Surface vibration displacement prediction based on a non-equidistant Grey Model

To predict the vibration displacement distributed on a vibrating surface, an r order Non-equidistant Grey Model (r-NGM) is proposed in this paper. This model is built by accumulating the initial discrete non-equidistant vibration displacement set with the r order Accumulated Generating Operation (r-AGO). The r-NGM is applied to a vibrating surface of a shaker to displacement prediction. The experimental result indicates that the predictive accuracy of r-NGM is positive to growth rate when r ranges from [0.1, 0.5], and negative when r ranges from (0.5, 1.0]. The error range is [-0.010, 0.006] for 0.5-NGM. As well, the error range is [-0.111, 0.111] for traditional grey model, which is over ten times higher than the former one. It demonstrates that the 0.5-NGM is superior to the traditional GM(1, 1) model when it applies to predicting the surface vibration displacement.