In order to solve the problems of inaccurate position judgement and insufficient sense of presence in the process of remote operation of mobile robotic arms via video in the tunnel environment, a positioning system based on ultra-wideband positioning technology and a sensing system based on the combination of 2D LIDAR and pitch rotary table are proposed, and a verification platform is built and experimentally studied. The research in the thesis proposes a new solution to the real-life problems faced by engineering technology and has certain research value.
As an important raw material in the process of aluminum electrolysis, the quality of prebaked anode is directly related to the technical indexes such as carbon consumption, production stability and aluminum purity of aluminum electrolysis. As an important process in the production of prebaked anodes, the end point of kneading affects the automation of raw anode production process, production efficiency and product qualification rate. In this paper, the collected data of the kneading process are processed and the model is established by using LSTM algorithm in machine learning, which can accurately predict the remaining time of kneading and realize the judgment of the end point of carbon kneading, and provide guidance value to the actual production.
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