Mingsheng Jin

Simulation and experiment research of magnetic gasbag polishing

The novel magnetic gasbag polishing technology is presented in this paper. It can be used in polishing the contact or non-contact zone between gasbag and mould surface. By means of the interaction between magnetic field and magnetic abrasive, the magnetic abrasive brush is formed, and abrasive particles filed can be controlled actively. The force of a single magnetic abrasive in the contact or non-contact zone is analyzed. Moreover, the simulation is performed for the magnetic field generated by permanent magnet in gasbag polishing tool. The original state and feature of magnetic field distribution are obtained. On this basis, the changes of magnetic field in different downward depth and inclination angle of polishing tool are simulated and compared. Then, the magnetic field distribution in actual polishing is obtained. The polishing effect of the neighborhood of gasbag contact zone is studied by fix-point and movement polishing experiment, and a smooth high quality surface can be obtained. After movement polishing with beeline trajectory, the surface roughness of the neighborhood of gasbag contact zone reaches Ra 0.25μm.

Material Removal Model and Contact Control of Robotic Gasbag Polishing Technique

Material removal model of robotic gasbag polishing is established on the basis of Preston equation and distributions of linear velocity and contact stress in the circular contact area between the flexible polishing tool and mould surface. Contact force determines the maximal contact stress and influences the material removal and surface quality. Linear velocity and contact stress fields together with the distribution of material removal are calculated and simulated respectively according to certain internal pressure, downward depth, inclining angle, rotating speed and structural characteristics of rubber gasbag. The material removal mechanism is analyzed for optimizing the polishing process and trajectory planning is proposed for more convenient operation. The theoretical analysis and experimental results indicate that the surface roughness Ra 5 nm can be obtained under the situations of effective cushioning action of flexible contact, reliable control accuracy of robotic gasbag polishing system, tiny wiped off process of mould surface, etc.

Research on LIF Image Denoising Based on Wavelet-Domain Multiscale HMT Model

In the process of computing laser induced fluorescence (LIF) image, a lot of noises will be brought into the system. Hidden Markov models have proven to be useful tools for statistical signal and image processing. In this paper, wavelet-domain multiscale hidden Markov tree HMT model is employed to denoise LIF image in order to acquire the process intermediate values of chemical mechanical polishing (CMP). This method utilizes the relativity of wavelet coefficients well. Firstly, the statistical characteristics of wavelet coefficients and transform are summarized. Then the dependencies between the wavelet coefficients are modeled as dependencies between the hidden states with the mixture Gaussian model and HMT model. Because the degree of coefficients shrinkage is determined based not only on the size of the coefficients but also on its relationship with its neighbors across scale, HMT-based denoising typically outperforms the standard threshold techniques. Finally, the experiments show that the denoising results of LIF image using this method are typically better than other standard method. The method can not only get rid of the noise preferably, but also increase the power signal-to-noise ratio (PSNR)