徐科军
个性化签名
- 姓名:徐科军
- 目前身份:
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学术头衔:
博士生导师
- 职称:-
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学科领域:
电力系统及其自动化
- 研究兴趣:
徐科军,1956年12月生,工学博士,教授,博士生导师。1988年毕业于中国矿业大学自动化系,获工学博士学位。1989年分配到合肥工业大学电气与自动化工程学院自动化研究所,从事科研、教学和实验室建设工作。1991年任讲师,1992年任副教授,1994年任教授,1995年遴选为博士生导师。1995年分别被机械工业部和安徽省评为首批高校跨世纪学科带头人培养对象。1996年被机械工业部评为中国机械工业青年科技专家。1997年被国家人事部评定为国家“百千万人才工程”人选。1998年获政府特殊津贴,2002年被教育部评为高校优秀骨干教师, 2004年入选安徽省高等学校“十五”优秀人才计划。
主讲过本科生课程3门,硕士研究生课程5门,博士研究生课程2门。指导的研究生在“挑战杯”全国大学生课外科技作品竞赛中获三等奖4项、鼓励奖2项;获2006年美国德州仪器DSP设计大奖赛三等奖;获“徐悲鸿奖学金”、“仪器仪表奖学金”、“亿利达奖学金”、“美的奖学金”和“校十佳科技标兵”等奖励17项,获校优秀硕士毕业论文一等奖1次、二等奖3次。已培养出博士6名,硕士20余名。
近十几年来主持完成和在研国家自然科学基金5项,主持完成和在研“863”计划3项,主持完成省部级项目多项。1998年获国家机械工业局科技进步二等奖(排序一),2004年获安徽省自然科学二等奖(排名第一),2003年获安徽省自然科学三等奖(排序一)1项,1998年获安徽省科技进步四等奖(排序二)1项。在清华大学、电子工业和机械工业等出版社出版著作和教材10部(一作或主编),其中,3本教材入选“十一五”国家级教材。共发表学术论文160余篇,其中,在“IEEE Trans. on IM”、“Review of Scientific Instruments”、“Measurement”、“Sensors and Actuators A” 、“科学通报”、“自动化学报” 和“仪器仪表学报”等小核心刊物上发表论文50多篇,被SCI和EI收录50余篇次,获安徽省自然科学优秀学术论文一等奖2项,二等奖6项,三等奖14项。获国家发明专利6项,实用新型专利3项。担任中国计量测试学会理事,“计量学报”、“光电子.激光”和“Journal of Information Acquisition”杂志编委等学术职务。主持建成合肥工业大学-美国德州仪器数字信号处理方案实验室。
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成果阅读
410
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成果数
7
【期刊论文】Estimation of wrist force/torque using data fusion of finger force sensors
徐科军, Ke-Jun Xu a, *, Qiao-Li Li a, Tao Mei b, Ting Wu a
Measurement 36(2004)11-19,-0001,():
-1年11月30日
This paper proposes a kind of estimation method of wrist force/torque for robots. The method adopts the data fusion technique according to the output variations of the finger force sensors installed in the gripper. The finger force sensors are used to measure the clamping force of the gripper in the design. When the accuracy of measurement is not required exactly and there is the limitation of weight and volume in space robots, we utilize the existing devices to estimate the wrist force/torque without the wrist force/torque sensor, which not only meets the practical requirement but also decreases the weight and cost of robots. An experimental bench is developed and the calibration experiments are conducted to detect the relationship between the wrist force/torque and finger forces. The experimental data are used to train a radial basis function (RBF) artificial neural network, and the construction and parameters of the network are obtained. The results of data fusion of the wrist force/torque are consistent with the practical calibration values, and the effectiveness of the wrist force/torque estimating technique is proved.
Wrist force and torque, Finger force sensor, Estimation, Multi-sensor data fusion, Artificial neural network
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徐科军, Ke-Jun Xu a) and Lin Jia
Rev. Sci. Instrum., Vol. 73, No.4, April 2002,-0001,():
-1年11月30日
There is nonlinearity in the dynamic characteristics of sensors under some conditions. Previous researchers have presented the nonlinear dynamic models of sensors only using a block, which make it difficult to compensate the nonlinear dynamic responses of sensors. In this article a Hammerstein model is adopted to describe the nonlinear dynamic models of sensors, and a one-stage identification algorithm is proposed to simplify the calculation. On this basis a two-step compensation method is presented for the nonlinear dynamic responses of sensors. The one-stage identification algorithm has advantages as follows: (1) One-stage identification simplifies the algorithm; (2) it depends only on the data of input and output of the system, and does not need to introduce auxiliary variables that could not be measured in practice; (3) it only needs dynamic calibration experimental data of systems, and does not need to do static calibration experiments. The simulation results and its application in the wrist force sensor show the methods proposed by this article are effective.
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【期刊论文】Adaptive notch filter-based signal processing method and system for vortex flowmeters
徐科军, Ke-Jun Xu, a), An-Min Wang, and Xun-Hong Lv
Rev. Sci. Instrum., Vol. 72, No.4, April 2001,-0001,():
-1年11月30日
In this Note the vortex sensor signal is modeled as a narrow band process, and the frequency of the vortex sensor signal is measured by the means of adaptive notch filtering. A real time processing system based on a digital signal processor is developed. The testing results show that the adaptive notch filtering method and the processing system are effective for vortex flowmeters.
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徐科军, 李成, 朱志能, 刘家军
自动化学报,2001,27(5):705~709,-0001,():
-1年11月30日
为了提高机器人腕力传感器的动态响应速度,在对传感器进行动态标定实验的基础上,采用FLANN方法设计动态补偿器,以DSP为处理核心,研制实时动态补偿系统。实验结果表明,经过补偿腕力传感器动态响应的调整时间缩短为原来的25%以下。
腕力传感器,, 动态补偿,, 函数联接型神经元网络,, 数字信号处理器.,
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【期刊论文】Dynamic Decoupling and Compensating Methods of Multi-Axis Force Sensors
徐科军, Ke-Jun Xu and Cheng Li
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 49, NO.5, OCTOBER 2000,-0001,():
-1年11月30日
Dynamic decoupling and compensating methods of multi-axis force sensors are proposed to solve simultaneously the dynamic coupling between axes and the slow dynamic response which are the two key problems in dynamic characterizing of the multi-axis force sensors and improve their dynamic quality. Four types of dynamic decoupling and compensating networks are shown, the design equations and procedures are presented, and the parameters of the networks are determined using a method based on a functional link artificial neural network (FLANN). The dynamic decoupling and compensating results for a wrist force sensor have proved the methods to be correct and effective.
Compensation,, decoupling,, functional link artificial neural network,, multi-axis force sensor.,
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【期刊论文】Dynamic Modeling of Multi-axis Wrist Force Sensor in Time Domain*
徐科军, XU Ke-Jun
CHINESE SCIENCE BULLETIN Vol. 39 No.4 February 1994,-0001,():
-1年11月30日
multi-axis wrist force sensor,, dynamic modeling,, system identification,, time series analysis.,
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【期刊论文】A Pole-zero Offset Method for Sensor's Dynamic Compensation*
徐科军, XU Ke-Jun, TANG Ting
CHINESE SCIENCE BULLETIN Vol. 39 No.16 August 1994,-0001,():
-1年11月30日
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