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For the purpose of improving the working performance of AWJ (Abrasive waterjet) grinding in actual machining, and revealing the unknown influence mechanism of waterjet machining prediction, this research conducted a theoretical and experimental investigation concerning with the influences caused by multi-phase flow models, on the fuzzy prediction of turbulence characteristics. First, typical flow models describing the abrasive waterjet were presented and enunciated; Second, a series of turbulence characteristics were defined to quantitatively demonstrate the waterjet flow, which are responsible for the actual performances of AWJ grinding in the contact zone; Then a new fuzzy prediction system equipped with logic protocols was established and introduced to predict turbulence characteristics based upon the machining parameters by employing different flow models, therefore a set of quantified prediction results generated from the CFD (Computational Fluid Dynamics) simulation, orthogonal experiments and actual measurements can be obtained and distinguished systematically. Through a detailed performance analysis with benchmark indexes and prediction comparisons, the theoretical superiorities and specific applications of these flow models were fully discussed and then an integrated conclusion assessing their inherent influence mechanism was acquired. Based on these innovative achievements, the instantaneous machining inspection or parameter optimization in AWJ grinding process can be facilitated, simultaneously the new research ideas aimed at waterjet monitoring or grinding improvements can be presented as well. ARTICLE HISTORY

Video tracking of drug tablet exerts important influences on the efficiency and reliability of its mass production; this topic also becomes a difficult and targeted focus for pharmaceutical production monitory in the past several years due to the high similarity and random distribution of those objectives to be searched for. By measuring the reflective lightness intensity of illumination lightness on tablet surface, reflective lightness intensity matrix was established and demonstrated in the form of grey image, presenting its shape topology and topography details in return. On this basis, a series of mathematical properties for describing reflective lightness intensity images were proposed, thereafter a set of fuzzy recognition system and its identification rules can be employed to classify those moving tablets with inputted image properties, which facilitates the determination of their instantaneous coordinate positions on given image frame accordingly. By repeating identical operations on the next frame, the real-time motions of tablet objectives were traced successfully. Orthogonal tracking experiment and performance comparisons verified the accuracy and reliability of this new method in pharmaceutical industry. With original suggestions concerning imaging arrangements, tablet descriptions and video tracking, this article provides reliable references and new research ideas for tablet tracking performance in high-yielding production domain.

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