Surface Crack Detection And Quantitative Evaluation Based On Eddy Current Pulsed Thermography

Nondestructive Testing (NDT) plays a significant role in the product quality assurance and equipment safety. The existence of crack usually leads to brittle fracture of material or component, causing catastrophic accidents and huge losses. Therefore, it is important to detect the crack. Because of the complex structure of component or device, the crack is too small to inspect, and the actual testing environment is complex.These problems make nondestructive testing technology faces many challenges. Eddy Current Pulsed Thermography (ECPT) has an increasing span of application with capabilities of rapid contactless and large surface area detection. As for ECPT, there are some achievements, however the research on the quantitative evaluation and error analysis of the defect are not thorough, which hinder the application of thermal imaging nondestructive testing technology in industry. Based on ECPT, the paper discusses the temperature distribution characteristics for the surface crack, and compares different thermal feature extraction methods. Furthermore, the quantitative evaluation is implemented to obtain objective judgment basis, which aids in providing the guidance for the crack quantitative detection.The main contents of this paper are as follows: 1) Based on ECPT, diverse thermal information of the crack tip and bottom from different size surface cracks are discussed and verified by simulation and experiment, and the temperature distribution characteristics are discussed in detail. Furthermore, this insight directly offers a guide for assessing .the detectability of different thermal feature extraction methods. 2) The commonly used thermal feature extraction methods are comprehensively evaluated, i.e.Pulsed Phase Thermography, Normalized Contrast, Thermographic Signal Reconstruction, Independent Component Analysis and Principle Component Analysis.The evaluation index F-Score is used to analyze and compare the detectability of different methods. The results show that better detection performance from Independent Component Analysis, which is able to effectively suppress the disturbance, enhance the defect information, and obtain high quality defect identification. These conclusions can provide objective choice basis for different thermal feature extraction methods. 3) The iterative threshold image segmentation method based on the histogram is proposed to segment crack defect in the thermal image. Furthermore, a large number of simulations and experiments are performed to verify the reliability and accuracy of the proposed method. Moreover, the processing programme of thermal image from pretreatment, post processing to quantitative evaluation are proposed in order to carry on the defect quantitative detection and evaluation, which provides a new idea for nondestructive testing and life evaluation of surface crack. In addition, the paper proposes a image segmentation method based on the genetic algorithm and the first order statistical properties of thermal image to select threshold automatically, which is able to effectively remove noise and other interference, and accurately separate the defects from the background. Moreover, other commonly used segmentation algorithms are compared with the proposed method, the results show that the proposed algorithm has better performance.