Optical multibead arrays for simple and complex odor discrimination

A fiber optic bead-based sensor array platform has been employed to discriminate between six different odors and air carrier gas. Six different bead sensor types, with over 250 replicates of each, were monitored before, during, and after odor exposure to produce time-dependent fluorescence response patterns that were unique for each sensor-analyte combination. A total of 2,683 sensors were analyzed with respect to changes in their fluorescence, and signals from identical sensor beads were averaged to improve signal-to-noise ratios. Analyte classification rates of 100% were achieved for three complex (coffee bean) odors and three pure (simple) odors (toluene, acetone, 1,3-dinitrotoluene) measured at their highest relative concentrations. When lower odor concentrations were employed, the system exhibited better than 85% classification rates for analyte discrimination. Sensor response repeatability to these odor stimuli has also been quantified statistically, which is vital in defining the detection limit of the overall system. These results demonstrate, for the first time, the utility of our bead array technology for discriminating between different odor types at various dilution levels.     

Neuromorphic Processing for Optical Microbead Arrays: Dimensionality Reduction and Contrast Enhancement

This paper presents a neuromorphic approach for sensor-based machine olfaction that combines a portable chemical detection system based on microbead array technology with a biologically inspired model of signal processing in the olfactory bulb. The sensor array contains hundreds of microbeads coated with solvatochromic dyes adsorbed in, or covalently attached on, the matrix of various microspheres. When exposed to odors, each bead sensor responds with corresponding intensity changes, spectral shifts, and time-dependent variations associated with the fluorescent sensors. The bead array responses are subsequently processed using a model of olfactory circuits that capture the following two functions: chemotopic convergence of receptor neurons and center on-off surround lateral interactions. The first circuit performs dimensionality reduction, transforming the high-dimensional microbead array response into an organized spatial pattern (i.e., an odor image). The second circuit enhances the contrast of these spatial patterns, improving the separability of odors. The model is validated on an experimental dataset containing the responses of a large array of microbead sensors to five different analytes. Our results indicate that the model is able to significantly improve the separability between odor patterns, compared to that available from the raw sensor response     

A measurement system for odor classification based on the dynamic response of QCM sensors

In this paper, an innovative measurement system for odor classification, based on quartz crystal microbalances (QCMs), is presented. The application proposed in this paper is the detection of typical wine aroma compounds in mixtures containing ethanol. In QCM sensors, the sensitive layer is, e.g., a polymeric layer deposited on a quartz surface. Chemical mixtures are sorbed in the sensitive layer, inducing a change in the polymer mass and, therefore, in the quartz resonance frequency. In this paper, the frequency shift is measured by a dedicated, fully digital front-end hardware implementing a technique that allows reducing the measurement time while maintaining a high-frequency resolution . The developed system allows, therefore, measuring variations of the QCM resonance frequency shifts during chemical transients obtained with abrupt changes in odor concentration. Hence, the reaction kinetics can be exploited to enhance the sensor selectivity. In this paper, some measurements obtained with an array of four sensors with different polymeric sensitive layers are presented. An exponential fitting of the transient responses is used for feature extraction. Finally, to reduce data dimensionality, principal component analysis is used.     

Information coding in artificial olfaction multisensor arrays

High-density sensor arrays were prepared with microbead vapor sensors to explore and compare the information coded in sensor response profiles following odor stimulus. The coded information in the sensor-odor response profiles, which is used for odor discrimination purposes, was extracted from the microsensor arrays via two different approaches. In the first approach, the responses from individual microsensors were separated (decoded array) and independently processed. In the second approach, response profiles from all microsensors within the entire array, i.e., the sensor ensemble, were combined to create one response per odor stimulus (nondecoded array). Although the amount of response data is markedly reduced in the second approach, the system shows comparable odor discrimination rates for the two signal extraction methods. The ensemble approach streamlines system resources without decreasing system performance. These signal compression approaches may simulate or parallel information coding in the mammalian olfactory system.     

Gamma radiation nose system based on In/sub 2/O/sub 3//SiO thick-film sensors

A prototype gamma radiation monitoring system based on In/sub 2/O/sub 3//SiO thick-film sensors array was designed. Four sensors had an identical pn-heterojunction structure with different material compositions. These sensors were subjected to gamma radiation emitted by /sup 137/Cs source with an activity of 370 kBq. Changes in their current-voltage characteristics were recorded and compared. The performance parameters of the devices, such as sensitivity to /spl gamma/ radiation exposure and working dose region, were found to be highly dependent on the composition of the materials used. To cover a wider range of radiation and improve the overall sensitivity, an approach of using sensor arrays was utilized. A dynamic selection of the multiple sensors of various sensitivities and working dose ranges was implemented by applying a pattern recognition analysis.     

Location information-aided task-oriented self-organization of ad-hoc sensor systems

A novel task-oriented self-organization algorithm that accounts for mostly location-dependent tasks and heterogeneous sensors inherent in dense ad-hoc sensor systems is proposed. It forms a sensor group for an announced task by sequentially selecting the best matched sensors using a leader election algorithm and a residual task calculation algorithm. To improve the associated communication overhead, the sensor node location information is used in task broadcasting, thus confining the algorithm implementation to a dynamically maintained contributor group which comprises of those sensors which may contribute to the task. Sensor localization is based on a refinement of an algorithm in which utilizes only the neighborhood information of each sensor node corresponding to its each preset radio transmission power level. The proposed self-organization algorithm and how various system parameters affect its performance are examined via extensive simulations. In a densely deployed sensor system, when the refined localization scheme is demonstrated to achieve very good localization, the proposed self-organization algorithm consistently yields a sensor group that covers the announced task.     

基于二维波束聚焦算法的低速冲击监测研究

冲击损伤监测是结构健康监测的主要研究内容之一,为提高冲击定位的精度以及传感器的利用效率,提出了一种基于十字阵列型传感器布置方法的二维波束聚焦冲击定位算法,在高精度的前提下有效减少了传统定位方法所需布置的传感器数量.通过十字阵列型的压电传感器布置方法,可以将远场的定位精度大大提高,对于内场的盲区采用四点圆弧定位算法进行冲...     

Designing a practical system for spectral imaging of skylight

In earlier work [J. Opt. Soc. Am. A 21, 13-23 (2004)], we showed that a combination of linear models and optimum Gaussian sensors obtained by an exhaustive search can recover daylight spectra reliably from broadband sensor data. Thus our algorithm and sensors could be used to design an accurate, relatively inexpensive system for spectral imaging of daylight. Here we improve our simulation of the multispectral system by (1) considering the different kinds of noise inherent in electronic devices such as change-coupled devices (CCDs) or complementary metal-oxide semiconductors (CMOS) and (2) extending our research to a different kind of natural illumination, skylight. Because exhaustive searches are expensive computationally, here we switch to a simulated annealing algorithm to define the optimum sensors for recovering skylight spectra. The annealing algorithm requires us to minimize a single cost function, and so we develop one that calculates both the spectral and colorimetric similarity of any pair of skylight spectra. We show that the simulated annealing algorithm yields results similar to the exhaustive search but with much less computational effort. Our technique lets us study the properties of optimum sensors in the presence of noise, one side effect of which is that adding more sensors may not improve the spectral recovery.     

矢量线阵二维波达方位估计的方法

声矢量传感器南声压传感器和质点振速传感器组成,它可以空间共点、时间同步测量声场的声压标量和振速矢量信息。钏对声压线阵无法同时分辨目标的方位角和俯仰角,而三维矢量传感器线阵会带来成本的增加和工程应用上的困难．利用二维矢量传感器组成的直线阵对目标的二维波达方位进行联合估计,详细推导了矢量阵MUSIC算法的数学表达式,并着重对矢量线阵在三维坐标不同轴上时对方位估计的影响进行了研究。仿真结果表明二维矢量线阵布放在水平的X轴或Y轴上时存在方位模糊．而布放在垂直的Z轴上时可以实现全空间无模糊定向,且对双目标也有较高的分辨率。     

Ordered‐Assembly Conductive Nanowires Array with Tunable Polymeric Structure for Specific Organic Vapor Detection

An artificial organic vapor sensor based on a finite number of 1D nanowires arrays can provide a strategy to allow classification and identification of different analytes with high efficiency, but fabricating a 1D nanowires array is challenging. Here, a coaxial Ag/polymer nanowires array is prepared as an organic vapor sensor with specific recognition, using a strategy combining superwettability‐based nanofabrication and polymeric swelling‐induced resistance change. Such organic vapor sensor containing commercial polymers can successfully classify and identify various organic vapors with good separation efficiency. An Ag/polymer nanowires array with synthetic polyethersulfone polymers is also fabricated, through molecular structure modification of the polymers, to distinguish the similar organic vapors of methanol and ethanol. Theoretical simulation results demonstrate introduction of specific molecular interaction between the designed polymers and organic vapors can improve the specific recognition performance of the sensors.     

Multi-task Joint Sparse Representation Classification Based on Fisher Discrimination Dictionary Learning

Recently, sparse representation classification (SRC) and fisher discrimination dictionary learning (FDDL) methods have emerged as important methods for vehicle classification. In this paper, inspired by recent breakthroughs of discrimination dictionary learning approach and multi-task joint covariate selection, we focus on the problem of vehicle classification in real-world applications by formulating it as a multi-task joint sparse representation model based on fisher discrimination dictionary learning to merge the strength of multiple features among multiple sensors. To improve the classification accuracy in complex scenes, we develop a new method, called multi-task joint sparse representation classification based on fisher discrimination dictionary learning, for vehicle classification. In our proposed method, the acoustic and seismic sensor data sets are captured to measure the same physical event simultaneously by multiple heterogeneous sensors and the multi-dimensional frequency spectrum features of sensors data are extracted using Mel frequency cepstral coefficients (MFCC). Moreover, we extend our model to handle sparse environmental noise. We experimentally demonstrate the benefits of joint information fusion based on fisher discrimination dictionary learning from different sensors in vehicle classification tasks.     

矢量水听器阵列自适应子空间跟踪算法

矢量水听器能同时共点获得声场中声压和振速,与其他水听器相比,能获得更多的信息量,具有很好的应用前景。矢量水听器阵列的MUSIC算法能实现360°无模糊方位估计,然而对于方位时变的目标源,该算法很难完成对上述目标源方位进行实时跟踪估计。鉴于此,将MALASE算法和MUSIC算法相结合,提出了一种矢量水听器阵列的自适应子空间跟踪算法。仿真结果表明,该算法既保留了MUSIC算法的性能,又实现了对目标源进行实时跟踪估计,且方位估计误差仅为0．4°左右。     

Tactile Sensing Using Force Sensing Resistors and a Super-Resolution Algorithm

This paper presents a tactile sensor consisting of an array of force sensing resistors (FSRs). The tactile sensing array can be seen as a coordinated system of touch sensors. The low spatial resolution measured with the FSRs compared to other force or pressure sensors required the use of a super-resolution algorithm. Super-resolution algorithms are often used in digital image processing to enhance the resolution of images. Multiple images taken from slightly different orientations are superimposed in such a way that a single higher-resolution image is obtained. Different touch sensors are briefly discussed and the use of FSRs is motivated. Image-registration techniques are discussed and the super-resolution algorithm developed for the application is presented. Some tests performed using the tactile sensor in a neck palpation device and the results of these tests are also presented.      

用于压/拉检测的机器人皮肤柔/弹性传感器阵列设计

基于炭黑/硅橡胶复合材料的压力以及拉伸敏感特性,设计了一种可用于检测机器人皮肤接触压力和拉伸特性的新型传感器阵列。该传感器阵列的弹性电极结构克服了传统传感器不可拉伸的缺点,实现了传感器阵列的柔/弹性;阵列中设计了9个检测压力的传感器单元和2个检测拉伸的传感器单元,通过传感器结构设计和拉/压干扰特性分析以及补偿算法解决了拉伸和压力同时测量时的干扰问题,并构建了求解压力与拉伸的数学模型。实验结果表明:该传感器阵列实现了对压力和拉伸的同步检测,可用于机器人柔性皮肤中关节等部位。     

Dielectrophoresis‐Assisted Integration of 1024 Carbon Nanotube Sensors into a CMOS Microsystem

Carbon‐nanotube (CNT)‐based sensors offer the potential to detect single‐molecule events and picomolar analyte concentrations. An important step toward applications of such nanosensors is their integration in large arrays. The availability of large arrays would enable multiplexed and parallel sensing, and the simultaneously obtained sensor signals would facilitate statistical analysis. A reliable method to fabricate an array of 1024 CNT‐based sensors on a fully processed complementary‐metal‐oxide‐semiconductor microsystem is presented. A high‐yield process for the deposition of CNTs from a suspension by means of liquid‐coupled floating‐electrode dielectrophoresis (DEP), which yielded 80% of the sensor devices featuring between one and five CNTs, is developed. The mechanism of floating‐electrode DEP on full arrays and individual devices to understand its self‐limiting behavior is studied. The resistance distributions across the array of CNT devices with respect to different DEP parameters are characterized. The CNT devices are then operated as liquid‐gated CNT field‐effect‐transistors (LG‐CNTFET) in liquid environment. Current dependency to the gate voltage of up to two orders of magnitude is recorded. Finally, the sensors are validated by studying the pH dependency of the LG‐CNTFET conductance and it is demonstrated that 73% of the CNT sensors of a given microsystem show a resistance decrease upon increasing the pH value.     

Analysis of Volatile Bread Aroma for Evaluation of Bread Freshness Using an Electronic Nose (E-Nose)

This paper presents the use of a tin-oxide sensor array and self-organized map (SOM)-based E-nose for analysis of volatile bread aroma and explores its ability to cluster bread odor data according to the freshness of bread. A low cost tin-oxide sensor array based electronic nose system has been used for the classification of state of freshness of bread. The sensor data was acquired for a period of 3 weeks, and an unsupervised self-organizing map (SOM) model was trained using this data to correlate the sensor response to classify the bread as fresh and stale. A comparative evaluation of 3 week' of bread data was carried out using the SOM. The results suggest that the system developed is able to predict the state of bread as fresh and stale up to 98% accuracy if the test bread data sets are of the same week. The classification accuracy reduces to 75-85% if test bread data sets are from different weeks. The model is also applied on three different brands of bread and similar classification results are obtained.     

Decentralized random decrement technique for efficient data aggregation and system identification in wireless smart sensor networks

Smart sensors have been recognized as a promising technology with the potential to overcome many of the inherent difficulties and limitations associated with traditional wired structural health monitoring (SHM) systems. The unique features offered by smart sensors, including wireless communication, on-board computation, and cost effectiveness, enable deployment of the dense array of sensors that are needed for monitoring of large-scale civil infrastructure. Despite the many advances in smart sensor technologies, power consumption is still considered as one of the most important challenges that should be addressed for the smart sensors to be more widely adopted in SHM applications. Data communication, the most significant source of the power consumption, can be reduced by appropriately selecting data processing schemes and the related network topology. This paper presents a new decentralized data aggregation approach for system identification based on the Random Decrement Technique (RDT). Following a brief overview of the RDT, which is an output-only system identification approach, a decentralized hierarchical approach is described and shown to be suitable for implementation in the intrinsically distributed computing environment found in wireless smart sensor networks (WSSNs). RDT-based decentralized data aggregation is then implemented on the Imote2 smart sensor platform based on the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. Finally, the efficacy of the RDT method is demonstrated experimentally in terms of the required data communication and the accuracy of identified dynamic properties.     

Temperature correction to chemoresistive sensors in an e-NOSE-ANN system

The influence of the temperature coefficient of resistance in the chemoresistive response of inherently conductive polymer (ICP) sensors in the performance of an artificial neural network (ANN) e-natural olfactory sensor emulator (e-NOSE) system is evaluated. Temperature was found to strongly influence the response of the chemoresistors, even over modest ranges (ca. 2/spl deg/C). An e-NOSE array of eight ICP sensor elements, a relative humidity (RH/spl plusmn/0.1%) sensor, and a resistance temperature device (RTD/spl plusmn/0.1/spl deg/C) was tested at five different RH levels while the temperature was allowed to vary with the ambient. A temperature correction algorithm based on the temperature coefficient of resistance /spl beta/ for each material was independently and empirically determined then applied to the raw sensor data prior to input to the ANN. Conversely, uncorrected data was also passed to the ANN. The performance of the ANN was evaluated by determining the error found between the actual humidity versus the calculated humidity. The error obtained using raw input sensor data was found to be 10.5% and using temperature corrected data, 9.3%. This negligible difference demonstrates that the ANN was capable of adequately addressing the temperature dependence of the chemoresistive sensors once temperature was inclusively passed to the ANN.     

Fault-tolerant sensor systems using evolvable hardware

This paper describes a system that is robust with respect to a sensor failure. The system utilizes multiple sensor inputs (three in this case) connected to a programmable device that averages the outputs from the sensors. The programmable device is programmed using evolvable hardware techniques. If one or more of the input sensors fail, then the controller detects the failure and initiates a reprogramming of the circuit. The system then continues to operate with a reduced number of sensors. The failure detection is accomplished by comparing the actual system output with a Kalman-filter estimate of the output. If the actual output and the filter estimate differ by an amount greater than the system uncertainty, then a failure is noted. The system is robust to several different failure modes: sensor fails as open circuit, sensor fails as short circuit, partial failures, multiple sensors fail, field programmable analog array input amplifier failure. This paper describes the experimental setup as well as results using actual temperature sensors. For all failure types, the system was able to recover to within 2% of the target value.