Research On Ultrasonic Test Signal Processing Technology Of Thick-section Carbon Fiber Reinforced Composite

Thick-section carbon fiber reinforced composite has widely used in key structure of airplane and also other industries. Nondestructive test for thick-section carbon fiber reinforced composite has also obtain a fast development. Ultrasonic nondestructive test has attracted much attention because of its high efficiency and harmless to humans. In many occasions, defect signal of nondestructive test for thick-section carbon fiber reinforced composite will be influenced by noise signal, it has a bad effect for flaw evaluation. The main research contents in this paper is realizing the extraction of ultrasonic signal with the effect of noise and then conduct frequency analysis after extraction. Based on the national natural science foundation project, the provincial science foundation project and the doctoral foundation project, several techniques were studied in this paper.In chapter 1,different defect types, nondestructive test techniques and porosity testing technology were discussed. Moreover, the significance of doing research on blind source separation and all-phase frequency was pointed out. Finally, the research background and chapters arrangement were introduced.In chapter 2, the basic principle of ultrasonic impulse reflection test were introduced, and a model of ideal defect-free thick-section carbon fiber reinforced composite was built and analyzed with time-frequency technique. The component analysis of backscattered signal was presented to support the necessity of research in this paper.In chapter 3, basic theory about blind source separation algorithm was studied, it was a foundation for blind source separation being used in signal processing of ultrasonic nondestructive test. The mathematical model of blind source separation was built, and basic theory analysis was showed. Then a algorithm based on minimization of mutual information was put forward, and algorithm performance was evaluated by simulation experiment. Finally, an optimization algorithm was presented, and it was proved with a batter algorithm performance.In chapter 4, combined with the optimization algorithm, the extractive technique of ultrasonic test signal was discussed. The ultrasonic inspection system was introduced, and the algorithm performance about recognition capability of ultrasonic test signal was tested. Combined with phase space reconstruction, blind source separation optimization algorithm and hurst parameter, isolated component of ultrasonic test signal was extracted, finally, isolated component of ultrasonic test signal was rebuilt into a denoising ultrasonic test signal.In chapter 5, based on ultrasonic test signal of thick-section carbon fiber reinforced composite, all-phase frequency analysis was studied. Firstly, the most important theory of all-phase frequency analysis was recommend, and compared the performance of data preprocessing with traditional FFT through simulation experiment. Then conducted simulation experiments of single frequency component and multi-frequency components to test the performance of apFFT algorithm, and spectrum correction with all-phase time-shifting phase difference method was studied. Finally, conducted simulation experiments of signal which contained weak signal, realized the weak signal detection, and the experiments of ultrasonic nondestructive test signal proved that apFFT algorithm recognized a plentiful components than traditional FFT algorithm.In chapter 6, main results and conclusions of this dissertation were systematically summarized, and the prospects and the future research work were discussed and forecast.