Fiber Bragg grating sensor interrogation system using a CCD side detection method with Superimposed blazed gratings

We present, for the first time to our knowledge, experimental evidence showing that superimposed blazed fiber Bragg gratings may be fabricated and used to extend the dynamic range of a grating-based spectrometer. Blazed gratings of 4° and 8° were superimposed in germanosilicate fiber by ultraviolet inscription and used in conjunction with a coated charged-coupled device array to interrogate a wavelength-division-multiplexing sensor array. We show that the system can be used to monitor strain and temperature sensors simultaneously with an employable bandwidth which is extendable to 70 nm.

In-fibre Bragg grating temperature sensor system for medical applications

A novel quasidistributed in-fiber Bragg grating (FBG) temperature sensor system has been developed for temperature proving in vivo in the human body for medical applications, e.g., hyperthermia treatment. This paper provides the operating principle of FBG temperature sensors and then the design of the sensor head. High-resolution detection of the wavelength-shifts induced by temperature changes are achieved using drift-compensated interferometric detection while the return signals from the FBG sensor array are demultiplexed with a simple monochromator which offers crosstalk-free wavelength-division-multiplexing (WDM). A “strain-free” probe is designed by enclosing the FBG sensor array in a protection sleeve. A four FBG sensor system is demonstrated and the experimental results are in good agreement with those obtained by traditional electrical thermocouple sensors. A resolution of 0.1°C and an accuracy of ±0.2°C over a temperature range of 30-60°C have been achieved, which meet established medical requirements.

In-fibre Bragg grating temperature sensor system for medical applications

A novel quasidistributed in-flber Bragg grating (FBG) temperature sensor system has been developed for temperature profiling in vivo in the human body for medical applications, e.g., hyperthermia treatment. This paper provides the operating principle of FBG temperature sensors and then the design of the sensor head. High-resolution detection of the wavelength-shifts induced by temperature changes are achieved using drift-compensated interferometric detection while the return signals from the FBG sensor array are demultiplexed with a simple monochromator which offers crosstalk-free wavelength-division-multiplexing (WDM). A "strain-free" probe is designed by enclosing the FBG sensor array in a protection sleeve. A four FBG sensor system is demonstrated and the experimental results are in good agreement with those obtained by traditional electrical thermocouple sensors. A resolution of 0.1°C and an accuracy of ±0.2°C over a temperature range of 30-60°C have been achieved, which meet established medical requirements.

Fiber Bragg grating sensor interrogation system using a CCD side detection method with superimposed blazed gratings

We present, for the first time to our knowledge, experimental evidence showing that superimposed blazed fiber Bragg gratings may be fabricated and used to extend the dynamic range of a grating-based spectrometer. Blazed gratings of 4° and 8° were superimposed in germanosilicate fiber by ultraviolet inscription and used in conjunction with a coated charged-coupled device array to interrogate a wavelength-division-multiplexing sensor array. We show that the system can be used to monitor strain and temperature sensors simultaneously with an employable bandwidth which is extendedable to 70 nm.

Low-Power Tracking Image Sensor Based on Biological Models of Attention

This paper presents implementation of a low-power tracking CMOS image sensor based on biological models of attention. The presented imager allows tracking of up to N salient targets in the field of view. Employing "smart" image sensor architecture, where all image processing is implemented on the sensor focal plane, the proposed imager allows reduction of the amount of data transmitted from the sensor array to external processing units and thus provides real time operation. The imager operation and architecture are based on the models taken from biological systems, where data sensed by many millions of receptors should be transmitted and processed in real time. The imager architecture is optimized to achieve low-power dissipation both in acquisition and tracking modes of operation. The tracking concept is presented, the system architecture is shown and the circuits description is discussed.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

Weighted subspace methods and spatial smoothing: analysis and comparison

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.

Some Algorithms for Eigensubspace Estimation

An important tool in signal processing is the use of eigenvalue and singular value decompositions for extracting information from time-series/sensor array data. These tools are used in the so-called subspace methods that underlie solutions to the harmonic retrieval problem in time series and the directions-of-arrival (DOA) estimation problem in array processing. The subspace methods require the knowledge of eigenvectors of the underlying covariance matrix to estimate the parameters of interest. Eigenstructure estimation in signal processing has two important classes: (i) estimating the eigenstructure of the given covariance matrix and (ii) updating the eigenstructure estimates given the current estimate and new data. In this paper, we survey some algorithms for both these classes useful for harmonic retrieval and DOA estimation problems. We begin by surveying key results in the literature and then describe, in some detail, energy function minimization approaches that underlie a class of feedback neural networks. Our approaches estimate some or all of the eigenvectors corresponding to the repeated minimum eigenvalue and also multiple orthogonal eigenvectors corresponding to the ordered eigenvalues of the covariance matrix. Our presentation includes some supporting analysis and simulation results. We may point out here that eigensubspace estimation is a vast area and all aspects of this cannot be fully covered in a single paper. (C) 1995 Academic Press, Inc.

Subspace-based DOA estimation using Fractional Lower Order statistics

Direction Of Arrival (DOA) estimation, using a sensor array, in the presence of non-Gaussian noise using Fractional Lower-Order Moments (FLOM)matrices is studied. In this paper, a new FLOM based technique using the Fractional Lower Order Infinity Norm based Covariance (FLIC) Matrix is proposed. The bounded property and the low-rank subspace structure of the FLIC matrix is derived. Performance of FLIC based DOA estimation using MUSIC, ESPRIT, is shown to be better than other FLOM based methods.

Micro-satellite angular rate estimation using second-order sliding mode observer

Development of computationally efficient and accurate attitude rate estimation algorithm using low-cost commercially available star sensor arrays and processing unit for micro-satellite mission is presented. Our design reduces the computational load of least square (LS)-based rate estimation method while maintaining the same accuracy compared to other rate estimation approaches. Furthermore, rate estimation accuracy is improved by using recently developed fast and accurate second-order sliding mode observer (SOSMO) scheme. It also gives robust estimation in the presence of modeling uncertainties, unknown disturbances, and measurement noise. Simulation study shows that rate estimation accuracy achieved by our LS-based method is comparable with other methods for a typical commercially available star sensor array. The robustness analysis of SOSMO with respect to measurement noise is also presented in this paper. Simulation test bench for a practical scenario of satellite rate estimation uses moment-of-inertia variation and environmental disturbances affecting a typical micro-satellite at 500km circular orbit. Comparison studies of SOSMO with 1-SMO and pseudo-linear Kalman filter show that satisfactory estimation accuracy is achieved by SOSMO.

Film bulk acoustic resonator nanosensors for multi-task sensing

This paper shows that film bulk acoustic resonator (FBAR) arrays can be very useful sensors either to detect physical parameters such as temperature and pressure directly or to detect bio-chemicals with extremely high sensitivities by incorporating a chemisorption layer or bio-probe molecules. Furthermore, it also shows that surface acoustic wave devices can be integrated with a FBAR sensor array on the same piezoelectric substrate as the microfluidics systems to perform transportation and mixing of biosamples etc. demonstrating the possibility to fabricate integrated lab-on-a-chip detection systems, in which all the actuators and sensors are operated by acoustic wave devices. This makes the detection system simple, low cost and easy to operate and hence has great commercial potential. © 2011 Inderscience Enterprises Ltd.

A 1,000 Frames/s Programmable Vision Chip with Variable Resolution and Row-Pixel-Mixed Parallel Image Processors

A programmable vision chip with variable resolution and row-pixel-mixed parallel image processors is presented. The chip consists of a CMOS sensor array, with row-parallel 6-bit Algorithmic ADCs, row-parallel gray-scale image processors, pixel-parallel SIMD Processing Element (PE) array, and instruction controller. The resolution of the image in the chip is variable: high resolution for a focused area and low resolution for general view. It implements gray-scale and binary mathematical morphology algorithms in series to carry out low-level and mid-level image processing and sends out features of the image for various applications. It can perform image processing at over 1,000 frames/s (fps). A prototype chip with 64 x 64 pixels resolution and 6-bit gray-scale image is fabricated in 0.18 mu m Standard CMOS process. The area size of chip is 1.5 mm x 3.5 mm. Each pixel size is 9.5 mu m x 9.5 mu m and each processing element size is 23 mu m x 29 mu m. The experiment results demonstrate that the chip can perform low-level and mid-level image processing and it can be applied in the real-time vision applications, such as high speed target tracking.

移动机器人分布式超声探测系统设计

设计制作了一种基于多处理器的移动机器人分布式超声环境探测系统.该系统由上位工作模式控制模块和下位智能超声传感器阵列组成.下位智能超声传感器选用收发一体式超声传感器,每个传感器均由独立的微处理器控制,完成实时数据处理、抗干扰处理、故障报警以及并行数据通信等功能.上位工作模式控制模块可以根据不同的控制策略,使下位传感器阵列采用“阈值比较法”和“改进型递推均值滤波”算法及EERUF方法并行循环工作模式,实现不同方向传感器分组并行工作,提高了探测的实时性和准确性,以及对移动机器人控制的鲁棒性.仿真和实验的结果都验证了该系统的可靠性和有效性.

基于多微处理器的智能超声探测系统

设计了一种基于多微处理器的智能超声探测系统。该系统采用由上位工作模式控制单元和下位智能超声传感器阵列组成的分布式结构。每个超声传感器均由独立的微处理器控制,并完成实时数据处理、抗干扰处理、故障报警以及数据通信等功能。上位控制单元根据移动机器人的运动状态采用不同的控制策略,使下位传感器阵列分组并行工作,提高了探测系统的实时性;下位传感器采用"阈值比较法"、"改进型递推均值滤波"算法和模糊信息处理技术,提高了探测系统的准确性、可靠性。将该探测系统安装于RIRA-II移动机器人上,进行了基于主动视觉和超声信息的运动目标跟踪实验,实验表明超声探测系统运行可靠、稳定。

用光学阵列传感器的机器人物体分类系统

本文介绍用光学阵列传感器的机器人物体分类系统。传感器直接安装在机器人的两个手指上。被抓物体的阴影通过光导纤维传到安放在“安全区”的光敏元件上。计算机识别物体的轮廓后命令机器人抓握物体,并把它运送到指定的地点从而达到物体分类的目的。