Research On Optimization And Improvement Of TFM For Welding Joint Detection

Total focusing method(TFM)is a cutting-edge array ultrasonic imaging detection method.Compared with traditional phased array imaging,TFM has higher defect imaging ability.However,there are two problems when TFM is used to detect the weld with reinforcement.First,the smaller the mesh division of TFM imaging,the higher the imaging resolution,but at the same time,the greater the amount of path reconstruction calculation.In particular,the oblique incidence method used in weld detection involves the calculation of sound beam path in layered medium,the complexity of the algorithm is high,and the contradiction between imaging accuracy and operation efficiency is more prominent;How to further improve the efficiency of the algorithm and calculate the sound beam path faster on the premise of maintaining the accuracy is the technical difficulty of TFM application.Second,TFM usually adopts the method of one transmitter and multiple receivers to collect signals.Due to the small aperture of the array element and weak excitation energy,especially in the process of weld detection,the collected array signals are vulnerable to tissue noise and process disturbance,resulting in the decline of signalto-noise ratio,which affects the image quality;How to combine array signal characteristics,TFM algorithm and signal processing technology to improve signal quality and realize higher precision and higher resolution imaging detection is one of the keys to realize the advantages of TFM technology in weld detection.Aiming at the problem of path reconstruction of oblique incidence TFM imaging,firstly,the acoustic path model of oblique incidence detection is established in this study,and the solution of interface refraction point is expressed as the solution of univariate quartic equation;Secondly,considering the approximate solution conditions in digital system,the applicability of Matrix Solving Method(MSM)and iterative method(including Two Section Method and Secant Method)to this problem is analyzed;Finally,several examples are used to compare the computational efficiency and accuracy of MSM and Secant Method,and an oblique incidence TFM algorithm(TFM-MSM)based on MSM is established.In this paper,the finite element method is used to simulate the Full Matrix Capture(FMC)data acquisition process,and the TFM-MSM algorithm is used for imaging.The results show that the algorithm can meet the positioning and quantitative requirements on the premise of high efficiency.Aiming at the problem that the decline of signal-to-noise ratio of FMC signal in TFM for weld detection affects the imaging quality,this study combined with the characteristics of ultrasonic array signal,introduces parameters such as Coherence Factor(CF),Generalized Coherence Factor(GCF)and Sign Coherence factor(SCF)as the weighting coefficients of signal adaptive filtering to form different filtering algorithms,which are combined with the above TFM-MSM imaging algorithm,Several oblique incidence TFM algorithms based on adaptive weighting are proposed: TFM-CF,TFM-GCF and TFMSCF.In order to quantitatively characterize the imaging quality,this study proposes to use the Full-width at Half-maximum(FWHM)of the target energy change curve and image contrast(CR)to quantitatively evaluate the resolution and discrimination of imaging respectively.A series of validation experiments such as simulation experiment,standard test block experiment and simulation test block experiment are carried out,and the imaging quality is compared and analyzed by using quantitative parameters.The results show that the imaging quality obtained by the adaptive weighting algorithm is significantly improved compared with the original TFM,achieves the effect of suppressing sidelobe and removing noise,and the imaging resolution and contrast are improved.Among them,the comprehensive performance of TFM-SCF algorithm is the best.In addition,the simulation test block detection experiment shows that the adaptive weighting algorithm can enhance the imaging of typical defects,make the characteristics of defects clearer,and help to identify and interpret defects.To sum up,the TFM algorithm based on MSM and adaptive weighting of SCF can improve the imaging efficiency and imaging quality of the TFM.Combining this algorithm with appropriate hardware can not only solve the problem of oblique incidence TFM for weld detection,but also have a wide application potential in other application fields.