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Uncertainty Analysis for Pump Test Based on Monte Carlo Method and Maximum Entropy

Author: ZhangHuanZhen
Tutor: ZhangXinMin
School: Shenyang University of Technology
Course: Fluid Machinery and Engineering
Keywords: Pump Test Uncertainty Monte Carlo method Maximum entropy method Particle swarm optimization
CLC: TH38
Type: Master's thesis
Year: 2011
Downloads: 60
Quote: 0
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Abstract


Since the promulgation of the \In recent years, a lot of people committed to finding the optimal assessment method achieved a lot , but in the field of pump test Uncertainty Evaluation , researchers rarely , coupled with our country's overall level of the pump industry is relatively backward , technical personnel is more the lack of seeking an effective assessment tools is imperative . This article gives a pump test Uncertainty Evaluation common problem Uncertainty Evaluation of the new method , the single-stage centrifugal pump performance test parameters Uncertainty evaluation method based on the Monte Carlo method and the maximum entropy method is effective combines the advantages of both methods , expand uncertainty Evaluation . The research work of the following aspects : the Uncertainty Evaluation feasibility analysis , as well as the pros and cons of each method and the applicability of comparison ; analysis of pump performance testing system to find the sources of uncertainty and its elimination arrive at these measures , and real-time data acquisition , combined with the actual single-stage water centrifugal pump performance testing and Bessel formula uncertainty Evaluation and Analysis ; collected data using the maximum entropy method for distributed simulation , simulation type of data distribution , according to the type of distribution of the obtained rejection method to generate a certain number of the corresponding distribution of the random number , then using Monte Carlo method for the assessment of the uncertainty , and the results assessed with the traditional way of comparison of the results may be conclusions ; difficult to choose the initial value problem solving process common issue of maximum entropy algorithm research , presents a program based on particle swarm algorithm to solve , no longer need to manually given initial value , but simply to improper given a range of procedures they can on their own in the space in the search for the optimal solution , especially human assessment procedures can be simplified to avoid some random factors select the initial value does not converge , and the test data are substituted into the calculation , and conventional the algorithm results were compared to verify the effectiveness of the algorithm .

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