Sensor Operating Conditions Research Articles

Time-Efficient SNR Optimization of WMS-Based Gas Sensor Using a Genetic Algorithm.

This paper presents the description of the wavelength modulation spectroscopy (WMS) experiment, the parameters of which were established by use of the Artificial Intelligence (AI) algorithm. As a result, a significant improvement in the signal power to noise power ratio (SNR) was achieved, ranging from 1.6 to 6.5 times, depending on the harmonic. Typically, optimizing the operation conditions of WMS-based gas sensors is based on long-term simulations, complex mathematical model analysis, and iterative experimental trials. An innovative approach based on a biological-inspired genetic algorithm (GA) and custom-made electronics for laser control is proposed. The experimental setup was equipped with a 31.23 m Heriott multipass cell, software lock-in, and algorithms to control the modulation process of the quantum cascade laser (QCL) operating in the long-wavelength-infrared (LWIR) spectral range. The research results show that the applied evolutionary approach can efficiently and precisely explore a wide range of WMS parameter combinations, enabling researchers to dramatically reduce the time needed to identify optimal settings. It took only 300 s to test approximately 1.39 × 1032 combinations of parameters for key system components. Moreover, because the system is able to check all possible component settings, it is possible to unquestionably determine the operating conditions of WMS-based gas sensors for which the limit of detection (LOD) is the most favorable.

Development and Practical Implementation of Digital Observer for Elastic Torque of Rolling Mill Electromechanical System

The strategic initiative aimed at building “digital metallurgy” implies the introduction of diagnostic monitoring systems to trace the technical condition of critical production units. This problem is relevant for rolling mills, which provide the output and determine the quality of products of metallurgical companies. Making up monitoring systems requires the development of digital shadows and coordinate observers, the direct measurement of which is either impossible or associated with numerous difficulties. These coordinates include the spindle torque applied by the spring-transmitting torque from the motor to the rolling stand rolls. The development and research are conducted by the example of the electromechanical systems of the horizontal stand at the plate mill 5000. The stand electric drive characteristics are given, and the emergency modes that cause mechanical equipment breakdowns are analyzed that. The relevance of analyzing transient torque processes in emergency modes has been accentuated. The paper points to the shortcomings of the system for elastic torque direct measurement, including low durability due to the harsh operating conditions of precision sensors. It also highlights the need to install the measuring equipment after each spindle. The disadvantage of the previously developed observer is the function of calculating the electric drive speed derivative. This causes a decrease in noise immunity and signal recovery accuracy. The contribution of this paper is building a digital elastic torque observer that has advantages over conventional technical solutions, based on the theoretical and experimental studies. The technique for virtual observer adjustment was developed and tested in the Matlab-Simulink software package. For the first time, a comprehensive analysis was conducted for spindle elastic torques in emergency modes that caused equipment damage. An algorithm was developed for an emergency shutdown of a stand electric drive in the worst-case mode of strip retraction between work and backup rolls, due to the overlap of the strip on the roll. Further, the algorithm was tested experimentally. The criteria for diagnosing pre-emergencies was then justified. An adaptive motor-braking rate controller was developed. The developed observer and emergency braking system are in operation at the mill 5000. Long experimental research proved the efficiency of dynamic load monitoring and the reduction in the number of equipment breakdowns.

NOISE INFLUENCE ON THE RESOLUTION OF THE SENSORS BASED ON MAGNETIC TRANSISTOR STRUCTURES

Absolute sensitivity is a parameter that directly connects the disturbing value with the response to it, is the determining physical characteristic of the absolute majority of the conversion structure, regardless on the operation principle. This parameter is also considered the main criterion for the quality of the product when using such structures as sensors of the corresponding values. Therefore, the problem of the transducer sensitivity increasing remains relevant in connection with the increasing the sensor number built on new principles: new materials, new functionality and increasing the requirements arising from the sensor operating conditions.

Investigation of effect of train body vibration on measurement of fluctuation pressure on the surface of high-speed train

This paper devotes to investigate the influence of vibration acceleration on measurement of piezoresistive pressure. For the sake of definiteness, sensor operation conditions in high-speed train are considered. Where, the sensor chip is loaded with dynamic accelerations with frequency within 20 Hz. The real state of the pressure sensor under different frequency vibration load is simulated by using large mass method (LMM). And the voltage output of the pressure sensor under different vibration loads was obtained by the joint simulation of electrical- structure. By analysis of different vibration loads and the voltage output of sensors, their internal relations are obtained. These outcomes provide a guidance for elimination of vibration influence in high-speed train surface fluctuation pressure measurement. It is also useful in other fields of pressure sensor operation in acceleration-loaded environments.

A grey-box machine learning based model of an electrochemical gas sensor

A grey-box machine learning based model of an electrochemical O2–NOx sensor is developed using the physical understanding of the sensor working principles and a state-of-the-art machine learning technique: support vector machine (SVM). The model is used to predict the sensor response at a wide range of sensor operating conditions in the presence of different concentrations of NOx and ammonia. To prepare a comprehensive training and test data set, the production sensor is first mounted on the exhaust system of a spark ignition, a diesel engine, and then on a fully controlled sensor test rig. The sensor is not modified, rather the sensor working temperature, all of the sensor cell potentials, and the pumping current of the O2 sensing cell are the model inputs that can be varied while the pumping current of the NOx sensing cell is considered as the model output. A 9-feature low order model (LOM) and a 45-feature high order model (HOM) are developed with linear and Gaussian kernels. The model performance and generalizability are then verified by conducting input-output trend analysis. The LOM with Gaussian kernel and the HOM with linear kernel have shown the highest accuracy and the best response trend prediction.

Optimisation of a silicon microstrip telescope for UA9 crystal channeling studies

A charged particle telescope based on silicon microstrip sensors has been used for several years for data taking at high rates in the CERN H8 beam line using a range of different incident particles. The electronic readout and data acquisition system is based on that developed for the CMS Tracker, and provides almost deadtime-free operation at trigger rates of up to about 10 kHz. The telescope was designed to characterise crystals in channeling studies by the UA9 experiment with the primary objective to validate them for use in a future LHC beam collimation system, hence is optimised for measurement of a single particle in the outgoing arm. The telescope has also been used for other studies of fundamental phenomena associated with the channeling process and further LHC applications. Some of these require a different layout of the telescope, for example to achieve a larger angular acceptance to study longer channeling crystals, or modifications to sensor operating conditions because of the very large electric charge and consequent ionisation energy loss associated with heavy ions. The telescope and its performance are described. Possible improvements are discussed.

Metrological Support for Wireless Sensor Systems

The paper identifies twelve problems of metrological reliability of wireless sensor systems that require their solution. The most urgent is the problem of determining the main parameters of the metrological reliability of wireless sensor systems. It is closely related to solving the problem of self-calibration of optical smart sensors that are part of the smart nodes of the system. The task of self-calibration of smart sensors is solved when three basic conditions are met: 1) when creating and using structurally redundant optical sensors designed to implement methods of redundant measurements; 2) when developing LEDs or other highly stable sources of optical radiation, including those with controlled parameters, for any given spectral range of wavelengths; 3) when creating in micro-performance filters on a priori given range of the spectrum of optical sines. The article describes two methods of metrological support for BSS smart sensors, based on the introduction of information redundancy by conducting three clock cycles of measuring physical quantity with a smart sensor, followed by processing the data using an a priori derived algorithm. The disadvantages and advantages of the methods are shown. It is stated that the use of the theory of excess measurements is the only correct way to solve the problem of self-calibration of sensors and measuring instruments. Given the harsh operating conditions of optical smart sensors, it is preferable to manufacture them using high technology. Today, in Ukraine, no one is engaged in a practical solution to the problems of metrological reliability of wireless sensor systems and the solution of the problems of self-calibration of smart sensors.

High magnetic field test of the ITER outer vessel steady-state magnetic field Hall sensors at ITER relevant temperature.

The ITER outer vessel steady-state magnetic field sensor diagnostics consist of sixty sensor units. Each sensor unit features a pair of ceramic-metal Hall sensors with a sensing layer made of bismuth. The sensors were tested simultaneously in the magnetic field ranging from -12 T to +12 T at the temperature range from 27 to 127 °C. The Hall coefficient and magnetoresistance of the bismuth layer related to the sensors were identified. In the sensor operating conditions, the Hall coefficient dependence on temperature was fitted with an exponential function with a relative error of less than 0.08%, and the dependence on the magnetic field was fitted with a Gaussian-like function with a relative error of less than 0.11%. An alternative expression based on the physical understanding of the free charge carrier transport in semimetals was derived to describe the dependence of the Hall coefficient on the magnetic field, and its fitting error of 1.2 mT in terms of the magnetic field measurement has met the ITER measurement accuracy requirements.

Colloidal lithography nanostructured Pd/PdOx core–shell sensor for ppb level H2S detection

In this work we report on plasma oxidation of palladium (Pd) to form reliable palladium/palladium oxide (Pd/PdOx) core–shell sensor for ppb level H2S detection and its performance improvement through nanostructuring using hole-mask colloidal lithography (HCL). The plasma oxidation parameters and the sensor operating conditions are optimized to arrive at a sensor device with high sensitivity and repeatable response for H2S. The plasma oxidized palladium/palladium oxide sensor shows a response of 43.1% at 3 ppm H2S at the optimum operating temperature of 200 °C with response and recovery times of 24 s and 155 s, respectively. The limit of detection (LoD) of the plasma oxidised beam is 10 ppb. We further integrate HCL, a bottom-up and cost-effective process, to create nanodiscs of fixed diameter of 100 nm and varying heights (10, 15 and 20 nm) on 10 nm thin Pd beam which is subsequently plasma oxidized to improve the H2S sensing characteristics. The nanostructured Pd/PdOx sensor with nanodiscs of 100 nm diameter and 10 nm height shows an enhancement in sensing performance by 11.8% at same operating temperature and gas concentration. This nanostructured sensor also shows faster response and recovery times (15 s and 100 s, respectively) compared to the unstructured Pd/PdOx counterpart together with an experimental LoD of 10 ppb and the estimated limit going all the way down to 2 ppb. Material characterization of the fabricated Pd/PdOx sensors is done using UV–vis spectroscopy and x-ray photoemission spectroscopy.

An electro-optical test system for optimising operating conditions of CCD sensors for LSST

We describe the commissioning of a system which has been built to investigate optimal operation of CCDs for the LSST telescope. The test system is designed for low vibration, high stability operation and is capable of illuminating a detector in flat-field, projected spot, projected pattern and Fe-55 configurations. We compare and describe some considerations when choosing a gain calibration method for CCDs which exhibit the brighter-fatter effect. An optimisation study on a prototype device of gain and full well with varying back substrate bias and gate clock levels is presented.

IDENTIFICATION OF NOMINAL DYNAMIC CHARACTERISTICS OF AIRCRAFT GAS TEMPERATURE SENSORS

The existing methods only allowed to determine the dynamic or average characteristics of specific copies of gas temperature sensors as the airflow test results of a limited number of specific copies of gas temperature sensors were carried out on a certified airflow equipment. The actual operating conditions of aircraft gas temperature sensors significantly differ from those at airflow equipment. The aim of the study was to develop methods of recalculation of a test results of a limited number of gas temperature sensors that were received at certified airflow equipment and to get nominal dynamic characteristics of a particular type of gas temperature sensors in the anticipated operating conditions. This study offers the algorithm for the identification of the nominal dynamic characteristics of gas temperature sensors that are used to measure the temperature of gases in aircraft gas turbine engines. The algorithm makes it possible to 1) register the transient characteristics of gas temperature sensors of a particular type at a predetermined rate of air flow, 2) calculate the heat transfer coefficient between the gas temperature sensors and the air flow at each airflow rate, 3) measure the average transient characteristics of the gas temperature sensors at each airflow rate, 4) set the parameters of the hyperbolic function of the nominal variables of the time constants of selected gas temperature sensors from the heat transfer coefficient. The heat transfer coefficient is calculated based on the expected operating conditions of the gas temperature sensors. The result of the study was that the parameters of the hyperbolic function of the nominal variables of the time constants for the dynamic model of the second order gas temperature sensors were found. The developed method makes it possible to predict the dynamic performance of the specific types of gas temperature sensors in the expected operating conditions.

Soil water content in southern England derived from a cosmic‐ray soil moisture observing system – COSMOS‐UK

AbstractCosmic‐ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area‐averaged near‐surface (top 10–20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011–2014 and are the first such field‐scale measurements made in the UK. These four sites are prototype stations for a UK COsmic‐ray Soil Moisture Observing System, and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator 10‐cm soil moisture layer shows that these data can be used to test and diagnose model performance and indicate the potential for assimilation of these data into hydro‐meteorological models. The application of these large‐area soil water content measurements to evaluate remotely sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COsmic‐ray Soil Moisture Observing System network are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

Low-frequency noise characterization of single CuO nanowire gas sensor devices

Low-frequency noise properties of single CuO nanowire devices were investigated under gas sensor operation conditions in dry and humid synthetic air at 350 °C. A 1/f noise spectrum was found with the normalized power spectral density of current fluctuations typically a factor of 2 higher for humid compared to dry atmosphere. A core-shell nanowire model is proposed to treat the noise as parallel combination of gas-independent bulk and gas-dependent surface noise components. The observed increase in 1/f noise in the presence of water vapor is explained in terms of Hooge's mobility fluctuation model, where the increased surface noise component is attributed to carrier scattering at potential fluctuations due to hydroxyl groups at the nanowire surface.

Virtual sensor array as a tool for classifying air pollution

This work examined the acquisition of information about gases using a virtual sensor array and classification. We were particularly interested in the approach in which classes are defined in a qualitative–quantitative manner, that is, by identifying the gas and concentration range. This type of information will be of interest for air pollution assessment purposes. In this field of application, it is often not necessary to provide very precise information. The idea of the virtual sensor array exploits the dependence of a gas sensor’s response on operating conditions. Originally it was developed as a means to improve the selectivity of an electronic nose when energy consumption by this device was a serious limitation. If the response of one sensor is measured in n time points, and each time point is characterised by different controlled exposure conditions, the sensor becomes analogous to an n-dimensional virtual sensor array. Compared with conventional approaches, a virtual sensor array based on a single sensor offers low power consumption, low volume, and low cost, which opens up new markets for wide application of portable and handheld devices. In this article, we show that a virtual sensor array and classification may serve as a reliable source of qualitative–quantitative information about gases. Twenty-six classes (five substances, each at five concentration ranges, and pure air) were recognised with a true positive rate higher than 99.14 ± 0.49% and a true negative rate higher than 99.21 ± 0.52%. As demonstrated, the basis for recognition could be a virtual sensor array associated with a low-power consuming sensor (210–280 mW). The complexity of the applied classifier could be adjusted depending on the choice of sensor operating conditions. For a complex classifier like support vector machine, dynamic exposure was sufficient to obtain high classification performance. A simpler classifier like k-nearest neighbours required more information, that is, information associated with static as well as dynamic exposure.

Fluctuations of the number of adsorbed micro/nanoparticles in sensors for measurement of particle concentration in air and liquid environments

A theoretical model of fluctuations of the number of adsorbed micro/nanoparticles in environmental sensors operating in air and liquids is presented, taking into account the effects of the mass transfer processes of the target particles in a sensor reaction chamber. The expressions for the total power of the corresponding adsorption-desorption noise, and for the corresponding signal-to-noise ratio are also derived. The presented analysis shows that the transfer processes can have a significant influence on the sensors limiting performance. The influence on both the fluctuations spectrum and the signal-to-noise ratio is estimated at different values of target particles concentration, functionalization sites surface density, and adsorption and desorption rate constants (the values are chosen from the ranges corresponding to real conditions). The analysis provides the guidelines for optimization of sensor design and operating conditions for the given target substance and sensor functionalization, in order to decrease the influence of the mass transfer, thus improving the ultimate performance (e.g. minimal detectable signal, signal-to-noise ratio) of sensors for particle detection. The calculations we performed show that it is possible to increase the signal-to-noise ratio for as much as two orders of magnitude by using the optimization that eliminates the mass transfer influence.

Effect of the titania substitution on the electronic structure and transport properties of FSS-made Fe2O3 nanoparticles for hydrogen sensing

Substitution of Fe2O3 with 5–20mol% TiO2 by flame spray synthesis (FSS) forms solid solutions of single crystal nanoparticles as small as 15.5nm with a correspondingly high specific surface area (95m2/g), as confirmed with X-ray diffraction and transmission electron microscopy. Their electronic structure and microstructure lends the solid solution a characteristic which can be exploited for H2 sensing, more so than with pure α-Fe2O3. With a combination of near edge X-ray absorption fine structure spectroscopy, and with electrochemical impedance analysis, that we apply under realistic sensor operation conditions, we are able to qualitatively probe the electronic structure and describe the mechanisms of hydrogen sensing at the molecular scale and correlate the hydrogen sensing property with charge transfer and valence band characteristics.

Non-linear dynamics of an electrothermally excited resonant pressure sensor

Non-linear dynamics of a resonant silicon bridge pressure sensor with electrothermal excitation has been investigated. Non-linear vibration model of the bridge resonator in the pressure sensor is developed by Euler–Bernoulli beam modeling. Besides non-linear geometric effect, the model also takes into account the measured pressure, the heating effect of the electrothermal excitation, and the residual internal force in the bridge. An approximate solution for this model is found via Galérkin procedure and the multiple scales method. From the solution, a bending parameter is extracted to quantitatively evaluate the bending of the bridge amplitude–frequency response. Dependence of the bending parameter on the sensor operating conditions is examined analytically and experimentally. Analytical calculations and experimental observations show good agreement qualitatively. An improved prediction for the critical vibration amplitude of the bridge is proposed, beyond which frequency hysteresis occurs. The critical vibration amplitude presented in this work is compared with those in other literatures. Moreover frequency output error of the sensor due to non-linear vibration is also examined. And finally several suggestions on resonant sensor design and operation with respect to non-linear effects are proposed.

Acoustic streaming induced elimination of nonspecifically bound proteins from a surface acoustic wave biosensor: Mechanism prediction using fluid-structure interaction models

Biosensors typically operate in liquid media for detection of biomarkers and suffer from fouling resulting from nonspecific binding of protein molecules to the device surface. In the current work, using a coupled field finite element fluid-structure interaction simulation, we have identified that fluid motion induced by high intensity sound waves, such as those propagating in these sensors, can lead to the efficient removal of the nonspecifically bound proteins thereby eliminating sensor fouling. We present a computational analysis of the acoustic-streaming phenomenon induced biofouling elimination by surface acoustic-waves (SAWs) propagating on a lithium niobate piezoelectric crystal. The transient solutions generated from the developed coupled field fluid solid interaction model are utilized to predict trends in acoustic-streaming induced forces for varying design parameters such as voltage intensity, device frequency, fluid viscosity, and density. We utilize these model predictions to compute the various interaction forces involved and thereby identify the possible mechanisms for removal of nonspecifically-bound proteins. For the range of sensor operating conditions simulated, our study indicates that the SAW motion acts as a body force to overcome the adhesive forces of the fouling proteins to the device surface whereas the acoustic-streaming induced hydrodynamic forces prevent their reattachment. The streaming velocity fields computed using the finite element models in conjunction with the proposed particle removal mechanism were used to identify the optimum conditions that lead to improved removal efficiency. We show that it is possible to tune operational parameters such as device frequency and input voltage to achieve effective elimination of biofouling proteins in typical biosensing media. Our simulation results agree well with previously reported experimental observations. The findings of this work have significant implications in designing reusable, selective, and highly sensitive biosensors.

The stop-flow mode of operation applied to a single chemiresistor

The stop-flow mode of operation was characterized as applied to a chemiresistor. In this mode, the main factor causing the alteration of exposure and operation conditions was the flow of gas. A chemiresistor was represented by the pool of 15 different TGS sensors. They were exposed to samples of air containing an analyte together with an interfering compound. The characteristics of the mode consisted of the following elements: (1) the analysis of sensor output signal, (2) the analysis of time variability of classification performance regarding the interfering compounds (3) the analysis of time variability of quantification error regarding the analyte. In order to characterize stop-flow mode the single-sensor perspective was adopted, i.e., classification and quantification models utilized time-point responses of single sensors. It was shown that exposure and operation conditions were well reflected in chemiresistor response, which showed a specific time-pattern. Interestingly, the distribution of classification useful information in sensor response was not related to sensor operation conditions in a fixed manner. It differed between sensors and gases. Contrarily, the distribution of quantification-useful information in sensor response was found specific for the stop-flow mode, irrespective of the sensor and the analyte. It was concluded that the operating conditions may be used as a means of shaping the content of quantification and classification useful information in sensors responses. The obtained results may serve as a guideline when considering the application of stop-flow as the mode of sensor operation.

A manganese porphyrin-based sensor for flow-injection potentiometric determination of thiocyanate

Metalloporphyrin-based ion-selective electrodes for flow-injection potentiometric determination of thiocyanate are described. The detection system is based on a coated glassy carbon electrode membrane sensor incorporating 5,10,15,20-tetraphenyl-21H,23H-porphine manganese(III) chloride as the active ingredient. The influences of the membrane composition, pH, and the effects of flow-injection parameters on the response of the system were investigated. At the optimized flow-injection potentiometric conditions, the sensor exhibited a Nernstian slope of -58.0 mV per decade of thiocyanate activity over the range 4.2 × 10-7–7.6 × 10-2M , where 50 μL of each sample solution was injected into the carrier solution. The detection limit of thiocyanate in the FIP mode was 4.2 × 10-7M . The selectivity of the flow-injection potentiometric system with respect to several common inorganic and organic anions was superior to that of the batch mode using the same sensor and similar operating conditions. The sensor was applied to the determination of thiocyanate in urine samples.