Time series analysis based overload detection algorithm for excavator

Abstract

In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially moving window method and correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue in advance. In this paper 16 channel sensor data are considered and each sensor frequency is 100Hz and sampling period is 1sec. So every sampling period 1600 data are gathered and computed, and the larger data, the longer process time. So this paper focuses on 2 topics. One is to short the process time. The other is to minimize the number of required sensors. To short the process time, this paper uses the moving window method. From the moving window method only data within each moving window are considered, so process time and process burden is shortened. And to minimize the number of required sensors, this paper uses the correlation function. From cross correlation function similar pattern sensors are eliminated and dissimilar pattern sensors are considered. And from using auto correlation function each dissimilar pattern sensor data are investigated to check overload or not. To prove the efficiency of the proposed overload detecting algorithm, this paper shows the computer simulation results.