%0 Journal Article
%T Optimization and Experimental Study of an Intelligent Bamboo-Splitting Machine Charging Manipulator
%A Li
%A Gui-Qi
%A Liu
%A Tian-Hu
%A Nie
%A Xiang-Ning
%A Wen
%A Yong-Lu
%J -
%D 2020
%R https://doi.org/10.1155/2020/4675301
%X A nonautomatic bamboo-splitting machine must charge with material and change tools manually. However, manual charging is very dangerous. An intelligent bamboo-splitting machine can feed automatically and change tools intelligently and has broad application prospects. A charging manipulator is an important part of an intelligent bamboo-splitting machine. The size of the manipulator was optimized here using a genetic algorithm. The capture rate, centering rate, and dynamic characteristics of an intelligent bamboo-splitting machine charging manipulator, in which key factors were considered, were experimentally studied. First, three different manipulators, with arm lengths at 210, 220, and 230£¿mm, were developed. Then, the bamboo materials were divided into three gradients (60¨C85, 85¨C110, and 110¨C135£¿mm) according to diameter ranges. Accelerators were used to measure the manipulator arm dynamic characteristics, and a high-speed charge-coupled device was used to record the grasping process. Experimental results showed that the manipulator capture rate with an arm length of£¿=£¿220£¿mm was as high as 100%, but that of manipulators with arm lengths of£¿=£¿210 and 230£¿mm was 96 and 98.67%, respectively. Thus, the manipulator with a 220£¿mm arm length showed better performance than the other two manipulators. Trend curves of the influence of material diameter on capture time were similar to an exponential function
%U https://www.hindawi.com/journals/jr/2020/4675301/