基于三轴加速度传感器的倾角测量系统的设计

基于美国AD公司ADXL345三轴加速度传感器,设计了一个以C8051F040单片机为核心的实时倾角测量系统,详细分析了模块的硬件实现以及软件实现方法。经实验结果表明,此系统结构简单,能够实时检测并显示倾角,具有较好的稳定度和精确度,实际应用中效果良好。     

Segmentation and recognition of human motion sequences using wearable inertial sensors

Multimedia Tools and Applications - The application of human motion monitoring technology based on wearable inertial sensors has achieved great success in the last ten years. But now the research...     

Development of new encryption system using Brownian motion based diffusion

Multimedia Tools and Applications - A new cryptographic model is proposed incorporating intertwining logistic map based confusion process and two dimensional Brownian Motion based diffusion...     

A novel method for estimating the heading angle for a home service robot using a forward-viewing mono-camera and motion sensors

International Journal of Control, Automation and Systems - This paper presents a novel method for estimating the heading angle of a home service robot. The images captured from a forward viewing...     

Development of smart sensors system for machine fault diagnosis

Machine fault diagnosis is a traditional maintenance problem. In the past, the maintenance using tradition sensors is money-cost, which limits wide application in industry. To develop a cost-effective maintenance technique, this paper presents a novel research using smart sensor systems for machine fault diagnosis. In this paper, a smart sensors system is developed which acquires three types of signals involving vibration, current, and flux from induction motors. And then, support vector machine, linear discriminant analysis, k-nearest neighbors, and random forests algorithm are employed as classifiers for fault diagnosis. The parameters of these classifiers are optimized by using cross-validation method. The experimental results show that smart sensor system has the similar performance for applying in intelligent machine fault diagnosis with reduced product cost. Developed smart sensors have feasibility to apply for intelligent fault diagnosis.     

Tracking vision system for real-time motion analysis

This paper describes a high-speed motion tracking system based on full-search correlation matching. Incorporating the Advanced Correlation Processor, which computes more than 500 motion vectors per frame, the system enables the detection and tracking of moving objects at a video rate. The system is implemented on a single board and can be mounted inside a PC. Thus, it is compact and economical, and is well suited for a wide variety of applications such as automatic surveillance, traffic monitoring and sports play analysis.     

Analog circuit for motion detection using a CCD camera based on a biological vision system and its application to mobile robots

We have proposed an analog motion detection circuit based on a biological vision system. A charge coupled device (CCD) camera was used as the input in order to obtain an input image. By using the CCD camera, it is possible to detect the movement of an object as a high-resolution image. Because the unit motion detection circuit is constructed with eight metal oxide semiconductor (MOS) transistors and one capacitor, the structure of the unit circuit is simple. The test circuit was constructed on a circuit board using discrete MOS transistors. The results from the test circuit showed that it can detect the direction of motion. The test circuit was connected to a microcomputer in a mobile robot. It was clear from the results that the motion detection circuit can control a mobile robot.     

车辆称重系统中加速度的测量与分析

针对公路运输车辆载荷质量的检测采用的计量器具体积大、工作位置固定、不能做到随时随地检测载荷质量的问题,提出一种采用变极距电容传感器的车载式载荷检测装置,该装置中的加速度传感器用于测量前进方向的加速度和竖直方向的加速度.通过实验测试及分析表明,加速度在车辆称重测量中的影响比较大,因此在装置的软件部分必须予以补偿.     

Development of wall models for LES of separated flows using statistical evaluations

Wall models are the key technology making possible the application of large eddy simulation to flows of engineering interest. In this paper, a new approach to the development of wall models is presented, which, in contrast to classical wall models, relies on a strong physical background and therefore is considered to be able to predict separated flows reliably. The idea is based on the concept of artificial viscosity. It requires definitions of the distribution of the eddy viscosity in the outer layer and the thickness of the viscous sublayer. The second issue is the critical aspect. Applying the artificial viscosity approach to the needs of LES wall modeling is discussed in detail and promising wall models are derived analytically. Statistical evaluations using nonlinear stochastic estimation are carried out in order to determine an important physical dependence involved in the new wall models, namely the ratio of the thickness of the viscous sublayer to the height of the wall-nearest cell. As test cases, the flow in plane channels and over a periodic arrangement of hills is considered. A posteriori results show clearly the advantages of the wall models developed, especially for separated flows.     

Human motion recognition using a wireless sensor-based wearable system

The future of human computer interaction systems lies in how intelligently these systems can take into account the user’s context. Research on recognizing the daily activities of people has progressed steadily, but little focus has been devoted to recognizing jointly activities as well as movements in a specific activity. For many applications such as rehabilitation, sports medicine, geriatric care, and health/fitness monitoring the importance of combined recognition of activity and movements can drive health care outcomes. A novel algorithm is proposed that can be tuned to recognize on-the-fly range of activities and fine movements within a specific activity. Performance of the algorithm and a case study on obtaining optimal features from sensor and parameter values for the algorithm to detect fine motor movements are presented.     

Evaluation of realtime people tracking for indoor environments using ubiquitous motion sensors and limited wireless network infrastructure

We present the development and evaluation of a realtime indoor localisation system for tracking people. Our aim was to track a person’s indoor position using dead-reckoning, while limiting position error without depending on extensive wireless network infrastructure. The Indoor People Tracker used wearable motion sensors, a floor-plan map and a limited wireless sensor network for proximity ranging. We evaluated how the position accuracy of the Indoor People Tracker was affected by floor-plan map features, wireless proximity range and motion information. The advantage of the Indoor People Tracker was found; it was able to achieve accurate position resolution with minimal error, while not depending on wireless proximity.     

Arm motion analysis using genetic algorithm for rehabilitation and healthcare

The worlds population is quickly aging. With an aging society, an increase in patients with brain damage is predicted. In rehabilitation, the analysis of arm motion is vital as various day to day activities relate to arm movements. The therapeutic approach and evaluation method are generally selected by therapists based on his/her experience, which can be an issue for quantitative evaluation in any specific movement task. In this paper, we develop a measurement system for arm motion analysis using a 3D image sensor. The method of upper body posture estimation based on a steady-state genetic algorithm (SSGA) is proposed. A continuous model of generation for an adaptive search in dynamical environment using an adaptive penalty function and island model is applied. Experimental results indicate promising results as compared with the literature.     

飞机迎角、侧滑角传感器图像检测系统的研制

利用图像处理技术，详述了飞机迎角、侧滑角图像的获取、边缘增强的目标分割、亚像素计算、定标误差修正、控制和处理单元的选择、转角电压检测与转换等技术难点的解决。经验证：此方法得到的检测结果稳定可靠、准确度及自动化程度高，代替老式的测角仪，可推广到主机厂、部队、航修厂、院校等单位。     

ECT传感器结构影响分析

设计一种便于分析径向屏蔽结构影响的有限元分析模型,全面分析了电容层析成像(Electrical Capaci-tance Tomography)系统中阵列传感器结构参数对系统性能的影响。在定量分析的基础上合理解释并提出定性的分析结果,为全面认识传感器结构对敏感场分布的影响以及传感器的设计提供依据。有利于深入了解敏感场分布,优化传感器以改善传感器性能。     

Cyclic motion design and analysis for a passive object manipulation using an active plate

We propose a novel scheme for manipulating a passive object using an active plate. In previous studies, cyclic manipulations that transport objects on a plate, position control of an object on a plate, and juggling have been realized. In most manipulations using plates, object motions in the direction of the gravitational force are not considered. The objective of this study is to control an object’s orientation with respect to the gravitational force direction using an active plate for realizing hitherto unrealized object motion. In this context, a tumble doll, which is a planar rigid sphere, is defined as the object. Motions of the object and active plate are designed to be cyclic. A state vector composed of the object’s angle and angular velocity is defined, and the cyclic motion is expressed as a nonlinear discrete system. Fixed points of the state vector are searched for in the designed cyclic motion. A stability analysis around the fixed points is conducted using a Poincaré map. As a result, the fixed points are shown to be asymptotically stable. Finally, experimental results are used to verify that the object’s angle can be manipulated with the designed cyclic motion using the plate.     

Kinematic calibration for collaborative robots on a mobile platform using motion capture system

For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.