Delay Time Identification and Dynamic Characteristics Study on ANN Soft Sensor

D. Du, Chongguang Wu, Xionglin Luo, Xin Zuo
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引用次数: 7

Abstract

Soft sensor software based on ANN (artificial neural network) using BP or RBF was developed to estimate unmeasured variables such as product quality online. Some important topics including how to determine the delay time, how to simulate the dynamic system were discussed and solved. We applied a 3 layers BP network to identify the delay time of nonlinear system, feedback output variables to input layer, and weight of all the input variables to describe dynamic characteristics of the system. This makes the ANN soft sensor reflect truly both the static and dynamic characteristics of the system and provide more adaptability
神经网络软传感器延迟时间辨识及动态特性研究
开发了基于人工神经网络的软测量软件,利用BP或RBF对产品质量等未测量变量进行在线估计。讨论并解决了延迟时间的确定、动态系统的仿真等重要问题。我们采用3层BP网络来识别非线性系统的延迟时间,将输出变量反馈给输入层,并将所有输入变量的权值描述系统的动态特性。这使得人工神经网络软传感器能够真实地反映系统的静态和动态特性,具有更强的适应性
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