The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system
Low-cycle fatigue cropping (LCFC) is a new method for metal bar separation, which solves the problems such as high active load and energy waste in traditional separate methods. A key issue for LCFC is to achieve high cropping efficiency and good cross-section quality simultaneously. To solve this pr...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/172295 |
| _version_ | 1826129673868804096 |
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| author | Ren, Yujian Liu, Boyang Zhang, Yi Dong, Yuanzhe Jin, Dong Zhao, Shengdun Gao, Jingzhou |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Ren, Yujian Liu, Boyang Zhang, Yi Dong, Yuanzhe Jin, Dong Zhao, Shengdun Gao, Jingzhou |
| author_sort | Ren, Yujian |
| collection | NTU |
| description | Low-cycle fatigue cropping (LCFC) is a new method for metal bar separation, which solves the problems such as high active load and energy waste in traditional separate methods. A key issue for LCFC is to achieve high cropping efficiency and good cross-section quality simultaneously. To solve this problem, a novel multi-sensor LCFC system is established to investigate the fracture characteristics of the 16 Mn notched metal bar. In an acoustic emission technique (AET) parameter, the ratio of rise time to amplitude (RA) is used as the control variable for optimization. A 3D microscopy is used to evaluate cross-section quality. Results showed that loading frequency has a big influence on the cross-section quality and the optimal loading frequency is determined. The shear failure model and tensile failure model dominate the crack propagation stage, and the tensile failure model causes poor cross-section quality. RA reflects the failure model change well. An RA-based control scheme is proven to improve the cross-section quality effectively. Combined with cropping time, a suitable RA value is determined. |
| first_indexed | 2024-10-01T07:44:23Z |
| format | Journal Article |
| id | ntu-10356/172295 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:44:23Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1722952023-12-05T05:00:28Z The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system Ren, Yujian Liu, Boyang Zhang, Yi Dong, Yuanzhe Jin, Dong Zhao, Shengdun Gao, Jingzhou School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Multi-Sensor LCFC System Loading Frequency Low-cycle fatigue cropping (LCFC) is a new method for metal bar separation, which solves the problems such as high active load and energy waste in traditional separate methods. A key issue for LCFC is to achieve high cropping efficiency and good cross-section quality simultaneously. To solve this problem, a novel multi-sensor LCFC system is established to investigate the fracture characteristics of the 16 Mn notched metal bar. In an acoustic emission technique (AET) parameter, the ratio of rise time to amplitude (RA) is used as the control variable for optimization. A 3D microscopy is used to evaluate cross-section quality. Results showed that loading frequency has a big influence on the cross-section quality and the optimal loading frequency is determined. The shear failure model and tensile failure model dominate the crack propagation stage, and the tensile failure model causes poor cross-section quality. RA reflects the failure model change well. An RA-based control scheme is proven to improve the cross-section quality effectively. Combined with cropping time, a suitable RA value is determined. This work is supported by the Aviation Joint Fund Project of National Natural Science Foundation of China (U1937203), National Natural Science Foundation of China (Grant No. 52105398), Natural Science Foundation Research Program of Shaanxi Province of China (Grant No. 2022JQ-440), Xi’an Science and Technology project (2017xasjl009), the China Scholarship Council (CSC NO. 202006280402), and the Open Foundation of State Key Laboratory of Compressor Technology (No. SKL-YSJ2020008). 2023-12-05T05:00:28Z 2023-12-05T05:00:28Z 2023 Journal Article Ren, Y., Liu, B., Zhang, Y., Dong, Y., Jin, D., Zhao, S. & Gao, J. (2023). The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system. International Journal of Advanced Manufacturing Technology, 125(3-4), 1371-1382. https://dx.doi.org/10.1007/s00170-022-10696-0 0268-3768 https://hdl.handle.net/10356/172295 10.1007/s00170-022-10696-0 2-s2.0-85145749677 3-4 125 1371 1382 en International Journal of Advanced Manufacturing Technology © 2023 The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature. All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Multi-Sensor LCFC System Loading Frequency Ren, Yujian Liu, Boyang Zhang, Yi Dong, Yuanzhe Jin, Dong Zhao, Shengdun Gao, Jingzhou The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title | The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title_full | The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title_fullStr | The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title_full_unstemmed | The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title_short | The investigation of fracture characteristics and process optimization of low-cycle fatigue cropping by using an AET-based multi-sensor system |
| title_sort | investigation of fracture characteristics and process optimization of low cycle fatigue cropping by using an aet based multi sensor system |
| topic | Engineering::Mechanical engineering Multi-Sensor LCFC System Loading Frequency |
| url | https://hdl.handle.net/10356/172295 |
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