Signal Processing Method And Algorithm For Improving Accuracy Of Immersion Ultrasonic Thickness Measurement And Flaw Detection Of Steel Pipe

The application of steel pipes is extensive,and it is of great significance to carry out strict quality inspection.In engineering applications,the coherent noise generated by the scattering of ultrasonic waves from the rough surface of the steel pipe will lead to misjudgment of the defects.The vibration of the steel pipe is the cause of increase of the echo side lobes due to the eccentricity of the probe center,and the waveform distortion lead to the increase of the thickness measurement error.Blind zone near the surface in delamination detection,will lead to missed detection of defects,affecting the reliability of detection.Consequently,this paper starts from the post-processing of acoustic signals,and systematically studies the noise reduction,high-precision calculation of time of flight and near-surface delamination signal extraction algorithm for steel pipe water immersion ultrasonic detection signals.A coherent noise suppression method based on spatial domain correlation filtering of complex analytic signal singular value decomposition CASVD is proposed to avoid misjudgment caused by coherent noise.The method is based on the difference between the coherent noise and the feature components of the target signal in the spatial domain.It is an improvement of the singular value decomposition algorithm for real-domain phase space reconstruction.Aiming at the problem that the range of effective singular values of existing algorithms is difficult to determine,a method for phase space reconstruction of complex analytic signals is proposed.The number of effective singular values is reduced,which reduces the randomness of traditional singular value decomposition in determining effective singular values.It has been proven to be able to identify the target signal in strong noise.In order to improve the accuracy and stability of dynamic thickness measurement,a segmented Fourier-Wavelet deconvolution SFWD algorithm is proposed to suppress the sidelobe caused by the eccentricity of the probe.Through the acoustic reflection and refraction laws,the acoustic path of the ultrasonic wave in the water coupling layer and the steel pipe is studied,and the causes of error are analyzed.Aiming at solving the insufficiency of the local time-frequency analysis ability of the existing Wiener filtering,the framing processing method of the ultrasonic A-scan signal is proposed,and the coefficient shrinkage of the two transform domains in the Fourier and wavelet domains is suppressed,which improves the accuracy of thickness measurement.In order to reduce the near-surface blind zone,an extrapolation method based on phase spectrum is proposed.Aiming at relieving the echo aliasing generated by the interface and delamination of steel pipe,the relationship between the blind zone and the time resolution of ultrasonic A-scan signals was studied.In view of the problem that the existing spectrum extrapolation method is greatly affected by noise,the phase spectrum is used for AR modeling to extrapolate the low frequency and high frequency spectrum.In order to adapt to different noise levels,Kalman filtering method is proposed for adaptive filtering,which effectively reduces the blind zone of the near surface region.In the engineering practice of steel pipe ultrasonic thickness measurement,a tracking gate algorithm for dynamic thickness measurement was invented,which relieved the thickness error caused by changes of probe lift-off.Based on the above various algorithms and related process requirements,the steel pipe water immersion ultrasonic testing software was developed.