Robotic Grinding Process Monitoring by Vibration Signal Based on LSTM Method

In robotic grinding, the trajectory deviation of the robot will change the grinding force and then affect the grinding material removal. Therefore, grinding force and material removal monitoring is important for the machining quality of robotic grinding. In this article, force and material removal estimation methods are proposed based on the acceleration signal. The dynamic model of robotic grinding is studied and the vibration force relationship can be obtained. Based on the vibration force relationship, the framework of the grinding force and material removal monitoring is established. In this framework, the peak value of the acceleration is first extracted by the signal process, and the long short-term memory (LSTM) network is used to train the vibration-force mapping model. Then the grinding removal can be calculated by the empirical formula. The experiments of robotic grinding are carried out. The real grinding force and the material removal can be estimated in time, which proved the effectiveness and potential of our method.

Automated summary

In this article, a method for monitoring grinding force and material removal in robotic grinding based on acceleration signal is proposed. The framework is established and experiments prove the effectiveness and potential of the method.