Stabilized fiber-optic extrinsic Fabry–Perot sensor system for acoustic emission measurement

A fiber-optic Fabry–Perot (F–P) acoustic emission (AE) sensor system based on an improved double wavelength stabilization technique is described. Without stabilization, the sensor system drifts out of quadrature due to the presence of low-frequency dynamic strains. The stabilization is achieved by using a dense wavelength division multiplexer (DWDM) to generate two quadrature phase-shifted output signals. An optimum model of double wavelength stabilization is established. The filtering wavelengths of DWDM are calculated using an optimization design method. The performance of the developed sensor system was verified by two preliminary tests. One was a test on the stabilization of operating point of fiber-optic F–P sensor, and other was the detection of simulated AE signals generated by the impact and pencil lead breaking. The test results demonstrate that simulated AE signals are successfully detected using this stabilized sensor system, which solves the fade-out problem.     

基于小波概率估计的图像融合方法研究

在研究了已有的图像融合方法后,提出基于小波变换和最大似然概率估计(MLE)相综合的融合方法,利用概率估计融合模型,首先对不同的传感器图像进行小波分解,然后对相应的子带求解仿射变换参数,根据Bayes规则进行最大后验概率似然估计,得到估计子带系数,最后通过小波反变换得到融合图像.在仿射变换的假设条件下定义融合规则,更适合传感器图像具有局部相反对比度的情况,采用此方法对航空可见光图像和红外图像进行融合实验,其结果与采用其它方法进行了对比,表明该方法的有效性.     

An uncertain information fusion method based on possibility theory in multisource detection systems

In multisource detection systems, the information representing detection characteristics is uncertain, also the relationship between detection characteristics and detection performance has uncertainty, meanwhile the influence degrees of each characteristic on the performance are also different. In order to represent and process these uncertain information effectively, this paper proposes an uncertain information fusion method based on possibility theory. Firstly, possibility distributions of a series of characteristic parameters about sensor information are constructed, and effective detection characteristics are extracted through the similarity measurement according to the similarity based on distances. The uncertain relationship between detection characteristics and detection performance is quantified, and a certainty calculation method of possibility distributions is proposed based on the combination of holistic and local characteristics. According to the above certainty, the weights of each characteristic are obtained to achieve the fusion of possibility distributions. Finally, the metallic and nonmetallic adhesive structure is taken as a case, and this case shows that this method not only considers the differences of the various characteristics contributed on adhesive performance, but also can achieve the fusion of possibility distributions under different situations. It is a more reasonable fusion method and fits the reality well in practice, also it provides new method and new idea for the fusion of possibility distributions.     

Identification of multiple transient faults based on the adaptive spectral kurtosis method

This paper proposes a multi-fault detection method based on the adaptive spectral kurtosis (ASK) analysis of the vibration signal from single sensor. A theoretical model of multiple bearing faults is established in this paper. Compared with the kurtogram and protrugram techniques, the proposed method can more effectively extract signatures of multiple bearing faults even in the presence of strong background noise. The performance of the proposed method in fault detection of the rolling element bearings is validated using simulation data and experimental signals from a bearing with multiple faults and two faulty bearings.     

多尺度传感网络失效节点检测系统设计

对多尺度传感网络中的失效节点进行准确检测与定位,实现故障节点的高效检测,保障传感网络的可靠运行。提出一种基于多传感器量化融合跟踪滤波检测的失效节点检测算法,并进行检测系统优化设计。构建多尺度传感网络的节点分布实体对象模型,进行失效节点检测系统总体设计和技术指标分析。设计基于多传感器量化融合跟踪滤波检测的失效节点检测算法。进行系统的硬件设计,包括A/D模块设计、时钟电路设计、程序加载电路设计、传感器通信模块设计和系统电源模块设计。在ARM Cortex?-M0平台上进行检测系统软件开发。系统仿真结果表明,该系统进行多尺度传感网络失效节点检测的准确度较高,提高了传感器网络的寿命周期。     

Design and implementation of spectrum sensing for cognitive radios with a frequency-hopping primary system

In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses.     

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.     

基于热释电红外传感器的多节点定位系统研究与设计

针对热释电红外传感器(PIR)在人体探测领域中越来越广泛的应用,研究设计了一种基于PIR的检测定位系统,可实时完成对人员目标入侵探测区域时的检测与定位,并预推出人员目标的行进轨迹;该系统由多个PIR感知节点组成,每个感知节点通过传感在动、静两种状态下对探测区域进行信息采集;最终融合多节点与不同状态下传感器采集的数据,算出各个传感器的探测角度值,以交叉定位的算法,得到目标的定位坐标;经实验证明,该系统运行稳定,检测灵敏,定位效果很好,拓宽了热释电传感器在定位定向方面的使用范围。     

Fusion of 3D laser scanner and depth images for obstacle recognition in mobile applications

The problem of obstacle detection and recognition or, generally, scene mapping is one of the most investigated problems in computer vision, especially in mobile applications. In this paper a fused optical system using depth information with color images gathered from the Microsoft Kinect sensor and 3D laser range scanner data is proposed for obstacle detection and ground estimation in real-time mobile systems. The algorithm consists of feature extraction in the laser range images, processing of the depth information from the Kinect sensor, fusion of the sensor information, and classification of the data into two separate categories: road and obstacle. Exemplary results are presented and it is shown that fusion of information gathered from different sources increases the effectiveness of the obstacle detection in different scenarios, and it can be used successfully for road surface mapping.     

A novel low-cost and small-size human tracking system with pyroelectric infrared sensor mesh network

This paper presents a low-cost and small-size human tracking system based on pyroelectric infrared (PIR) sensor mesh network. A wireless pyroelectric sensor network is developed using PIRs and PIR cone optics. The layout of PIRs and sensor nodes are well investigated and the real detection range of PIR is analyzed. A simple and effective PIR signal processing method is designed to get the event signal, and an innovative location method based on detecting angle bisectors of PIRs and data fusion is proposed. An improved Kalman filter and a particle filter are used for human tracking respectively. Simulation and Experimental results have shown that the human tracking system can effectively recognize, locate and track a human target with promising accuracy.     

Performance study of a liquid-core Bragg fiber sensor in presence of a defect layer

Performance parameter of a Bragg fiber waveguide based resonant sensor in presence of a defect layer in cladding regions is theoretically studied. The Bragg fiber waveguide consists of a liquid-core surrounded by alternate high and low refractive indices materials in cladding regions. Reflectivity of the proposed waveguide based resonant sensor is formulated using transfer matrix method for a non-homogeneous multilayer cylindrical system. The waveguide shows a band gap region with a narrow defect mode in the band gap region under the considered wavelength range. Instead of taking a whole band gap as a sensing signal, here the defect peak is taken as the sensing signal. It is observed that the intensity of defect mode is more sensitive for core refractive index than the intensity of traditional band gap region (lobe). This study shows that the higher sensitivity can be achieved by creating the defect at a position in cladding region where the intensity of transmitted light lies between 40% and 90%. Presence of a defect layer is able to increase the detection accuracy of the sensor and, hence increase the overall performance of this sensor.     

LED based fiber optic surface plasmon resonance sensor

Modeling of a miniaturized fiber optic sensor based on surface plasmon resonance utilizing a broad band diffuse source is presented. Attenuated total internal reflection with Kretschmann configuration is the basis of the theoretical model. For simulation both meridional and skew rays are considered. The performance of the sensor is evaluated in terms of sensitivity, detection accuracy and signal to noise ratio. Effects of the numerical aperture of the fiber, core diameter and length of the sensing region on the performance parameters of the sensor are studied. The results are obtained for gold and silver metallic layer on the core of the fiber. The theoretical results obtained are compared with SPR based fiber optic sensor utilizing focused beam on the end face of the fiber from a collimated source. The advantages of using broadband LED (diffuse source) source for launching light in the fiber are the miniaturization, compactness and low cost of the sensor.     

A Label-Free Oligonucleotide Based Thioflavin-T Fluorescent Switch for Ag<Superscript>+</Superscript> Detection with low Background Emission

A novel fluorescent Ag⁺ sensor was developed based on the label-free silver (I) specific oligonucleotide (SSO) and Thioflavine T (ThT) monomer-excimer switch. C-rich SSO which contain C-C mismatched base pairs can selectively bind to Ag⁺ ions and the formed duplexes which constructed by C-Ag⁺-C structure are thermally stabilized without largely altering the double helical structure. ThT give very weak fluorescent in bulk solution and/or in the presence of SSO. However ThT shows high fluorescence in the presence of SSO and Ag⁺ at the same time mainly because ThT excimer, which has the high quantum yield, formed and stabilized in the minor or major groove. Based on the discovery, we developed the novel Ag⁺ sensor. Under the optimum condition, the selectivity of this system for Ag⁺ over other metal ions in aqueous solution is remarkably high, and Ag⁺ can be quantified over the dynamic range of 30–450 nM, with a limit of detection of ~16 nM and a linear correlation coefficient of 0.995.     

Iterative inverse beamforming algorithm and its application in multiple targets detection of passive sonar

With the increasing of detection ability of passive sonar,the weak signal detection problem in multiple interferences becomes more and more important.In the time/bearing record(TBR) display of sonar detection,when there exist traces of multiple interferences,the identification of weak signal is difficult or impossible.The adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is quite difficult due to the real time calculation of inverse matrix of input data correlation matrix.The iterative inverse beamforming(IBF) algorithm for solving the optimum filter vector,which is expressed by inverse matrix of the ocean environment data,is derived in this paper,by which,the optimum filter can be eventually expressed as a sum of series simple matrices of constructed from sensor data.Based on the algorithm proposed in this paper,some examples of at sea experiment are provided.The strong interferences are cancelled and the weak signal is emerged,even it didn't appear in the conventional beamforming(CBF) processing.     

Development of a vision-based lane detection system considering configuration aspects

Vision-based lane-sensing systems require accurate and robust sensing performance in lane detection. Besides, there exists trade-off between the computational burden and processor cost, which should be considered for implementing the systems in passenger cars. In this paper, a stereo vision-based lane detection system considering sensor configuration aspects such as field of view (FOV), span pixels, resolution, etc is developed. An inverse perspective mapping method is formulated based on the relative correspondence between the left and right cameras so that the 3D road geometry can be reconstructed in a robust manner. The selection rule of the sensor configuration and specifications is investigated for a standard highway. Based on the selected sensor configurations, it is shown that sensing region range on the camera image coordinate can be determined for the best lane-sensing performance. The proposed system is implemented on a passenger car and its real-time sensing performance is verified experimentally.     

Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.     

Efficient parallel interference cancellation algorithm for multiuser detection schemes in CDMA-based 20.48-Gb/s optical MIMO-OFDM system over 1200 km of SSMF

This paper presents an efficient algorithm to cancel the parallel interference for multiuser detection (MUD) schemes in code division multiple access (CDMA) based 20.48 Gb/s optical multiple input multiple output orthogonal frequency division multiplexing (O-MIMO-OFDM) system over 1200 km of standard single mode fiber (SSMF). The performance of the system is compared by simulation results using the efficient algorithm and minimum mean square error (MMSE) schemes. It shows the superior performance of efficient algorithm.     

Multi-harmonic detection in wavelength modulation spectroscopy systems

Two multi-harmonic detection methods for wavelength modulation spectroscopy (WMS) systems are presented and compared. The two possibilities discussed in this paper are: simultaneous curve fitting of multiple harmonic spectra, and reconstruction of the transmission from harmonic coefficients. The optimum number of harmonics is four and 25 harmonics, respectively. Compared with standard single-harmonic curve fitting, the methods give about a factor of 3 better performance than standard second-harmonic curve fitting. Concluding, multi-harmonic detection is better than single-harmonic detection and should be used if the system bandwidth is high enough to allow for proper detection of the higher harmonics.     

Three-dimensional recognition of occluded objects by using computational integral imaging

We have proposed a method to recognize partially occluded three-dimensional (3D) objects by using 3D volumetric reconstruction integral imaging (II). An II system captures multiple perspectives of occluded objects by using a microlens array. The reconstruction of the occluded 3D scene and target recognition are done digitally to reduce the effects of the occlusion. To verify system performance, we have implemented an optimum filter for object recognition. Both two-dimensional (2D) images and 3D II volumetric reconstructed images are considered. The correlation results of occluded 3D images for volumetric reconstruction show substantial improvements compared with those for conventional 2D imaging of occluded images.     

噪声方差未知时的分布式量化估计融合方法

为了解决观观测噪声和信道噪声概率分布不完全已知时的多传感器分布式量化估计融合问题,提出了一种期望极大化算法(EM算法)的分布式量化估计融合方法。该方法将未知的噪声参数以及局部量化器量化概率建模为EM算法中二元高斯混合模型参数,利用极大似然估计方法的估计不变性得到目标参数的估计融合结果。仿真实验结果表明:该方法在局部传感器观测样本数目大于6000和信噪比大于6 dB时与已有理想信道条件下的估计方法性能相当。本文方法对水下分布式协同探测问题提供了一种简化的估计融合实现途径。