Analysis of SNR for Acoustic Vector Sensor Linear Array in Volume and Surface-generated Noise Fields

Acoustic vector sensor consists of pressure and particle velocity sensors,which measure the three-dimensional acoustic particle velocity,as well as the pressure at one location at the same time.By preserving the amplitude and phase information of the pressure and particle velocity,they possess a number of advantages over traditional scalar sensors.Signal-to-noise ratio (SNR) gain (which is often called array gain) is one of such advantages and is always interested by all of us.But it is not unchangeable if the spatial correlation of the noise field varies.Much more important,it is difficult to be given if the noise becomes complex.In this paper,spatial correlation of the vector field of isotropic volume-noise and surface-generated noise has been introduced briefly.Based on the results,the combined SNR output of a vector linear array is investigated and the maximum gain is given in the specified noise.Computer simulation shows that the output of one array in the same noise is not the same in different gestures.And then we find the best gesture through SNR calculation and obtain the biggest gain,which has important meaning to guide how to deploy an array in practice.We also should use the array with respect to the characteristics of the real ambient noise,especially in anisotropic noise field.

Two-Level Linear Clustering Protocol Based on Wireless Sensor Networks

Aiming at the defects of the nodes in the low energy adaptive clustering hierarchy （LEACH） protocol, such as high energy consumption and uneven energy consumption, a two-level linear clustering protocol is built. The protocol improves the way of the nodes distribution at random. The terminal nodes which have not been a two-level cluster head in the cluster can compete with the principle of equivalent possibility, and on the basis of the rest energy of nodes the two-level cluster head is selected at last. The single hop within the cluster and single hop or multiple hops between clusters are used. Simulation experiment results show that the performance of the two-level linear clustering protocol applied to the Hexi corridor agricultural field is superior to that of the LEACH protocol in the survival time of network nodes, the ratio of success, and the remaining energy of network nodes.

A NEW SOLVENT POLYMERIC MEMBRANE pH SENSOR WITH WIDE LINEAR pH RANGE

A new solvent polymeric membrane (SPM)pH2sensor based on 4,4'-bis (N, N-didecylamino)methyl)azobenzene as neutral carricr has been reported. It has excellent pH response characteristics with the linear response range (1.7—13.2)much wider than that of similar SPM pH sensors reported so far. The sensor has a theoretical Nernstian response of 57.4+0.2V/pH(at 20℃)without super—Nernstian response phenomenon.

A Calibration Method Based on Linear InGaAs in Fiber Grating Sensors Interrogation System

In accordance with the characteristics of wavelength shift detection in fiber grating sensor interrogation system,the wavelength interrogation system which uses linear InGaAs as the spectrum receiver is proposed.Orientation of optic spectrum line affects the silt of volume phase grating and size of InGaAs photosensitive unit,thus the calibration method is needed.Based on an analysis of InGaAs imaging model,least square curve fitting method is proposed to detect spectrum wavelength and InGaAs photosensitive unit position.The experimental results show that the methods are effective and the demodulation system precision is improved.

On-Machine Measurement of the Straightness and Tilt Errors of a Linear Slideway Using a New Four-Sensor Method

Although there are some multi-sensor methods for measuring the straightness and tilt errors of a linear slideway, they need to be further improved in some aspects, such as suppressing measurement noise and reducing precondition.In this paper, a new four-sensor method with an improved measurement system is proposed to on-machine separate the straightness and tilt errors of a linear slideway from the sensor outputs, considering the influences of the reference surface profile and the zero-adjustment values. The improved system is achieved by adjusting a single sensor to di erent positions. Based on the system, a system of linear equations is built by fusing the sensor outputs to cancel out the e ects of the straightness and tilt errors. Three constraints are then derived and supplemented into the linear system to make the coe cient matrix full rank. To restrain the sensitivity of the solution of the linear system to the measurement noise in the sensor outputs, the Tikhonov regularization method is utilized. After the surface profile is obtained from the solution, the straightness and tilt errors are identified from the sensor outputs. To analyze the e ects of the measurement noise and the positioning errors of the sensor and the linear slideway, a series of computer simulations are carried out. An experiment is conducted for validation, showing good consistency. The new four-sensor method with the improved measurement system provides a new way to measure the straightness and tilt errors of a linear slideway, which can guarantee favorable propagations of the residuals induced by the noise and the positioning errors.

Using Linear Intersection for Node Location Computation in Wireless Sensor Networks

Knowing the locations of nodes in wireless sensor networks (WSN) is essential for many applications. Nodes in a WSN can have multiple capabilities and exploiting one or more of the capabilities can help to solve the localization problem. In this paper, we assume that each node in a WSN has the capability of distance measurement and present a location computation technique called linear intersection for node localization. We also propose an applied localization model using linear intersection and do some concerned experiments to estimate the location computation algorithm.

Optimization method of linear barrier coverage deployment for multistatic radar

To address the problem of building linear barrier coverage with the location restriction, an optimization method for deploying multistatic radars is proposed, where the location restriction splits the deployment line into two segments. By proving the characteristics of deployment patterns, an optimal deployment sequence consisting of multiple deployment patterns is proposed and exploited to cover each segment. The types and numbers of deployment patterns are determined by an algorithm that combines the integer linear programming(ILP)and exhaustive method(EM). In addition, to reduce the computation amount, a formula is introduced to calculate the upper threshold of receivers’ number in a deployment pattern. Furthermore, since the objective function is non-convex and non-analytic, the overall model is divided into two layers concerning two suboptimization problems. Subsequently, another algorithm that integrates the segments and layers is proposed to determine the deployment parameters, such as the minimum cost, parameters of the optimal deployment sequence, and the location of the split point. Simulation results demonstrate that the proposed method can effectively determine the optimal deployment parameters under the location restriction.

Lookup Table Optimization for Sensor Linearization in Small Embedded Systems

This paper treats the problem of designing an optimal size for a lookup table used for sensor linearization. In small embedded systems the lookup table must be reduced to a minimum in order to reduce the memory footprint and intermediate table values are estimated by linear interpolation. Since interpolation introduces an estimation uncertainty that increases with the sparseness of the lookup table there is a trade-off between lookup table size and estimation precision. This work will present a theory for finding the minimum allowed size of a lookup table that does not affect the overall precision, i.e. the overall precision is determined by the lookup table entries’ precision, not by the interpolation error.

Time Series-, Time-Frequency- and Spectral Analyses of Sensor Measurements in an Offshore Wave Energy Converter Based on Linear Generator Technology

Inside the second experimental wave energy converter (WEC) launched at the Lysekil research site on the Swedish west coast in March 2009 a number of sensor systems were installed for measuring the mechanical performance of the WEC and its mechanical subsystems. One of the measurement systems was a set-up of 7 laser triangulation sensors for measuring relative displacement of the piston rod mechanical lead-through transmission in the direct drive. Two measurement periods, separated by 2.5 month, are presented in this paper. One measurement is made two weeks after launch and another 3 months after launch. Comparisons and correlations are made between different sensors measuring simultaneously. Noise levels are investigated. Filtering is discussed for further refinement of the laser triangulation sensor signals in order to separate noise from actual physical displacement and vibration. Measurements are presented from the relative displacement of the piston rod mechanical lead-through, from magnetic flux in the air gap, mechanical strain in the WEC structure, translator position and piston rod axial displacement and active AC power. Investigation into the measurements in the time domain with close-ups, in the frequency domain with Fast Fourier transform (FFT) and with time-frequency analysis with short time Fourier transform (STFT) is carried out to map the spectral content in the measurements. End stop impact is clearly visible in the time-frequency analysis. The FFT magnitude spectra are investigated for identifying the cogging bandwidth among other vibrations. Generator cogging, fluctuations in the damping force and in the Lorenz forces in the stator are distinguished and varies depending on translator speed. Vibrations from cogging seem to be present in the early measurement period while not so prominent in the late measurement period. Vibration frequencies due to wear are recognized by comparing with the noise at generator standstill and the vibration sources in the generator. It is concluded that a moving average is a sufficient filter in the time domain for further analysis of the relative displacement of the piston rod mechanical lead-through transmission.

Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors

Hand gesture recognition (HGR) is used in a numerous applications,including medical health-care, industrial purpose and sports detection.We have developed a real-time hand gesture recognition system using inertialsensors for the smart home application. Developing such a model facilitatesthe medical health field (elders or disabled ones). Home automation has alsobeen proven to be a tremendous benefit for the elderly and disabled. Residentsare admitted to smart homes for comfort, luxury, improved quality of life,and protection against intrusion and burglars. This paper proposes a novelsystem that uses principal component analysis, linear discrimination analysisfeature extraction, and random forest as a classifier to improveHGRaccuracy.We have achieved an accuracy of 94% over the publicly benchmarked HGRdataset. The proposed system can be used to detect hand gestures in thehealthcare industry as well as in the industrial and educational sectors.

基于线结构光扫描的烟支表面缺陷检测方法研究

在烟支表面缺陷检测时,为解决传统二维图像方法无法获得深度信息的问题,提出一种基于线结构光传感器旋转扫描的检测方法。烟支在两同向辊轮的旋转带动下实现自转,通过线结构光视觉传感器获取物体轴向轮廓线,使用随机采样一致性拟合轮廓线,通过计算原始点到拟合轮廓的距离判断缺陷点。选取某品牌烟支在检测过程中得到的原始数据,其中多组样本的Kappa值均达到0.97,重复性达到99.3%。研究为烟支缺陷检测提供参考。

基于势平衡多伯努利滤波的多传感器纯方位多目标跟踪

被动传感器不主动发射信号,通常仅获得目标的角度量测信息,无法获得径向距离信息,这种仅利用角度量测信息对多目标跟踪的方法称为纯方位多目标跟踪。实际应用中,纯方位多目标跟踪面临三个主要问题:一是由于被动传感器只获取目标的角度量测,导致量测信息不完备;二是量测方程存在高度非线性;三是由于传感器可能接收到杂波等非目标产生的量测,导致量测源不确定。针对上述问题,本文提出一种多传感器贪婪伪线性粒子势平衡多伯努利滤波。首先采用Rao-Blackwell理论将混合目标状态向量分解,将与量测值相关的位置分量视为非线性分量,而与量测值无关的速度分量视为线性分量,并分别采用粒子滤波器(Particle Filter,PF)和卡尔曼滤波器(Kalman Filter,KF)进行处理,从而有效降低粒子滤波采样维度。其次,针对传统粒子采样严重依赖模型的问题,基于伪线性卡尔曼滤波器(Pseudo-linear Kalman Filter,PLKF)设计一种新型粒子采样方法,即利用PLKF和最新量测信息构造重要性密度函数,并对非线性分量进行粒子采样;在更新阶段采用贪婪量测划分策略选取最优量测集合,并利用最优量测集合中量测信息实现多目标状态集中式融合估计。最后,通过仿真结果验证,本文所提滤波器能在杂波环境中仅利用角度量测对目标进行有效稳定的跟踪,相较于对比方法,所提滤波器能够更为准确估计目标数量和状态。

低轨星座传感器资源调度的自主任务规划建模方法

低轨星座传感器资源的优化调度是复杂多约束下的任务规划问题,为了满足多个运动目标全程跟踪与监视的资源实时优化调度需求,提出一种星上自主快速求解的规划模型.在对自主任务规划问题进行详细建模的基础上,考虑各项约束条件与优化因素,将原问题转化成简易的0-1线性整数规划模型,并构建多目标跟踪试验场景对所提方法进行了仿真验证.仿真结果表明,基于简易规划模型的资源调度可实现多目标的全程跟踪与监视.

基于手机传感器识别行人步态的PSO-ELM算法

针对因手机携带位置不同对传感器产生干扰而导致行人步态识别准确率降低的问题,提出了一种粒子群优化极限学习机(PSO-ELM)识别算法。首先,基于极限学习机(ELM)分类方法,借助分层ELM多层降维的特点,利用粒子群优化算法对ELM算法参数进行寻优,设计有效识别行人手机携带位置的分层PSO-ELM分类方法。然后,通过线性判别分析的降维算法和PSO-ELM完成对行人步态的有效识别。实验使用Android手机对五种携带位置四种步态下的加速度和角速度数据进行采集,结果表明:在识别手机携带位置层面,训练集与测试集的识别准确率分别达到99.54%、99.47%;在识别行人步态层面,两种准确率分别达到95.74%、95.31%,证明所提算法具有较高的步态识别准确率。

基于自适应小波回声神经网络的光纤陀螺测角仪温度误差补偿技术

基于光纤陀螺的测角仪可以实现对各项角运动参数的一体化动态精密测量,但在实际应用中,光纤陀螺测角仪受到温度变化的影响,导致测量精度下降。针对这一问题,本文提出了一种基于自适应小波回声神经网络的光纤陀螺测角仪温度误差补偿技术。为了提高温度误差建模的进度,提高传统神经网络的逼近能力,通过自适应前向线性预测滤波器对建模用测角仪温度漂移数据进行预处理,并采用自适应小波回声神经网络建立温度漂移模型,能够避免传统神经网络结构设计的盲目性和局部最优等问题,增强了网络学习能力和泛化能力,并利用自适应律代替神经网络梯度进行网络训练,提升神经网络的逼近精度和收敛速度。实验结果表明,该模型可以提高光纤陀螺测角仪的测量精度和环境适应性,为光纤陀螺测角仪的性能优化和实际应用提供了可靠的技术支撑。

LOCALIZATION ALGORITHM USING DISTANCE AND ANGLE INFORMATION IN WIRELESS SENSOR NETWORKS

A localization algorithm using distance and angle information is proposed in wireless sensor networks. Assuming that node axial orientations are unknown, all angles are measured to calculate the angle differences between two nodes viewed by the third one. Then, localization problems are formulated as convex optimization ones and all geometric relationships among different nodes in the communication range are transformed into linear or quadratic constraints. If all measurements are accurate, the localization problem can be formulated as linear programming （LP）. Otherwise, by incorporating auxiliary variables, it can be regarded as quadratic programming （QP）. Simulations show the effectiveness of the proposed algorithm.

纳米银修饰ITO电极快速测定水中吡虫啉

利用恒电压沉积纳米银制备了对吡虫啉响应良好的电化学传感器。采用扫描电镜(SEM)、电化学阻抗谱(EIS)对电极进行了表征。探讨了缓冲液pH、扫描速率、干扰物质对实验结果的影响。研究表明,最佳实验条件(0.01 mol/L、pH=7的PBS缓冲液,扫描速率100 mV/s)下,在10~100μmol/L浓度范围内含吡虫啉线性伏安扫描的还原峰电流与其浓度呈线性关系(R2=0.980 0),LOD值为0.04μmol/L。该修饰电极具有电稳定性良好、可重复使用等一系列优点。对河水的添加回收率为90.05%~103.1%,与液相色谱测定的结果相符,表明该传感器在实际样品检测和环境保护中具有良好的应用前景。

基于电涡流效应的绝对式直线位移传感器误差分析及抑制方法研究

基于电涡流效应的绝对式直线位移传感器具有结构简单、分辨率高、响应速度快和抗干扰能力强的特点。相比于增量式直线位移传感器,该类型的传感器不仅不受断电的影响,还能实现更加快速和精确的绝对定位。但是,传感器制造、安装及电信号处理等环节处理不理想会产生无效电动势,带来对极内的1次、2次和4次误差。针对上述问题,使用信号补偿的方式抑制1次和2次误差,采用空间移相的方式消除感应信号中的3次谐波,以此抑制4次误差。对优化后的传感器进行误差抑制实验,验证了误差来源分析的正确性以及抑制方法的有效性。实验表明:误差抑制后的传感器节距内误差峰峰值由32μm优化为6μm,性能大幅度提升。

高分辨率光纤法珀传感器解调系统设计

光纤法珀传感器的腔长测量精度取决于解调系统的分辨率,现有的解调系统的分辨率多大于10 nm,难以实现10 nm以内腔长变化的测量。针对该问题,提出了以7 450像元数的线阵图像传感器为基础搭建解调系统,通过硬件设计与软件算法提高特征信号质量,完成腔长数据提取,实现了一种高分辨率光纤法珀传感器解调系统。实验结果表明,该系统在0~20μm的腔长测量范围内,实现了2.7 nm的光学分辨率,精度达到0.013 5%FS。

动磁式直线电机定位误差检测与校正

提出一种针对动磁式直线电机定位方案的误差检测及校正的方法。首先,通过相位检测算法检测传感器阵列的相位偏差是否符合要求;然后,通过幅值相位纠正算法实现对磁场数据归一化,并对小幅度相位偏差引起的位置误差进行校正;最后,对数据采集和处理过程中的延时误差进行补偿。对动子运动方向的磁栅尺寸误差补偿后,定位精度达到了±92μm。