Methods for Detecting and Predicting Localized Rapid Deterioration of Track Irregularity Based on Data Measured with High Frequency

Author:

TANAKA Hirofumi1,YAMAMOTO Shuhei1,OSHIMA Takashi1,MIWA Masashi1

Affiliation:

1. Track Geometry & Maintenance Laboratory, Track Technology Division

Publisher

Railway Technical Research Institute

Subject

Mechanical Engineering

Reference5 articles.

1. [1] Tsubokawa, Y., Yazawa, E., Ogiso, K. and Nanmoku, T., "Development of the Car Body Mounted Track Measuring Device with the Inertial Mid-chord Offset Method," QR of RTRI, Vol.53, No.4, pp.216-222, 2012.

2. [2] Kasai, R., Saito, Y., Komatsu, Y, Ogiso, K., Yahagi, H. and Konishi, S., "Development outline of track facility monitoring device and future prospects," JR East Technical Review, No.55, pp.21-24, 2016 (in Japanese).

3. [3] Sano, K., Miwa, M., Yamaguchi, T., Yoshida, N., Yasaka, K. and Sakaguchi, K., "Developing an Efficient Method of Applying High-Frequency Measured Track Inspection Data to Diagnosis of Track Condition and Establishment of Optimal Track Maintenance Strategy," RTRI REPORT, Vol.29, No.8, pp.47-52, 2015 (in Japanese).

4. [4] Tanaka, H., Yamamoto, S., Ohshima, T., Mori, T. and Saito, Y., "Development of detection method of track irregularity of quick growth using high frequency track measurement data that applies the cross correlation method," Journal of Railway Engineering, Vol.21, pp.1-8, 2017 (in Japanese).

5. [5] Yamamoto, S., Miwa, M., Tanaka, H. and Kashima, T., "Building a track irregularity prediction model considering characteristics of high frequency measurement data," Journal of Railway Engineering, Vol.21, pp.9-16, 2017 (in Japanese).

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Traffic Track Dynamic Data Analysis Based on BP Neural Network Model;2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE);2023-02-24

2. Prediction Models for Railway Track Geometry Degradation Using Machine Learning Methods: A Review;Sensors;2022-09-26

3. <b>Development and Validation of Drive-by Detection Method for Resonant Bridges</b>;Quarterly Report of RTRI;2022-05-01

4. Advancing Railway Asset Management Using Track Geometry Deterioration Modeling Visualization;Journal of Transportation Engineering, Part A: Systems;2022-02

5. Drive-by methodology to identify resonant bridges using track irregularity measured by high-speed trains;Mechanical Systems and Signal Processing;2021-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3