Precision grinding is generally used as the final finishing process, and it determines the surface quality of the machined component. It’s very difficult to achieve on-line measurement of the surface roughness. The purpose of this research was to study the surface roughness prediction and avoid the defect happening in the grinding process. A surface roughness prediction model was proposed in this paper, which presented the relationship between surface roughness and the wear condition of grinding wheel and grinding parameters. An AE sensor was used to collect the grinding signals during the grinding process to obtain the grinding wheel wear condition. Besides, a fuzzy neural network was used to obtain the prediction surface roughness. Grinding trials were performed on a high precision CNC cylindrical grinder (MGK1420) to evaluate the surface roughness prediction model. Experiment verified that the developed prediction system was feasible and had high prediction accuracy.

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This paper used the 3d modeling software to establish SOLID model and simplified it. And it used ANSYS workbench to make the simulation analysis on dynamic performance of the universal joint. Compared undamped free vibration modal analysis with the inherent frequency measurement experimental results, to verify the accuracy of the finite element model, and prove its no resonance phenomenon.

In this paper, Using rigid-flexible coupling method the auto synchronous belt drive system dynamics model is established. We can make the rigid-flexible coupling analysis of auto synchronous belt drive system through Recurdyn, designed and auto synchronous belt vibration displacement measurement device was developed, measuring the midpoint of the belt in the process of synchronous belt transmission vibration curve of change over time. Has an important value to improve auto synchronous belt transmission stability and reduce the transmission noise.