efficiency of other indexes is 5 s$km1.The amplitude envelopes obtained by Hilbert transform in the subgrade sections and tunnel sections are the most sensitive,followed by scanning area.The number of intersections with the time axis in the bridge sections was the most sensitive,followed by the scanning area.The scanning area can adapt to different substructures such as subgrade,bridges and tunnels,with high comprehensive sensitivity.Originality/value–The research can provide appropriate characteristic indexes from the high-frequency radar original signal to quantitatively evaluate ballast bed condition under different substructures.
基金上海财经大学"十一五""211工程"重点学科平台建设项目"中国重大经济指数编制及数据库建设研究"的资助+3 种基金国家社科基金项目"统计指数理论的发展和应用研究"(05BTJ007)的资助教育部新世纪优秀人才支持计划(NCET-04-0429)的资助上海市重点学科建设项目资助(项目编号:Supported by Shanghai Leading Aca-demic Discipline ProjectB803)