Research On The Technology Of CFRP Laminate Defect And Fiber Orientation Detection Using Infrared Thermal Wave Radar Imaging

Carbon fiber reinforced polymer(CFRP) has the merits of high-specific strength, high-specific modulus and anti-fatigue performances, which lead to the wide application of CFRP in the fields of aircraft, aerospace, petrochemical, automotive and military industries. However, many defects(i.e. porosity, impact damage, fiber breakage and delamination) are usually exhibited during the fabrication of CFRP laminate, which directly affect the CFRP laminate properties. Meanwhile, lay-up orientation errors of CFRP laminates readily appear during the artificial stacking process, which influence the mechanical performance of CFRP laminate. Therefore, it is necessary to find a relative simple, effective and fast non-destructive testing and evaluation(NDT&E) technique which meets the demand for the CFRP laminates with subsurface defect detection and fiber lay-up orientation inspection during the fabrication and service process. Infrared thermal wave radar imaging(IR-TWRI) methodology combines thermal wave imaging and linear frequency modulated radar detection, it has the merits of strong anti-interference, dynamic depth-revolution detection, high sensitivity and large thermal wave bandwidth, which apparently improves the signal-noise-ratio(SNR) of thermal wave signal. IR-TWRI is a new kind of infrared thermography, which provides a novel NDT&E approach for the CFRP laminate with subsurface defect detection and fiber lay-up orientation measurement. Therefore, the corresponding methodologies and techniques were deeply studies, which has been presented as followings.Firstly, the heat diffusion and temperature distribution of CFRP laminate has been investigated through numerical simulation, which the Chirp heat flux was loaded on the surface of CFRP laminate sample. The response features of thermal wave radar signal(TWRS) in time-frequency domain were obtained and analyzed by finite element analysis(FEA), and then, the TWRS characteristics were derived and extracted by the proposed algorithms which were named the Hilbert transform transient time domain integration(HTT-TDI) and dual chirp lock-in correlation(Chirp Lock-in).Secondly, the effects of test parameters and defect geometry size on the TWRS characteristic were studied by numerical simulation. The feasibility of fiber lay-up orientation measurement using IR-TWRI was discussed, and FEA was simultaneously used to analyze the effects of testing parameters and fiber lay-up orientations on the TWRS characteristics distribution, which provides the theoretical foundation for the experimental investigations.Subsequently, an IR-TWRI system with a laser as the excitation source was developed, which can be employed for the efficient and reliable inspections of the subsurface defects and fiber lay-up orientation of CFRP laminate. The effects of testing parameters, defect geometry size and fiber lay-up orientation on TWRS response characteristics were deeply studied by experiments and the advantages of the proposed algorithms for TWRS characteristic(Cross-correlation, HTT-TDI and Chirp Lock-in) extraction were obtained, these were used to verify the validation of numerical analysis. In additional, the reasonable range of testing parameters selection was derived from these experimental investigations.Next, based on the reliability analysis theory and methodologies for NDT&E, the relevant investigations on probability of detection(POD) of IR-TWRI for CFRP laminate subsurface defect inspection were conducted, and the defect determination criteria was proposed based on the feature distributions of TWRS. The effects of testing parameters and TWRS characteristic extraction algorithms on POD level was investigated, and the POD data of IR-TWRI for CFRP laminate subsurface defect were obtained with the different defect detection threshold levels, which strongly offered a significant support for the engineering application.Finally, the quantitative identification of the subsurface defect and fiber lay-up orientation using IR-TWRI were researched, and an inverse heat transfer approach was proposed to estimate the subsurface defect size and fiber lay-up orientation of CFRP laminate by combining the numerical optimization into the finite element model updating. In order to improve the ill-posed problem in the optimization process, a hybrid algorithm combining simulated annealing(SA) algorithm and Nelder-mead simplex search algorithm(NM) was proposed to quickly and precisely identify the defect diameter and depth, and the maximum estimation errors for the defect diameter and depth were less than 6% for artificial internal laminate defects with diameter of 8.0 to 12.0, and depth of 0.6 mm to 2.0 mm. The exploratory investigations on the identification of fiber lay-up orientation were performed on the CFRP laminate samples to demonstrate the feasibility of the proposed method. The results present that the proposed method can be used to quantitatively identify the fiber lay-up orientation of the 7 layer CFRP laminate, and the maximum prediction error of each lay-up orientation angle is less than 6 degrees.