Chunnian Zeng

The Effect of Spray Distance and Scanning Step on the Coating Thickness Uniformity in Cold Spray Process

In the process of cold spray applications, robot kinematic parameters represent significant influences on the coating quality. Those parameters include: spray distance, spray angle, gun relative velocity to substrate, scanning step, and cycle numbers. The combined effects which are caused by their interactions determine the coating thickness. The increasing requirements of coating productivity lead to the objectivity of analyzing the effect of robot kinematic parameters. So it becomes necessary to optimize the robot trajectory for spraying process in order to obtain a desired coating thickness. This study aims at investigating the relationship between the coating profile and the spray distance, scanning step, and introducing the basic principle of a software toolkit named thermal spray toolkit (TST) developed in our laboratory to generate the optimized robot trajectories in spray processes including thermal spray and cold spray. Experiments have been carried out to check the reliability of the simulated coating profile and the calculated coating thickness by TST.

Computer-Aided Robot Trajectory Auto-generation Strategy in Thermal Spraying

This paper is concerned with a new methodology which is designed to auto-generate the robotic trajectory for thermal spraying process. Based on it, a software package named Thermal Spray Toolkit is developed and integrated in the main frame of off-line programming software RobotStudio™ (Product of ABB Company, Sweden). This toolkit implements the robotic trajectory planning in an interactive manner between RobotStudio™ and the finite element analysis software (FES). It allows rearranging the imported node index created on the surface of workpiece by FES and in turn generating the thermal spraying needed robot trajectories. Several parameters in thermal spraying, such as scanning step and torch-substrate relative velocity which have major influence on the coating deposition, are considered in the trajectory generation process. Experiment is carried out to check the reliability of the generated robot trajectory.

A Global Approach to the Optimal Trajectory Based on an Improved Ant Colony Algorithm for Cold Spray

AbstractnThis paper is concerned with finding a global approach to obtain the shortest complete coverage trajectory on complex surfaces for cold spray applications. A slicing algorithm is employed to decompose the free-form complex surface into several small pieces of simple topological type. The problem of finding the optimal arrangement of the pieces is translated into a generalized traveling salesman problem (GTSP). nOwing to its high searching capability and convergence performance, an improved ant colony algorithm is then used to solve the GTSP. Through off-line simulation, a robot trajectory is generated based on the optimized result. The approach is applied to coat real components with a complex surface by using the cold spray system with copper as the spraying material.

A visual target tracking algorithm based on improved Kernelized Correlation Filters

Visual target tracking is one of fundamental research of computer vision field and play an important role in the surveillance application, but it is also one of the difficulties due to the instability of the tracking scene. In this paper, we analyze the major drawbacks of the original Kernelized Correlation Filter (KCF) tracker which causes tracking failure when target experience complicated scenarios such as deformation, heavy occlusion and scale variations. In order to alleviate these drawbacks, we propose an improved KCF tracker, The tracker adopts a cascade classifier which composed by Multi-scale correlation filter and NN classifier. In each frame the tracking results are estimated by the relative variation of the target size. Experimental results of benchmark sequences show that the proposed algorithm has favorably performance against state-of-the-art methods of accuracy and robustness.

A wavelet transform based power allocation strategy for lithium battery and ultra capacitor hybrid vehicular power system

Hybridization of battery with other energy storage devices, such as Ultra-Capacitors (UC) are often equipped in vehicular applications, therefore a well-designed Energy Management Strategy (EMS) is necessary for it can be effective for power sharing between the lithium battery and UC. This paper puts forward a wavelet transform based power allocation strategy for the EMS of Hybrid Electrical Vehicles (HEV). The original power demand signal is decomposed by wavelet transform into high frequency and low frequency components, and then the decomposed power demands are allotted to the lithium battery and UC respectively according to their output characteristics. The developed strategy is validated by a typical HEV model in ADVISOR, the experiment result shows that the wavelet transform based power allocation strategy can dramatically improve the efficiency of the overall system, which helps minimizing the waste of energy and enhancing the transient performance of HEV.

Performance evaluation of binary descriptors for mobile robots

Mobile robot technology has been one of the most promising topics recently. As the basis of mobile robots, object recognition has important research significance to perceive environments. Float-point descriptors like SIFT are widely used for object recognition, but need large storage and computational costs. To overcome the limitations of float-point descriptors applied to mobile robots, binary descriptors are put forward. Since the property of object recognition algorithms can be affected by the selection of descriptors, evaluation of different descriptors to compare performance of them is necessary. However, evaluation of up-to-date binary descriptors for mobile robots is lack. In this paper, an evaluation of several algorithms based on binary descriptors i.e. BRIEF, ORB, BRISK and FREAK on a mobile robot object recognition dataset is provided. To find an efficient descriptor for mobile robots, some typical performance metrics are used to analyze the results of evaluation. And an improved object recognition strategy is presented. It can enhance the performance of binary descriptors for object recognition of mobile robots. This paper can provide a practical reference for researchers in this field.

Adaptation of the object recognition method based on random ferns for mobile robots

Due to the rapid development of the mobile robot technology, the vision-based object perception in changing scenes is of great practical significance. However, visual object recognition algorithms in constrained scenes, such as low image resolution, motion blur and background clutter is lacking. In this study, the performance of a representative object recognition algorithm called random ferns was evaluated on the mobile robot dataset. Meanwhile, some parameters of the random ferns are modified according to the characteristics of mobile robots, and then the effects of each parameter are analyzed to explore the relations to the final object recognition. The results show the adaptation of the random ferns object recognition for mobile robots was successful and provided a good reference for further application of the algorithm for mobile robots.

A fast object segmentation method for mobile robots based on improved depth information

Due to the rapid development of mobile robots technology, the object recognition is of great practical significance. The real-time performance and robustness of object segmentation in cluttered environments is a considerable problem in robot vision. In this paper, a new object segmentation method using depth information is presented. Firstly, this approach obtains the object candidate region using the depth clue, then accomplished the depth filtering in the object candidate region. Next, the object region is extended to get the better edge information. Finally, the foreground is extracted and the segmentation results is realized on the color image. This method of object segmentation was tested on a real mobile robot platform and the results of experiments confirmed the excellent performance of the proposed method.

Mesh-based trajectories generation strategy and thermal distribution analysis in thermal spraying

The strategy of robot trajectory generation is still an experience issue in industry applications. This paper introduces a mesh-based method to generate different patterns of trajectory for thermal spraying applications. In this method, the appropriate mesh is generated on the coating surface of model in CATIA, the mesh information including the node index, position and orientation is then imported into an off-line programming software RobotStudioTM (Product of ABB Company, Swiss) by a secondary development user interface. In the environment of RobotStudioTM, robot targets are generated according to the mesh information and user-defined robot relative parameters. The different trajectory patterns formed by varied execution order of robot targets are simulated in RobotStudioTM. By analyzing the real time speed of Tool Center Point (TCP), the most appropriate trajectory can be determined. Finally, the recorded TCP speed is considered as the displacement of thermal source in ANSYS, the thermal distribution of the workpiece during the thermal spray process is analyzed accordingly in this article.

A robot trajectory sample algorithm for optimizing thermal spraying torch velocity on the complex surface

During the process of thermal spray applications, the spray torch is usually driven by the robot, and its movements are in turns controlled by robot trajectories. The increasing requirements of coating productivity lead to the objectivity of generating robot trajectories on the complex surface. However, when the spray torch moves in a constant given torch velocity, the large curvature change of the coating surface will cause the sudden transition of one or several robot axes and thus lead to the undulation of torch velocity. This study aims at introducing a new trajectory point sample algorithm for optimizing the robot trajectory, and thus leads to desired torch velocity. Thermal distribution analysis of the thermal spray process is carried out to check the reliability of the optimization algorithm and the optimized robot trajectory.