CAJ | 학술논문

针对水电机组所处特定的环境以及任意点盘车连续采样数据，结合国内外盘车研究现状，提出利用粒子群优化算法（Particle Swarm Optimization ，PSO）进行正弦拟合，求取正弦信号参数。以某抽水蓄能电厂为实例，利用Mat‐lab为仿真平台对连续采样数据进行分析研究。数据处理结果表明，利用PSO算法对水电机组连续盘车采样数据进行处理，与工程实际情况相符，具有高精确性等优点。目前该方法已应用于某抽水蓄能机组全自动智能盘车系统中，取得了较好效果。
침대수전궤조소처특정적배경이급임의점반차련속채양수거，결합국내외반차연구현상，제출이용입자군우화산법（Particle Swarm Optimization ，PSO）진행정현의합，구취정현신호삼수。이모추수축능전엄위실례，이용Mat‐lab위방진평태대련속채양수거진행분석연구。수거처리결과표명，이용PSO산법대수전궤조련속반차채양수거진행처리，여공정실제정황상부，구유고정학성등우점。목전해방법이응용우모추수축능궤조전자동지능반차계통중，취득료교호효과。
In this paper ,a method which can extract sinusoidal signal parameters based on particle swarm optimization algorithm (PSO) is proposed .The simulation research on the alignment data processing for the unit in a pumped storage power plant is conduc‐ted by using the MATLAB simulation platform .The results show that the PSO algorithm hydroelectric generating continuous cran‐king sampling data processing is in line with the actual situation of the project and in line with higher accuracy and other advantages . The method has been applied to fully automatic intelligent run out check system for pumped storage units ,and achieved good results .