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As the key technology in the weld seam visual tracking system, the laser strip center extraction is highly valued to the performance of detection system. In this paper, a laser strip center extraction methodology based on geometrical center method, direction template and gray centroid method is proposed. Firstly, the laser strip center is picked up as an approximate skeleton by geometric center method. Then a normal judgment method based on the Lagrange mean theorem is designed to determine the normal direction of the skeleton. At last, accurate laser strip center gray is obtained by gray centroid method. The experimental results indicate that suggested method is both simple and accurate, and meet the speed and precision requirement of the weld seam detection.

The manipulator is widely applied in bolt disassembly in the field of remanufacturing. The intelligent manipulator with the ability of generating suitable operating path is increasingly required. To improve the path planning ability of manipulator in bolt disassembly, a strategy of dual path planning using a hybrid algorithm which combines an improved genetic algorithm (GA) and A* algorithm is proposed in this paper. The model of bolt disassembly sequence and algorithm are first established to find out the shortest disassembly path. The improvement of selecting and crossing operators are designed to enhance the stability and efficiency of basic GA. Both basic GA and improved GA are used and compared in the simulation of path planning with MATLAB. Then, the A* algorithm is adopted to accomplish the obstacle avoidance based on the path obtained with improved GA. Last, the experiment focusing on the bolt disassembly of a specific reduction gearbox is performed, and the correctness and feasibility of the hybrid algorithm are verified in the simulation and experiment.

Straight metal pipes are widely used in petroleum exploration and transmission equipment systems. Straightening is one of effective methods for ensuring or repairing the bending during straight metal pipe rolling, heat treatment, assembly and operational application. However, the flatten phenomenon of straight metal pipe during straightening process is unavoidable. Therefore, it is significant to study the flatten phenomenon of straight metal pipe in straightening process. Based on the theory of elastoplastic deformation, the flatten phenomenon of straight metal pipe is analyzed. Further, the straightening stroke model of straight metal pipe for guiding the straighten operation is established. Afterwards, the theoretical straightening stroke model is analyzed on the basis of simulation. Finally, the experimental system was built up. A series of related experiments were carried out to verify the rationality of the model.

As an important form of additive manufacturing, welding is widely used in steel components welding work of construction, shipbuilding and other fields. In this study, an intelligent welding path generation algorithm based on multi-section interpolation is proposed in order to deal with non-standard multi-pass welding grooves which are difficult to be handled by automatic welding equipment in the construction site. Firstly, the non-standard grooves are classified and the reasons for their occurrence are discussed. Secondly, an automatic welding additive manufacturing system framework is discussed and an appropriate detection method is selected. Then, combining with the welding standard of non-standard grooves and the characteristics of the welding process, a multi-section interpolation-based welding path generation algorithm is proposed. Finally, a visual experiment platform was built to detection the typical non-standard groove and the welding experiment is implemented to verify the feasibility of the algorithm. According to the path generated by the algorithm, the welded steel components test plate meets the actual engineering standard after quality inspection. The experimental results and simulation results conclude the algorithm can be used to generate the welding path of the non-standard groove.

The applied straightening moment and the springback after unloading with respect to the straightening process of rectangle-section metal bars have a direct influence on the straightening accuracy and efficiency. In this article, an asymmetrical hardening material model is first proposed to describe the stress–strain curves considering the asymmetrical features of yield stress and plastic hardening stage in tension and compression, and it is also compared with the traditional linear hardening material model. To accurately evaluate the elasto-plastic bending deformation and the springback in the straightening process, an analytical model for the loading and unloading moments is then established. The strain and stress distributions in elastic and plastic regions during the straightening process are also discussed in this article. Finally, the straightening experiments of rectangle-section metal bars under different heat-treated conditions are conducted on the ROSE-JZ50 straightening machine with displacement sensors, force sensors and strain gauges to validate the proposed analytical straightening model.

The cross-sectional shape of a linear guideway has been processed before the straightening process. The cross-section features influence not only the position of the neutral axis, but also the applied and residual stresses along the longitudinal direction, especially in a multi-step straightening process. This paper aims to present an analytical model based on elasto-plastic theory and three-point reverse bending theory to predict straightening stroke and longitudinal stress distribution during the multi-step straightening process of linear guideways. The deviation of the neutral axis is first analyzed considering the asymmetrical features of the cross-section. Owing to the cyclic loading during the multi-step straightening process, the longitudinal stress curves are then calculated using the linear superposition of stresses. Based on the cross-section features and the superposition of stresses, the bending moment is corrected to improve the predictive accuracy of the multi-step straightening process. Finite element analysis, as well as straightening experiments, have been performed to verify the applicability of the analytical model. The proposed approach can be implemented in the multi-step straightening process of linear guideways with similar cross-sectional shape to improve the straightening accuracy.

Finding a reliable quality inspection system of resistance spot welding (RSW) has become a very important issue in the automobile industry. In this study, improvement in the quality estimation of the weld nugget&rsquo, s surface on the car underbody is introduced using image processing methods and training a fuzzy inference system. Image segmentation, mathematical morphology (dilation and erosion), flood fill operation, least-squares fitting curve and some other new techniques such as location and value based selection of pixels are used to extract new geometrical characteristics from the weld nugget&rsquo, s surface such as size and location, shape, and the numbers and areas of all side expulsions, peaks and troughs inside and outside the fusion zone. Topography of the weld nugget&rsquo, s surface is created and shown as a 3D model based on the extracted geometrical characteristics from each spot. Extracted data is used to define input fuzzy functions for training a fuzzy logic inference system. Fuzzy logic rules are adopted based on knowledge database. The experiments are conducted on a 6 degree of freedom (DOF) robotic arm with a charge-coupled device (CCD) camera to collect pictures of various RSW locations on car underbodies. The results conclude that the estimation of the 3D model of the weld&rsquo, s surface and weld&rsquo, s quality can reach higher accuracy based on our proposed methods.