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Online Damage Monitoring for High-Speed Train Bogie Using Guided Waves: Development and Validation

Abstract : The safety of high-speed trains has therefore become a key concern not only in the design process but also in their operation. Usually, plenty of testing jobs are performed through periodical maintenance to ensure the integrity of train structures, using offline nondestructive evaluation methods with relatively low cost-effectiveness. Based on the groupÕs efforts in the past ten years, a guided wave based damage detection and monitoring technique was developed to provide an online structural damage inspection approach, aiming to increase the safety of bogie structures and improve train operation efficiency. Miniaturized standard PZT sensors were developed to compose a pitch-catch based active sensor network for guided wave excitation and acquisition in the train bogie, and a compact system built with the proposed technique was implemented online to inquire information on structural health conditions. As a part of the conformance testing of ChinaÕs latest high-speed train model, experiments on a bogie frame of the train were carried out, especially when the train was running at a high speed, to validate the proposed technique and system, taking into account the complicated working states and the highly variable circumstances of the train, which are usually hard to be simulated in the lab. Several practical experiments were involved in the testing, including the survival rate of the sensor network, disturbance of mechanical vibration to signals, influences of actions of train (such as urgency brake), artificial damage detection, and so on. After running and testing for more than 1500 km, the experimental results from different conditions demonstrated high reliability and accuracy of the technique and the system.
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Submitted on : Tuesday, July 8, 2014 - 9:54:52 AM
Last modification on : Monday, November 15, 2021 - 12:36:01 PM
Long-term archiving on: : Wednesday, October 8, 2014 - 11:27:04 AM


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  • HAL Id : hal-01020332, version 1



Qiang Wang, Zhongqing Su, Ming Hong. Online Damage Monitoring for High-Speed Train Bogie Using Guided Waves: Development and Validation. EWSHM - 7th European Workshop on Structural Health Monitoring, IFFSTTAR, Inria, Université de Nantes, Jul 2014, Nantes, France. ⟨hal-01020332⟩



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