The Development Of Eddy Current Testing System Based On GMR And Research On Reliability Of Deep-Seated Flaws Detection

Inspection of defects deeply buried in multi-layered conductive structures is a complex and urgent problem to tackle in a number of industries ranging from aerospace industry to nuclear and petrochemical engineerings. Based on the principle of low-frequency Eddy Current Testing (ECT), the experimental ECT scanning system using Giant Magneto-Resistance (GMR) sensors and the reliability of inspection of deep flaws using Probability of Detection (POD) theory and Taguchi method are studied. The main work and innovations of the thesis are as follows:1 The exciting frequency must be decreased for the sake of inspecting deep-seated flaws due to the skin-effect of eddy currents. Firstly, the GMR based ECT probe is developed. Then the automatic compensation method for zero potential of the GMR eddy current probe is studied. The experimental results show that the GMR based probe has higher sensitivity and detection ability for deep-seated flaws than the coil-type probe.2 The Probability of Detection (POD) theory is introduced to evaluate the reliability of ECT. The process for building the model of POD is described in detail, especially the POD modeling based on the function model method. The application shows that the reliability of inspection can be efficiently evaluated.3 The Taguchi method is studied for optimizing the experimental design to improve the reliability in deep-seated flaws detection in eddy current testing. The experimental results indicate that all the factors which affect the experiments are determined and their influences can be evaluated using this method. The optimum parameters can be found with the Taguchi method, and the reliability is improved effectively.The probe based on GMR and automatic compensation for zero potential improve the detection ability for deep-seated flaws, the reliability of inspection can be efficiently evaluated by POD, the Taguchi method improves the reliability in deep-seated flaws detection.