Respiratory crack location method for beam structures based on bilinear frequency separation

doi:10.16731/j.cnki.1671-3133.2024.03.019

Abstract

Abstract: Aiming at the problem of early respiratory crack location of beam structures,based on the difference of bilinear degree of different measuring points of beams with respiratory cracks,a bilinear frequency separation method for respiratory crack location of beam structures was proposed. By using the techniques of zero search and signal segmentation,the structural responses of different spatial positions were decomposed into positive and negative response components corresponding to bilinear effects,which reflect the dynamic behavior of the structure in the crack opening state and closed state,respectively. The difference of frequency components of split components at different measuring points is related to the location and depth of cracks,so the distance damage index of bilinear frequency components was constructed to realize the location of cracks. The numerical study of the influencing factors such as crack location,crack depth,excitation frequency and amplitude,natural structure shape and noise shows the effectiveness of the method and can provide a theoretical basis for practical engineering applications.

Key words: crack location, bilinear characteristics, zero search, respiratory crack, signal segmentation

CLC Number:

TH113

JIANG Yang, LU Zhiwen, FENG Kewei. Respiratory crack location method for beam structures based on bilinear frequency separation[J]. Modern Manufacturing Engineering, 2024, 522(3): 140-147.

References

[1] 蒋勉,张文安,伍济钢,等.一种利用振动响应非线性估计的叶片裂纹定位方法[J].机械科学与技术,2018,37(4):8.
[2] PRAWIN J.Localization of breathing crack in beamlike structures using superharmonic components based on singular value decomposition approach[J].International Journal of Structural Stability and Dynamics,2020,20(1):2050014.
[3] CAO M,RADZIERISKI M,XU W,et al.Identification of multiple damage in beams based on robust curvature mode shapes[J].Mechanical Systems and Signal Processing,2014,46(2):468-480.
[4] KARA M.A higher order statistical moment based approach for the distribution of eigenvalues of beams with variable cracked depth[J].Mechanical Systems and Signal Processing,2021,161:107965.
[5] SHA G,RADZIENSKI M,′CAO M,et al. A novel method for single and multiple damage detection in beams using relative natural frequency changes,Mech[J].Syst.Sig.Process,2019(132):335-352.
[6] 吴琪强,郭帅平,王钢,等.基于固有频率的风力机叶片裂纹精确定位与程度识别[J].振动与冲击,2019,38(24):10.
[7] LI J,LAW S S,DING Y.Substructure damage identification based on response reconstruction in frequency domain and model updating[J].Eng.Struct,2012(41):270-284.
[8] ALAMDARI M M,LI J,SAMALI B.FRF-based damage localization method with noise suppression approach[J].Sound Vib,2014(333):3305-3320.
[9] 郭帅平,吴琪强,李学军,等.基于模态参数的梁结构多裂纹定位与程度识别[J].振动与冲击,2020,39(23):9.
[10] 唐盛华,苏彬建,方志,等.基于均匀荷载面曲率的简支裂纹梁损伤识别[J].计算力学学报,2019,36(6):8.
[11] BOVSUNOVSKY A,SURACE C.Non-linearities in the vibrations of elastic structures with a closing crack:a state of the art review[J].Mechanical Systems and Signal Processing,2015,62:129-148.
[12] ASNAASHARI E,SINHA J K.Development of residual operational deflection shape for crack detection in structures[J].Mechanical Systems and Signal Processing,2014,43(1/2):113-123.
[13] PRAWIN J. Breathing crack damage diagnostic strategy using improved MFCC features[J]. Journal of Intelligent Material Systems and Structures, 2021,32(20):2437-2462.
[14] PRAWIN J.A novel time domain-based multiple breathing crack diagnosis technique using Quadratic-Teager Kaiser Energy(Q-TKE)[J].Structural Health Monitoring,2023,22(6):3785-3804.
[15] PRAWIN J,RAO A R M.A method for detecting damage-induced nonlinearity in structures using weighting function augmented curvature approach[J].Structural Health Monitoring,2019,18(4):1154-1167.
[16] PRAWIN J,RAO A R M.Reference-Free Breathing Crack Identification of Beam-Like Structures Using an Enhanced Spatial Fourier Power Spectrum with Exponential Weighting Functions[J].Nature reviews Cancer,2019,19(2):1950017.
[17] PRAWIN J,RAO A R M.Vibration-based breathing crack identification using non-linear intermodulation components under noisy environment[J].Structural Health Monitoring,2020,19(1):86-104.
[18] PRAWIN J,LAKSHMI K,RAO A R M.A novel vibration based breathing crack localization technique using a single sensor measurement[J].Academic Press,2019,122:117-138.
[19] PENG Z,LI J,HAO H,et al.Nonlinear structural damage detection using output-only Volterra series model[J].Structural Control and Health Monitoring,2021,28(9):e2802.
[20] SMITH S,WANG G,WU D.Bayesian approach to brea-thing crack detection in beam structures[J].Engineering Structures,2017,148(10):829-838.
[21] JIANG M,WANG D,KUANG Y,et al.A bicoherence-based nonlinearity measurement method for identifying the location of breathing cracks in blades[J].International Journal of Non-Linear Mechanics,2021,135:103751.
[22] LU Z R,YANG D,LIU J,et al.Nonlinear breathing crack identification from time-domain sensitivity analysis[J].Applied Mathematical Modelling,2020,83:30-45.
[23] YAN G,STEFANO A D,MATTA E,et al.A novel approach to detecting breathing-fatigue cracks based on dynamic characteristics[J].Journal of Sound and Vibration,2013,332(2):407-422.
[24] WEI Q,CAO M,SGEN L,et al.A novel DISTINCT method for characterizing breathing features of nonlinear damage in structures[J].Mechanical Systems and Signal Processing,2023,196:110333.
[25] PRAWIN J. A novel singular spectrum analysis-based baseline-free approach for fatigue-breathing crack identification[J].Journal of intelligent material systems and structures, 2018,29(10):2249-2266.
[26] 胡家顺,冯新,周晶.呼吸裂纹梁非线性动力特性研究[J].振动与冲击,2009,28(1):6.
[27] AL-HABABI T,ALKAYEM N F,ZHU H,et al.Effective identification and localization of single and multiple breathing cracks in beams under gaussian excitation using time-domain analysis[J].Mathematics,2022,10(11):1853.
[28] CAO M,LU Q,SU Z,et al.A nonlinearity-sensitive approach for detection of “breathing” cracks relying on energy modulation effect[J].Journal of Sound and Vibration,2022,524:116754.