Fuzzy Performance between Surface Fitting and Energy Distribution in Turbulence Runner

Shan

Engineering Applications of Computational Fluid Mechanics

et al. 2017

Self Cite

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

Section: Fuzzy Predictionmentioning

confidence: 99%

Fuzzy prediction of AWJ turbulence characteristics by using typical multi-phase flow models

Shan

Engineering Applications of Computational Fluid Mechanics

et al. 2017

Self Cite

“…Stainless steel material was employed to manufacture the experimental platform, with the purpose of avoiding the high light reflective index and mirror effect of background material, causing these two physical phenomena to reduce the contrast ratio and blur the objective clearance in video image remarkably [ 38 , 39 ]. On the stainless steel pathways, the drug tablets were scattered into the monitoring field for high-speed video detection.…”

Section: Experiments For Drug Tablet Trackingmentioning

confidence: 99%

Image Tracking for the High Similarity Drug Tablets Based on Light Intensity Reflective Energy and Artificial Neural Network

Zhou

Computational and Mathematical Methods in Medicine

et al. 2014

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It is obvious that tablet image tracking exerts a notable influence on the efficiency and reliability of high-speed drug mass production, and, simultaneously, it also emerges as a big difficult problem and targeted focus during production monitoring in recent years, due to the high similarity shape and random position distribution of those objectives to be searched for. For the purpose of tracking tablets accurately in random distribution, through using surface fitting approach and transitional vector determination, the calibrated surface of light intensity reflective energy can be established, describing the shape topology and topography details of objective tablet. On this basis, the mathematical properties of these established surfaces have been proposed, and thereafter artificial neural network (ANN) has been employed for classifying those moving targeted tablets by recognizing their different surface properties; therefore, the instantaneous coordinate positions of those drug tablets on one image frame can then be determined. By repeating identical pattern recognition on the next image frame, the real-time movements of objective tablet templates were successfully tracked in sequence. This paper provides reliable references and new research ideas for the real-time objective tracking in the case of drug production practices.

“…Simultaneously, Hellín et al [8] and Opan et al [9] respectively reported their instructive studies of irrigation effctiveness improvement using the DPSA-based (Dynamic Programming Successive Approximation) optimization model. More studies concerning the irrigation effectiveness schedule, and the effect of subsurface drip irrigation compared with that of surface drip irrigation, can be summarized from literature [10,11] accordingly. Relevant researches focusing on the upgrading of supplemental irrigation effectiveness for wheat production are published in literature [12] , either.…”

Section: Introductionmentioning

confidence: 99%

Influence analysis of sprinkler irrigation effectiveness using ANFIS

International Journal of Agricultural and Biological Engineering

Wen

et al. 2019

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In order to improve sprinkler irrigation quality and promote actual irrigation efficiency, the influence analysis of sprinkler irrigation effectiveness (SIE) using ANFIS (Adaptive Neural Fuzzy Inference System) was implemented to balance moisture infiltration and water redistribution in soil field. Firstly, using a detailed description of governing equations proposed for sprinkler irrigation flow, the theoretical foundation and mathematical model of irrigation effectiveness can be established; Secondly, based on a complete preparation of experimental irrigation conditions, a series of calibration indexes quantifying SIE for sprinkler irrigation quality and infiltration efficiency were proposed; Then thirdly, a novel ANFIS system was designed and introduced to evaluate these key effectiveness indexes in actual working operations, so that a series of detailed influence analysis and comprehensive infiltration assessment focusing on sprinkler irrigation effectiveness could be achieved afterwards, which result to the realization of better infiltration equilibrium and higher water redistribution efficiency in actual irrigation test. Therefore, the qualification of sprinkler irrigation effectiveness was achieved, and in addition, the moisture infiltration improvement and soil moisture uniformity were facilitated also in return.