Sensor Performance Degradation Research Articles

Performance Degradations of MISFET-Based Hydrogen Sensors with a Pd-Ta2O5-SiO2-Si Structure During Long-Term Operation.

We present the generalized experimental results of performance degradation of hydrogen sensors based on metal-insulator-semiconductor field effect transistor (MISFET)with the structure Pd-Ta2O5-SiO2-Si. The n-channel MISFET elements were fabricated on silicon single chips together with temperature sensors and heater-resistors by means of conventional -technology. Two hundred cycles of responses to different hydrogen concentrations were measured during eight weeks using special measuring and temperature stabilization circuitries with a feedback loop based on the chip’s thermo-sensor and heater. We show how the response parameters change during long-term tests of sensors under repeated hydrogen impacts. There were two stages of time-dependent response instability, the degradation of which depends on operating conditions, hydrogen concentrations, and time. To interpret results, we proposed the models, parameters of which were calculated using experimental data. These models can be used to predict performances of MISFET-based gas analysis devices for long-term operation.

Sensitivity enhancement and temperature compatibility of graphene piezoresistive MEMS pressure sensor

MEMS pressure sensor has shown a remarkable change in revenue collection during the year 2018. Due to recent growth in smart microsystem technology for automation systems, demand has grown substantially for sensors. High sensitivity, flexibility, miniaturization and bulk production are some of the key factors of a pressure sensor in achieving new heights in the MEMS market. In this paper, Graphene piezo resistive material has been analysed for pressure sensing elements and compared with Polysilicon in terms of sensitivity and sensor performance degradation at different temperature. MEMS pressure sensors using Polysilicon and Graphene piezo resistive materials were simulated on silicon (100) substrate by COMSOL Multiphysics 5.3a version. The simulation result shows that at room temperature polysilicon pressure sensor performs well with pressure sensitivity of 3.81 mV/psi as well as it is found that graphene pressure sensor also shows better results at room temperature showing a pressure sensitivity of 3.98 mV/psi. As on frequently increasing the temperature it is noticed that polysilicon pressure sensitivity degrades with a factor of 0.64 mV/psi. However, graphene pressure sensor shows very less variation in sensitivity at higher temperature. Although it shows a small increment of 0.02 mV/psi in the pressure sensitivity. This analysis opens the path to utilise the graphene pressure sensor at high temperature.

Nonlinear spectrum broadening and its impact on performance of Rayleigh-scattering-based distributed strain/temperature fiber optic sensors

A Rayleigh-scattering-based distributed strain/temperature fiber optic sensor using low-coherence light is experimentally investigated at probe pulse powers well above the nonlinear effect threshold. OTDR technology is used for special channel interrogation. It is established that for an SMF-28e+ fiber this threshold is about 100 mW. Exceeding this power leads to the degradation of sensor performance and is explained by nonlinear spectrum broadening. The evolution of the probe pulse spectrum is investigated using a tunable MEMS filter. A novel version of the arrangement for the sensor is proposed, which partially overcomes the limitations associated with said effect. As low as 2.2 µε, the RMS noise level for strain is demonstrated at a distance of 25 km. The spatial resolution is estimated as 1.5 m, the data collection time is 20 min, and the average power in the fiber is about 0.2 mW, which allows the sensor to be used for infrastructure monitoring under explosive conditions.

Structural damage detection considering sensor performance degradation and measurement noise effect

In the real civil structures, material deterioration, overloading and environmental corrosion inevitably lead to sensor performance degradation or sensor fault. Sensor performance degradation or sensor fault usually introduce observable changes in the measured structural responses, which may be incorrectly interpreted as structural damage. This paper proposes a novel approach to quickly distinguish sensor fault from structural damage and locate the faulty or degraded sensors. Two steps are involved in this approach. In the first step, the root mean square of the generalized likelihood ratio test (GLRT) is used to detect and localize the structural damage or degraded sensors. In the second step, a new index is proposed used along with the statistical process control chart to distinguish sensor performance degradation from structural damage. The proposed index is the percentage of the extreme value of the largest principal component scores of the generalized likelihood ratio, which not only has excellent noise tolerance but also can distinguish sensor performance degradation from structural damage. The applicability and efficiency of the proposed approach are validated by numerical studies on a planar 11-element truss structure and experimental studies on a simply-supported steel beam in the laboratory. The results demonstrate that the proposed approach can locate the damage accurately when taking into account of sensor performance degradation and environmental noise in the measurements. The proposed index is able to accurately and quickly determine the source of the novelty in the responses.

Study of point- and cluster-defects in radiation-damaged silicon

Non-ionising energy loss of radiation produces point defects and defect clusters in silicon, which result in a significant degradation of sensor performance. In this contribution results from TSC (Thermally Stimulated Current) defect spectroscopy for silicon pad diodes irradiated by electrons to fluences of a few 1014cm−2 and energies between 3.5 and 27 MeV for isochronal annealing between 80 and 280∘C, are presented. A method based on SRH (Shockley–Read–Hall) statistics is introduced, which assumes that the ionisation energy of the defects in a cluster depends on the fraction of occupied traps. The difference of ionisation energy of an isolated point defect and a fully occupied cluster, ΔEa, is extracted from the TSC data.For the VOi (vacancy-oxygen interstitial) defect ΔEa=0 is found, which confirms that it is a point defect, and validates the method for point defects. For clusters made of deep acceptors the ΔEavalues for different defects are determined after annealing at 80∘C as a function of electron energy, and for the irradiation with 15 MeV electrons as a function of annealing temperature. For the irradiation with 3.5 MeV electrons the value ΔEa=0 is found, whereas for the electron energies of 6–27 MeV ΔEa>0. This agrees with the expected threshold of about 5 MeV for cluster formation by electrons. The ΔEavalues determined as a function of annealing temperature show that the annealing rate is different for different defects. A naive diffusion model is used to estimate the temperature dependencies of the diffusion of the defects in the clusters.

Nuclear power plant sensor fault detection using singular value decomposition-based method

In a nuclear power plant, periodic sensor calibration is necessary to ensure the correctness of measurements. Those sensors which have gone out of calibration can lead to malfunction of the plant, possibly causing a loss in revenue or damage to equipment. Continuous sensor status monitoring is desirable to assure smooth running of the plant and reduce maintenance costs associated with unnecessary manual sensor calibrations. In this paper, a method is proposed to detect and identify any degradation of sensor performance. The validation process consists of two steps: (i) residual generation and (ii) fault detection by residual evaluation. Singular value decomposition (SVD) and Euclidean distance (ED) methods are used to generate the residual and evaluate the fault on the residual space, respectively. This paper claims that SVD-based fault detection method is better than the well-known principal component analysis-based method. The method is validated using data from fast breeder test reactor.

Structural response recovery based on improved multi-scale principal component analysis considering sensor performance degradation

This article proposes an improved multi-scale principal component analysis approach to recover the structural dynamic response in the time domain from data measured by performance-deteriorated sensors. The proposed approach builds on discrete wavelet transform, principal component analysis, and inverse discrete wavelet transform. The main approach is based on a cross-correlation calculation to better preserve the true structural vibration behavior as well as to recover the structural response from data measured by deteriorated sensors. Three sensor performance degradation models are considered in this study. Numerical studies are conducted first to demonstrate the effectiveness and accuracy of the proposed approach to recover the structural vibration response of an example spatial truss model considering sensor performance degradation under different loading scenarios. Experimental data on an in-field benchmark bridge are also analyzed to further validate and demonstrate the performance of the proposed approach.

A sensor-driven structural health prognosis procedure considering sensor performance degradation

This article presents a general framework for sensor-driven structural health prognosis and its application to probabilistic maintenance scheduling. Continuously collected sensor data is used to update the parameters of the stochastic structural degradation model. Uncertainty in sensor data (i.e. measurement error) is explicitly modelled as an evolving stochastic process. The proposed framework utilises Bayesian theorem and Markov Chain Monte Carlo (MCMC) sampling to calculate the posterior distributions of stochastic parameters of the structural degradation model. Bayesian updating allows the use of dynamic diagnostic information with prior knowledge for improved prognosis including risk analysis and remaining useful life (RUL) estimation. Although the proposed sensor-driven structural health prognosis procedure is illustrated with a fatigue-related example, it is applicable to more general applications such as corrosion and pavement cracking. A case study of the fatigue details found in a prototype steelgirder bridge has been conducted to demonstrate the proposed prognosis and maintenance scheduling procedure.

A Game Theoretic Sensor Resource Allocation Using Fuzzy Logic

A sensor resource management system that employs fuzzy logic to provide the utility functions to a game theoretic approach is developed. The application looks at a virtual fence problem where several unattended ground sensors are placed in remote locations to act as virtual sentries. The goal of the approach is to maximize the battery life while tracking targets of interest. This research also considers the incorporation of uncertainty into the fuzzy membership functions. Both type-2 fuzzy logic and the use of conditional fuzzy membership function are employed. The type-2 fuzzy logic is employed in the case of acoustical sensor tracking accuracy degradation, while the condition-based membership functions are used to adapt to different conditions, such as environmental conditions and sensor performance degradation, over time. The resource management process uses fuzzy logic to determine which of the sensor systems on a sensor pod is used to provide initial classification of the target and which sensor or sensors are to be used in tracking and better classifying the target if it is determined to be of value to the mission. The three different approaches are compared to determine when the best times for the more complex approaches are warranted.

Landsat 4 Thematic Mapper Calibration Update

The Landsat 4 Thematic Mapper (TM) collected imagery of the Earth's surface from 1982 to 1993. Although largely overshadowed by Landsat 5 which was launched in 1984, Landsat 4 TM imagery extends the TM-based record of the Earth back to 1982 and also substantially supplements the image archive collected by Landsat 5. To provide a consistent calibration record for the TM instruments, Landsat 4 TM was cross-calibrated to Landsat 5 using nearly simultaneous overpass imagery of pseudo-invariant calibration sites (PICS) in the time period of 1988-1990. To determine if the radiometric gain of Landsat 4 had changed over its lifetime, time series from two PICS locations (a Saharan site known as Libya 4 and a site in southwest North America, commonly referred to as the Sonoran Desert site) were developed. The results indicated that Landsat 4 had been very stable over its lifetime, with no discernible degradation in sensor performance in all reflective bands except band 1. In contrast, band 1 exhibited a 12% decay in responsivity over the lifetime of the instrument. Results from this paper have been implemented at USGS EROS, which enables users of Landsat TM data sets to obtain consistently calibrated data from Landsat 4 and 5 TM as well as Landsat 7 ETM+ instruments.

Integrity of piezoceramic patch transducers under cyclic loading at different temperatures

In this study the loading limits, damage behavior and long-term integrity of piezoceramicpatch transducers, based on monolithic PZT (lead zirconium titanate) wafers (PIC 255),were investigated. The study involved quasi-static and long-term cyclic testing undertensile and compressive mechanical loading of the patches, at different temperatures. Astrain-cycle lifetime diagram was established for tensile loading at room temperature, and+60,+100 and−40 °C. In all cases of tensile loading, cracking in the PZT ceramic was found to bethe relevant failure mechanism which was shown to be correlated with theobserved degradation of sensor performance of the patches. No mechanicaldamage was found under compressive loading at strain levels of up to−0.6%. Finite element (FE) analyses were performed using 3D material modeling withelectromechanical coupling, achieving very good predictability of the sensor and actuatorperformance. Analytical calculations and numerical simulation were used to interpretexperimental findings and to allow the transfer of results to various applications. Based onmicro-structural investigations of the cracked PZT wafers and FE simulation, fracturemechanics analyses of the local stress situation in the PZT ceramic were carried out.

Effect of surface roughness on the extinction-based localized surface plasmon resonance biosensors

We investigated the effect of surface roughness on the sensor performance of extinction-based localized surface plasmon resonance (LSPR) biosensors. The sensor measures resonance wavelength shifts in transmittance caused by biomolecular interactions that are amplified by periodic nanostructures. The numerical computation was conducted using rigorous coupled-wave analysis with Gaussian random surface profiles. The results suggest that, when a surface has a roughness smaller than 2 nm in height deviation, the sensitivity of a LSPR biosensor is not significantly influenced regardless of correlation length (CL). However, we found that the extinction peak amplitude and curve width are affected substantially by a decrease in CL. At a less than 100 nm CL, surface roughness can induce interference between localized surface plasmons excited by the surface and nanowires, which can lead to major degradation of sensor performance.

Charge Transfer to MEMS Pressure Sensors By Glow Discharge Plasmas

Electrical charging resulting in temporary performance degradation of automotive MEMS pressure sensors has been observed. A method of charge transfer from the outside of a statically charged hose, along the inside the hose, through the module port, to a sensor inside the module is proposed. Specifically, the existence of a glow discharge plasma through the hose, is analyzed with respect to temporary performance degradation. The Paschen equation is used to theoretically predict the breakdown voltage in terms of pressure and distance in the rarified, charged environment to which the ports of the pressure sensors are exposed. Experimental results show no glow or performance degradation in the dark discharge regime, over repeated trials. In the glow discharge regime, visible purple glow with accompanying degradation is observed. At the transition point between the dark and glow regimes, at 20 torr and 5000 V for a discharge distance of 3.5 cm in this experiment, repeated trials resulted in a mixture of glow/degradation and nonglow/unaffected cases. Other proposed modes of charge transfer are qualitatively ruled out, while a quantitative correlation between glow and performance degradation is observed. Therefore, the glow discharge plasma is indicated as the most likely charge transfer mechanism

Memory effects in highly resistive p–i–n heterojunctions for optical applications

Large area p–i–n diode structures based on amorphous hydrogenated silicon can be used as single element image sensors where the information is read out by a scanning laser beam. A high sensitivity is reached with silicon–carbon alloy contact layers. The higher defect density in the large band gap material is usually a problem for efficient carrier collection in solar cell applications. When used as an image sensor, however, the charge stored in deep defects represents an easy way to realize short-term image storage. In the case of a p-(Si:H)/i-(Si:H)/n-(Si x C 1− x :H) sensor structure we have measured a memory effect of approximately 1% after several minutes of image projection. Metastable sensor degradation is observed in accordance with the Staebler–Wronski effect. Fast degradation of sensor performance — corresponding to 90% erasable image storage capability — was studied in an unalloyed structure using a Nd:YAG laser system. The response can be modeled by a stretched exponential decay with parameters depending on the laser pulse energy.

Methods of estimating allowable motion perturbations in side-scan sonar systems

This document describes the effects of nonideal hydrophone array motion on sonar image quality and derives the allowable motion errors for vehicles carrying side-scan sonar systems. Estimates of the quantity of motion that causes just noticeable sensor performance degradation as well as those that render the sensors useless are derived using two different methods. Using a special resolution target, examples of simulated image distortion resulting from several types of motion are presented. A method for quantitatively measuring the actual image distortion in situ is described.

Over-range behavior of sealed-cavity polysilicon pressure sensors

This paper reports the over-range behavior of sealed-cavity polysilicon pressure sensors with full-scale pressures ranging from 0.24 to 2.0 MPa (35 to 290 psi). Because of a built-in over-pressure stop, a fracture pressure between 24 and 41 MPa (3500 to 6000 psi) is observed, which is relatively insensitive to the particular size or range of the sensors investigated. Stress simulations using the finite-element method confirm this and provide a theoretical framework for designing over-range capabilities. Below the fracture range, no degradation in sensor performance is apparent after repetitive cycles of over-pressure to 21 MPa (3000 psi) and the zero repeatability is better than 0.1% of span. These results suggest outstanding over-range capabilities of sealed-cavity polysilicon sensors and exceptional mechanical strength and reproducibility of polysilicon diaphragms for pressure sensing.