A Reference Matching-Based Temperature Compensation Method for Ultrasonic Guided Wave Signals

The ultrasonic guided wave-based structural damage diagnosis method has broad application prospects in different fields. However, some environmental factors such as temperature and loads will significantly affect the monitoring results. In this paper, a reference matching-based temperature compensation for ultrasonic guided wave signals is proposed to eliminate the effect of temperature. Firstly, the guided wave signals measured at different temperatures are used as reference signals to establish the relationship between the features of the reference signals and temperature. Then the matching algorithm based on Gabor function is used to establish the relationship between the amplitude influence coefficient obtained by the reference signal and the corresponding temperature. Finally, through these two relationships, the values of the phase and amplitude influence coefficients of the guided wave signals at other temperatures are obtained in a way of interpolation in order to reconstruct the compensation signals at the temperature. The effect of temperature on the amplitude and phase of the guided wave signal is eliminated. The proposed temperature compensation method is featured such that the compensation performance can be improved by multiple iteration compensation of the residual signal. The ultrasonic guided wave test results at different temperatures show that the first iterative compensation of the proposed method can achieve compensation within the temperature range greater than 7 °C, and the compensation within the temperature range greater than 18 °C can be achieved after three iterations.

[1]  A. Croxford,et al.  The influence of temperature variations on ultrasonic guided waves in anisotropic CFRP plates. , 2015, Ultrasonics.

[2]  Wieslaw J. Staszewski,et al.  Cointegration approach for temperature effect compensation in Lamb-wave-based damage detection , 2013 .

[3]  Keith Worden,et al.  Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data , 2011, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[4]  Keith Worden,et al.  A multiresolution approach to cointegration for enhanced SHM of structures under varying conditions – An exploratory study , 2014 .

[5]  Kuldeep Lonkar,et al.  A novel physics-based temperature compensation model for structural health monitoring using ultrasonic guided waves , 2014 .

[6]  Hoon Sohn,et al.  Effects of environmental and operational variability on structural health monitoring , 2007, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[7]  J. B. Harley,et al.  Scale transform signal processing for optimal ultrasonic temperature compensation , 2012, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  Krishnan Balasubramaniam,et al.  Structural health monitoring of composite structures using Lamb wave tomography , 2004 .

[9]  Xinlin Qing,et al.  Identification and Compensation Technique of Non-Uniform Temperature Field for Lamb Wave-and Multiple Sensors-Based Damage Detection , 2019, Sensors.

[10]  Yishou Wang,et al.  Validation and evaluation of damage identification using probability-based diagnostic imaging on a stiffened composite panel , 2015 .

[11]  P. Cawley,et al.  The use of Lamb waves for the long range inspection of large structures , 1996 .

[12]  Shenfang Yuan,et al.  A quantitative multidamage monitoring method for large-scale complex composite , 2013 .

[13]  J. Michaels,et al.  A methodology for structural health monitoring with diffuse ultrasonic waves in the presence of temperature variations. , 2005, Ultrasonics.

[14]  Hae Young Noh,et al.  Investigation on the Effects of Environmental and Operational Conditions (EOC) on Diffuse-Field Ultrasonic Guided-Waves in Pipes , 2014 .

[15]  Yinghui Lu,et al.  Numerical implementation of matching pursuit for the analysis of complex ultrasonic signals , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[16]  Jyrki Kullaa,et al.  Structural Health Monitoring under Nonlinear Environmental or Operational Influences , 2014 .

[17]  S. Salamone,et al.  Temperature effects in ultrasonic Lamb wave structural health monitoring systems. , 2008, The Journal of the Acoustical Society of America.

[18]  Gaëtan Kerschen,et al.  Structural damage diagnosis under varying environmental conditions—Part I: A linear analysis , 2005 .

[19]  Xinlin Qing,et al.  Piezoelectric Transducer-Based Structural Health Monitoring for Aircraft Applications , 2019, Sensors.

[20]  Zhong Lu,et al.  ON THE OPTIMIZATION OF TEMPERATURE COMPENSATION FOR GUIDED WAVE STRUCTURAL HEALTH MONITORING , 2010 .

[21]  Shenfang Yuan,et al.  An adaptive filter–based temperature compensation technique for structural health monitoring , 2014 .

[22]  Wieslaw J. Staszewski,et al.  Ultrasonic/Guided Waves for Structural Health Monitoring , 2005 .

[23]  Sang Jun Lee,et al.  COMPARISON OF THE EFFECTS OF APPLIED LOADS AND TEMPERATURE VARIATIONS ON GUIDED WAVE PROPAGATION , 2011 .

[24]  Jennifer E. Michaels,et al.  IMPACT OF APPLIED LOADS ON GUIDED WAVE STRUCTURAL HEALTH MONITORING , 2011 .

[25]  Du Chaoliang Lamb Wave High-resolution Damage Imaging Method Based on Non-dispersive Signal Construction , 2013 .

[26]  Christian Brauner,et al.  Non-damage-related influences on Lamb wave–based structural health monitoring of carbon fiber–reinforced plastic structures , 2014 .

[27]  Paul D. Wilcox,et al.  The temperature stability of guided wave structural health monitoring systems , 2006 .

[28]  Gaëtan Kerschen,et al.  Structural damage diagnosis under varying environmental conditions - Part II: local PCA for non-linear cases , 2005 .