| 基于粒子群优化的PID神经网络在热电偶数学建模中的应用 |
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| 引用本文： | 徐宏宇,朱永丽.基于粒子群优化的PID神经网络在热电偶数学建模中的应用[J].沈阳航空工业学院学报,2011,28(5):89-91. |
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| 作者姓名： | 徐宏宇 朱永丽 |
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| 作者单位： | 沈阳航空航天大学电子工程学院,辽宁沈阳,110136 |
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| 基金项目： | 2010辽宁省教育厅资助项目(项目编号:L2010421) |
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| 摘 要： | 为提高热电偶的测温精度，在对热电偶进行数学建模时，结合粒子群算法对PID神经网络进行优化，并设计了实际多路电偶数据采集电路对温度数据进行采集和验证。通过实验验证，粒子群算法的运用加快了PID神经网络的收敛速度、提高了系统稳定性，从而得到了更加精确的热电偶模型，提高了系统的测温精度。
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| 关 键 词： | 热电偶 粒子群优化 PID神经网络 |
The application of PIDNN in thermocouple mathematical modeling based on particle swarm optimization |
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| XU Hong-yu,ZHU Yong-li.The application of PIDNN in thermocouple mathematical modeling based on particle swarm optimization[J].Journal of Shenyang Institute of Aeronautical Engineering,2011,28(5):89-91. |
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| Authors: | XU Hong-yu ZHU Yong-li |
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| Institution: | XU Hong-yu,ZHU Yong-li(School of Electronics Information Engineering,Shenyang Aerospace University,Liaoning Shenyang 110136) |
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| Abstract: | In order to improve thermocouple measurement accuracy,the paper puts forward a mathematical modeling of thermocouple combined with a PID neural network(PIDNN) based on Particle Swarm Optimization.And a system is designed to collect and test multichannel temperature data.Experiments show that the use of Particle Swarm Optimization enhances both the convergence speed of the PID neural network and the stability of the system.A more accurate thermocouple temperature model is achieved. |
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| Keywords: | thermocouple particle swarm optimization PID neural network |
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