Track Condition Monitoring System Research Articles

Development and Operation of Track Condition Monitoring System Using In-Service Train

Railway tracks must be managed appropriately because their conditions significantly affect railway safety. Safety is ensured through inspections by track maintenance staff and maintenance based on measurements using dedicated track geometry cars. However, maintaining regional railway tracks using conventional methods is becoming difficult because of their poor financial condition and lack of manpower. Therefore, a track condition diagnostic system is developed, wherein onboard sensing devices are installed on in-service vehicles, and the vibration acceleration of the car body is measured to monitor the condition of the track. In this study, we conduct long-term measurements using the system and evaluate changes in the track conditions over time using car-body vibration data. Filed test results showed that sections with degraded tracks were identified using car-body vibration data. The track degradation trend can be constructed using the results obtained. Furthermore, this study demonstrated that the track maintenance effect could be confirmed. A method for improving train position using the yaw angular velocity is proposed. The track irregularity position can be shown more clearly by monitoring the track condition using position-corrected data using the proposed method. It is also shown that the time-frequency analysis of measured car-body vertical acceleration is effective for evaluating the track condition more clearly.

Development and operation of track condition monitoring system using in-service train

Monitoring the condition of railway tracks effectively increases the safety of railways. A system that uses a compact on-board sensing device was previously developed for monitoring the track condition of railways. The system's position identification method uses GPS map-matching.However, this system had an error of several tens of meters depending on GPS reception conditions. In this study, the position correction method was tested using curvature calculated from yaw angular acceleration. The results of the test study indicated that it is possible to diagnose the location of track irregularities more clearly.

Condition monitoring of railway track from car-body vibration using time–frequency analysis

ABSTRACT Proper maintenance of railway tracks is essential to ensure railway safety. A track condition monitoring system was developed for the preventive maintenance of the track by installing the on-board sensing device in the in-service vehicles and monitoring the track condition by measuring the car-body acceleration. This paper describes the application of time–frequency analysis for the condition monitoring of railway tracks. Car-body acceleration simulated by a 10-DOF vehicle model, with a faulty track, was used to identify the track faults using Hilbert–Huang transform (HHT). Field tests were carried out using the developed track condition monitoring system to show the effectiveness of the time–frequency analysis using HHT. Simulation studies and field test results showed that HHT can yield a good time–frequency resolution and that intrinsic mode functions (IMFs) can provide the detailed information of track faults.

Study of railway traffic safety based on the railway track condition monitoring system

The solution to the problem of monitoring the railway track, as well as potentially dangerous objects and phenomena in the adjacent territories, is determined by the need to implement increased requirements for traffic safety (primarily to the geometric parameters of the devices of a long railway track under construction and functioning load-bearing highways), prevention of technological disasters and large-scale negative effects of natural phenomena on the railways. The continuous process of integrating methods and means of monitoring and preventing emergencies into a single information management system is shown. The possibility of determining a dynamic model of the adverse effect of the train on the track and the most unfavorable for the track train and traction parameters, which must be avoided when forming trains in this section, is established. Three key factors are formulated, the use of which will reduce the negative impact on the track from trains. The concept of information technology improvement of the monitoring system for potentially dangerous sections of the railway on the basis of new innovative technologies has been developed.

Energy-efficient hybrid MAC protocol for railway monitoring sensor network

In the present work, a new protocol is proposed i.e. application-specific hybrid medium access control (ASHMAC) to efficiently handle data traffic generation in the railway track condition monitoring system. ASHMAC protocol is an improved version of the bit-map-assisted (BMA) medium access control (MAC) protocol by which it can efficiently handle continuous monitoring data traffic as well. Simulation and mathematical models have been developed and proposed for ASHMAC protocol. Its performance is compared with the other MAC protocols. The results reveal that the proposed protocol consumes 25–50% less energy w.r.t. time division multiple access (TDMA), energy-efficient TDMA, and BMA at low to medium data traffic conditions. For high data traffic conditions, the energy consumption of the proposed ASHMAC protocol is approximately equal to the other protocols. The transmission latency of ASHMAC is approximately 50% less than energy-efficient BMA. Both analytical and simulation results show the overall superiority of the proposed protocol.

Condition Monitoring of Railway Tracks from Car-Body Vibration Using a Machine Learning Technique

A track condition monitoring system that uses a compact on-board sensing device has been developed and applied for track condition monitoring of regional railway lines in Japan. Monitoring examples show that the system is effective for regional railway operators. A classifier for track faults has been developed to detect track fault automatically. Simulation studies using SIMPACK and field tests were carried out to detect and isolate the track faults from car-body vibration. The results show that the feature of track faults is extracted from car-body vibration and classified from proposed feature space using machine learning techniques.

A Track Condition Monitoring System using In-service Vehicle for Regional Railways

A Track Condition Monitoring System using In-service Vehicle for Regional Railways

2P25 Development of track condition monitoring system using in-service vehicle and monitoring examples(Shotgun Session)

Condition monitoring of railway tracks are essential in ensuring the safety of railways. Preventive maintenance repairing before an accident occurs is an important challenge. Current inspection method of tracks is by track maintenance staff and by track inspection car. These method can be highly accurate inspection, but it is limited to use in local lines. Therefore the condition monitoring techniques that can be adopted in the local railway is required. In the context, a condition monitoring system of railway track using in-service vehicle has been developed. In-service vehicles equipped with sensors and GPS systems can act as probes to detect and analyze real-time vehicle vibration. Such trains are known as "probe vehicles". Recently, a compact size on-board sensing device has been developed. This paper describes the track condition monitoring system using the compact size on-board sensing device and the diagnosis software. It is known that a car-body acceleration is effective for making rough estimate of track condition. This diagnosis software uses RMS of car-body acceleration as evaluation index for basic analysis. However, the RMS values can't isolate the track faults due to the lack of frequency information. Thus, continuous wavelet transform (CWT) and discrete wavelet transform (DWT) are employed to extract different type of the track faults. The validity of this software was evaluated by simulation studies. Simulation results showed that the diagnosis software is useful for track condition monitoring. Monitoring experience in a local railway line showed that the system is effective for practical use.

小型レール診断装置を用いた軌道状態診断システムの開発

小型レール診断装置を用いた軌道状態診断システムの開発

G1800103 在来線用レール状態診断システムの開発

Condition monitoring of railway tracks is essential in ensuring the safety of railways. In-service vehicles equipped with sensors and GPS systems can act as probes to detect and analyze real-time vehicle vibration. Such trains are known as "probe vehicles". Recently, a compact size on-board sensing device has been developed. This paper describes the track condition monitoring system using the compact size on-board sensing device and the diagnosis software. The diagnosis software provides a function to detect track irregularities using RMS of the car-body acceleration. It also provides a function to analyze in time-frequency domain using wavelet transform. Monitoring experience in a local railway line showed that the system is effective for practical use.

Track geometry estimation from car-body vibration

Track maintenance works based on track geometry recordings are essential to enhance the safety and comfort of railway transportation. The track condition monitoring system is mainly used for the choice of area needing track tamping works for the purpose of the good riding comfort. An advantage of car-body acceleration measurement devices is their simple structures, which make it easier to carry out maintenance. However, the car-body acceleration waveform is considerably different from track geometry. This paper demonstrates the possibility to estimate the track geometry of Shinkansen tracks using car-body motions only. In an inverse problem to estimate track irregularity from car-body motions, a Kalman Filter (KF) was applied to solve the problem. Estimation results showed that track irregularity estimation in vertical direction is possible with acceptable accuracy for real use.