Identification Of Tiny Metal Defects Based On Chaotic Dynamics

With the rapid development of modern industry,the application field of metal parts is more and more extensive.he service life and quality of metal parts are much concerned,especially in modern machinery and defense products,such as large industrial equipment,aircraft and weapons.Due to the impact factors of industrial equipment,production conditions and industrial materials,there are always defects inside or on the surface of metal materials.Furthermore,the fatigue damage is caused under the condition of high temperature,high pressure and corrosion.S Thus detection of surface or subsurface defects for metal parts is very important to effectively prevent industrial injury and casualties.In this paper,advantages and disadvantages of the nondestructive testing technologies are compared,a suitable array eddy current detection technology is chosen.The key problems of detection technique is studied.The main research is as follows:1.Because the speed and accuracy of eddy current testing with single sensor is restricted,Six-coil array sensor is designed.The adjacent excitation strategy is used.As a result,the impact on electromagnetic field caused by small defects from multi views can be detected.The distribution of the electromagnetic field is simulated by COMSOL Multiphysics.The parameters of sensitivity and spatial resolution are analyzed to optimize the sensor design.The new sensor array have higher sensitivity,compared with the traditional sensors.2.The information of defects cannot be identified directly from one-dimensional eddy current signal.In this paper,chaotic dynamics method is proposed to analyze the eddy current signal.In order to recover the Inherent law of the eddy current system,the signal of one-dimensional eddy current is transformed to multi-dimensional one based on based on phase space reconstruction.Then the largest Lyapunov exponent,K entropy and correlation dimension are used to reveal the chaotic dynamics of eddy current signal.3.In this paper,eddy current signal with different size,depth and shape of defect detection method based on entropy algorithm is proposed.In order to improve the sensitivity of the sensor to the local area of the electromagnetic field,The eddy current signal is focused through the window function.The size and shape of the flaws are identified by analyzing complexity of the measured signal with the aid of phase space,approximate entropy and fuzzy entropy method.The results show that the entropy,i.e.the complexity,of eddy current signal is increased with the growth of flaw size.Furthermore,different shapes of the flaws can the effectively distinguished by the profile of mean fuzzy entropy.