Title :
Bolt tightening control using neural networks
Author :
Fujinaka, Toru ; Nakano, Hikofumi ; Omatu, Slgeru
Author_Institution :
Graduate Sch. of Eng., Osaka Prefecture Univ., Japan
Abstract :
We propose a method of controlling the tightening operation of bolts using a device called an impact wrench. A neural network is used for classifying the material and shape of the work to which the bolts are being tightened. Then another neural network is used for estimating the relationship between the clamping force of the bolt and its incremental angle. The input to the actuator of the impact wrench is determined based on the estimated value of the clamping force. A simulation study shows satisfactory results in comparison to those achieved by a skilled factory worker
Keywords :
assembling; backpropagation; factory automation; feedforward neural nets; force control; neurocontrollers; torque control; backpropagation; bolt tightening; clamping force; force control; impact wrench; incremental angle; multilayer neural network; torque control; Automobiles; Clamps; Fasteners; Force measurement; Industrial accidents; Neural networks; Shafts; Shape; Torque; Wheels;
Conference_Titel :
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location :
Tucson, AZ
Print_ISBN :
0-7803-7087-2
DOI :
10.1109/ICSMC.2001.973476