悬臂梁结构损伤检测仿真研究

以悬臂梁结构为研究对象,针对户外条件下结构损伤检测过程复杂、周期长、检测效果不理想的问题,提出了模态曲率变化率法.通过大型商用有限元软件ABAQUS,建立梁结构有限元模型,基于模态曲率变化率法构建损伤指标,对梁结构进行损伤检测定位,并与模态应变能法的损伤检测效果进行了对比.结果表明:模态曲率变化率法计算过程简单,能够准确快捷地对悬臂梁结构进行损伤识别定位.     

基于曲率模态振型的刚架结构损伤检测

结构损伤前后动力特性的变化来快速、直接、方便地判定损伤的存在、程度及位置．本文采用曲率模态对刚架结构的损伤检测进行了研究．首先用有限元法计算出结构的位移模态振型,然后用差分法计算出曲率模态振型．数值模拟结果表明：曲率模态振型对结构的损伤敏感,可同时确定结构损伤的存在、程度和位置,并且可以用于结构多位置损伤的检测．实验结果证实了数值模拟结论．     

一种辨识Hammerstein模型的新方法

本文结合参数估计理论和函数逼近论中的一些理论结果,提出了一种开环辨识Hammerstein模型的新方法.这种方法能够克服目前广泛采用的辨识Hammerstein模型的方法中的缺点,获得模型线性动态部分参数的渐近无偏估计及无记忆非线性特性,具有接近最佳逼近效果和较好收敛性的逼近多项式.     

切比雪夫多项式及其插值法在检测中的应用研究

介绍了切比雪夫多项式及其插值算法的实现，结合传感器输出特性的非线性补偿、非线性校正以及检测系统中的复杂计算，分别给出了应用实例。结果表明，这些方法能用于智能传感器系统以及嵌入式微控制器中的软件数据处理，提高检测的实时性和精度，在工程上具有很好的应用价值。     

一种光伏板位置检测系统设计

光伏板一般成片的安装在建筑物的屋顶或者是一些荒凉无遮挡地带,如何有效监测光伏板的安装位置,对于故障的定位和检修,保障系统稳定运行,减少事故的发生具有重要意义。为了实现光伏板位置定位,减少通讯线缆和施工量,该文设计了一种基于PLC的光伏板位置检测系统。每个光伏板安装带有PLC功能的控制器,光伏逆变器通过PLC与各个光伏板控制器之间组网,实现数据交互,逆变器通过4G传输模块将光伏板的位置信息传递给手机等入网设备,实际测试结果表明,系统可准确地获取各个光伏板位置信息,便于故障发生时迅速实现定位。该系统不需要特意安装通讯线缆,可直接通过装置间的电力线实现通讯,大大减少了安装量和安装难度,降低了产品成本,对促进新能源领域的发展具有重要的作用。     

一种深度图像中的表面曲率估计算法

曲率估计在深度图像分析中占有重要地位,传统的有限差分或局部拟合方法未考虑到表面上可能出现的不连续性,因而会不可避免地出现错误,为了得到有效可靠的曲率估计,本文提出了基于自适应局部表面拟合和鲁棒最大似然的估计的曲率估计算法,首先,提出曲面是分片光滑的假设,表面曲率需从该像素所属的光滑曲面片来估计,其次,定义了能量函数来度量拟合窗的平滑度,在局部表面拟合时,依据最小化能量函数的原则来自适应移动拟合窗的中心,以使拟合窗达到最“光滑”,最后,采用鲁棒最大似然估计以消除仍然存在的“局外点”的影响,理论分析和实验结果证明估计算法是稳健,可靠,有效的且计算复杂度小。     

一种暂态电能质量检测新方法的研究

电能质量扰动带来的复杂信号调制特性,使得从电能质量监测数据中提取扰动信号特征依然面临困难。为提高噪声背景下复合电能质量扰动检测准确性,采用自适应无参经验小波变换(APEWT)对扰动信号进行模态分解,进而基于频率加权能量算子(FWEO)对单模态分量进行能量计算,同时通过解调提取用于扰动定位的瞬时频率和幅值特征量。一方面,APEWT中基于自适应频带分割的小波滤波器组输出仅包含有效模态分量,有效避免了模态混叠现象的出现;另一方面,FWEO噪声鲁棒性有效提高了强噪声背景下扰动特征提取的准确性。将算法应用到仿真及实测信号,结果显示该方法能够有效地追踪扰动信号的瞬时变化,且解调得到的瞬时频率和幅值也进一步证明了方法的可行性和有效性。     

一种基于Chebyshev的网络流量异常检测方法

网络安全问题已日趋频繁出现在人们的生产与生活当中,并越来越受到重视。为了能及时有效地预警网络异常,提出一种基于网络流量的异常检测方法,并针对流量数据的特性而采用时间序列的检测方式。在滑动窗口内先对序列进行格拉布斯坏点数据预处理,再利用欧式距离提前判定和切比雪夫多项式系数判定相结合方法,对其进行快速异常检测。仿真实验分析表明:在一定条件下,该算法在保证较好的检测精度的前提下,仍具有较快的检测速度,可以满足实时检测的需要。     

一种过程检测与控制中的保护方法

智能仪表通常以计算机为核心,而计算机在工业过程控制中,由于外部环境及接口复杂,因而干扰源较多,可能会引发计算机“死机”,或程序“飞掉”,或数据被“冲掉”。在经费许可的情况下,可添置附加设备以克服上述问题,诸如滤波器、高抗干扰电源,并采取屏蔽、接地等措施,在布线方式上也有一定的讲究。 然而,干扰是绝对存在的,抑制于扰只是相对而言,很难说完全解决这个问题。因为干扰源的产生、干扰的强弱是个很复杂的问题。因此,我们的目的不在于彻底消除干扰,这样花的代价太大,而是采取如何在干扰危害时,能够保住内存的数据不被破坏,并能迅速从“死机”状态中摆脱出来,继续正常工作。能够作到这一点,在一般情况的工业过程控制中就能不失控。为此,我们采用廉价的单稳态触发器,即可实现这个目的。     

一种在高维空间中聚类检测重复记录的新方法

数据清理是构建数据仓库中的一个重要研究领域。检测相似重复记录是数据清洗中一项非常重要的任务。提出了一种聚类检测相似重复记录的新方法,该方法是基于N-gram将关系表中的记录映射到高维空间中,并且通过可调密度的改进型DBSCAN算法IDS来聚类检测相似重复记录。并用实验证明了这种方法的有效性。     

用于板结构损伤检测的磁致伸缩传感器

基于铁磁性材料的磁致伸缩特性,提出一种用于非铁磁性板结构损伤检测的磁致伸缩传感器。该传感器分为激励和接收两部分,由8字型线圈、镍带以及偏置永磁铁组成。根据磁致伸缩效应,激励部分在板中激励导波,波在板中传播,遇缺陷及边缘反射,通过磁致伸缩逆效应,由接收部分接收其反射信号。根据反射信号的到达时间和波在板中传播的速度,可判断出板中缺陷所在位置。改变恒定偏置磁场与时变磁场的方向可以在板中激励不同波型的导波。实验结果证明:该传感器设计是可行的,且具有价格便宜、灵敏度高、可与被测结构分离等优点。     

A robust locating multi-optima approach for damage identification of plate-like structures

This paper proposes a robust optimization approach for multiple damage identification of plate-like structures. Different from traditional particle swarm optimizations (PSOs), a combined PSO and niche technique (NPSO) is proposed to solve multimodal optimization problems, with the full consideration of subswarm creation, merging and absorbing mechanism. As a hypersensitive parameter to damage, the curvature mode shape is adopted to construct the objective function. Case studies are conducted to investigate the effectiveness and robustness of the algorithm on multi-damage identification. Simulation results show that the proposed algorithm exhibits robust search performance on identifying damage locations accurately with good convergence behavior. It is hoped that this study can provide guidance on robust damage detection, especially when the structure is subject to multiple damages and external disturbances.     

Optimal control of the dynamic state of a thin compound plate

This paper addresses new optimal control problems for dynamic deflections of a thin compound plate with quadratic cost functionals. Theorems on the existence of optimal controls are proved for all the cases considered. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 151–175, July–August 2006.     

A new approach to fuzzy modeling and control for nonlinear dynamic systems: Neuro-fuzzy dynamic characteristic modeling and adaptive control mechanism

The study on nonlinear control system has received great interest from the international research field of automatic engineering. There are currently some alternative and complementary methods used to predict the behavior of nonlinear systems and design nonlinear control systems. Among them, characteristic modeling (CM) and fuzzy dynamic modeling are two effective methods. However, there are also some deficiencies in dealing with complex nonlinear system. In order to overcome the deficiencies, a novel intelligent modeling method is proposed by combining fuzzy dynamic modeling and characteristic modeling methods. Meanwhile, the proposed method also introduces the low-level learning power of neural network into the fuzzy logic system to implement parameters identification. This novel method is called neuro-fuzzy dynamic characteristic modeling (NFDCM). The neuro-fuzzy dynamic characteristic model based overall fuzzy control law is also discussed. Meanwhile the local adaptive controller is designed through the golden section adaptive control law and feedforward control law. In addition, the stability condition for the proposed closed-loop control system is briefly analyzed. The proposed approach has been shown to be effective via an example. Recommended by Editor Young-Hoon Joo. This work was jointly supported by National Natural Science Foundation of China under Grant 60604010, 90716021, and 90405017 and Foundation of National Laboratory of Space Intelligent Control of China under Grant SIC07010202. Xiong Luo received the Ph.D. degree from Central South University, Changsha, China, in 2004. From 2005 to 2006, he was a Postdoctoral Fellow in the Department of Computer Science and Technology at Tsinghua University. He currently works as an Associate Professor in the Department of Computer Science and Technology, University of Science and Technology Beijing. His research interests include intelligent control for spacecraft, intelligent optimization algorithms, and intelligent robot system. Zengqi Sun received the bachelor degree from Tsinghua University, Beijing, China, in 1966, and the Ph.D. degree from Chalmers University of the Technology, Gothenburg, Sweden, in 1981. He currently works as a Professor in the Department of Computer Science and Technology, Tsinghua University. His research interests include intelligent control of robotics, fuzzy neural networks, and intelligent flight control. Fuchun Sun received the Ph.D. degree from Tsinghua University, Beijing, China, in 1998. From 1998 to 2000, he was a Postdoctoral Fellow in the Department of Automation at Tsinghua University, where he is currently a Professor in the Department of Computer Science and Technology. His research interests include neural-fuzzy systems, variable structure control, networked control systems, and robotics.     

Dynamic response of gravity dam model with crack and damage detection

Gravity dam is a typical structure that has been frequently used in the fields of water conservancy engineering, and the safety of the structure has received widespread attention recently. Due to earthquakes or other reasons, gravity dams normally have damage such as cracks in practical service. Damage in the structures can alter the structural dynamic behavior and seriously affect structural performance. Maintaining safety and integrity of the gravity dam structures requires a better understanding of dynam...     

Simultaneous fault detection and antisaturated control based on dynamic observer for inverted pendulum control system

This paper focuses on the problem of simultaneous fault detection and antisaturated control for an inverted pendulum control system. The system input is the acting control voltage that generates the force on the cart. However, the acting control voltage is obviously limited by the voltage amplitude. This means that the actuator of the constructed system model is saturated. Hence, the detector/controller unit produces two signals: the detection and antisaturated control. In this process, the effects of disturbances and noises on detection and control purposes need to be suppressed. Finally, two simulation examples verify the effectiveness of the method.     

一种无线传感器网络目标检测动态阈值算法

介绍了无线传感器网络目标检测基本流程;着重分析了无线传感器网络在实际应用中每个传感器自身存在目标检测范围差异的问题;针对这种情况下的无线传感器网络目标检测问题,提出了一种传感器本地决策阈值的动态算法;最后通过仿真实验,比较了动态阈值算法与其他三种目标检测算法的目标检测误报率。仿真结果表明,提出的动态阈值算法具有较低的检测误报率。