Damage Localization in a Beam by Lifting Wavelet Scheme and Photographic based Experimentation

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Authors

  • Ravi Nigam
     Swami Vivekananda University, Kolkata - 700121, West Bengal ,IN
  • Ramnivas Kumar
     Government Engineering College, Jamui - 811313, Bihar ,IN
  • Nisit Kumar Parida
     Indian Institute of Technology (Indian School of Mines), Dhanbad - 826004, Jharkhand ,IN
  • Ranjan Kumar
     Swami Vivekananda University, Kolkata - 700121, West Bengal ,IN
  • Soumya Ghosh
     Swami Vivekananda University, Kolkata - 700121, West Bengal ,IN
  • Sayan Paul
     Swami Vivekananda University, Kolkata - 700121, West Bengal ,IN

DOI:

https://doi.org/10.18311/jmmf/2023/43926

Keywords:

Crack Detection, Discrete Wavelet Transform, Image Edge Detection, Lifting Wavelet, Stainless Steel Beam, (SS-304)

Abstract

The structures under fatigue loading are fault prone. The damage reduces the local stiffness. This local stiffness leads to a slope discontinuity in the structure's elastic line. Localizing the local discontinuity reveals the location of the damage. Wavelet transform is a powerful tool to localize a local slope discontinuity in a signal. The major challenges in the localization of damage in a beam are obtaining the high spatial resolution beam deflection and eliminating the border distortion. The high spatial resolution shrinks the border distortion as well as gives more localized crack detection. The reduced border distortion leads to the detection of cracks very close to the ends of the beam. In the present work, finite element analysis is used for getting the simulated beam deflection. The lifting wavelet is used for the localization of cracks in the beam. The lifting wavelet has certain advantages over the classical wavelet. The lifting wavelet possesses perfect reconstruction and a narrower border distortion zone. A comparative study is presented between the discrete wavelet transform and the lifting wavelet transform for localizing the crack. The ability of lifting wavelet is tested for different noise conditions and multiple crack localization. A photographic method is used to get the high-resolution of experimental beam deflection of stainless-steel material.

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Published

2024-05-24

How to Cite

Nigam, R., Kumar, R., Parida, N. K., Kumar, R., Ghosh, S., & Paul, S. (2024). Damage Localization in a Beam by Lifting Wavelet Scheme and Photographic based Experimentation. Journal of Mines, Metals and Fuels, 71(12A), 153–159. https://doi.org/10.18311/jmmf/2023/43926

Issue

Volume 71, Issue 12A , 2023

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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References

Kumar R, Nigam R, Singh SK. Selection of suitable mother wavelet along with vanishing moment for the effective detection of crack in a beam. Mechanical Systems and Signal Processing. 2022; 163:108136. https://doi. org/10.1016/j.ymssp.2021.108136

Kumar R, Singh SK. Crack detection near the ends of a beam using wavelet transform and high-resolution beam deflection measurement. European Journal of Mechanics-A/Solids. 2021; 88:104259. https://doi. org/10.1016/j.euromechsol.2021.104259

Morassi A, Rollo M. Identification of two cracks in a simply supported beam from minimal frequency measurements. Journal of Vibration and Control. 2001; 7:729–39. https://doi.org/10.1177/107754630100700507

Masoud AA, Al-Said S. A new algorithm for crack localization in a rotating timoshenko beam. Journal of Vibration and Control. 2009; 15:1541–61. https://doi. org/10.1177/1077546308097272

Labib A, Kennedy D, Featherston CA. Crack localisation in frames using natural frequency degradations. Computer Structures. 2015; 157:51–9. https://doi.org/10.1016/j. compstruc.2015.05.001

Rrzos PF. Identification magnitude the of crack location modes and from in a cantilever beam from the vibration modes. Journal of Sound and Vibration. 1990; 138:381– 8. https://doi.org/10.1016/0022-460X(90)90593-O

Kim JT, Stubbs N. Improved damage identification method based on modal information. Journal of Sound and Vibration. 2002; 252:223–38. https://doi.org/10.1006/ jsvi.2001.3749

Sekhar AS. Crack identification in a rotor system: A model-based approach. Journal of Sound and Vibration. 2004; 270:887–902. https://doi.org/10.1016/S0022- 460X(03)00637-0

Sekhar AS. Model-based identification of two cracks in a rotor system. Mechanical Systems and Signal Processing. 2004; 18:977–83. https://doi.org/10.1016/ S0888-3270(03)00041-4

Dimarogonas AD. Vibration of cracked structures: A state of the art review. Engineering Fracture Mechanics. 1996; 55:831–57. https://doi.org/10.1016/0013- 7944(94)00175-8

Sekhar AS. Multiple crack effects and identification. Mechanical Systems and Signal Processing. 2008; 22:845–78. https://doi.org/10.1016/j.ymssp.2007.11.008

Sabnavis G, Kirk RG, Kasarda M, Quinn D. Cracked shaft detection and diagnostics: A literature review. Shock and Vibration Digest. 2004; 36:287-96. https:// doi.org/10.1177/0583102404045439

Sazonov E, Klinkhachorn P. Optimal spatial sampling interval for damage detection by curvature or strain energy mode shapes. Journal of Sound and Vibration. 2005; 285:783–801. https://doi.org/10.1016/j. jsv.2004.08.021

Zhong S, Oyadiji SO. Sampling interval sensitivity analysis for crack detection by stationary wavelet transform. Structural Control and Health Monitoring. 2013; 20(1):45-69. https://doi.org/10.1002/stc.469

Montanari L, Spagnoli A, Basu B, Broderick B. On the effect of spatial sampling in damage detection of cracked beams by continuous wavelet transform. Journal of Sound and Vibration. 2015; 345:233–49. https://doi. org/10.1016/j.jsv.2015.01.048

Zhong S, Oyadiji SO. Crack detection in simply supported beams without baseline modal parameters by stationary wavelet transform. Mechanical Systems and Signal Processing. 2007; 21:1853–84. https://doi.org/10.1016/j. ymssp.2006.07.007

Wang Q, Deng XM. Damage detection with spatial wavelets. International Journal of Solids and Structures. 1999; 36:3443–68. https://doi.org/10.1016/S0020- 7683(98)00152-8

Kim H, Melhem H, Damage detection of structures by wavelet analysis, Engineering Structures. 2004; 26:347– 62. https://doi.org/10.1016/j.engstruct.2003.10.008

Solis M, Algaba M, Galvin P. Continuous wavelet analysis of mode shapes differences for damage detection. Mechanical Systems and Signal Processing. 2013; 40:645–66. https://doi.org/10.1016/j.ymssp.2013.06.006

Nigam R, Singh SK. Crack detection in a beam using wavelet transform and photographic measurements. Structures. 2020; 25:436-47. https://doi.org/10.1016/j. istruc.2020.03.010

Kumar R, Singh SK. A variance-based approach for the detection and localization of cracks in a beam. Structures. 2022; 44:1261-77. https://doi.org/10.1016/j. istruc.2022.08.068

Mallat S. A Wavelet Tour of Signal Processing. 2009. New York: Academic Press.

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