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The distribution of measured operating data of hydraulic turbines is non-structural and uneven density. The moving least squares method was used to fit the measured operating parameters to obtain the spatial characteristic surface of the water turbine, which can reflect the local characteristics of data surface and avoid the distortion caused by the differences of data distribution density. The Riyadh criteria was used to perform preliminary data filtering. The support radius was adaptively determined by local fitting across different ranges of discrete sample points. The robust moving least square surface reconstruction model was established combined with the Mahalanobis distance denoising method. Compared with the least squares method, the example calculation results show that the moving least squares method fits the operating characteristics of hydraulic turbines with higher accuracy and supplements the local data effectively. The result can reflect the operating characteristics of hydraulic turbines authenticity, which provides a reference for correcting the operating characteristic curve given by the turbine manufacturer.
[1] 刘艳娜,郑源,王荣兴.水电机组工作参数测量失误时水轮机效率计算[J].水电能源科学,2021,39(7):159-162.
[2] 杨桀彬,杨建东,王超.基于空间曲面的水泵水轮机机组数学模型及仿真[J].水力发电学报,2013,32(5):244-245.
[3] 邵卫云,张雄.水泵水轮机全特性曲线的拟合—移动最小二乘近似[J].水力发电学报,2004(5):102-106.
[4] 陈玉,王煜,戴凌全.水轮机模型综合特性曲线数值处理方法研究[J].水资源与水工程学报,2020,31(3):155-161.
[5] 常近时.水力机械装置过渡过程[M].北京:高等教育出版社,2005:102-104.
[6] 马伟超,杨桀彬,赵志高,等.混流式水轮机特性曲线在多重边界条件下的分区方法[J].农业工程学报,2021,37(11):31-39.
[7] 孙佳祥,张成立,徐连奎,等.低比速混流式水轮机特性曲线的近似模拟[J].水电能源科学,2018,36(7):127-129,123.
[8] 许力,田佳乐,齐鹏云,等.基于MEA-BP的水轮机运转特性曲线拟合及应用[J].人民长江,2019,50(9):141-145.
[9] 程效军.海量点云数据处理理论与技术[M].上海:同济大学出版社,2014:58-60.
[10] 林毅,吉鸿江,韩佳佳,等.一种基于马氏距离的系统故障诊断方法[J].计算机科学,2020,47(增刊2):57-63.
Basic Information:
DOI:10.20040/j.cnki.1000-7709.2023.20230827
China Classification Code:TV734.1;TV136.1
Citation Information:
[1]LI Peng,LIU Yan-na.Construction of Hydraulic Turbine Operating Characteristic Surface Based on Moving Least Square Method[J].Water Resources and Power,2023,41(11):183-186+17.DOI:10.20040/j.cnki.1000-7709.2023.20230827.
2023-10-31
2023-10-31
2023-10-31