Key Engineering Materials Vols. 291-292

Abstract: A novel scheme for ball bearing faults detection is presented based on Hilbert-Huang transformation and its energy spectrum. The basic method is introduced in detail. The energy spectrum is applied in the research of the faults diagnosis for the ball bearing of machine tool. Firstly, the analyzed vibration signals are separated into a series of intrinsic mode function using the empirical mode decomposition. Then, the energy spectrum is applied to the intrinsic mode function. The experimental results show that this method based on Hilbert-Huang transformation and energy spectrum can effectively diagnosis the faults of the ball bearing.

Abstract: Time-frequency and transient analysis have been widely used in signal processing and faults diagnosis. These methods represent important characteristics of a signal in both time and frequency domain. In this way, essential features of the signal can be viewed and analyzed in order to understand or model the faults characteristics. Historically, Fourier spectral analyses have provided a general approach for monitoring the global energy/frequency distribution. However, an assumption inherent to this method is the stationary and linear of the signal. As a result, Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, empirical mode decomposition and the Hilbert spectrum, in analysis of vibration signals and gear faults diagnosis for a machine tool. The results show that this method may provide not only an increase in the spectral resolution but also reliability for the gear faults diagnosis.

Abstract: Aiming at the problems on estimate of the initial transformation, matching precision and global optimization in matching, this paper presents a matching method, which is based on rough localization and exact adjustment. By means of rotation, translation and coincidence of the minimum bounding boxes of surface and measured points, rough localization is realized, which produces a good estimate for the follow-up iterative algorithm. The closest points that were calculated via the normal projection of the sample points then establish the correspondence between two objects. An iterative process is used in the exact adjustment to ensure the global optimization of match. For reducing the effect of bad points or local distortion, a maximum distance criterion is adopted to refine the transformation between objects. A computer simulation is given to demonstrate that the algorithm is steady and effective.

Abstract: As one of major methods to meet information integration of numerical control machines in workshop, DNC (Direct Numerical Control or Distributed Numerical Control) oriented networked manufacturing (Web-DNC system) differs dramatically from conventional ones by having: (1) concurrently supporting networked manufacturing; (2) sharing the numerical control machines via network; (3) optimizing the configuration and reorganization of numerical control resources. This paper deals with the key technologies of Web-DNC system, including: the implementing architecture model with four layers (user layer, service layer, agent layer and facility layer) and the topology architecture. The BL2000 SCM is selected as a COM server to meet the required capabilities of DNC controller. Compared with the communication architecture with fieldbus, a simpler function model of DNC communication technology based on Ethernet technology is presented. A Web-DNC system prototype is developed and proved to be effective in information integration of numerical control machines in injecton workshop.

Abstract: In micro stereovision system, false matching due to the randomicity of image signal makes 3D reconstruction data contain a large amount of abnormal data in the form of noise (pulse noise, Gauss noise). In order to obtain a more accurate 3D reconstruction shape, a novel method of 3D scattered data processing, which is a combination of wavelet transform and extended Vector Median Filters, is proposed to use wavelet transform to realize primary denosing, and use extended Vector Median Filters to further denoise thereby achieving higher precision 3D measurement. In wavelet based denosing, wavelet based edge detector in vector space removes edge abnormal points effectively, moreover, boundary tracking is used to prune out the image background from the matching area to remove exterior abnormal points. Then the local areas determined by edges are filtered by extended vector median filter. Experimental results indicate that the method proposed is effective to removing abnormal data from the 3D reconstructed data and enables 3D measurement position accuracy to reach 3 m µ .