Optimized Railway Track Condition Monitoring and Derailment Prevention System Supported by Cloud Technology

Chellaswamy, C.; Geetha, T.; Rao, M. Surya Bhupal; Vanathi, A.

doi:10.1177/0361198120980438

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Variational autoencoder (VAE) networks can not only learn the structural features and internal correlation between data sets deeply but also make the network hidden layer variables learn the distribution rules of original data by adding constraints. Moreover, the model warning robustness is stronger [5].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Wind Turbine Gearbox Based on Multisensor Data Fusion

Zhang

Zhou

2022

Journal of Control Science and Engineering

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In order to improve the operation efficiency of wind turbine gearbox and reduce the operation and maintenance cost of wind farm, a fault diagnosis system for wind turbine gearbox based on multisensor data fusion was proposed. First, the different time-domain statistical characteristic parameters of the original vibration signal were calculated, and the information fusion of the feature level and the data level was carried out by means of parallel superposition to obtain the fused data set. Second, a fault classification and recognition model based on GMO-KELM was established by using the fusion data set. Finally, the proposed method was used to monitor the status of the measured data of the gearbox on the vibration test bed of rotating machinery. The experimental results showed that the average training accuracy and the average test accuracy of GMO-KELM method were 100% and 95.58%, respectively, which were much higher than those of other methods. Through experiments and analyses, it was shown that the proposed method was effective and feasible. Compared with other similar methods, the proposed method had the best classification performance.

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Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Wind Turbine Gearbox Based on Multisensor Data Fusion

Zhang

Zhou

2022

Journal of Control Science and Engineering

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“…KAMOSHITA Shogo et al [24] developed a bogie for reducing the risk of derailment. Chellaswamy C et al [25] describe an easy way to monitor railway track abnormalities and update information on the track's status to the cloud.…”

Section: Introductionmentioning

confidence: 99%

Study on Dynamic Damage of Crash Barrier under Impact Load of High-Speed Train

Qian,

Wang,

et al. 2024

Sustainability

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The derailment of a high-speed train in a tunnel will cause a very serious accident, but there are few research articles on anti-collision facilities in tunnels. In order to promote the sustainable development of high-speed trains and reduce the severity of accidents caused by derailment in tunnels of high-speed trains, this paper puts forward a crash barrier scheme in tunnels through the method of numerical simulation; the coupling finite element model of train–crash barrier–tunnel is established by using ABAQUS. The changes in lateral velocity and lateral displacement after the train hits the crash barrier without embedding steel bars are explored. We also explore the influence of different reinforcement amounts on the changes in the lateral speed and lateral displacement of trains under the condition of embedding steel bars. The results show that with the increase in stirrups and vertical reinforcement, the anti-impact and sustainable operation capability of the crash barrier are greater. It can also be seen from the lateral displacement of the train that the train shows the reverse movement trend, and the crash barrier plays a good role in intercepting the train. These research results can provide a reference for the sustainable development of transportation infrastructure construction.

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