A Novel Fusion Technique Based Functional Link Artificial Neural Network for LMC Measuring

摘要：

Lumber moisture content (LMC) measuring is a key industry process of wood drying. The precise of LMC will be disturbed by many ambient factors such as temperature, equilibrium moisture content, wind speed etc. Data Fusion is a novel technique to solve the coupling problem of multi-parameters. A novel fusion technique based functional link artificial neural networks (FLANN) is put forward to remove the ambient temperature disturbance. In the FLANN, functional expansion substitutes the hidden layer of multilayer perceptron (MLP). It increases the dimension of the input signal space by polynomials. Compared with MLP, FLANN exhibits a much simpler structure, less training computation and faster convergence. The calibration tests and simulation studies show that FLANN based fusion technique can eliminate effectively the disturbance from ambient factors and realize steady, real-time, high-accuracy measurement of lumber MC.

作者: Jiawei ZHANG Jun CAO Liping SUN

作者单位: Northeast Forestry University, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）