基于Reflected Sigmoid径向基函数重建温度场优化算法
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摘要
微波加热在工业领域中广泛应用,利用超声波测温对其温度场重建可以实时监控设备内部温度,重建算法是实现温度场重建的关键。经典的重建算法为最小二乘法,其在重建过程中为保证结果唯一性,要求有效声波路径数大于区域划分数,重建结果的边界处会出现温度信息缺失。优化声波换能器安装位置,减少待测区域边界位置信息损失,提出基于Reflected Sigmoid径向基函数重建温度场算法,结合病态矩阵广义逆矩阵求解,可有效避免子区域划分条件限制,弥补了经典算法的缺陷。通过仿真实验及对比,所提算法可降低5%的误差。
Microwave heating is widely used in the industrial field. Using ultrasonic temperature measurement to monitor the internal temperature of the device in real time,the reconstruction algorithm is the key to reconstruct temperature field. The second most multiplication method is a classical algorithm. To ensure that the result is unique,the number of effective acoustic path needs to be larger than the number of regional divisions,and the information on the boundary of the reconstruction result will be missing. The installation position of the acoustic transducer is optimized and the information loss of the boundary position of the area to be tested is reduced. A temperature field algorithm based on Reflected Sigmoid radial basis function reconstruction is proposed,which is combined with the generalized inverse matrix of ill-conditioned matrix to avoid the sub-region division conditional constraints.Through experimental comparison,the error is reduced by 5% with the algorithm.
Microwave heating is widely used in the industrial field. Using ultrasonic temperature measurement to monitor the internal temperature of the device in real time,the reconstruction algorithm is the key to reconstruct temperature field. The second most multiplication method is a classical algorithm. To ensure that the result is unique,the number of effective acoustic path needs to be larger than the number of regional divisions,and the information on the boundary of the reconstruction result will be missing. The installation position of the acoustic transducer is optimized and the information loss of the boundary position of the area to be tested is reduced. A temperature field algorithm based on Reflected Sigmoid radial basis function reconstruction is proposed,which is combined with the generalized inverse matrix of ill-conditioned matrix to avoid the sub-region division conditional constraints.Through experimental comparison,the error is reduced by 5% with the algorithm.
引文
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11 柳丹,石为人,熊庆宇,等.基于高斯径向基的子区域优化温度场重建算法[J].计算机应用研究,2015(9):2618-2621Liu Dan,Shi Weiren,Xiong Qingyu,et al. Optimization of temperature field reconstruction algorithm based on Gaussian radial basis[J]. Journal of Computer Applications,2015(9):2618-2621
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14 Li Z C,Huang H T,Wei Y. Ill-conditioning of the truncated singular value decomposition,Tikhonov regu-larization and their applications to numerical partial differen-tial equations[J]. Numerical Linear Algebra with Applica-tions,2015,18(2):205-221
2 Michalski D,Strk K,Piasecka M. Comparison of two surface temperature measurement using thermocouples and infrared camera[J].The European Physical Journal Conferences,2017,143:02075
3 李志勇,沈国清.声学测温技术在电站锅炉中的应用研究[J].电力安全技术,2017,19(4):35-38Li Zhiyong,Shen Guoqing. Application of acoustic temperature measurement technology in power plant boilers[J]. Electric Power Safety Technology,2017,19(4):35-38
4 沈雪华.基于声学测温的温度场重建算法研究[D].重庆:重庆大学,2016Shen Xuehua. Research on temperature field reconstruction algorithm based on acoustic temperature measurement[D]. Chongqing:Chongqing University,2016
5 施超,胡斌,梁晓瑜.基于超声波的结构内部温度场重建方法研究[J].机械工程学报,2017,53(12):44-51Shi Chao,Hu Bin,Liang Xiaoyu. Research on reconstruction method of internal temperature field of structure based on ultrasonic wave[J].Journal of Mechanical Engineering,2017,53(12):44-51
6 范洪辉,朱洪锦,柳田裕隆,等.超声波信号渡越时间参数法测量空气中温度分布[J].应用声学,2010,29(1):53-57Fan Honghui,Zhu Hongjin,Liu Tianyulong,et al. Measurement of temperature distribution in air by ultrasonic signal transit time parameter method[J]. Applied Acoustics,2010,29(1):53-57
7 颜华,李欣,王善辉.基于最小二乘法和克里金插值的三维温度场重建[J].沈阳工业大学学报,2014,36(3):303-307Yan Hua,Li Xin,Wang Shanhui. Three-dimensional temperature field reconstruction based on least squares method and Kriging interpolation[J]. Journal of Shenyang University of Technology,2014,36(3):303-307
8 Chen Y,Xu K B,Liu S S. Application study on multiple acoustic paths intersection in temperature field measurement[J]. Advanced Materials Research,2014,902:167-172
9 Jia R,Xiong Q,Xu G,et al. A method for two-dimensional temperature field distribution reconstruction[J]. Applied Thermal Engineering,2017,111:961-967
10 Liu S,Wang C C L. Quasi-interpolation for surface recon-struction from scattered data with radial basis function[J]. Computer-Aided Geometric Design,2012,29(7):435-447
11 柳丹,石为人,熊庆宇,等.基于高斯径向基的子区域优化温度场重建算法[J].计算机应用研究,2015(9):2618-2621Liu Dan,Shi Weiren,Xiong Qingyu,et al. Optimization of temperature field reconstruction algorithm based on Gaussian radial basis[J]. Journal of Computer Applications,2015(9):2618-2621
12 Fasshauer G E,Mccourt M J. Stable evaluation of gaussian radial basis function interpolants[J]. Society for In-dustrial and Applied Mathematics,Journal on Scientific Computing, 2012,34(2):737-762
13 刘冬,王飞,黄群星,等.三维炉膛温度场重建中病态矩阵方程的求解研究[J].中国电机工程学报,2007,27(26):72-77Liu Dong,Wang Fei,Huang Qunxing,et al. Solution of ill-conditioned matrix equation in three-dimensional furnace temperature field reconstruction[J]. Proceedings of the CSEE,2007,27(26):72-77
14 Li Z C,Huang H T,Wei Y. Ill-conditioning of the truncated singular value decomposition,Tikhonov regu-larization and their applications to numerical partial differen-tial equations[J]. Numerical Linear Algebra with Applica-tions,2015,18(2):205-221