Literature DB >> 31370343

Active Monitoring of Fatigue Crack in the Weld Zone of Bogie Frames Using Ultrasonic Guided Waves.

Jiajia Yan1, Hashen Jin, Hu Sun, Xinlin Qing.   

Abstract

The bogie frame is an important structure of railway vehicles, transmitting the traction, braking force, lateral force, and vertical force during the traction operation. With the development of high speeds and heavy loads, the appearance of fatigue cracks in the bogie frames is increasing, which reduces the driving life of railway vehicles and even causes serious traffic accidents. Real-time monitoring on the integrity of the bogie is an inevitable requirement for ensuring the safe operation of railway vehicles. In this paper, ultrasonic guided wave-based active structural health monitoring (SHM) was developed to identify the fatigue crack of the bogie frame. Experiments were conducted on a welded T-shape specimen with a thickness of 12 mm. A total of 10 piezoelectric lead zirconate titanate (PZT) disks were mounted around the weld zone of the specimen, five of which were used as actuators, and the other five were used as sensors. Five-peak modulation narrow-band sine waves were input into the actuators to excite the specimen. From the sensor signals, the advanced damage index (DI) was calculated to identify the propagation of the crack. The experimental results demonstrate that crack damage as small as 2 mm in the weld zone of the bogie frame can be successfully detected. Some practical issues for implementing the SHM in real applications, such as crack quantification and environmental compensation, were also discussed.

Entities:  

Keywords:  bogie frame; fatigue crack; guided wave; sensor network; structural health monitoring

Year:  2019        PMID: 31370343      PMCID: PMC6696295          DOI: 10.3390/s19153372

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

1.  A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE †.

Authors:  David Agis; Francesc Pozo
Journal:  Sensors (Basel)       Date:  2019-11-21       Impact factor: 3.576

2.  Monitoring of Fiber-Reinforced Composite Single-Lap Joint with Electromechanical Impedance of Piezoelectric Transducer.

Authors:  Jianjian Zhu; Xinlin Qing; Qijian Liu; Xiao Liu; Yishou Wang
Journal:  Materials (Basel)       Date:  2019-10-04       Impact factor: 3.623

3.  Lamb Wave-Based Damage Localization and Quantification in Composites Using Probabilistic Imaging Algorithm and Statistical Method.

Authors:  Jiahui Guo; Xianping Zeng; Qijian Liu; Xinlin Qing
Journal:  Sensors (Basel)       Date:  2022-06-25       Impact factor: 3.847

  3 in total

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