Hideyuki Miyaji

Input load identification using a holographic neural network

A machine generates and undergoes dynamic loads during its operation. These dynamic loads are the main source of vibration and noise. If the dynamic loads can be identified exactly, it will become possible to provide the data effective for the reduction of vibration and noise. However, by the method of identification of dynamic loads of the conventional multiple-input systems, noise has a large influence on accuracy. Thus, in this paper, an identification method based on a neural network is proposed for independent multiple-input loads, and the results of the simulation by using the conventional method and the neural network are shown and compared in detail.

Force Identification Using Neural Network

Due to various causes, a machine generates and undergoes dynamic loads during its operation. These dynamic loads are the main source of vibration and noise. If dynamic loads can be identified exactly, it will become possible to provide data effective for the reduction of vibration and noise. However, by the method of identification of dynamic loads of the conventional multiple input systems, noise has large influence on the accuracy. Thus, in this paper, the identification method based on neural network (NN) are proposed for independent multiple input loads, and the result of the simulation by using the conventional method and NN are shown and compared in detail.Copyright