振动板声辐射模态伴随系数的测量

以工程常见四端位移为零的振动板为例,提出一种新的压电式传感器的设计方法测量第一阶声辐射模态伴随系数．利用特定形状的PYDF（Polyvinylidene fluoride聚偏氟乙烯）薄膜作为误差传感器,使PVDF输出信号为所需要的第一阶声辐射模态伴随系数．结果表明PVDF传感器不仅适用四边简支,四边固定以及介于两者之间的边界条件板结构,而且所设计的PVDF形状作为误差传感器对振动结构表面振速分布变化十分敏感．试验数据表明利用PVDF传感器测量振动结构第一阶声辐射模态伴随系数是可行的。     

基于多传感器信息融合的车速估计方法

准确地测量计算车辆的纵横向速度是现代汽车控制系统的关键,在横摆角速度传感器、加速度计和车轮角速度传感器等多种汽车传感器所测得的信号基础上建立估计系统的状态方程和测量方程,通过汽车动力学模型计算出车辆的纵横向参考速度,最后用卡尔曼滤波技术对车速进行估计.并对参考车速误差的影响进行分析.仿真结果表明该方法估计效果好,误差小,具有可靠性和有效性.     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

工业现场LED数据显示屏系统的开发

分析工业现场LED数据显示屏主要是将各种类型传感器采集的数据，提出利用数据采集转换芯片，或者利用接口传送到LED显示屏上，进行数据的实时显示方案。     

基于DV-Hop误差修正的煤矿井下人员定位算法

为了提高无线传感器网络的节点定位精度,提出了基于DV-Hop误差修正的质心定位算法.针对煤矿井下巷道的线型结构,首先提出信标节点以均匀间隔交叉分布的模型,再根据各个信标节点平均每跳的距离误差以及平均每跳的单位距离误差,对离未知节点最近的3个信标节点之间的距离进行2次修正,最后利用3圆交点的质心定位算法进行定位.仿真结果表明,该算法比目前的定位精度提高1m左右,比较适合煤矿井下这种特定的线型结构.     

Principle and Realization Method of Tunnel Deformation Detection Based on Image Recognition and Data Transmission Technology

<正>To detect the deformation of the tunnel structure based on image sensor networks is the advanced study and application of spatial sensor technology.For the vertical settlement of metro tunnel caused by internal and external stress after its long period operation,the overall scheme and measuring principle of tunnel deformation detection system is introduced. The image data acquisition and processing of detection target are achieved by the cooperative work of image sensor,ARM embedded system.RS485 communication achieves the data transmission between ARM memory and host computer.The database system in station platform analyses the detection data and obtains the deformation state of tunnel inner wall,which makes it possible to early-warn the tunnel deformation and take preventive measures in time.     

基于Elman神经网络的无线传感器网络测距模型

以无线传感器网络为研究对象，在无线传感器网络覆盖范围内的不同距离内采集信号强度值，利用Elman神经网络建立信号强度值与距离之间的映射关系，将采集到的信号强度作为模型的输入进行训练，利用训练好的网络模型进行测距，结果表明具有良好的网络测距性能。     

Influence of Node Dynamics on Cluster Global Time Continuity

The cluster global time can change in wireless sensor networks due to leader re-elections and node disabilities between two successive synchronizations,which will affect temporal relationships.This paper analyzes cluster global time continuity,using global time change models for the node dynamics.The results prove that defining the global time using the cluster average time(AGT) is more stable than defining it using a single node’s local time(SGT).With normally distributed clock-parameter assumptions,the AGT change bounds are at most 70.7% of those for the SGT’s.The impacts of the initial phase and frequency skew distributions on the global time continuity are also investigated to show that the initial phase variations may strongly influence the continuity.Simulations show that the AGT is more stable with less disabled nodes or larger clusters.The appropriate cluster size is 20-40 when there are less than 15 disabled nodes.     

基于NE555时基电路的人体红外遥感开关的设计

研究利用NE555时基电路及人体热释电传感器设计一款遥控开关,利用人体辐射的红外线控制照明灯的亮灭,替代现在的声控开关,满足照明场所临时短时间的照明要求.