基于状态空间特征提取的微裂纹定量检测
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摘要
非线性超声法对机械结构微裂纹检测的敏感性与有效性较好,但传统非线性超声法一般不能实现微裂纹定量检测。针对此问题,提出一种针对微裂纹的定量检测方法,通过提取裂纹引发的构件状态空间改变量以对裂纹进行识别、定量检测。该方法采用激光束与待测构件相互作用激发超声波,对其时域响应信号重构表征构件动态特性的状态空间,提取非线性特征参数巴氏距离(bhattacharyya distance,简称BD)对状态空间变量进行分析以对裂纹进行识别,进而利用扫描法实现裂纹的定量检测。通过对铝合金表面不同类型微裂纹的检测实验,验证了该方法对构件表面微裂纹定量检测的有效性。
The sensitivity of nonlinear ultrasonic features to small crack is recognized much higher than what can be achieved by conventional linear features.However,in most of cases,the conventional nonlinear ultrasonic features can only locate the crack but difficult to quantify.In this paper,a novel technique for the quantification detection of small crack is presented.The structure needing to be detected is radiated by laser to produce a nonlinear ultrasound and its state space predictive model is constructed based on its dynamical responses in time domain.Then the Bhattacharyya Distance is adopted as the quantification metric to detect the crack.Furthermore,the crack is quantified using the feature extracted from the entire scanned area.An example of the approach and experimental measurement is given for alloys with different kinds of cracks.The experimental results show the reliability of the approach.
The sensitivity of nonlinear ultrasonic features to small crack is recognized much higher than what can be achieved by conventional linear features.However,in most of cases,the conventional nonlinear ultrasonic features can only locate the crack but difficult to quantify.In this paper,a novel technique for the quantification detection of small crack is presented.The structure needing to be detected is radiated by laser to produce a nonlinear ultrasound and its state space predictive model is constructed based on its dynamical responses in time domain.Then the Bhattacharyya Distance is adopted as the quantification metric to detect the crack.Furthermore,the crack is quantified using the feature extracted from the entire scanned area.An example of the approach and experimental measurement is given for alloys with different kinds of cracks.The experimental results show the reliability of the approach.
引文
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[2]王芝,吴维亮,肖黎,等.闭合型疲劳裂纹的亚谐波损伤识别方法[J].振动工程学报,2015,28(4):567-573.Wang Zhi,Wu Weiliang,Xiao li,et al.Damage detection for closed fatigue crack using sub-harmonic component[J].Journal of Vibration Engineering,2015,28(4):567-573.(in Chinese)
[3]李拯,吴维亮,屈文忠,等.基于非线性超声调制的疲劳裂纹识别方法[J].中国机械工程,2015,26(17):2384-2388.Li Zheng,Wu Weiliang,Qu Wenzhong,et al.Fatigue crack detection using nonlinear ultrasonic modulation method[J].China Mechanical Engineering,2015,26(17):2384-2388.(in Chinese)
[4]屈文忠,李拯,王芝,等.基于非线性超声调制方法的损伤识别与定位[J].振动、测试与诊断,2016,36(5):852-857.Qu Wenzhong,Li Zheng,Wang Zhi,et al.Damage detection and localization using nonlinear ultrasonic modulation method[J].Journal of Vibration,Measurement&Diagnosis,2016,36(5):852-857.(in Chinese)
[5]Jiao Jingpin,LüHongtao,He Cunfu,et al.Fatigue crack evaluation using the non-collinear wave mixing technique[J].Smart Materials&Structures,2017,26(6):065005.
[6]Singh A K,Chen B Y,Tan V B C,et al.Finite element modeling of nonlinear acoustics ultrasonics for the detection of closed delaminations in composites[J].Ultrasonic,2017,74:89-98.
[7]Liu P P,Hoon S,Byeongjin P.Baseline-free damage visualization using noncontact laser nonlinear ultrasonics and state space geometrical changes[J].Smart Materials and Structures,2015,24(6):1-13.
[8]Nichols J M.Structural health monitoring of offshore structures using ambient excitation[J].Applied Ocean Research,2003,25(3):101-114.
[9]Nichols J M.Using state space predictive modeling with chaotic interrogation in detecting joint preload loss in a frame structure experiment[J].Smart Materials&Structures,2003,12(4):580-601.
[10]Gang Liu,Zhu Mao,Michael T,et al.Localizaiton of nonlinear damage using state-space-based predictions under stochastic excitation[J].Smart Materials&Structures,2014,23(2):1-14.
[11]Taken F.Detecting strange attractors in turbulence dynamical systems and turbulence[M].Berlin:Springer,1980:366-381.
[12]Raser A M,Swinney H L.Independent coordinates for strange attractors from mutual information[J].Physical Review A,1986,33(2):1134-1140.
[13]Cao L.Practical method for determining the minimum embedding dimension of a scalar time series[J].Physica D:Nonlinear Phenomena,1997,110(1-2):43-50.
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