Optimization of working position and posture of a 5-DOF hybrid automatic drilling system based on an improved GA-BP neural network
Author:
Affiliation:
1. College of transportation, Ludong University, Yantai, Shandong, China
2. College of intelligent manufacturing industry, Ludong University, Yantai, Shandong, China
Funder
National Natural Science Foundation of China
the Shandong Provincial Natural Science Foundation
Ludong University
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2023.2211426
Reference33 articles.
1. Drilling wear detection and classification using vibration signals and artificial neural network
2. Computer integrated work-space quality improvement of the C4 parallel robot CMM based on kinematic error model for using in intelligent measuring
3. Inverse and forward kinematics and workspace analysis of a novel 5-DOF (3T2R) parallel–serial (hybrid) manipulator
4. End stiffness modeling for automatic horizontal dual-machine cooperative drilling and riveting system
5. Pose error compensation based on joint space division for 6-DOF robot manipulators
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