Research On Acquisition And Processing Of Acoustic Emission Signal For 7N01 Aluminum Alloy Fragmentation

The safe operation of railway trains is related to people's lives and property. And with the growth of the train speed, it makes a higher demand of the nondestructive testing of trains. The real time online monitoring in operating conditions of railway trains becomes the development trend of the modern non-destructive testing. Because acoustic emission detection technology can detect active defects, it has been widely used in various instruments and equipment on line. Based on the background, the subject use acoustic emission detection technology to research the bending deformation behavior of 7N01 aluminum alloy, using on railway train. The subject trys to describe the changing discipline of acoustic emission signals in the different deformation stages of aluminum alloy.First, this paper established a aluminum alloy acoustic emission signal acquisition system. The three-point bending was adopted, and loading program is determined too. We discuss the setteing of parameters of the acoustic emission signal acquisition system, and make detailed introduction about the preparation work of the experiment. This paper also determine the bending deformation of acoustic emission signals of the aluminum alloy test piece and the prefabricated gap test piece, and confirm the noise signal acquisition program under the laboratory conditions.With parameters analysis and related analysis methods, this paper analyzed the characters of acoustic emission signals in different bending deformation stages of the 7N01 aluminum alloy base metal test piece and the prefabricated gap test piece. And explained the distribution rules of signal amplitude and energy's characteristic parameters theoretically, according to related acoustic emission source mechanisms. The researches find that energy with counts and duration is most relevant, which are approximately linear correlated. They are least relevant with rising time, or even negative correlated. The correlation with magnitude is between the two.In this paper, we use wavelet package to make 3-layers'decomposition and reconstruction of the acoustic emission signal waveforms, calculate the energy of eight sub-bands reconstructed signals, construct and extract the feature vector based on energy elements, and analyze the eight sub-bands reconstructed signals'energy distribution of acoustic emission signals of the aluminum alloy in different deformation stages. The results find that with the increase of deformation, the trend of signal's frequency components is from lower frequency to higer ones.