| Natural diamond tool with high edge quality is important for ultra-precision manufacturing technology, and takes a great role in precision manufacturing process of many critical devices in high-tech areas. However, general quality of diamond tool made by domestic companies is still lower than expected and precision diamond tool imported from foreigner countries often cost a lot and may be delivered in a long time. These problems put limitations on the development of our nation’s high-tech industry.Mechanical grinding is an important method to achieve diamond tool with high edge quality. It has shown in grinding experiences that Acoustic Emission(AE) signal, which produced in the grinding process, is so sensitive to crystal orientation of grinding surface on diamond tool and damage state of tool edge that can view as one of important assistant in grinding operation. Nevertheless, effective information implied in the AE signal is hard to recognize by traditional methods of signal processing. Operators would rather trust their own ears to perceive any change of heard signal empirically in application. Thus, research on mechanism means more to enhance automation level of diamond tool grinding process and to strengthen support of precision manufacturing technology.According to two basic technical requirements, which are crystal orientation identification of grinding tool surface and damage state identification of tool edge, this thesis reports researches on specific methods of AE signal processing and application of AE signal monitoring.The first is about research on mechanism of stimulating, transmitting and monitoring of AE signal in diamond tool grinding. Poisson Process model is adopted in analysis of stimulation of AE signal and illustrates how AE signal emerges and why sub-signal in high frequency band of AE signal has non-Gaussian features. In addition, Linear Time-invariant System theory is adopted in analysis of transmitting and monitoring process and illustrates why transmitting and monitoring process may not change such non-Gaussian features. Experiments also prove that the non-Gaussian feature is an inherent feature of AE signal in diamond tool grinding. These facts build an important foundation for subsequent research.The second is about research on relationship between feature parameters of AE signal and crystal orientation of grinding surface on diamond tool. Feature parameter vector is built and consists of five components, which are three low order statistics(Mean, Variance and RMS) to describe signal energy level and two high order statistics(Skewness and Kurtosis) to describe signal energy concentration level. It is analyzed how each component changes with grinding direction, and it finds that circular distribution of high order components have a symmetry character as same as crystal orientation of diamond material and other factors(grinding velocity & grinding pressure) will not affect such a relationship. Then, cluster analysis to monitored signal samples is carried out based on method of Self-organized Network(SOM) and two distinct clusters in high dimensional feature space, which are soft grinding direction cluster and hard grinding direction cluster, are found using improved visualization method. These methods may help to lower uncertainty in grinding direction adjusting in diamond tool grinding.The third is about research on relationship between feature parameters of AE signal and damage state of tool edge. Fractal dimension method is adopted to describe damage state of tool edge, and time series model is built to analyze sub-signal in frequency band of monitored AE signal. Based on high order cumulant method, parameters of time series model are estimated recursively. Moreover, relationship between tool edge damage state and signal model parameters is established after lots of experiments, and it is studied how other factors(grinding velocity & grinding pressure) affect such a relationship. These achievements may help to learn damage state of tool edge in a real time and can reduce chances secondary damage to tool edge because of repeated offline checking and iterating feeding.The final is about research on application method of AE signal monitoring in diamond tool grinding. Kinematics relationship of planetary spindle in diamond tool grinding machine is analyzed and automatic method of adjusting grinding direction is examined. Dynamic mechanism that grinding pressure acting on tool edge quality is analyzed and automatic method of controlling grinding pressure is examined. In addition, AE Signal Monitoring System is integrated into the Open Experiment Architecture of Diamond Tool Grinding. Based on these achievements, it will implement that automation of grinding direction adjusting and grinding pressure controlling in the grinding process of diamond tool. Efficiency and quality of diamond tool will obtain credible guarantee. |
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