應用雷射都卜勒測速儀於噴水推進器參數設計研究

本研究以模型自推實驗方式進行數據蒐整，結合逆向工程及3D列印的技術，仿製噴水推進器模型，並藉由「防水型負荷計」及「雷射都卜勒測速儀」，進行「噴嘴出口速度分佈」、「流量」及「推力」量測，續運用「實驗設計法」與「統計分析」相關原理進行實驗規劃及試驗，以有效率且系統化的方式設計實驗組合。另針對「噴水推進器」之設計，由於影響輸出效率及推力的因素甚多，本研究以「轉子葉片數」、「定子葉片數」及「定子安置角度」等三項控制因子進行初步探討，藉由田口法進行穩健設計，將實驗數據的信號雜訊比(S/N)作為參數設計指標，經由變異數分析探討各因子的貢獻度及彼此之間的交互作用影響，後續利用類神經網路(ANN)中「徑向基底函數網路(RBFN)」建構非線性模型，經由自適應粒子群算法(APSO)求得最佳因子水準組合，以期獲得最佳推力參數設計的噴水推進器。

關鍵字

逆向工程；噴水推進器；類神經網路；實驗設計；自適應粒子群演算法

並列摘要

This research aims to adopt the reverse engineering and 3D printing technology to imitate a model of water-jet propulsion and to conduct a parameter design. Using ＂Load Cell＂ and ＂Laser Doppler Velocimetry (LDV)＂, this study carried out to measure the velocity distribution of nozzle, the flow rate and the estimation of thrust. An efficient and systematic way is used to investigate the robust design based on Taguchi method that is one of the designs of experiments (DOE). There are many factors influencing the output efficiency and thrust on the performance of the water-jet propulsion system. In this study, three control factors, such as ＂number of rotor blades＂, ＂number of stator blades＂ and ＂stator placement angle＂ are discussed. The signal-to-noise ratio (S/N) of the experimental data is used as the index of parameter design, and the contribution of each factor and the mutual influence of each factor are discussed through the analysis of variation. The work successfully proposes a modeling by using the Radial Basis Function Network (RBFN) in ANN; the optimum factor-level combination is obtained by the adaptive particle swarm optimization (APSO) in order to get the parameter design of the best thrust of waterjet propulsion.

並列關鍵字

Reverse Engineering ； Water-Jet Propulsion ； Artificial Neural Network (ANN) ； Design of Experiments ； Adaptive particle Swarm Optimization (APSO)

國際替代計量

應用雷射都卜勒測速儀於噴水推進器參數設計研究

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