Performance Of Sensing System Research Articles

Model-Based Position and Reflectivity Estimation of Fiber Bragg Grating Sensor Arrays.

We propose an efficient model-based signal processing approach for optical fiber sensing with fiber Bragg grating (FBG) arrays. A position estimation based on an estimation of distribution algorithm (EDA) and a reflectivity estimation method using a parametric transfer matrix model (TMM) are outlined in detail. The estimation algorithms are evaluated with Monte Carlo simulations and measurement data from an incoherent optical frequency domain reflectometer (iOFDR). The model-based approach outperforms conventional Fourier transform processing, especially near the spatial resolution limit, saving electrical bandwidth and measurement time. The models provide great flexibility and can be easily expanded in complexity to meet different topologies and to include prior knowledge of the sensors. Systematic errors due to crosstalk between gratings caused by multiple reflections and spectral shadowing could be further considered with the TMM to improve the performance of large-scale FBG array sensor systems.

Nondestructive Evaluation of Far-Side Corrosion Around a Rivet in a Multilayer Structure

ABSTRACTThis paper presents a sensor system for inspection of far-side defects around rivets in a multilayer structure. The sensor system includes 64 InSb Hall sensors arrayed in 0.52-mm intervals, over a total length of 33.28 mm. The sensor system was tested on two flat specimens, which have two layers of an aluminum alloy, with and without far-side defects around rivets. The sensor system performance was estimated via both the receiver operating characteristic and the probability of detection (POD) curves. Furthermore, a quantitative evaluation of the surface area, depth, and volume of a defect having a POD greater than 90% was carried out.

A Novel Wearable Device for Food Intake and Physical Activity Recognition.

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure.

A self-calibrated Wireless Sensing System for monitoring the ambient industrial environment. From lab to real-time application

The sensing performance of a self-calibrated Wireless Sensing System (WSS) was evaluated under laboratory and real environment conditions. The Wireless Sensing Node consists of a sensor array based on chemocapacitors, which is integrated with appropriate low power consumption read-out electronics and is connected with appropriate wireless module. The sensing system was evaluated and calibrated under laboratory conditions with two different VOCs transfer methods: dynamic and static. The sensing unit calibration deals with changes of VOCs and/or humidity concentration and temperature variations, simulating the real industrial environment. Finally the WSS was placed in the workspace of a printed flexing packaging industrial installation and comparison with the already installed commercial detectors was performed. A very good agreement between the results of the two measurement systems is demonstrated. Additionally these results showed that the WSS is characterized by fast response with high repeatability and long-term stability. Concluding, this system is suitable for the targeted application.

Investigation of the Shielding Length on Yukawa System Crystallization in Mobile Sensor Network Applications

In modern information technology, mobile sensor networks (MSNs) play an important role in industrial or military applications, so sensor deployment is a key issue in MSN research. Based on wireless communication theory, hexagonal topology is known to provide the best field coverage, limited nodes, and minimal system cost. In the 2-D dusty plasma physical system, plasma particles are capable of forming a good hexagonal structure based on Yukawa system crystallization. Therefore, this strategy can be applied to node deployment algorithm in MSN applications. For this paper, we used a 2-D dusty plasma simulation in order to provide node deployment for a large sensor network, and, for better performance evaluations, adopted the Delaunay triangulation in order to determine adjacent particles of a given dust particle. Sensor deployment distributions and system performance were carefully examined by considering various values for the shielding length and the computation scale in simulations. Here, we discuss the influence of the shielding rule in Yukawa system crystallization on sensor deployment applications. Our results indicate that the algorithm leads to better field coverage with perfect hexagonal topology, good system uniformity, and lower energy consumption, and can be considered as an aid for fast deployment experiments when thousands of wireless sensors are required within a large-scale area.

Miniature Multiaxial Optoelectronic Shear Stress Sensing System Based on a Segmented Photodiode

Recording shear stresses is becoming relevant in an increasing number of applications, e.g., in rehabilitation sciences, where detecting foot-sole interaction is very important. This paper describes a portable and complete system to record multiaxial shear stresses. The sensing operation itself is based on the changing coupling of light between a vertical-cavity surface-emitting laser (VCSEL) and a segmented photodiode. Applying shear stress causes lateral displacement of both optoelectronic components leading to variation in the photocurrent. By combining signals from different photodiode segments, multiaxial shear stresses can be detected. A standalone system was designed to drive the VCSEL and to readout the signals from the different photodiode segments in order to measure shear stress as well as to evaluate the sensing system performance. Furthermore, the sensor signals can be efficiently monitored and visualized on a tablet or PC in real-time using dedicated software. The design presented in this article is optimized to measure shear forces with a magnitude up to 2 N and arbitrary direction. Yet, by changing the transducer material this range can be tuned for a specific application.

Detection Capacities of Distributed and Centralized Systems: A Comparative Study

Distributed systems using many inexpensive sensors widely distributed over a large area present an alternative way for target detection and potential paradigm change in environmental sensing. The diversity of opportunities for detection by widely distributed sensors seems attractive, but how one compares the detection performance based on the observations made from many distributed sensors, each with small gain, with that from a centralized system with a high array gain has not been studied theoretically or experimentally. Treating the target-radiated signal as a communication signal, transmitting continuous Gaussian-distributed alphabets, the Shannon channel capacity yields the maximum information that the receivers can learn about the (target) transmitted signal. For this idea case, the channel capacity can then be used as a metric to compare the performance of various sensor systems. Matched track processing is introduced to motivate a capacity-based detector and the corresponding detection capacity. Based on that, it is found that the distributed systems can achieve, in principle, an area of coverage two to three times larger than that of a centralized system under the right conditions, and the area of coverage by the entire system can be significantly larger than the sum of detection areas of individual nodes for distributed systems.

Improved Performances of Ethanol Sensor Fabricated on Al-Doped ZnO Nanosheet Thin Films

The effect of Al-doped ZnO (AZO) to the sensitivity improvement of ethanol vapor sensor was investigated. The pure ZnO and AZO thin films were synthesized by chemical bath deposition method. Analysis of the crystal structure, chemical composition, and morphology of the samples are carried out using X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), and scanning electron microscopy (SEM). XRD results show that the phase formed is polycrystalline Zn, while the EDS measurements show that the composition of after synthesized AZO were 1.48 at%, 2.90 at%, and 3.55 at%. The SEM results showed flowerlike microstrcuture and nanosheet shaped are formed in the resulting thin films, which are captured by the formation of sheets of transparent structure in AZO. Moreover, the resulting ZnO and AZO sensors were exposed to the different concentration of ethanol vapor as much as 200, 400, and 600 ppm, respectively. The measurement of vapor sensor system performance was tested to analyze the sensitivity and the responsiveness of the AZO thin films. The sensors have highest sensitivity at certain amount of Al doping. It is obtained that the optimum sensitivity of the sensor is investigated at the sample of 2.9 at% Al-ZnO. The sensitivity for pure ZnO sample at concentration of 200, 400, and 600 ppm of ethanol were 70.88%, 78.21%, and 88.57%, respectively. The highest sensitivity for AZO samples is 95.29% at low ethanol concentrations (200 ppm) and 96.68% at the high concentration (parts per million), respectively.

Miniaturized Photoacoustic Trace Gas Sensing Using a Raman Fiber Amplifier

This paper presents the development of a Raman fiber amplifier optical source with a maximum output power of 1.1 W centered around 1651 nm, and its application in miniaturized 3D printed photoacoustic spectroscopy (PAS) trace gas sensing of methane. The Raman amplifier has been constructed using 4.5 km of dispersion shifted fiber, a 1651 nm DFB seed laser and a commercial 4W EDFA pump. The suppression of stimulated Brillouin scattering (SBS) using a high frequency modulation of the seed laser is investigated for a range of frequencies, leading to an increase in optical output power of the amplifier and reduction of its noise content. The amplifier output was used as the source for a miniature PAS sensor by applying a second modulation to the seed laser at the resonant frequency of 15.2 kHz of the miniature 3D printed gas cell. For the targeted methane absorption line at 6057 cm-1 the sensor system performance and influence of the SBS suppression is characterized, leading to a detection limit (1σ) of 17 ppb methane for a signal acquisition time of 130 s, with a normalized noise equivalent absorption coefficient of 4.1•10-9 cm-1 W Hz-1/2 for the system.

Development of a Bridge Weigh-in-Motion Sensor: Performance Comparison Using Fiber Optic and Electric Resistance Strain Sensor Systems

This paper addresses the problems of effective <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> measurement of the real-time strain for bridge weigh in motion in reinforced concrete bridge structures through the use of optical fiber sensor systems. By undertaking a series of tests, coupled with dynamic loading, the performance of fiber Bragg grating-based sensor systems with various amplification techniques were investigated. In recent years, structural health monitoring (SHM) systems have been developed to monitor bridge deterioration, to assess load levels and hence extend bridge life and safety. Conventional SHM systems, based on measuring strain, can be used to improve knowledge of the bridge’s capacity to resist loads but generally give no information on the causes of any increase in stresses. Therefore, it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, adhesives layer, and strain sensor. The results show the benefits in the use of optical fiber networks under these circumstances and their ability to deliver data when conventional sensors cannot capture accurate strains and/or peak strains.

Acoustic emission detection and position identification of transverse cracks in carbon fiber–reinforced plastic laminates by using a novel optical fiber ultrasonic sensing system

Utilizing optical fiber technique to structural health monitoring of composite materials is attracting attention recently due to the inherent advantages in optical fiber sensor. However, acoustic emission signals with low energy and high frequency from transverse cracks in carbon fiber–reinforced plastic laminates are difficult to be detected by normal optical techniques. In this work, we present a phase-shifted fiber Bragg grating balanced sensing system to detect acoustic emission signals generated in a carbon fiber–reinforced plastic laminate in a three-point bending test. We demonstrated that the phase-shifted fiber Bragg grating balanced sensing system with a broad bandwidth and high sensitivity can detect high-frequency, low-energy acoustic emission signals caused by transverse cracks. In our experiments, the transverse cracks were identified very well through the detected acoustic emission signals. The relationship between the strain and the acoustic emission signals, and the typical waveforms of the acoustic emission signals were investigated. Furthermore, accurate position identification using acoustic emission detection by the phase-shifted fiber Bragg grating sensor was demonstrated. All the results obtained from the phase-shifted fiber Bragg grating sensor were compared to the results obtained from commercial lead–zirconate–titanate acoustic emission sensors. We found that the phase-shifted fiber Bragg grating balanced sensing system performance was comparable to the commercial lead–zirconate–titanate acoustic emission sensors.

A Fast Estimation of the EO/IR System Performances Using the Image Simulation in a Turbulent Atmosphere

The paper presents a fast evaluation method for the image quality acquired with the EO/IR sensors. The principle of the proposed method is based on the analysis of the histograms of the images acquired using atmospheric turbulence simulations and, then, by the analysis ofthe histograms extracted from simulations. It is assumed that the assessment of an EO/IR sensor system performance can be known in poor visibility conditions, where the atmospheric turbulences have an essential contribution.

Adaptive Fault Diagnosis for T–S Fuzzy Systems With Sensor Faults and System Performance Analysis

It is well known that there always exist some level of time delay between fault occurrence and fault accommodation, which is called as the time delay due to fault diagnosis (TDDTFD) in this paper. TDDTFD may cause severe loss of system performance and stability. This paper investigates the TDDTFD's adverse effect on the system performance. First, a fault diagnosis (FD) model is constructed to diagnose sensor faults which integrate time-varying gain and bias faults, where a novel FD algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Meanwhile, the time spent at each step in FD and its analytical expression are derived strictly. Further, the analysis of the system performance degraded by TDDTFD is developed, and the conditions under which the magnitudes of sensor faults should be satisfied such that the state of the faulty system controlled by the normal controller remains bounded during TDDTFD are derived. In addition, the corresponding solutions are proposed to minimize the adverse effect of the time delay. Finally, simulation results of near-space vehicle attitude dynamics are presented to demonstrate the efficiency of the proposed approach.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Volumetric mass flow sensor for citrus mechanical harvesting machines

A volume-based mass flow sensor system was developed to estimate the total mass of fruit travelling on the inclined and horizontal conveyors of two citrus mechanical harvesting systems. A LIDAR (light detection and ranging) sensor was used to scan the conveyor cross-sectional area and use the distance related-information to estimate the bulk volume and total mass of fruit on the conveyor by integrating the data over time. A custom algorithm was developed to analyze the data and calculate the fruit volume. Fruit volume was used to estimate the total fruit mass.Sensor system was tested in the laboratory on two different conveyor systems: an inclined conveyor used in a mechanical harvester (conveyor flap height=8cm), and a horizontal conveyor used in a debris removal system (conveyor flap height ⩽3cm). The tested conveyor speeds ranged from 0.59m/s to 1.71m/s. The system performance for the tested speed ranges was an average error of 7% (standard deviation [SD]±7%) and 7% (SD±5%) for the inclined and horizontal conveyors, respectively. The average total fruit mass estimation error during mechanical harvesting was 10% (SD±6%) for 11 field trails that involved scanning 512–1356kg of the fruit on a horizontal conveyor of a debris removal system. Overall, the developed sensor system can be used for volumetric yield monitoring of citrus. The sensor system performance will likely be improved using instant conveyor speed during the estimation of total fruit mass.

Performance comparison of distributed and centralized systems based on information

Distributed systems using many sensors widely distributed over a large area present an alternative way for target detection and environmental sensing. The diversity of opportunities for detection by widely distributed sensors seems attractive but the signals received on distributed sensors are usually not coherent due to the wide separations between the receivers. Hence, conventional approaches based on signal coherence/gain no longer apply. In this paper, information theory will be used to compare their performance. Treating the target radiated signal as a communication signal, transmitting continuous Gaussian-distributed alphabets, the Shannon channel capacity yields the maximum information that the receivers can learn about the (target) transmitted signal. The channel capacity can then be used as a metric to compare the performance of various sensor systems in the ideal case. Matched tracking processing is introduced to motivate a capacity-based detector and detection capacity. Based on that, it is found that the distributed systems can achieve in principle an area of coverage two to three times larger than that of a centralized system under the right conditions, and the area of coverage by the entire system can be significantly larger than the sum of detection areas of individual nodes.

Designing Sensitive Wearable Capacitive Sensors for Activity Recognition

We investigate the design space of flexible, textile capacitive sensors for applications in human activity recognition. In a previous paper, we showed that conductive textile patches can be used to measure capacitance of the human body and could reveal information about a broad range of activities. In this paper, we systematically investigate how different design parameters such as electrode size, electric field frequency, and the concrete analog circuit design influence sensor performance. To this end, we combine FEM electric field simulations, circuit analysis, and measurements. We illustrate the performance of sensor systems that implemented according to the design guidelines that we derived. Results from four typical activity recognition scenarios were considered, including heart rate and breathing rate monitoring, hand gesture recognition, swallowing monitoring, and gait analysis.

UAV-borne X-band radar for collision avoidance

SUMMARYThe increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.

Design and Analysis of an Embedded Accelerometer Coupled Self-Mixing Laser Displacement Sensor

This paper presents the operating principle and signal processing needed for the design of a reliable solid-state accelerometer (SSA) coupled self-mixing (SM) interferometric laser displacement sensor for embedded applications. The influence of signal processing methods and accelerometer characteristics on the complete sensing system performance is studied, and four different SSA-SM sensing systems are examined and characterized. Through comparing their performance, the sensing system precision is limited by the noise density of the employed accelerometer as well as the used SM displacement retrieval technique, whereas the system bandwidth is mainly limited by the choice of a given accelerometer. Furthermore, this paper analyzes the phase and gain-matching properties that the SSA-SM should reach to guarantee proper extraneous vibrations correction. Finally, the proof of concept of a real-time SSA-SM sensing system indicating 30-dB correction is presented. This prototype demonstrates the possibility of using such a real-time sensing system for embedded and industrial applications in which the presence of extraneous movements would hinder traditional sensors use.

Spectral probability density as a tool for marine ambient noise analysis

The empirical probability density of the power spectral density has been successfully applied as tool to assess signal variability and sensor system performance in the seismic literature. This paper presents the application of this analysis method to underwater ambient noise measurements, and demonstrates its utility in assessing the field performance of passive acoustic monitoring systems and the statistical distribution of noise levels across the frequency spectrum. Using example datasets from an autonomous passive acoustic recorder in the Moray Firth, Scotland, UK, and a cabled subsea observatory in the Strait of Georgia, British Columbia, we show how this method can reveal data limitations such as persistent tonal components and insufficient dynamic range, and phenomena such as bimodality and outliers, which may be undetected by standard analysis techniques. We then combine this approach with conventional percentiles and spectral averages, illustrating how the underlying noise level distributions influence these metrics, and propose this technique as a standard, integrative presentation of ambient noise spectra. Finally, the paper presents cumulative probability density as a method for frequency-domain characterization of chronic noise exposure in marine acoustic habitats.