Hao Zhang

In response to the challenges associated with weld treatment during the on-site corrosion protection of hydraulic steel gates, this paper proposes a method utilizing a magnetic adsorption climbing robot to perform corrosion protection operations. Firstly, a magnetic adsorption climbing robot with a multi-wheel independent drive configuration is proposed as a mobile platform. The robot body consists of six joint modules, with the two middle joints featuring adjustable suspension. The joints are connected in series via an EtherCAT bus communication system. Secondly, the kinematic model of the climbing robot is analyzed and a PID trajectory tracking control method is designed, based on the kinematic model and trajectory deviation information collected by the vision system. Subsequently, the proposed kinematic model and trajectory tracking control method are validated through Python3 simulation and actual operation tests on a curved trajectory, demonstrating the rationality of the designed PID controller and control parameters. Finally, an intelligent software system for weld defect detection based on computer vision is developed. This system is demonstrated to conduct defect detection on images of the current weld position using a trained model.

The development of clean energy resources, including hydro power, plays an important role in protecting the global environment. Multi-layer bellows are key components and are widely used in hydro power plants. Due to the special multi-layer structures, conventional arc welding is prone to the defects of pores and insufficient fusion when fabricating or repairing such bellows. Precise laser welding with a high energy density and a low heat input has the potential to join multi-layer bellows in a high-quality manner. In this study, a comparative investigation was conducted on the arc welding and laser welding of multi-layer 316L stainless steel sheets and B610CF high-strength steel plates regarding the weld quality, microstructure and tensile properties. The results show that laser-welded joints produced a narrower heat-affected zone and a full weld without visible defects. Compared with arc welding, laser welding had more equiaxed grain regions in the fusion zone and a homogeneous elemental distribution in the heat-affected zone. This led to a more reliable welded joint using laser welding.

Cutting is a crucial step in the industrial production process, particularly in the manufacture of large structures. In certain spatial positions, using a mobile robot, especially a wall-climbing robot (WCR) with adsorption function, is essential for carrying cutting torches to cut large steel components. The cutting quality directly impacts the overall manufacturing quality. Therefore, effectively tracking the cutting trajectory of wall-climbing cutting robots is very important. This study proposes a controller based on a kinematic model and PID optimization. The controller is designed to manage the robot’s kinematic trajectory, including the torch slider, through the kinematic modeling of the wall-climbing cutting robot (WCCR). The stability of the control law is proven using the Lyapunov function, which controls the linear and angular velocities of the WCCR and the motion speed of the cross slider. Simulations verify that the control law performs well in tracking both straight-line and circular trajectories. The impact of different control law parameters on straight-line trajectory tracking is also compared. By introducing PID optimization control, the controller’s anti-interference capabilities are enhanced, addressing the issue of motion velocity fluctuation when the WCCR tracks curved trajectories. The simulation and experiment results demonstrate the effectiveness of the proposed controller.