基于MATLAB的BP神经网络实现减振器缺陷产品自动识别

Application of BP Neural Network in Defective Product of Shock Absorber Based on MATLAB

减振器是汽车悬架的重要组成部分,其性能直接影响整车的安全性和舒适性,减振器示功图是判断减振器是否合格的重要依据。目前,减振器示功图的类型识别都依赖人的经验。文章通过在MATLAB中训练BP神经网络,实现了减振器缺陷产品的自动识别,该研究具有巨大的市场价值。

Shock absorber is an important part of automotive suspension,it will direct influence the safety and comfort of a vehicle. Indicator diagram of shock absorber plays an important role in identifying whether it is qualified. At present, shape identification of the indicator diagram of shock absorber depends heavily on experience. The paper trained BP neural networks with MATLAB to realize automatic identification the defective products of shock absorber. The study has tremendous market value. [ Ch, 1 fig. 2 tab. 9 ref. ]