journal article·2024-12-16Open access

A Study on the Feasibility of Natural Frequency-Based Crack Detection

Xutao Sun, Sinniah Ilanko, Yusuke Mochida, Rachael C. Tighe

Applied Sciences· Volume 14· Issue 24

Abstract

Owing to the long-standing statement that natural frequency-based crack detection is not sensitive enough to localised damage to identify small cracks, many natural frequency-based crack detection methods are validated by detecting cracks of moderate size. However, a direct comparison between the crack severity causing a measurable natural frequency change and the crack severity reaching the initiation of crack propagation or leading to brittle fracture is constantly ignored. Without this understanding, it is debatable whether the presented crack detection methods are feasible in practical situations. Through natural frequency calculation and linear elastic fracture mechanics, this study is dedicated to filling the above gap in knowledge. To directly utilize the solution of stress intensity factor, common fracture toughness test specimens featuring a single-edge crack are used. These specimens are essentially cracked rectangular plates under uniform uniaxial tension. Considering the stress resultants obtained via the extended finite element method, the natural frequency of the loaded cracked plates is calculated using the Rayleigh–Ritz method incorporating corner functions. In addition, assuming the specimens as structural components under remote uniform tension, the development of critical load versus crack length is derived based on the solution of the stress intensity factor. Thus, critical crack lengths corresponding to a series of safety factors are obtained by equating service load with critical load. After obtaining natural frequencies of the cracked plates with critical crack lengths, the natural frequency drop caused by a critical crack can be computed. Hence, the critical crack length can be compared with the crack length when the frequency drop is measurable. It is found that the brittleness of the employed metals plays a vital role in the feasibility of natural frequency-based crack detection.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Structural Health Monitoring Techniques · Ultrasonics and Acoustic Wave Propagation · Infrastructure Maintenance and Monitoring

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

The School of Engineering, The University of Waikato, Gate 1 Knighton Road, Private Bag 3105, Hamilton 3240, New Zealand

References (76)

Show source-provided references
1. Damage assessment based on the structural frequency-response function10.1007/BF02328993 ↗
2. Damage detection using a modified Laplacian operator on mode shape data10.1006/jsvi.1997.0961 ↗
3. Damage detection from changes in curvature mode shapes10.1016/0022-460X(91)90595-B ↗
4. Structural damage detection from modal strain energy change10.1061/(ASCE)0733-9399(2000)126:12(1216) ↗
5. Damage detection in structures using changes in flexibility10.1006/jsvi.1994.1002 ↗
6. Crack detection in beams by rankordering of eigenfrequency shifts10.1006/mssp.1994.1006 ↗
7. Crack detection in beams using experimental modal data and finite element model10.1016/j.ijmecsci.2005.06.008 ↗
8. Crack detection in prestressed concrete structures by measuring their natural frequencies10.1007/s13349-018-0295-2 ↗
9. Crack detection near the ends of a beam using wavelet transform and high resolution beam deflection measurement10.1016/j.euromechsol.2021.104259 ↗
10. A novel method for single and multiple damage detection in beams using relative natural frequency changes10.1016/j.ymssp.2019.06.027 ↗
11. A novel method for crack detection in beam-like structures by measurements of natural frequencies10.1016/j.jsv.2014.04.031 ↗
12. Crack identification method in beam-like structures using changes in experimentally measured frequencies and Particle Swarm Optimization10.1016/j.crme.2017.11.008 ↗
13. On the application of modified cuckoo optimization algorithm to the crack detection problem of cantilever Euler–Bernoulli beam10.1016/j.compstruc.2015.05.008 ↗
14. Crack Identification in Thin Plates With Anisotropic Damage Model and Vibration Measurements10.1115/1.1985432 ↗
15. Crack Detection of Fan Blade Based on Natural Frequencies10.1155/2018/2095385 ↗
16. Implementation of the modal flexibility variation to fault identification in thin plates10.1016/j.actaastro.2009.06.020 ↗
17. Effect of temperature on modal variability of a curved concrete bridge under ambient loads10.1061/(ASCE)0733-9445(2007)133:12(1742) ↗
18. Long term vibration monitoring of an RC slab: Temperature and humidity effect10.1016/j.engstruct.2005.09.001 ↗
19. Effects of environmental and operational variability on structural health monitoring
20. One-year monitoring of the Z24-Bridge: Environmental effects versus damage events10.1002/1096-9845(200102)30:2<149::AID-EQE1>3.0.CO;2-Z ↗
21. Health monitoring based on dynamic flexibility matrix: Theoretical models versus in-situ tests10.4236/eng.2017.92004 ↗
22. Crack detection of arch dam using statistical neural network based on the reductions of natural frequencies10.1016/j.jsv.2007.01.008 ↗
23. Multi-crack detection in general cross-section swept wings based on natural frequency changes10.1177/1077546320964010 ↗
24. Rotor crack detection based on high-precision modal parameter identification method and wavelet finite element model10.1016/j.ymssp.2008.08.003 ↗
25. Tada, H., Paris, P.C., and Irwin, G.R. (2000). The Stress Analysis of Cracks Handbook, ASME Press. [3rd ed.].10.1115/1.801535 ↗
26. Dowling, N.E. (2013). Mechanical Behavior of Materials: Engineering Methods for Deformation, Fracture, and Fatigue, Pearson. [4th ed.].
27. A Path Independent Integral and the Approximate Analysis of Strain Concentration by Notches and Cracks10.1115/1.3601206 ↗
28. Irwin, G.R. (1960, January 16–19). Plastic zone near a crack and fracture toughness. Proceedings of the Seventh Sagamore Ordnance Materials Research Conference, Session VI, Syracuse, New York, NY, USA.
29. Elastic crack growth in finite elements with minimal remeshing10.1002/(SICI)1097-0207(19990620)45:5<601::AID-NME598>3.0.CO;2-S ↗
30. Vibration analysis of rectangular plates with side cracks via the Ritz method10.1016/j.jsv.2009.01.018 ↗
31. High degree efficient symmetrical Gaussian quadrature rules for the triangle10.1002/nme.1620210612 ↗
32. Scattered data interpolation methods for electronic imaging systems: A survey10.1117/1.1455013 ↗
33. Laser Beam Position-Dependent PSD-Based Calibrated Self-Vibration Compensated Noncontact Vibration Measurement System10.1109/TIM.2018.2875604 ↗
34. Labib, A. (2018). Crack Detection in Frames Using Natural Frequency Degradations. [Ph.D. Thesis, Cardiff University].
35. Crack detection of cantilever beam by natural frequency tracking using experimental and finite element analysis10.1016/j.aej.2018.10.002 ↗
36. Vibration damping of flax fibre-reinforced polypropylene composites10.1007/s12221-017-7418-y ↗
37. Kannappan, L. (2008). Damage Detection in Structures Using Natural Frequency Measurements. [Ph.D. Thesis, University of New South Wales].
38. A review of extended/generalized finite element methods for material modeling10.1088/0965-0393/17/4/043001 ↗
39. Modeling quasi-static crack growth with the extended finite element method Part I: Computer implementation10.1016/j.ijsolstr.2003.08.002 ↗
40. Vibrations and stability of a loaded side-cracked rectangular plate via the MLS-Ritz method10.1016/j.tws.2016.05.013 ↗
41. Sih, G.C. (1973). Solutions of plane crack problems by mapping technique. Methods of Analysis and Solutions of Crack Problems: Recent Developments in Fracture Mechanics Theory and Methods of Solving Crack Problems, Springer.10.1007/978-94-017-2260-5 ↗
42. Measurement of elastic properties of AISI 52100 alloy steel by ultrasonic nondestructive methods10.2140/jomms.2012.7.951 ↗
43. Hertzberg, R.W., Vinci, R.P., and Hertzberg, J.L. (2012). Deformation and Fracture Mechanics of Engineering Materials, John Wiley & Sons. [5th ed.].
44. ASM Handbook Committee (1978). Metals Handbook: Vol. 2, Properties and Selection–Nonferrous Alloys and Pure Metals, American Society for Metals.
45. Kalpakjian, S. (2010). Manufacturing Engineering and Technology, Pearson Education. [6th ed.].
46. Hearn, E.J. (1985). Mechanics of Materials 1: The Mechanics of Elastic and Plastic Deformation of Solids and Structural Materials, Pergamon.
47. Free vibration analysis of Euler-Bernoulli beam with double cracks10.1007/BF02916309 ↗
48. Experimental dynamic analysis of cracked free-free beams10.1007/BF02322697 ↗
49. Experimental investigation on the enhancement of vibration and flutter characteristics of damaged composite plates using piezoelectric patches10.1016/j.compstruct.2021.114518 ↗
50. Crack identification through scan-tuning of vibration characteristics using piezoelectric materials10.1088/1361-665X/aa520a ↗
51. Vibration-based monitoring of an FRP footbridge with embedded fiber-Bragg gratings: Influence of temperature vs. damage10.1016/j.compstruct.2022.115295 ↗
52. Crack identification in beam-type structural elements using a piezoelectric sensor10.1080/10589759.2020.1843652 ↗
53. Crack identification of functionally graded beam using distributed piezoelectric sensor10.1177/10775463221095649 ↗
54. Li, D., and Wang, Y. (2020). Thermally Stable Wireless Patch Antenna Sensor for Strain and Crack Sensing. Sensors, 20.10.3390/s20143835 ↗
55. Zohra, F.T., Dey, S., Salim, O., Masoumi, H., and Karmakar, N. (2020, January 5–7). Design and Analysis of a UHF RFID Crack Sensor for Health Monitoring of Mining Conveyor Belt. Proceedings of the 2020 27th International Conference on Telecommunications (ICT), Bali, Indonesia.10.1109/ICT49546.2020.9239495 ↗
56. A Novel “Smart Skin” Sensor for Chipless RFID-Based Structural Health Monitoring Applications10.1109/JIOT.2020.3026729 ↗
57. Temperature variation compensated damage classification and localisation in ultrasonic guided wave SHM using self-learnt features and Gaussian mixture models10.1088/1361-665X/ac5ce3 ↗
58. Liu, N., and Schumacher, T. (2020). Improved Denoising of Structural Vibration Data Employing Bilateral Filtering. Sensors, 20.10.3390/s20051423 ↗
59. Kralovec, C., and Schagerl, M. (2020). Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures. Sensors, 20.10.3390/s20030826 ↗
60. Fully plastic J-integral solutions for surface cracked plates under biaxial loading10.1016/j.engfracmech.2005.12.014 ↗
61. J-Integral Solution for Elastic Fracture Toughness for Plates with Inclined Cracks under Biaxial Loading10.1061/(ASCE)EM.1943-7889.0001444 ↗
62. A novel vibration based breathing crack localization technique using a single sensor measurement10.1016/j.ymssp.2018.12.019 ↗
63. Application of entropy in identification of breathing cracks in a beam structure: Simulations and experimental studies10.1177/1475921717704626 ↗
64. Structural fatigue crack localisation based on spatially distributed entropy and wavelet transform10.1016/j.engstruct.2022.114544 ↗
65. Cui, S., Maghoul, P., and Wu, N. (2022, January 25–28). Structural Fatigue Crack Localization Based on EMD and Sample Entropy. Proceedings of the Canadian Society of Civil Engineering Annual Conference 2022, Whistler, BC, Canada.
66. Structural Health Monitoring Framework Based on Internet of Things: A Survey10.1109/JIOT.2017.2664072 ↗
67. An IoT based building health monitoring system supported by cloud10.1007/s40860-020-00107-0 ↗
68. Simone, M.C.D., Lorusso, A., and Santaniello, D. (2022, January 18–20). Predictive maintenance and Structural Health Monitoring via IoT system. Proceedings of the 2022 IEEE Workshop on Complexity in Engineering (COMPENG), Florence, Italy.
69. Vibration-based structural condition assessment using convolution neural networks
70. Gillich, N., Tufisi, C., Sacarea, C., Rusu, C.V., Gillich, G.-R., Praisach, Z.-I., and Ardeljan, M. (2022). Beam Damage Assessment Using Natural Frequency Shift and Machine Learning. Sensors, 22.10.20944/preprints202201.0111.v1 ↗
71. Eltouny, K., Gomaa, M., and Liang, X. (2023). Unsupervised Learning Methods for Data-Driven Vibration-Based Structural Health Monitoring: A Review. Sensors, 23.10.3390/s23063290 ↗
72. Bridge Damage Detection in Presence of Varying Temperature Using Two-Step Neural Network Approach10.1061/(ASCE)BE.1943-5592.0001708 ↗
73. A data-driven approach for drive-by damage detection in bridges considering the influence of temperature change10.1016/j.engstruct.2021.113783 ↗
74. Irwin, G.R., Krafft, J., Paris, P., and Wells, A. (1967). Basic Aspects of Crack Growth and Fracture, Naval Reserach Laboratory. NRL Report 6598.
75. De Los Rios Giraldo, J.O. (2017). Damage Identification in Skeletal Structures: A Dynamic Stiffness Approach. [Ph.D. Thesis, The University of Waikato].
76. Development of laser vibrometer