Analysis Of Acoustic Emission Signals In Grinding Of Engineering Ceramics

Nowadays grinding is the primary mechanical processing method of engineering ceramics,but the efficiency and processing quality of engineering ceramics grinding technology still need to be improved.Besides,the processing cost is too high,which limits the application of engineering ceramics to a great extent.In order to improve the grinding technology of engineering ceramics,real-time online monitoring of the grinding process has become an important research subject.It has been more than 30 years since the acoustic emission technology was introduced into the field of grinding,and the research on grinding acoustic emission monitoring has yielded many achievements,which greatly promotes the efficiency,precision and automation of grinding processing.Therefore,the intelligent monitoring system of grinding based on acoustic emission technology has become an inevitable trend in the development of grinding technology.Firstly,the material properties of engineering ceramics are briefly introduced,and the influences of molding methods and crystal structure are analyzed as well.The characteristics of engineering ceramics general grinding and the advantages of three new grinding methods are introduced.The research and related progress of grinding applying with acoustic emission technology are illustrated.Secondly,the basic theories of acoustic emission,including the primary concepts,detection principles and analysis methods,are outlined.An experimental platform for acoustic emission monitoring engineering ceramic grinding is set up.The experimental objects are mainly Partially Stabilized Zirconia ceramics and Alumina ceramics.And the experimental scheme is designed.Thirdly,the influencing factors of grinding force and grinding temperature in the grinding process of engineering ceramics are discussed.Based on the analysis of acoustic emission signals of engineering ceramics grinding,the effects of grinding depth and feed speed on acoustic emission are discussed.Combining the empirical values of grinding force and grinding temperature with the analysis results of acoustic emission signals,the mathematical model of the root mean square(abbreviated RMS)of acoustic emission signals and grinding force as well as RMS and grinding temperature is established.Furthermore,the relationship of acoustic emission,grinding force and grinding temperature of engineering ceramics is discussed.The waveform feature parameter correlation analysis method,spectrum analysis method and wavelet packet analysis method are adopted to analyze the frequency characteristics and energy distribution of the acoustic emission signals in detail.Finally,the wavelet packet energy spectrum coefficients are taken as the input to establish the classification model of engineering ceramics by Support Vector Machine applying with the Genetic Algorithm optimization.The accuracy rate of recognition reaches 100%.