TIAN Wei, LI Guoliang, ZHENG Wei, ZHANG Jin, WANG Changrui, BAI Quan, WANG Wang, LI Pengcheng. Scanning Path Optimization Method in Wing Skin Nondestructive Testing Production Line[J]. Aeronautical Manufacturing Technology, 2023, 66(6): 14-21.
TIAN Wei, LI Guoliang, ZHENG Wei, ZHANG Jin, WANG Changrui, BAI Quan, WANG Wang, LI Pengcheng. Scanning Path Optimization Method in Wing Skin Nondestructive Testing Production Line[J]. Aeronautical Manufacturing Technology, 2023, 66(6): 14-21. DOI: 10.16080/j.issn1671-833x.2023.06.014.
Scanning Path Optimization Method in Wing Skin Nondestructive Testing Production Line
The composite wing skin has the characteristics of large size
complex shape and easy rebound. It can’t be used for nondestructive testing by traditional methods such as machine tools. But the robot has the characteristics of flexibility and intelligence
which provides a new idea for nondestructive testing. A scanning path optimization method of large wing skin continuous surface is proposed to solve this kind of problems. Dual robots equipped with ultrasonic scanning equipment
adopting the strategy of two-time inspection: the composite surface is reconstructed by the first scanning
so the accuracy of the second transmission nondestructive inspection is improved. According to the shape of the wing
a general scanning strategy parallel to the stringer is proposed. The points are grouped by the least squares method according to the curvature
the path is optimized by the hybrid genetic LM algorithm. The algorithm means the improved genetic algorithm is used for heuristic global optimization and the LM algorithm is used for deterministic local optimization
so that the optimal scanning path can be obtained efficiently. Then
the simulation is carried out in RoboDK
and the robot is equipped with ultrasonic detection end to scan the skin. Finally
the precision of the optimized path is verified by the laser scanner on the robot. Simulation and experiment results show that
compared with traditional detection methods
the average detection efficiency of this method is improved by 9.2%. It meets the constraints of ultrasonic detection.