Research on data fusion technology of the online monitoring system for optics bonnet polishing

Abstract

Bonnet polishing has been successfully used for ultra-precision machining of the large-aperture aspheric optics. To accomplish online monitoring of executive condition of the removing function and state of the polishing machine, key technological parameters and processing condition factors need to be acquired in real time and coupled back. A novel data fusion method which combines hardware synchronous signal and correcting algorithm based on the principle of linear extrapolation is proposed in allusion to data acquisition distortion caused by asynchronous sampling frequency and communication delay between different systems. The estimate values are obtained by dynamically correcting original acquired data, and the upper bound of the error is deduced with the speed and the acceleration of the signal. The simulation results showed that the data fusion method can significantly reduce the error of data acquisition. The experimental results confirmed that the data fusion method can be effectively applied to monitor the optics bonnet polishing process online.