A lack of accurate description of the meshing characteristics and the corresponding frictional mechanism of the harmonic drive gear has limited progress toward modeling the hysteresis stiffness. This paper presents a ...A lack of accurate description of the meshing characteristics and the corresponding frictional mechanism of the harmonic drive gear has limited progress toward modeling the hysteresis stiffness. This paper presents a method for detection and quantification of the meshing characteristics of the harmonic drive gear based on computer vision. First, an experimental set-up that integrates a high speed camera system with a lighting system is developed, and the image processing is adopted to extract and polish the tooth profiles of the meshed teeth pairs in each acquired video sequence. Next, a physical-mathematical model is established to determine the relative positions of the selected tooth pair in the process of the gear engagement, and the combined standard uncertainty is utilized to evaluate the accuracy of the calculated kinematics parameters. Last, the kinematics analysis of the gear engagement under the ultra-low speed condition is performed with our method and previous method, and the influence of the input rotational speed on the results is examined. The results validate the effectiveness of our method, and indicate that the conventional method is not available in the future friction analysis. It is also shown that the engaging-in phase is approximately a uniform motion process, the engaging-out phase is a variable motion process, and these characteristics remain unchanged with the variation of the input rotational speed. Our method affords the ability to understand the frictional mechanism on the meshed contact surfaces of the harmonic drive gear, and also allows for the dynamic monitoring of the meshing properties.展开更多
Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in thi...Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in this paper, a distributed real-time auto- surveillance system is presented. The freeway traffic videos are taken as input video from Pan Tilt Zoom （PTZ） camera, and then produces an analysis of the states and activity of the vehicles in the region of interested （ROI）, if there is any abnormal instance, an alarm and corresponding traffic video are sent to awake surveillants by Ethernet. To achieve this functionality, our system relies on three main procedures. The first one initializes the system. It detects the ROI of the scene, and performs the camera calibration to remove the perspective effect of the incoming image. The second one segments moving vehicles from the images, eliminate shadow and tracks them real-time. It uses a set of methods to obtain the background of the image, extracts the moving regions and tracks these moving regions by matching them between frames of the video sequence to obtain high-level information such as color, size, velocity, and trajectories of moving vehicles. In the third procedure, activities of vehicles are analyzed based on a series of preset situations which would happen on freeway. The detail information of each vehicle and the global statistical information are checked to find out any abnormal instance, and then triggered an alarm. We present details of the system, together with experiment results which demonstrate the accuracy and time responses.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11272171)the Beijing Natural Science Foundation(Grant No.3132030)the Education Ministry Doctoral Fund of China(Grant No.20120002110070)
文摘A lack of accurate description of the meshing characteristics and the corresponding frictional mechanism of the harmonic drive gear has limited progress toward modeling the hysteresis stiffness. This paper presents a method for detection and quantification of the meshing characteristics of the harmonic drive gear based on computer vision. First, an experimental set-up that integrates a high speed camera system with a lighting system is developed, and the image processing is adopted to extract and polish the tooth profiles of the meshed teeth pairs in each acquired video sequence. Next, a physical-mathematical model is established to determine the relative positions of the selected tooth pair in the process of the gear engagement, and the combined standard uncertainty is utilized to evaluate the accuracy of the calculated kinematics parameters. Last, the kinematics analysis of the gear engagement under the ultra-low speed condition is performed with our method and previous method, and the influence of the input rotational speed on the results is examined. The results validate the effectiveness of our method, and indicate that the conventional method is not available in the future friction analysis. It is also shown that the engaging-in phase is approximately a uniform motion process, the engaging-out phase is a variable motion process, and these characteristics remain unchanged with the variation of the input rotational speed. Our method affords the ability to understand the frictional mechanism on the meshed contact surfaces of the harmonic drive gear, and also allows for the dynamic monitoring of the meshing properties.
文摘Video based surveillance systems have been widely used on freeway for traffic monitoring, as the cameras can provide the most intuitionistic information. In order to manage all the traffic videos automatically, in this paper, a distributed real-time auto- surveillance system is presented. The freeway traffic videos are taken as input video from Pan Tilt Zoom （PTZ） camera, and then produces an analysis of the states and activity of the vehicles in the region of interested （ROI）, if there is any abnormal instance, an alarm and corresponding traffic video are sent to awake surveillants by Ethernet. To achieve this functionality, our system relies on three main procedures. The first one initializes the system. It detects the ROI of the scene, and performs the camera calibration to remove the perspective effect of the incoming image. The second one segments moving vehicles from the images, eliminate shadow and tracks them real-time. It uses a set of methods to obtain the background of the image, extracts the moving regions and tracks these moving regions by matching them between frames of the video sequence to obtain high-level information such as color, size, velocity, and trajectories of moving vehicles. In the third procedure, activities of vehicles are analyzed based on a series of preset situations which would happen on freeway. The detail information of each vehicle and the global statistical information are checked to find out any abnormal instance, and then triggered an alarm. We present details of the system, together with experiment results which demonstrate the accuracy and time responses.
