Secure Vibration Control of Flexible Arms Based on Operators’ Behaviors

Abstract

Data analysis technique has been applied in many fields including smart industrial manufacture, which even leads to the industry 4.0 era. In this paper, we study how to control the vibration of flexible arms by exploiting analysis on operators’ behaviors, so as to guarantee the safety of the instrument and users around. Vibration problem usually happens when starting and stopping the flexible arm. There are two common vibration problems. One is the unstable rotation, i.e., the so-called “one fast-one slow” effect. The other is the inaccurate stopping position, because of the vibration after stopping. In addition, current flexible arms are usually controlled/operated by human (i.e., the operator). The starting and stopping effects are highly depended on the expertise of operators. Our work in this paper takes a novel perspective from the operator, and we strive to search the best starting and stopping approaches to minimize the vibration. To be specific, we first analyze the possible states of a moving flexible arm, and theoretically determine the strategy for keeping safe states. Next, we empirically study which operations can lead to safe motion states, by conducting various real world tests and simulations. Finally, we summarize the findings and suggest safe operations. In the integrated process, we exploit data analysis technique and it shows significant effectiveness in solving industrial safety problem of flexible arm’s vibration control.