Novel Real-Time Seam Tracking Algorithm Based on Vector Angle and Least Square Method

Real-time seam tracking can improve welding quality and enhance welding efficiency during the welding process in automobile manufacturing.However,the teaching-playing welding process,an off-line seam tracking method,is still dominant in automobile industry,which is less flexible when welding objects or situation change.A novel real-time algorithm consisting of seam detection and generation is proposed to track seam.Using captured 3D points,space vectors were created between two adjacent points along each laser line and then a vector angle based algorithm was developed to detect target points on the seam.Least square method was used to fit target points to a welding trajectory for seam tracking.Furthermore,the real-time seam tracking process was simulated in MATLAB/Simulink.The trend of joint angles vs.time was logged and a comparison between the off-line and the proposed seam tracking algorithm was conducted.Results show that the proposed real-time seam tracking algorithm can work in a real-time scenario and have high accuracy in welding point positioning.

Assessment on the Water Resources Carrying Capacity in Karst Area Based on the Cosine Vector Included Angle

[Objective] The research aimed to assess the water resources carrying capacity in Guizhou Province based on the cosine vector included angle method. [Method] By using the cosine vector included angle method, the index weight was determined. The projection value of water resources carrying capacity in Guizhou Province was counted by using the multi-objective gray relational projection method. Moreover, the projection value which was counted by the index weight determined by the mean-variance method was as the control. [Result] The projection values which were obtained by two kinds of methods were very close, and the ordering result was consistent. [Conclusion] In the assessment of water resources carrying capacity, it was feasible to use the cosine vector included angle method to determine the index weight.

Rapid vision-based system for secondary copper content estimation

A vision-based color analysis system was developed for rapid estimation of copper content in the secondary copper smelting process. Firstly, cross section images of secondary copper samples were captured by the designed vision system. After the preprocessing and segmenting procedures, the images were selected according to their grayscale standard deviations of pixels and percentages of edge pixels in the luminance component. The selected images were then used to extract the information of the improved color vector angles, from which the copper content estimation model was developed based on the least squares support vector regression (LSSVR) method. For comparison, three additional LSSVR models, namely, only with sample selection, only with improved color vector angle, without sample selection or improved color vector angle, were developed. In addition, two exponential models, namely, with sample selection, without sample selection, were developed. Experimental results indicate that the proposed method is more effective for improving the copper content estimation accuracy, particularly when the sample size is small.

Wind rotation characteristics of the upper tropospheric monsoon over the central and eastern tropical Pacific

In this study, to investigate whether the variation of wind direction in the upper tropospheric monsoon over the central and eastern tropical Pacific shows similar characteristics to the classical monsoon region, the authors introduced a wind vector angle methodology that describes the size of the angle of the wind direction variation, as well as the directed rotary angle, which includes not only the size of the angle but also how the wind vector rotates. On this basis, the authors utilized and improved the directed rotary angle methodology to investigate the evolution of wind direction in detail, and the study confirmed the presence of the same four rotation features in the upper tropospheric monsoon region. Furthermore, the authors also identified the precise variation of wind direction in pentads with seasonal evolution, and found the onset time of the upper tropospheric monsoon may be earlier than the classical monsoon while the termination time may be later. The results further support and supplement the theory of global monsoons, which unifies the low-level and upper tropospheric monsoon as one monsoon system.

Missing Data Imputation for Traffic Flow Based on Improved Local Least Squares

Complete and reliable field traffic data is vital for the planning, design, and operation of urban traf- fic management systems. However, traffic data is often very incomplete in many traffic information systems, which hinders effective use of the data. Methods are needed for imputing missing traffic data to minimize the effect of incomplete data on the utilization. This paper presents an improved Local Least Squares （LLS） ap- proach to impute the incomplete data. The LLS is an improved version of the K Nearest Neighbor （KNN） method. First, the missing traffic data is replaced by a row average of the known values. Then, the vector angle and Euclidean distance are used to select the nearest neighbors. Finally, a regression step is used to get weights of the nearest neighbors and the imputation results. Traffic flow volume collected in Beijing was analyzed to compare this approach with the Bayesian Principle Component Analysis （BPCA） imputation ap- proach. Tests show that this approach provides slightly better performance than BPCA imputation to impute missing traffic data.

Robust multi-objective optimization of rolling schedule for tandem cold rolling based on evolutionary direction differential evolution algorithm

According to the actual requirements,profile and rolling energy consumption are selected as objective functions of rolling schedule optimization for tandem cold rolling.Because of mechanical wear,roll diameter has some uncertainty during the rolling process,ignoring which will cause poor robustness of rolling schedule.In order to solve this problem,a robust multi-objective optimization model of rolling schedule for tandem cold rolling was established.A differential evolution algorithm based on the evolutionary direction was proposed.The algorithm calculated the horizontal angle of the vector,which was used to choose mutation vector.The chosen vector contained converging direction and it changed the random mutation operation in differential evolution algorithm.Efficiency of the proposed algorithm was verified by two benchmarks.Meanwhile,in order to ensure that delivery thicknesses have descending order like actual rolling schedule during evolution,a modified Latin Hypercube Sampling process was proposed.Finally,the proposed algorithm was applied to the model above.Results showed that profile was improved and rolling energy consumption was reduced compared with the actual rolling schedule.Meanwhile,robustness of solutions was ensured.