頁籤選單縮合
題名 | Assessment of the Shock-Absorption Performance of a High Capacity Suspension System by Neural Networks |
---|---|
作者 | Lee, Y. W.; | 書刊名 | Journal of Mechanics |
卷期 | 30:1 2014.02[民103.02] |
頁次 | 頁39-48 |
分類號 | 447.11 |
關鍵詞 | NARX networks; Double wishbone suspension; Generalized frequency response functions; GFRFs; |
語文 | 英文(English) |
英文摘要 | The objective of this study is to develop a framework using nonlinear autoregressive model process with exogenous inputs (NARX) neural networks (NNs) to identify the dynamic hysteresis of high load capacity suspension systems. Here, a vertical excitation test is used to simulate various terrains at an oscillation frequency range from 0.1Hz to 10Hz by using NARX NNs. The model results are in good agreement with suspension component oscillation responses that manifest as variations in model order selection as the excitation frequency approaches 7Hz. Furthermore, mapping the models into generalized frequency response functions (GFRFs), elucidates any unanticipated couplings between surroundings and mechanical hysteresis within the suspension. The proposed approach’s systematic design procedure is advantageous because it provides a cost-efficient method that achieves precise identification of online data. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。