Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19181
Title: Online damage monitoring for high-speed train bogie using guided waves: Development and validation
Authors: Wang, Q
Su, Z 
Hong, M
Keywords: Compact system development
Online damage detection and monitoring
Structural health monitoring
Train bogie
Issue Date: 2014
Publisher: INRIA
Source: 7th European Workshop on Structural Health Monitoring, EWSHM 2014 - 2nd European Conference of the Prognostics and Health Management (PHM) Society, 2014, p. 143-150 How to cite?
Abstract: The high-speed railway industry has enjoyed a rapid development in the past decade, especially in Greater China. 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 group's 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 China's 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.
Description: 7th European Workshop on Structural Health Monitoring, EWSHM 2014, 8-11 July 2014
URI: http://hdl.handle.net/10397/19181
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