Extraction And Identification Of Ultrasonic Echo Signal Characteristics Of Metal Materials

The exploitation and utilization of metal mineral resources guarantee the development of modern industry.With increasing use of metal materials,once fake and inferior products appear,it will have a very serious impact on industrial production and life safety,so the quality inspection of metal materials is very important.Ultrasonic detection technology is widely used in engineering due to its strong penetration,non-contact,harmless to materials and human body,easy to operate and so on,which is called "green nondestructive testing technology".Ultrasonic detection relay on the interaction of ultrasonic wave and the sample,and then to measure the reflection,transmission and scattering of echo and other related parameters,so that achieve the defect detection of metal materials,parameter measurement,structure and mechanical properties characterization,and so on.In this thesis,single probe and phased array ultrasonic probe are used to collect ultrasonic echo of metal material,and the feature is extracted by the algorithm of signal processing to realize the identification of metal material.The main work and innovations of this thesis are as follows:1 According to the requirements of metal material detection in engineering,ultrasonic pulse transmitting/receiving system and phased array echo signal acquisition system are used to extract the ultrasonic echo signal of the sample,calculate are the echo signal of metal material by the weighted Euclidean distance and correlation function,so it realize the identification of metal material.The results show the standard sample material can be identified quickly and accurately,it can calculated the metal material echo signal by the weighted Euclidean distance and correlation function.2 Using ultrasonic pulse transmitting/receiving system and phased array system,the echo signals of four kinds of similar metal materials are collected respectively,and the ultrasonic echo signals of similar metal materials are decomposed by EMD,and the generalized phase permutation entropy of the characteristic decomposition component(Intrinsic Mode Function,IMF)is calculated.Finally,the most significant difference characteristic quantity is found as the parameter of material identification.By calculating the entropy information of instantaneous phase of each characteristic decomposition component of echo signal,the generalized phase permutation entropy can amplify the slight difference between similar metal materials according to the adjustment of parameter q and ?.3 Using the feature which is reconstructed components of the ultrasonic echo signal by calculating generalized phase permutation entropy,it can clustered and analyzed the feature by the KNN and KSVM algorithm respectively,and then draw the cluster scatter plot.Finally,we calculated and compared the classification accuracy of the two algorithms.The result show that the accuracy of KSVM clustering is higher than 99.1%,and KSVM has better detection performance for the identification of similar materials.The research results will provide a way for quality inspection,defective identification and classification of metal materials with similar properties.