JDR Vol.15 No.3 pp. 353-359
doi: 10.20965/jdr.2020.p0353


Condition Monitoring of Yangon Circular Railway and Yangon–Mandalay Railway Based on Car-Body Acceleration Response Using a Portable Device

Hein Thura Aung*,†, Kazuki Inoue**, Sao Hone Pha***, and Wataru Takeuchi**

*Department of Electronic Engineering, Yangon Technological University
Gyo Gone, Insein, Yangon 11011, Myanmar

Corresponding author

**Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

***Remote Sensing and GIS Research Center, Yangon Technological University, Yangon, Myanmar

July 31, 2019
March 1, 2020
March 30, 2020
railway track, onboard sensor measurement, cabin vibration, smart phone

The population of Yangon has increased more than two times in the last 40 years and will reach 9.5 million by 2035. Owing to changes in car import policies, the number of cars in Yangon has increased from 3.6 million to 6.3 million in 5 years. This causes severe traffic congestion, resulting in social, economic, and environmental impacts. Rail transportation is one solution to this problem, but regular maintenance of railway tracks is necessary. In this study, onboard sensor measurement and satellite image analysis are used to monitor rail track conditions for the early detection of damage. The accelerometer in a smartphone is placed against the car body to measure the vertical and lateral acceleration. The smartphone vibrates as the cabin vibrates when the train passes irregular rail track sections. Phased-array-type L-band synthetic aperture radar images are analyzed using the interferometric technique to detect rail track irregularities. Thus, the rail track conditions can be estimated effectively.

Cite this article as:
H. Aung, K. Inoue, S. Pha, and W. Takeuchi, “Condition Monitoring of Yangon Circular Railway and Yangon–Mandalay Railway Based on Car-Body Acceleration Response Using a Portable Device,” J. Disaster Res., Vol.15 No.3, pp. 353-359, 2020.
Data files:
  1. [1] Department of Population, Ministry of Immigration and Population, “The Union Report: Census Report Volume 2,” 2015, [accessed August 24, 2017]
  2. [2] CEIC, “Myanmar Motor Vehicle Statistics,” [accessed July 24, 2019]
  3. [3] Japan International Cooperation Agency (JICA), “The Republic of the Union of Myanmar a strategic urban development plan of Greater Yangon: The Project for the Strategic Urban Development Plan of the Greater Yangon: Final Report,” 2013.
  4. [4] Myanma Railways, “Developing a Myanma’s Rail Network that meet demand,” 2015.
  5. [5] Myanma Railways, “Environmental Impact Assessment Report for Yangon Circular Railway Line Upgrading Project in the Republic of the Union of Myanmar,” Draft Final, pp. 1-69, 2016.
  6. [6] M. Shimada, “On the ALOS/PALSAR Operational and Interferometric Aspects,” J. of the Geodetic Society of Japan, Vol.56, No.1, pp. 13-39, doi: 10.11366/sokuchi.56.13, 2010 (in Japanese).
  7. [7] M. Arimoto, Y. Fukushima, M. Hashimoto, and Y. Takada, “Land Subsidence in Semarang, Indonesia, Observed by InSAR Time-Series Analysis Using ALOS/PALSAR Data,” J. of the Geodetic Society of Japan, Vol.59, No.2, pp. 45-56, doi: 10.11366/sokuchi.59.45, 2013 (in Japanese).
  8. [8] M. Hashimoto, “Ground deformation in the Kyoto basin and the Osaka plain detected by ALOS/PALSAR,” J. of Natural Disaster Science, Vol.33, No.2, pp. 115-125, 2014 (in Japanese).
  9. [9] F. Chen, H. Lin, Z. Li, Q. Chen, and J. Zhou, “Interaction between permafrost and infrastructure along the Qinghai-Tibet Railway detected via jointly analysis of C- and L-band small baseline SAR interferometry,” Remote Sensing of Environment, Vol.123, pp. 532-540, doi: 10.1016/j.rse.2012.04.020, 2012.
  10. [10] M. North, T. Farewell, S. Hallett, and A. Bertelle, “Monitoring the Response of Roads and Railways to Seasonal Soil Movement with Persistent Scatterers Interferometry over Six UK Sites,” Remote sensing, Vol.9, doi: 10.3390/rs9090922, 2017.
  11. [11] B. Zhao, T. Nagayama, M. Toyoda, N. Makihata, M. Takahashi, and M. Ieiri, “Vehicle Model Calibration in the Frequency Domain and its Application to Large-Scale IRI Estimation,” J. Disaster Res., Vol.12, No.3, doi: 10.20965/jdr.2017.p0446, pp. 446-455, 2017.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 19, 2024