相关小波法在腕力传感器动态特性分析中的研究

在机器人腕力传感器的动态特性分析中，最关键的步骤之一是从传感器输入输出信号中提取精确的脉冲响应函数和频响函数。介绍了一种新的提取腕力传感器脉冲响应函数的方法——相关小波法。在建立腕力传感器的简化动力学模型的基础上，模拟了机器人与环境相互碰撞及机器人在强噪声环境中的典型工作条件，用相关小波法提取了模型系统的脉冲响应函数和频响函数，并与传统的FFT方法进行了比较。结果表明，相关小波法比FFT方法具有更明显的优势，获得了更高精度的脉冲响应函数和频响函数的提取。相关小波法为腕力传感器，同时也为其他传感器的动态特性分析提供了一种新的、有效的方法。

Study on Dynamic Characteristic Analysis of Wrist Force Sensor Using Correlation Wavelet Method

In the dynamic analysis of robot's wrist force sensor, one of the most important steps is to extract the accurate impulse response function (IRF) or frequency response function (FRF) from the input and the output signals of the sensor. A novel correlation wavelet method for extracting the IRF of wrist force sensor is presented. Based on the dynamic model of the wrist force sensor, the dynamic characteristics of the sensor are simulated in two cases when robot impacts with the environments and works in a noisy circumstance. The correlation wavelet method is then used to extract IRF and FRF of the sensor model. The simulation results show that compared with the traditional FFT method, correlation wavelet method exhibits obvious advantages over FFT method, and the accuracy of the results is greatly improved. Correlation wavelet method provides a new and effective method for dynamic analysis of robot's wrist force sensor as well as other sensors.