A risk-based sensor placement methodology

A risk-based sensor placement methodology is proposed to solve the problem of optimal location of sensors to protect population against the exposure to, and effects of, known and/or postulated chemical, biological, and/or radiological threats. Risk is calculated as a quantitative value representing population at risk from exposure at standard exposure levels. Historical meteorological data are used to characterize weather conditions as the frequency of wind speed and direction pairs. The meteorological data drive atmospheric transport and dispersion modeling of the threats, the results of which are used to calculate risk values. Sensor locations are determined via an iterative dynamic programming algorithm whereby threats detected by sensors placed in prior iterations are removed from consideration in subsequent iterations. In addition to the risk-based placement algorithm, the proposed methodology provides a quantification of the marginal utility of each additional sensor. This is the fraction of the total risk accounted for by placement of the sensor. Thus, the criteria for halting the iterative process can be the number of sensors available, a threshold marginal utility value, and/or a minimum cumulative utility achieved with all sensors.     

Improvement in real time detection and selectivity of phthalocyanine gas sensors dedicated to oxidizing pollutants evaluation

A sensor microsystem prototype, using copper phthalocyanine thin film as sensitive layer, and dedicated to ozone evaluation, was developed. The methodology implemented is based on cyclic sensor recalibrations by thermal cleaning of the sensitive membrane, and on pollutant concentration quantification according to the kinetics of sensor response. Results of laboratory experiments for various NO₂ and O₃ concentrations, in the range of 10-200 ppb, illustrate the selectivity of CuPc sensors towards ozone, obtained by our methodology. We have shown that ozone selectivity is especially improved for short time of exposure (few minutes) and for phthalocyanine layer maintained at low temperature (80 °C). For optimal conditions, our microsystem exhibits a threshold lower than 10 ppb, a resolution lower than 10 ppb, and good reproducibility of measurements. Performances obtained in real urban atmosphere are satisfying to ensure real time evaluation of ozone during several days. Long-term stability and the detection of NO₂ by associating chemical filters to our microsystem will be also discussed.     

Sensor Fusion Methodology to Overcome Cross-Axis Problem for Micromachined Thermal Gas Inertial Sensor

Micromachined thermal gas inertial sensors are novel devices that take advantages of simple configuration, large working range, high shock resistance, and good reliability in virtue of using gaseous medium instead of mechanical proof mass as key moving and sensing elements. Basing on multidimentional movements of gas flow in a small chamber, the sensor generally undergoes a cross-axis problem. In this paper, a study on the cross-axis sensitivity of the thermal gas rotation sensor is reported. The cross-axis problem of the sensor is resulted from the multidimensional coupling movement of the convection flow in the sensor chamber and possibly be diminished by a tailored structural design. Unlike using a complex scheme on the mechanical structure, combining more than two sensors to form an integrated compensation system and using a fusion methodology to decouple cross rotations are proposed in this paper. The method helps to enhance practical applications for thermal rotation sensors.      

Capacitance Sensors for Void-Fraction Measurements and Flow-Pattern Identification in Air–Oil Two-Phase Flow

The design methodology of capacitance sensors for void-fraction measurement in adiabatic two-phase flow systems is presented in this paper. The effect of design parameters on the capacitance output has been theoretically and experimentally investigated for two types of sensor configurations: concave and ring types. Experiments were performed using air–oil two-phase flow to determine the signal-to-noise ratio, sensitivity, and time response of the capacitance sensors. The results show that the ring-type sensors are more sensitive to the void-fraction signal than the concave type for the same spatial resolution. The predictions from the theoretical model for the ring-type sensors are in better agreement with the experimental results than for the concave type. The mean value, time trace, power spectral density (PSD), and the probability density function (PDF) of the void-fraction signal from the capacitance sensors are used to objectively identify the flow pattern. The method was validated using high-speed video images of the flow and comparing the results to those from the signal analysis.     

Analysis and characterization of a mechanical sensor to monitor stress in interconnect features

A mechanical rotating stress sensor fabricated in copper has been characterized in 100 nm single damascene technology. Geometrical variations to the structure produce a distinctive behaviour which can be used to fit the actuating stress. Existing analytical models were tested and shown to be unable to describe the structure due to geometric non-linearities not considered by these one-dimensional solutions. A model based on the large strain finite element method was developed to include this non-linearity and fully describe the sensor design for all geometrical variations. The stress determined from the Cu rotating sensors is comparable to measurements performed using high intensity X-ray diffraction on similar samples. Furthermore, the simulation methodology is validated for calibrated Al sensors. All of the studied samples show an excellent fit with the developed finite element analysis, demonstrating the validity of the model to predict smaller geometries, showing that the sensor can be utilized in future integration schemes and applied to other material systems.     

Optimal experimental design in stochastic structural dynamics

This paper provides a methodology for optimal prediction of the response of randomly vibrating structures using information from a limited number of measurements. The objective is to optimize the locations of sensors for the purpose of making the most accurate predictions of the response at unmeasured locations in structural systems. The kriging method is used to find the response predictions and the corresponding mean-square errors at unmeasured locations. The mean-square errors in the predictions depend on the locations of sensors and the correlation characteristics of the response evaluated from the model of dynamics and the characteristics of the excitation. The response predictions depend also on the information contained in measurements. The optimal sensor locations are selected to minimize the total mean-square error of the response predictions at unmeasured points. This leads to a complicated non-convex optimization problem in which multiple local and global optima may exist. A hybrid optimization method based on evolution strategies is used to determine a global minimum. The optimal experimental design method presented in the paper is illustrated by designing the optimal sensor locations for an elastic beam and a plate subjected to a class of random stationary loads.     

Continuous-Flow System for On-Line Water Monitoring Using Back-Side Contact ISFET-Based Sensors

A multiparametric continuous-flow system for on-line monitoring of water based on ISFET sensors is described. The ISFETs used have silicon nitride as gate material, and the electrical contacts are placed on the back side of the chip. This is a technological improvement that allows for a more compact ISFET packaging and greatly increases the lifetime of the sensor compared with planar type ISFETs, since the electrical parts are separated from the chemical environment. A special probe has been designed in order to encapsulate and apply these ISFETs into the flow system. Further, a reference electrode based on standard Ag/AgCl technology has been constructed according to the ISFET probe design in order to integrate both sensors in the same flow-through cell. These probes can be easily replaced in the flow system and are made of cheap and easily mechanized materials. Using these flow-through sensors, a continuous-flow system for the determination of pH, NH(4)(+), Ca(2+), and NO(3)(-) in waters has been designed. The system configuration is based on a modular design (one setup for each parameter and a common sampling channel), which allows simple manipulation and maintenance as well as a good flexibility for different analytical requirements. A study of the system characteristics was performed by following the specifications for water monitoring. Under the conditions established for the flow system, a sampling rate of 20 h(-)(1) was obtained for each parameter, and long-term stabilities of at least 3 weeks of daily work for ISFET sensors and 5 months for the reference electrode have been achieved. The response performances obtained show the feasibility of the BSC ISFET probe use in continuous-flow monitoring.     

Chemical vapor detection using a capacitive micromachined ultrasonic transducer

Distributed sensing of gas-phase chemicals using highly sensitive and inexpensive sensors is of great interest for many defense and consumer applications. In this paper we present ppb-level detection of dimethyl methylphosphonate (DMMP), a common simulant for sarin gas, with a ppt-level resolution using an improved capacitive micromachined ultrasonic transducer (CMUT) as a resonant chemical sensor. The improved CMUT operates at a higher resonant frequency of 47.7 MHz and offers an improved mass sensitivity of 48.8 zg/Hz/μm(2) by a factor of 2.7 compared to the previous CMUT sensors developed. A low-noise oscillator using the CMUT resonant sensor as the frequency-selective device was developed for real-time sensing, which exhibits an Allan deviation of 1.65 Hz (3σ) in the presence of a gas flow; this translates into a mass resolution of 80.5 zg/μm(2). The CMUT resonant sensor is functionalized with a 50-nm thick DKAP polymer developed at Sandia National Laboratory for dimethyl methylphosphonate (DMMP) detection. To demonstrate ppb-level detection of the improved chemical sensor system, the sensor performance was tested at a certified lab (MIT Lincoln Laboratory), which is equipped with an experimental chemical setup that reliably and accurately delivers a wide range of low concentrations down to 10 ppb. We report a high volume sensitivity of 34.5 ± 0.79 pptv/Hz to DMMP and a good selectivity of the polymer to DMMP with respect to dodecane and 1-octanol.     

基于信息熵与谱有限元法的传感器优化布置

为从测量数据中获得尽可能多信息,减少待识别模型参数的不确定性,提出面向结构模型参数识别的传感器优化布置方法。为避免用静态形函数传统有限元方法建模对结构动力特性及传感器优化布置影响,采用高精确动力学法即谱有限元法对结构进行动力学建模。以结构模型参数识别结果的不确定性最小作为传感器优化布置准则,该不确定性程度通过信息熵标量指标量化,用贝叶斯统计系统识别法进行识别。采用整数编码遗传算法在所有可能的传感器配置组合中极小化信息熵指标,获得给定数目的传感器最优布置位置。通过弹性地基带弹性接头的周期管梁模型数值仿真及模型试验验证所提方法。     

Optimal design of sensor networks for vehicle detection, classification, and monitoring

The tracking and identification of vehicles for the purpose of surveillance is a widespread application. Observations from a network of sensors can be used to make decisions regarding the identity of vehicles, as well as their trajectories. Generally, the information provided by a sensor network is limited, so vehicles may be misclassified, go undetected, and/or their trajectories may not be determined uniquely. Often, assumptions are made regarding, for example, traffic composition and possible vehicle trajectories. Because the performance of a sensor network can be sensitive to these assumptions, the conclusions made by the network about the identity and trajectory of vehicles can be highly inaccurate. In this paper, these assumptions are treated as possible models of reality that are subsequently evaluated in a decision framework. Mathematical models for vehicle movement and sensor behavior are developed. Candidate designs for the sensor network are considered, where each design is defined by the number, location, and range of the sensors. Methods from decision theory are used to determine the optimal design for the sensor network.     

Comment: Toward the practical use of expert system technique for process disturbance management

A methodology is proposed which can be used to design real-time expert systems for on-line process disturbance management. This methodology encompasses diverse functional aspects that are required for an effective process disturbance management: (1) intelligent process monitoring and alarming, (2) on-line sensor data validation and sensor failure diagnosis, (3) on-line hardware (besides sensors) failure diagnosis, and (4) real-time corrective measure synthesis. Accomplishment of these functions is made possible through the integrated application of the various models: goal-tree success-tree, process monitor tree, sensor failure diagnosis, and hardware failure diagnosis models. This paper presents and discusses the various models along with the overall algorithm of the methodology. The application of the methodology to a target process, a typical main feedwater system of a nuclear power plant which employs a complex control mechanism, will be presented in a companion paper.     

A grid of dielectric sensors to monitor mold filling and resin cure in resin transfer molding

A grid of 50 dielectric sensors has been embedded in the walls of a mold to monitor resin transfer molding (RTM). The capacitance of each sensor increased as resin occupied the space between sensor plates, and it decreased with curing. Monitoring data can be used for process control to prevent dry spots and to determine when to de-mold the part. In previous studies, Skordos et al. [Skordos AA, Karkanas PI, Partridge IK. A dielectric sensor for measuring flow in resin transfer molding. Meas Sci Technol 2000;11:25–31] used a lineal sensor, Hegg et al. [Hegg MC, Ogale A, Mescher A, Mamishev AV, Minaie B. Remote monitoring of resin transfer molding processes by distributed dielectric sensors. J Compos Mater 2005;39(17)] used three large sensors. As experimentally shown in this study, these lineal or large-plate dielectric sensors may mislead since a sensor measures total fraction of the sensor’s plate area occupied by resin but not the resin’s whereabouts. To avoid ambiguity and yet maintain detailed monitoring, a sensor grid was made at the projections of embedded orthogonal electrodes. The developed sensor operation system eliminated tedious and costly manufacturing of conventionally shielded separate sensors. The success of the developed sensor system was demonstrated in RTM experiments.     

Development of life extension strategies for Australian military aircraft, using structural health monitoring of composite repairs and joints

The DSTO Centre of Expertise for Structural Mechanics (COE-SM) has recently developed methodologies for simulating structural health monitoring (SHM) systems for adhesively bonded composite repairs to Australian military aircraft. System design, interrogation strategy, and sensor placement are discussed, with particular emphasis on the development of techniques for embedding optical fibre sensors for optimal SHM system response.     

Sensor technologies for monitoring metabolic activity in single cells-part II: nonoptical methods and applications

A review of solid-state chemical and electrochemical sensors to detect metabolic activity at the extracellular, single-cell level is presented in the context of the development of lab-on-a-chip research instrumentation. Metabolic processes in cells are briefly reviewed with the goal of quantifying the role of metabolites within the cell. Sensors reviewed include both research and commercial devices that can noninvasively detect extracellular metabolites, including oxygen, carbon dioxide, and glucose. Metabolic activity can also be sensed nonselectively by measuring pH gradients. Performance metrics, such as sensitivity, sensor size, drift, time response, and sensing range, are included when available. Highly suitable sensor technologies for monitoring cellular metabolic activity include electrochemical sensors, scanning electrochemical microscopy, ion-sensitive field effect transistor sensors, and solid-state light-addressable potentiometric sensors. Other less-suitable, but still potentially viable, solid-state sensing technologies are also reviewed briefly, including resonant chemical sensors (surface acoustic wave and quartz crystal microbalance), conductivity or impedance sensors, and sensors with multiple transduction stages. Specific biological applications which benefit from detection of extracellular metabolic events at the single-cell level are discussed to provide context to the practical use of these sensor technologies; these applications include case studies of various diseases (cancer, diabetes, mitochondrial disorders. etc.), cell and tissue differentiation; cell and tissue storage; cell life cycle and basic cellular processes; and developmental biology.     

Frequency-coded chemical sensors

We have developed a new method to intelligently sample analytes and introduce the analytes to sensors. The method automatically adjusts sampling duration according to the sensors' response to the analytes and converts the amplitude of the sensor output to a frequency output, giving us another opportunity to reduce noise in the signal. It also addresses some of the common sensor issues such as response time, saturation, chemical dynamic range, and sensor protection, saving precious detection time, protecting sensors, and enabling sensitive sensors built for low-concentration detection to be used for high-concentration detection as well. We have put together a system using a tuning fork chemical sensor as a sample sensor to demonstrate the feasibility and benefits of the new sensing technique.     

Optical-fiber sensor using tailored porous sol-gel fiber core

A new concept in optical-fiber chemical sensors, the active fiber core optical sensor (AFCOS), is presented. In this sensor, the fiber core acts as a transducer. The sensitivity of an AFCOS sensor is compared with that of an active coating [evanescent wave (EW)] based optical-fiber sensor. Requirements for a fiber core to act as a chemical sensor are discussed. Novel techniques for making a porous sol-gel silica fiber, doping chemical reagents into the fiber, and constructing a chemical sensor using the porous fiber as a transducer have been developed. The microstructure of the fabricated sol-gel silica fiber and the effect of the fiber's microstructure on the capability of the porous sol-gel silica fiber for guiding light are discussed. A humidity sensor employing a CoCl/sub 2/-doped porous sol-gel fiber as a transducer has been constructed as an example. The test results for the humidity sensor verified a theoretical analysis indicating that an optical-fiber chemical sensor using an active fiber core as a transducer has a much higher sensitivity than that of an EW-based sensor.     

Partial analytical solution of a model used for measuring oxygen diffusion coefficients of polymer films by luminescence quenching

Many aspects of optical chemical sensor design would benefit from a better knowledge of the diffusion properties of the analyte in the polymer host. The response times of such sensors to a step change of analyte concentration are of vital interest for many applications of fast-responding sensors. Further, the diffusion properties govern their quenching behavior and their sensitivity. A method for determination of the diffusion constant of oxygen in polymers has been developed and used by several groups in the past. The underlying mathematical model for luminescence quenching by molecules of a gas in a single sensing layer on an impermeable support has not yet been completely derived in an analytical form and still uses tedious numerical methods. We present a partial analytical solution to the problem of modeling the time dependence of luminescence generated by in- or out-diffusion of a gaseous quencher in a polymer film in which a luminophor is immobilized and offer a suitable method to predict sensor response times.     

Improvement of surface acoustic wave gas and biosensor response characteristics using a capacitive coupling technique

As for many other electronic devices and circuits, electrical contact to surface acoustic wave sensors is usually made using bonding wires. This technique is known to result in reliable contact under most conditions, but it does so with several disadvantages. First, electrical contact is not reversible, impeding replacement of sensor devices. Second, bonding wires are quite delicate and should not be exposed to high gas or liquid flows. Third, the presence of bonding wires may limit the potential to miniaturize a sensor housing or flow cell. Therefore, a capacitive coupling technique was developed to replace bonding wires. This permitted redesign of flow cells and sensor arrays, resulting in flow cell volumes of 80 microL to 60 nL. As a consequence, response times were reduced to 1-2 s in gas sensing and a few minutes in liquid sensing, respectively. At the same time, sensor devices can be easily replaced, and the system is less susceptible to malfunction.     

A novel integrated acoustic gas and temperature sensor

Acoustic temperature sensors have the advantages of a high-resolution frequency output and ease of integration with other acoustic sensors but require hermetic packaging to prevent sensor contamination. Surface-skimming bulk-wave (SSBW) devices have been found to be much less sensitive to surface contamination than other acoustic devices, and although their temperature response has been studied extensively, they have not been studied specifically as temperature sensors. Surface acoustic wave (SAW) based chemical sensors requiring temperature measurement or control are susceptible to temperature measurement error because the temperature cannot be measured in the same location as the chemical sensor. The objectives of this work were to examine the temperature characteristics and performance of a SSBW temperature sensor when integrated with a SAW condensation and humidity sensor in a novel design. The SSBW temperature sensor had over an order of magnitude less sensitivity to condensation and water uptake in certain polyimide films than an integrated SAW gas sensor indicating that this design is practical for sensing films in the delay path where film thickness is carefully considered.     

A model-based approach to on-line process disturbance management: The application

A model-based methodology for developing a real-time expert system for on-line process disturbance management has been presented in the companion paper (Reliab. Engng Sys. Safety, Vol. 28, pp. 265–305). The methodology includes diverse functional aspects required for effective process disturbance management: intelligent process monitoring and alarming, sensor failure diagnosis, hardware (except sensors) failure diagnosis, and corrective measure synthesis.The application of the methodology to a target process—the main feedwater system of a pressurized water reactor (PWR) nuclear plant employing a complex control scheme—is presented in this paper. The performance tests of the real-time expert system, MOAS II, developed by the application of the methodology demonstrate that the expert system successfully carries out its intended functions: early detection of occurring disturbance, correct diagnosis of the disturbance cause, and presentation of optimal control advice to the operator. Therefore, the model-based technique lends itself to the development of a valuable operator aid for on-line process disturbance management.