Research on Intelligent Cable Installation Control Technology Based on Deep Learning and Finite State Machine
This study proposes an intelligent cable installation control method based on deep learning and finite state machine.By identifying and processing the installation video of cable accessories,this method can record the duration of the process and determine whether the process meets the standards.Firstly,establish a dataset based on cable accessory installation videos,and then build a deep neural network model for object detection based on YOLOv8 to learn cable accessory features.Next,define a finite state machine model to record installation time and process,and use deep neural network detection results to determine the current state for managing installation processes.Finally,compare the process state transition time with the standard time to determine the compliance status.The experimental results show that this method can quickly and accurately identify the installation process of cable accessories and effectively determine whether the process meets the standards.This method can be used to improve the efficiency and quality of cable installation,and provide technical support for intelligent cable installation systems.
deep neural networkfinite state machineintelligent controlinstallation of cable accessoriesprocess identificationvideo analysisYOLOv8object detection
万方数据
维普
