A novel fusion technique based functional link artificial neural network for LMC measuring

Lumber moisture content (LMC) measuring is a key industry process of wood drying. The precise of LMC win 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.