Development of a new tactile sensor by using a frequency characteristics of sliding friction having a vertical vibration

我们对滑动销的垂直振动对摩擦系数的影响进行了研究，并通过对滑动系统动力学的数值分析，成功地确定了摩擦的频率特性。垂直振动降低了滑动过程中的接触载荷，从而降低了摩擦系数。数值模拟结果表明，摩擦频率特性不仅包含材料的摩擦学特性，还包含材料的力学特性。这意味着，频率特性是一个有用的测量触觉传感系统。将双层Kohonen神经网络滤波应用于摩擦的频率特性，验证了采用振动滑动传感器系统选料的有效性。在这些研究过程中，在实验和数值分析中都观察到混沌振动。混沌振动对减小滑动摩擦有至关重要的作用。

We had been conducting a study on the effect of vertical vibration of a sliding pin on the friction coefficient and fund that the frequency characteristics of friction were successfully determined by the numerical analysis of the dynamics of a sliding system. And the vertical vibration reduces the contacting load during sliding, which results in reducing the coefficient of friction. These numerical simulations showed that the frequency characteristics of friction contains mechanical properties of materials as well as tribological characteristics of materials. This means that the frequency characteristics is a useful measure for tactile sensing systems. Double layered Kohonen neural network filter was applied to the frequency characteristics of friction and the validity of using the vibrating sliding sensor system for selecting materials is verified. In the process of these study, chaotic vibration was observed in both experimental and numerical analysis. The chaotic vibration showed a crucial effect on reducing the sliding friction.