Abstract
Rail defects such as fatigue cracks have been one of the leading root causes of a number of derailments in the past. Cracks that initiate and propagate below the surface are difficult to detect using traditional non-destructive testing (NDT) methods. Acoustic emission (AE) is a more effective method for detecting and monitoring crack growth in rails online. This study investigates the applicability of AE for quantifying damage propagation in austenitic cast manganese steel used in manufacturing railway turnouts. The relationship between AE and crack growth rate in austenitic cast manganese steel samples that were fatigue tested in a three-point bending configuration was investigated by evaluating the AE activity with respect to direct current potential drop (DCPD) measurements and scanning electron microscopy (SEM) fractographic analysis of the tested samples. From the results obtained, it was not possible to observe a clear relationship between AE activity and the actual crack growth rate. Based on the SEM fractographic analysis, this is likely due to the plasticity occurring at the tip of the fatigue crack in the tested samples. This is plausible since the cast manganese steel samples had been cut off from a plate that had not been previously work hardened. The effect of carbides present in the microstructure is an additional contributing factor. Further tests should be carried out on cast manganese steel samples that have been work hardened prior to fatigue testing.
| Original language | English |
|---|---|
| Pages (from-to) | 398-403 |
| Number of pages | 6 |
| Journal | Insight: Non-Destructive Testing and Condition Monitoring |
| Volume | 64 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 1 Jul 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
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Dive into the research topics of 'Quantitative analysis of the structural health of railway turnouts using the acoustic emission technique'. Together they form a unique fingerprint.Research output
- 1 Conference contribution
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Quantitative analysis of the structural health of railway turnout using acoustic emission technique
Kongpuang, M., Culwick, R., Cheputeh, N., Marsh, A., Jantara, V. L., Vallely, P., Kaewunruen, S. & Papaelias, M., Aug 2021, 17th International Conference on Condition Monitoring and Asset Management (CM 2021). British Institute of Non-Destructive Testing, p. 432-444Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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