| 基于后向散射法测量蒸汽湿度反演算法的优化 |
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| 引用本文： | 黄竹青,胡青松,黄章俊,唐振洲,袁志超.基于后向散射法测量蒸汽湿度反演算法的优化[J].应用光学,2019,40(4):612-619. |
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| 作者姓名： | 黄竹青 胡青松 黄章俊 唐振洲 袁志超 |
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| 作者单位： | 1.长沙理工大学 能源与动力工程学院, 湖南 长沙 410114 |
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| 基金项目： | 国家自然科学基金51376025湖南省自然科学基金2018JJ2442 |
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| 摘 要： | 为了精准测量汽轮机末级蒸汽湿度,提出在激光后向异轴角散射法的基础上建立蒸汽湿度测量模型和湿蒸汽参数反演优化模型。根据该优化模型采用粒子群算法对加入高斯白噪声的仿真数据和模拟汽缸的实验数据进行反演寻优,并将得到的反演结果与人工鱼群算法和传统的均匀搜索方法进行了对比。采用粒子群算法时 r 0.5 、K、N 的反演结果误差为0.05、0.66和0.51%,反演时间为306.41 s;采用鱼群算法时 r 0.5 、K、N 的反演结果误差为2.96、19.98和4.68%,反演时间为411.05 s;采用均匀搜索算法时 r 0.5 、K、N 的反演结果误差为5.00、27.14和7.95%,反演时间为246.42 s。结果表明:粒子群算法能够克服人工鱼群算法和均匀搜索方法两者的不足,可以在较短时间内获得精度高且稳定可靠的反演结果,为湿蒸汽参数测量提供了更加准确的数据,并对其他颗粒物参数测量反演提供了理论依据。
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| 关 键 词： | 光学测量 后向散射法 粒子群算法 反演 MIE散射 |
| 收稿时间： | 2018-12-07 |
Optimization of steam humidity measurement inversion algorithm based on back angle scattering method |
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| HUANG Zhuqing,HU Qingsong,HUANG Zhangjun,TANG Zhenzhou,YUAN Zhichao.Optimization of steam humidity measurement inversion algorithm based on back angle scattering method[J].Journal of Applied Optics,2019,40(4):612-619. |
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| Authors: | HUANG Zhuqing HU Qingsong HUANG Zhangjun TANG Zhenzhou YUAN Zhichao |
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| Affiliation: | 1.College of Energy and Power Engineering, Changsha University of Science & Technology, Changsha 410114, China2.Xiangtan University, Xiangtan 411105, China |
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| Abstract: | A steam humidity measurement model and a wet steam parameter inversion optimization model were established based on the laser back-axis angular scattering method in order to measure the steam trubine humidity at the final stage accurately. According to the optimization models, the particle swarm optimization (PSO)algorithm was used to perform multiple inversion optimizations on the simulation data which was added the Gaussian white noise and the experimental data of the simulated cylinder. The obtained inversion results were compared with the artificial fish-swarm algorithm and the traditional uniform search method as well. When the PSO algorithm was used, the inversion results of r0.5, K and N were 0.05, 0.66 and 0.51% respectively, the inversion time was 306.41 s. When the artificial fish-swarm algorithm was used, the inversion results of r0.5, K and N were 2.96, 19.98 and 4.68% respectively, the inversion time was 411.05 s. When the uniform search algorithm was used, the inversion results of r0.5, K and N were 5.00, 27.14 and 7.95% respectively, the inversion time was 246.42 s. The results show that the PSO algorithm can overcome the shortcomings of both artificial fish-swarm algorithm and uniform search method, which can obtain high precision, stable and reliable inversion results in a short time. It provides more accurate data for wet steam parameter measurement and theoretical basis for other particle parameter measurement inversions. |
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| Keywords: | optical measurement back scattering method particle swarm optimization inversion Mie scattering |
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