# Development and Operation of Track Condition Monitoring System Using In-Service Train
## 7 Conclusions  
We conducted long-term vibration measurements using in-service vehicles of regional railways, identified sections with degraded tracks using car-body vibration data, and presented figures that show changes in the track conditions over time. The track degradation trend can be constructed using the results obtained. Furthermore, this study demonstrated that the track maintenance effect could be confirmed.  
Rapid track degradation and the effects of track maintenance in regional railways are difficult to understand owing to the difficulty in conducting frequent track geometry measurements because of their poor financial condition and lack of manpower. Therefore, the track condition must be monitored frequently based on the vibration acceleration data measured using in-service vehicles. Moreover, track geometry cars cannot operate on tracks in regional railways, and railway operators typically conduct only static track inspections without applying any load to the track. In a static inspection, the track condition differs from the state in which the vehicles operate on the track in actual scenarios. Therefore, car-body vibration accelerations measured using in-service trains must be utilised to maintain track conditions. This system can be used in conjunction with track recording car measurement data for efficient maintenance.  
Position information calculated via map matching using a GNSS was corrected using the curvature obtained from the yaw angular velocity. Position correction using the curvature appeared to be effective for position information calculated via map matching using a GNSS. Additionally, the track irregularity position can be shown more clearly by monitoring the track condition using position-corrected data.  
In future studies, we will add more correction points and verify other sections between the stations to confirm the effectiveness of the proposed method. In this study, we used the track data used by railway operators to manage the tracks as the reference positions for the curve start/end points (BTC, ETC); however, these data may not match the actual track geometry. Therefore, we will consider creating an accurate position information DB of the curve start/endpoints using high-precision positioning methods, such as the real-time kinematic method and quasi-zenith satellite system, and then use it for correction.  
We also showed that a time-frequency analysis of the measured car-body vertical acceleration is effective for evaluating track conditions. We will evaluate the effect of track maintenance more comprehensively by comparing the vibration acceleration measurements with the track geometry measurement results after track maintenance. Furthermore, we plan to predict the progress of track condition degradation based on previous changes in the vibration acceleration.  
Conceptualization, H.T.; methodology, H.T.; software, H.O. and T.T.; validation, H.T., H.O. and T.T.; analysis, H.T., H.O. and T.T.; data curation, H.T., T.T., S.O. and H.O.; writing--original draft preparation, H.T.; writing--review and editing, H.O., T.T., S.O. and H.T.; visualization, H.T. and H.O.; supervision, H.T.; project administration, H.T.; funding acquisition, H.T. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Nihon University Research Grant for Social Implementation (19-006) (2019-2021) and JSPS KAKENHI Grant Number 20K04368.