Mode identification of broadband Lamb wave signal with squeezed wavelet transform

Wang, Shen; Huang, Songling; Wang, Qing; Zhang, Yu; Zhao, Wei

doi:10.1016/j.apacoust.2017.04.014

Cited by 26 publications

(14 citation statements)

References 18 publications

(17 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…g(θ, τ )e −j2π(θt+f τ −uθ) dudτ dθ (7) where z(t) is the analytic signal, u is variable of integration, τ is the time-shift or lag, θ is the frequency-shift or Doppler and g(θ, τ ) is the kernel function or parameterization function. If g(θ, τ ) = 1, then the distribution becomes WD.…”

Section: Methods Of Mode Identification a Instantaneous Frequencymentioning

confidence: 99%

See 1 more Smart Citation

Multimodal Lamb Wave Identification Using Combination of Instantaneous Frequency with EMD

Wang

Huang

Sun

et al. 2019

2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

Self Cite

View full text Add to dashboard Cite

Lamb wave is guided plate wave that has potential in industrial inspection for non-destructive evaluation. However, the multimodal nature of Lamb wave obstructs the extraction and interpretation of information in signal. This work proposes a Lamb wave mode identification method combining instantaneous frequency (IF) with empirical mode decomposition (EMD). Firstly, EMD is implemented on multimodal signal and separates it into individual mode functions. Then the individual functions are analyzed by high-resolution time-frequency distribution. Finally, IF curve is obtained in the time-frequency domain and corresponding time information is used to calculate wave velocity. Lamb wave mode is determined by comparing the wave velocity with theoretical value. To verify the effectiveness of the proposed method, simulation presents the situation of boundary reflection and experiment presents the mode conversion by defect. Both simulation and experiment demonstrate the good performance of the mode identification method.

show abstract

Section: Methods Of Mode Identification a Instantaneous Frequencymentioning

confidence: 99%

“…The empirical mode decomposition (EMD) based short time Fourier transform to extract TOF was proposed to recognize overlapped Lamb wave [6]. The squeezed wavelet transform was applied to analyze the simulated broadband Lamb wave signal and the advantage of this transform was the ability of signal reconstruction [7].…”

Section: Introductionmentioning

confidence: 99%

Multimodal Lamb Wave Identification Using Combination of Instantaneous Frequency with EMD

Wang

Huang

Sun

et al. 2019

2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

Self Cite

View full text Add to dashboard Cite

show abstract

“…9(a): u same (black line) is almost superposed on the top and bottom signals (dashed lines). The error calculated in (14) is plotted in Fig. 9(b) (black line), showing that for small misalignments, the error on selecting the same polarisation is much lower than for the opposite polarisation.…”

Section: B Transducer Alignment and Mismatch Errormentioning

confidence: 99%

“…In this case when no mode conversion occurs, the cosine that modulates u same should be identically unity when there is no misalignment; consequently, E same should be null. Comparing (14) and (12), one may see that…”

Section: B Transducer Alignment and Mismatch Errormentioning

confidence: 99%

Mode Selectivity of SH Guided Waves by Dual Excitation and Reception Applied to Mode Conversion Analysis

Kubrusly

Freitas

Weid

et al. 2018

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

View full text Add to dashboard Cite

Shear horizontally (SH) guided waves, generated by periodic permanent magnet arrays, have been used previously in nondestructive evaluation of metal plates and pipes. When an SH guided wave interacts with a defect or a change in sample thickness, the incident SH wave may undergo mode conversion. Analysis of mode conversion is complicated, due to the interference of several propagating modes in the received signal that can often temporally overlap. This paper proposes a mode selection technique to help understand the interaction of SH guided waves with changes in sample thickness. Using an understanding of the propagation characteristics of the guided waves, SH guided waves are sequentially generated and detected on both surfaces of the plate, capturing four distinct waveforms. By superposition of the detected signals, symmetric modes can be clearly separated from antisymmetric modes in the processed received signals. For this method to work well, the transducers used should have very similar responses and be precisely positioned on exactly opposite positions either side of the plate. Finite element simulations are also performed, mirroring the experimental measurements, and the results correlate well with the experimental observations made on an 8-mm-thick plate with a region of simulated wall thinning machined into the sample.

show abstract

“…In particular, the time-domain analyses have been used extensively, such as the least-squares method [1,2], Monte Carlo method [3][4][5], and filtering methods [6][7][8]. Besides, the methods of wavelet analysis [9][10][11] and Hilbert-Huang transform [12][13][14], in which the vibration signals are decomposed into the frequency/time-domain signals, have also received much attention.…”

Section: Introductionmentioning

confidence: 99%

Parameter Identification for Structural Health Monitoring with Extended Kalman Filter Considering Integration and Noise Effect

et al. 2018

View full text Add to dashboard Cite

Since physical parameters are much more sensitive than modal parameters, structural parameter identification with an extended Kalman filter (EKF) has received extensive attention in structural health monitoring for civil engineering structures. In this paper, EKF-based parameter identification technique is studied with numerical and experimental approaches. A four-degree-of-freedom (4-DOF) system is simulated and analyzed as an example. Different integration methods are examined and their influence to the final identification results of the structural stiffness and damping is also studied. Furthermore, the effect of different kinds of noise is studied as well. Identification results show that the convergence speed and estimation accuracy under Gaussian noises are better than those under non-Gaussian noises. Finally, experiments with a five-story steel frame are conducted to verify the damage identification capacity of the EKF. The results show that stiffness with different damage degrees can be identified effectively, which indicates that the EKF is capable of being applied for damage identification and health monitoring for civil engineering structures.

show abstract

Mode identification of broadband Lamb wave signal with squeezed wavelet transform

Cited by 26 publications

References 18 publications

Multimodal Lamb Wave Identification Using Combination of Instantaneous Frequency with EMD

Multimodal Lamb Wave Identification Using Combination of Instantaneous Frequency with EMD

Mode Selectivity of SH Guided Waves by Dual Excitation and Reception Applied to Mode Conversion Analysis

Parameter Identification for Structural Health Monitoring with Extended Kalman Filter Considering Integration and Noise Effect

Contact Info

Product

Resources

About