Conventional Temperature Sensors Research Articles

MoS2high temperature sensitive element with a single Si3N4protective layer.

Temperature sensors find extensive applications in industrial production, defense, and military sectors. However, conventional temperature sensors are limited to operating temperatures below 200°C and are unsuitable for detecting extremely high temperatures. In this paper, a method for thermal protection of molybdenum disulfide (MoS2) films is proposed and a MoS2 high temperature sensor is prepared. By depositing a monolayer of Si3N4 onto MoS2, not only is the issue of high-temperature oxidation effectively addressed, but also the contamination by impurities that could potentially compromise the performance of MoS2 is prevented. Moreover, the width of the Schottky barrier of metal/MoS2 is reduced by using PECVD deposition of 400 nm Si3N4 to form an ohmic contact, which improves the electrical performance of the device by three orders of magnitude. The sensor exhibits a positive temperature coefficient measurement range of 25 to 550°C, with a maximum temperature coefficient of resistance (TCR) of 0.32%·°C-1. The thermal protection method proposed in this paper provides a new idea for the fabrication of high-temperature sensors, which is expected to be applied in the high-temperature field.&#xD.

A temperature sensor based on Si/PS/SiO2 photonic crystals

The present research deals with the extremely sensitive temperature-sensing capabilities of defective one-dimensional photonic crystal structures (Si/PS/SiO2). The proposed structure is realized by putting a defective layer of material silicon Dioxide (SiO2) in the middle of a structure consisting of alternating layers of silicon (Si) and porous silica (PS). The transfer matrix method has been employed to examine the transmission characteristics of the proposed defective one-dimensional photonic crystal in addition to MATLAB software. The transmission spectra of the proposed structure in the visible light domain are computed throughout a temperature range of 25–900 °C, and we study the thermal properties related to the defective mode. Additionally, the impacts of changing the defect layer's thickness are examined. Due to the effects of thermal expansion and the thermo-optical coefficient, the defect mode varies significantly as the temperature increases. Our investigation shows that the proposed structure considerably impacts the transmission intensity of the defective mode. The theoretically obtained numeric values of the quality factor and sensitivity are 2216.6 and 0.085 nm/°C, respectively. The challenges presented by conventional temperature sensors could be overcome by the suggested defective photonic crystal sensor. These results are enough to support our claim that the present design can be used as an ultra-sensitive temperature sensor.

Ultra-high sensitivity temperature sensor based on PDMS-assisted-cascaded Mach–Zehnder Interferometer

In this paper, we propose and demonstrate an ultra-high sensitivity temperature sensor based on Polydimethylsiloxane (PDMS) assisted-cascaded Mach–Zehnder Interferometers (PAC-MZI). The sensor is first fabricated by periodically embedding four segments of hollow core fibers (HCF) in a single-mode fiber(SMF). Then, we drill holes into the sidewall of the HCF with a CO2 laser. Finally, the vacuum aspiration technique is used to introduce the PDMS into the HCF. In addition to serving as a beam splitter and combiner, the PDMS-filled HCF also guides multiple modes. The evolution of the transmission spectra during the fabrication process is thoroughly examined. The experimental temperature sensitivity of the sensor surpasses that of conventional interferometric temperature sensors by about 300 times to 9.53 nm/°C. Combining the advantages of easy packaging, compact structure, and high sensitivity, the proposed sensor has a wide range of potential applications in the field that require high-sensitivity temperature measurement.

Spindle Condition Monitoring With a Smart Vibration Sensor and an Optimized Deep Neural Network

Abstract This article presents a spindle condition monitoring methodology using a low-power smart vibration sensor and a near real-time deep neural network (DNN) classifier. The most frequent spindle failures, such as imbalance, ingression, and evidence of a crash with the workpiece, are analyzed in this study. Experiments were designed to induce various failure events to monitor the spindle behavior using conventional vibration, current and temperature sensors, and an intelligent vibration sensor. The smart sensor is a device with internal signal processing identifying eight dominant frequencies and the amplitude/power distributions. It requires low power and generates narrow bandwidth messages that can be communicated wirelessly. A Fog device and a test plan are designed to monitor and store a dataset needed to train a DNN classifier. The Fog device generates temperature, current, and vibration signals from sensors connected to the spindle and sends them to data storage in the cloud. The signals were analyzed using both conventional vibration analysis and Artificial Intelligence-based classifiers. Metrics such as crest factor, skewness, kurtosis, and overall enveloping were used to assess their ability to identify the failure condition. The data from the smart sensor are used to train an optimized DNN, and the spindle defect classification performance is measured. With 960 data points per failure mode and training data taken over 960 min of operation, the optimized DNNs can classify the spindle states with an accuracy of 98%. The study shows real-time spindle condition classification feasibility over long periods using inexpensive and low-power smart vibration sensors.

Potential distribution over temperature sensors of p-n junction diodes with arbitrary doping of the base region

In p-n-junction temperature sensors connected in the forwardbiased, the temperature dependence of the built-in potential is important, while in the reverse biased p-n-junction temperature sensors, it is necessary to study the temperature dependence of the built-in potential and space-charge region width.For this case, as well as for homogeneous and gradient alloyed cases, the temperature dependence of built-in potential and space-charge region widthare studied and mathematical analysis is presented for these cases.Based on these mathematical analysis, the results are obtained for cases where the base region of p-n-junction temperature sensors is doped at different concentrations with a homogeneous or inhomogeneous distributions of impurities. It is well known that in conventional temperature sensors, when the main current transport mechanism is determined by generation-recombination processes in space charge region, the dependence of the space charge region width on the temperature can affect the linearity of temperature response curve of sensor, it is desirable to increase the doping rate of the base region to weaken this effect, or it is necessary to use p-n junction.

Ultrasensitive Cryogenic Temperature Sensor Based on a Metalized Optical Fiber Fabry-Perot Interferometer

Cryogenic technologies are becoming essential in future applications in aerospace, quantum computing, cryogenic computing, and superconducting research. A highly sensitive temperature sensor is critical for such cryogenic applications. In this paper, we propose an extrinsic Fabry–Perot interferometer (EFPI) for cryogenic temperature measurement, leveraging the high thermal deformation of the copper sleeve to overcome the sensitivity drop issue in temperatures below 50 K for conventional cryogenic temperature sensors. Experimental results exhibit a temperature sensitivity of 2.836 nm/K throughout a temperature range of 5 K-50 K with a 15.82 μm long EFPI cavity, which is over three orders higher than the recently reported metal-coated FBG. The high sensitivity holds for the entire temperature range from 5 K to 295 K with excellent sensing repeatability. Our device, featuring a compact structure, and capability for multiplexing, is with great promise in cryogenic applications.

Calibration of Fiber Bragg Grating - Sensors for Subsequent Temperature and Pressure Measurements in Li-Ion Pouch Cells

The monitoring of temperature during operation of lithium ion batteries is crucial for a stable and safe performance of a battery system. However, a major challenge is to obtain exact internal temperature progression upon charge and discharge processes. Though commonly used resistance temperature sensors can give considerably accurate temperature values, they are limited to the application outside of the cell due to the distortion of their signal through induction effects of the applied cell currents, if installed inside the pouch cell and therefore, they are not suitable for in situ measurements. This poses serious problems especially for big cell stacks, as core temperatures for those cells differ greatly from the outer parts and particularly the surface of the cell encasement. Fiber Bragg Grating (FBG) sensors on the other hand, provide data that are unaffected by induction effects as their operating principle is solely based on the reflection of light of certain wavelengths within a glass fiber. However, a specific difficulty is the distinction between temperature and pressure effects, as the reflected signal is sensitive to both. Often times additional tubing around the sensor is needed to eliminate pressure effects or an additional sensor is placed in close proximity, inside or outside, to the FBG-sensor as a reference. The former, however, can affect the cell stack physically acting as a defect spot with unwanted side effects.In our work, we show that a careful calibration of the FBG-sensor can be accomplished, so that both effects can be separated and the FBG-sensor can then be used to gather information not only about temperature but also about volume changes in an operating cell. Therefore, a temperature calibration took place, with the cell being held at a constant SoC. Subsequently, a calibration of the SoC - dependent pressure-induced mechanical deformation was performed at very low C-rate to minimize thermal effects. The so gathered calibration parameters can then be applied to all performed cycling tests, regardless of the C - rate. A calibration routine and mathematical solution to separate the influences of temperature and pressure to receive exact in situ temperature values for a 10 Ah lithium ion battery cell is presented. The calibration method is applied to cycling and rate tests at various C-rates.The results show, that wavelength shifts upon charging and discharging processes are mainly resulting from volume changes of the active cell components, meaning that the FBG – sensor has a very high sensitivity towards pressure changes. With the before mentioned calibration method the impact of mechanical deformation on the FBG - sensor can be subtracted from the raw data and allow for a direct temperature reading. The temperature data correlates with data gathered from commonly used sensors placed on the outside of the pouch cell. Tests with varying discharge rates confirm these results and show, that the method produces precise temperature data even at different C-rates, even though only slow C-rates were applied during calibration.In detailed comparison, the FBG - sensors show a faster response towards temperature changes compared to conventional external temperature sensors, which can be related to the insulating effect of the pouch foil. In case of high discharge rates, we were able to show that the measured temperatures inside of the pouch cell are higher in comparison to the outside ones. Furthermore, SoC - induced changes in pressure measured by two FBG-sensors, which were located at different positions on the cell stack, are almost identical. This indicates that pressure build-up within a pouch cell occurs evenly through the cell stack.

Determination of Internal Temperature Differences for Various Cylindrical Lithium-Ion Batteries Using a Pulse Resistance Approach

The temperature of lithium-ion batteries is crucial in terms of performance, aging, and safety. The internal temperature, which is complicated to measure with conventional temperature sensors, plays an important role here. For this reason, numerous methods exist in the literature for determining the internal cell temperature without sensors, which are usually based on electrochemical impedance spectroscopy. This study presents a method in the time domain, based on the pulse resistance, for determining the internal cell temperature by examining the temperature behavior for the cylindrical formats 18650, 21700, and 26650 in isothermal and transient temperature states for different states of charge (SOCs). A previously validated component-resolved 2D thermal model was used to analyze the location of the calculated temperature TR within the cell, which is still an unsolved question for pulse resistance-based temperature determination. The model comparison shows that TR is close to the average jelly roll temperature. The differences between surface temperature and TR depend on the SOC and cell format and range from 2.14K to 2.70K (18650), 3.07K to 3.85K (21700), and 4.74K to 5.45K (26650). The difference decreases for each cell format with increasing SOC and is linear dependent on the cell diameter.

Advanced landing gear fibre Bragg grating sensing and monitoring system

In this paper an advanced optical-based landing gear load sensing and monitoring system is presented. The system measures strains using fibre Bragg grating sensor that are converted into loads and torque at the landing gear wheels and provides this data for use by the aircraft systems for integration with aircraft health monitoring, hard landing detection, flight management, flight controls and ground controls. A complete sensing system was developed in the European Union Clean Sky 2 Joint Technology Initiative Advanced Landing Gear Sensing and Monitoring (ALGeSMo), described herein. This involved: the integration of optical fibres into a composite structure, the development of an optical harness (cabling and connectors) meeting aircraft installation requirements, the readout of the optical fibre sensors with state-of-the-art miniature optoelectronics and the processing and communication of the data. Apart from specific tests on the various components, a bespoke test rig was developed to rigorously test the whole sensing and monitoring system on an A320 main landing gear slider tube to validate the performance of the system. The system-level tests performed on the test rig showed a very good correlation with applied actuator loads and additional conventional strain and temperature sensors. It demonstrates that loads along all three axis of the landing gear and the torque about the wheel axle can be accurately measured. Tests performed at cold and elevated temperatures, however, revealed that the generally applied one-dimensional temperature compensation equation is not accurate enough for this application, due to the non-uniform non-stationary temperature field. The ALGeSMo research activities have advanced the state of the art in several key areas for the deployment of optical sensing systems for safety-critical applications, such as integration of optical fibres into composite material, robust optical connections, avionic-compliant optical interrogator and landing gear load measurement up to technology readiness level technology readiness level 5.

Development of a Temperature Sensor Using Spin-Crossover Fe(pyrazine)[Pt(CN)4I] Nanoparticles

Recently, temperature sensors are required to have a high resolution and precise characterization that can measure at a reduced scale due to the research trend of device miniaturization. Therefore, we developed an optical temperature sensor using Fe^2+ based spin-crossover material that has different spin states of Low spin and High spin depending on the temperature. The operating range of the spin-crossover (SCO) was adjusted in the range of 295-365 K with an appropriate ratio of iodine. The color induced by temperature change was observed using a microscope and was converted to the color intensity with grayscale. The exothermal phenomenon of the microheater was observed at room temperature. Au microheater with a wide of 4 μm and a resistance of 166 Ω was applied with a current from 10 to 70 mA where the Fe(pyrazine)[Pt(CN)₄I] SCO nanoparticles were covered on the surface of Au with a thick layer of 58 μm. The exothermal phenomenon of the Au microheater is increased sequentially with an increment of the current. Finally, we confirmed that the SCO temperature sensor was acceptable by comparing it with the values calculated or measured by another conventional temperature sensor. Therefore, as an optical temperature sensor that can be observed in visible light, it is suitable for measuring the temperature changes that occur in microdevices.

Highly Accurate, Fully Digital Temperature Sensor With Curvature Correction

In this paper, a highly accurate, fully digital temperature sensor with a curvature correction scheme is proposed. Conventional analog temperature sensors are complex and require a large area. Digital temperature sensors are simple with small area, but they have large inaccuracies due to process variations and curvature errors. In particular, curvature errors become more severe as the technology scales down. Thus, a highly accurate curvature correction method is proposed that can be used even in the latest technology nodes. The proposed curvature correction method achieves lower temperature errors with a smaller area than the conventional curvature correction method by using a simple correction. A temperature error that occurs up to 17 °C before the curvature correction is reduced to a range of −0.6 °C to +0.8 °C after the curvature correction. In addition, the measurement results indicate that the resolution is 0.09 °C /bit in the temperature range from 0 °C to 100 °C. The implementation in 14 nm technology node Xilinx ZCU102 field-programmable gate arrays proves that the proposed temperature sensor is very cost effective, while using only 85 slices. Compared with previous digital temperature sensors, the proposed temperature sensor achieves the smallest error and uses the smallest number of hardware resources while being implemented in a state-of-the-art technology node.

Using knowledge inference to suppress the lamp disturbance for fire detection

Fire detection in buildings is crucial for people's lives and property. Conventional temperature and smoke sensors have many disadvantages: the limited cover range; detection delays; the difficulty in distinguishing smoke and fire. Recently, research on convolutional neural networks (CNN) for fire image detection has become a hot topic. However, existing fire classification and object detection methods are often interfered with by flashlights, red objects and the high-brightness background, resulting in a high false alarm rate. Besides, light and lamps often exist in buildings. To address this issue, this paper focuses on introducing scene prior knowledge and causal inference mechanisms to suppress the lamp disturbance. Firstly, we train the YoloV3 network to detect and recognize lamps. Secondly, to reduce the dataset bias, we mask the lamp regions with the proposed Local Grabcut segmentation method. Last, compared with direct fire classification methods, our proposed methods reduce about 34.6% false alarm rate based on InceptionV4 networks. The experimental results verify the effectiveness among different CNN architectures (Resnet101, Firenet, Densenet121). The code is online at https://github.com/kailaisun/fire-detection-without-lamp.

Ultra-sensitive silicon temperature sensor based on cascaded Mach-Zehnder interferometers.

An ultra-sensitive temperature sensor without sacrificing detection range is demonstrated on the silicon-on-insulator (SOI) platform using cascaded Mach-Zehnder interferometers (MZIs). The sensitivity enhancement is achieved by tailoring the geometric parameters of the two MZIs to have similar free spectral ranges (FSRs) but quite different sensitivities. The proposed sensor only needs single lithography for the sensing unit, without introducing negative thermo-optic coefficient (TOC) materials. The measured sensitivity is 1753.7 pm/°C from 27°C to 67°C, which is higher than any reported results on a silicon platform and about 21.9 times larger than conventional all-silicon temperature sensors.

Optical whispering-gallery mode barcodes for high-precision and wide-range temperature measurements

Temperature is one of the most fundamental physical properties to characterize various physical, chemical, and biological processes. Even a slight change in temperature could have an impact on the status or dynamics of a system. Thus, there is a great need for high-precision and large-dynamic-range temperature measurements. Conventional temperature sensors encounter difficulties in high-precision thermal sensing on the submicron scale. Recently, optical whispering-gallery mode (WGM) sensors have shown promise for many sensing applications, such as thermal sensing, magnetic detection, and biosensing. However, despite their superior sensitivity, the conventional sensing method for WGM resonators relies on tracking the changes in a single mode, which limits the dynamic range constrained by the laser source that has to be fine-tuned in a timely manner to follow the selected mode during the measurement. Moreover, we cannot derive the actual temperature from the spectrum directly but rather derive a relative temperature change. Here, we demonstrate an optical WGM barcode technique involving simultaneous monitoring of the patterns of multiple modes that can provide a direct temperature readout from the spectrum. The measurement relies on the patterns of multiple modes in the WGM spectrum instead of the changes of a particular mode. It can provide us with more information than the single-mode spectrum, such as the precise measurement of actual temperatures. Leveraging the high sensitivity of WGMs and eliminating the need to monitor particular modes, this work lays the foundation for developing a high-performance temperature sensor with not only superior sensitivity but also a broad dynamic range.

Differences in temperature measurement by commercial room temperature sensors: Effects of room cooling system, loads, sensor type and position

Thermostats control the heating, ventilation and air-conditioning (HVAC) system of a building based on the temperature they measure. Integration with communication network technologies allows wireless sensors to be used as the temperature sensing component of an HVAC system, increasing the flexibility in the selection and positioning of sensors. This study compared the temperature measuring performance of nine wireless and two conventional wired temperature sensors against reference air and globe temperature sensors in a climate chamber with a two-person office setup. The influence of sensor position, room cooling system (all-air or radiant with ventilation) and cooling load (33, 61 W/m2) was studied.Sensors placed at the same position had a measurement difference of up to 1.8 K, and assumptions about the type of temperature a sensor measures (air or globe) had the largest impact on the deviation from the reference temperatures. As opposed to common assumptions, conventional wired temperature sensors measured closer to globe temperature sensors and could be a possible indicator for the operative temperature. When the load settings were high, measurements in radiant system cases had smaller deviations from the reference sensors compared with all-air systems, due to the chilled surface compensating for the radiation from the loads.

Temperature-Compensated Spread Spectrum Sound-Based Local Positioning System for Greenhouse Operations

A spread spectrum sound-based local positioning system (SSSLPS) has been developed for indoor agricultural robots by our research group. Such an SSSLPS has several advantages, including effective propagation, low cost, and ease of use. When using sound velocity for field position measurements in a greenhouse, spatial and temporal variations in temperature during the day can have a major effect on sound velocity and subsequent positioning accuracy. In this research, a temperature-compensated sound velocity positioning was proposed and evaluated in comparison to a conventional temperature sensor method. Results indicate that this new proposed method has a positioning accuracy to within 20 mm in a 3 m × 9 m ridged greenhouse. It has the potential to replace the current system of using the temperature sensors in a greenhouse.

Polymer Optical Fibre Temperature Sensors - A Review

Polymer optical fibre (POF) temperature sensors are rapidly replacing conventional temperature sensors owing to their unique and attractive features, such as small size, immunity to electromagnetic interference, multiplexing, and remote sensing capabilities. The recent developments in temperature sensing using polymer optical fibres are presented. Polymer optical fibre (POF) temperature sensors of various types: macro-bend fibre sensors, microfibre resonators, fibre Bragg grating, Fabry-Perot interferometers, and POF sensors coated with zinc oxide nanorods are discussed. This study also includes dual-parameter sensors to demonstrate intrinsic sensitivities of polymer fibres to temperature, relative humidity, and strain. The prospects and challenges of POF temperature sensors in the automotive industry, biomedical sector, chemical industry, and electrical power applications are also highlighted. This review aims to help researchers in this field identify areas of further work towards improving the accuracy and operating range of POF temperature sensors.

Rapid Detection for Salmonella typhimurium by Conventional Resistive Temperature Sensor Based on Photothermal Effect of Carboxylated Graphene Oxide

Photothermal effect of nanomaterial has been applied to the establishment of rapid detection method such as test strip. Previously, the detector for the photothermal test strip method mainly was a bulky thermal imaging camera or an infrared-sensing temperature sensor of which the detection data obtained is unstable due to its susceptibility to environmental changes. Herein, a resistive temperature sensor which is more stable and less susceptible to external environment was adopted. A test strip was used to detect Salmonella enterica Typhimurium (Salmonella typhimurium). The carboxylated graphene oxides (GOs), which have a more excellent photothermal effect, labeled with anti-Salmonella typhimurium antibodies, were used as a nanomarker to produce thermal signal. Subsequently, temperature variation signal (ΔT) generated by carboxylated GOs exposed to 808 nm laser was detected by conventional resistive temperature sensor directly. Under optimal conditions, a standard curve of ΔT with respect to the different numbers of Salmonella typhimurium was established, the detection limit was 104 CFU·mL-1 and the detection time was 20 min. The proposed detection method with high sensitivity, specificity, and efficiency can be used as a novel and on-site screening technology to detect Salmonella typhimurium in food, environmental, or clinical samples.

Hybrid CMOS-PCM temperature sensor

In this paper, we propose a hybrid CMOS and phase-change memory (PCM)-relaxation-oscillator based circuit for temperature-sensing applications. Unlike conventional CMOS temperature sensors based on ring- or relaxation-oscillators, the proposed sensor does not require any curvature calibration technique for linearity improvement of the thermal response. The presented system explores the temperature dependence of Ovonic-threshold-switching voltage (Vth) and DC OFF state resistance (ROFF) of a PCM device. The proposed temperature sensor exhibits a resolution of ∼0.04 °C (for the 0 °C to 80 °C temperature range) with 0.51 nJ energy consumption per conversion in simulations.

Geospatial assessment of land surface temperature in Nagpur, India: an impact of urbanization

Temperature is one of the factors which affects the meteorological phenomenon prevailing in an urban area and ultimately leads to climate change and global warming. Measurement of surface temperature with conventional temperature sensors is tedious, has single point value and expensive. Satellite data of 2005, 2008, 2010 and 2016 are used to assess the land use land cover (LULC) and to measure the land surface temperature (LST) during the hottest month of May in Nagpur city, India. Based on the image analysis, it is observed that there is an increase in the average temperature from 40.0 to 44.6 oC. This may be due to an increase in built-up area from 55.5 to 69.8% during 2005 to 2016, respectively. It has also been revealed that the outskirts of the city are hotter than the central portion of the city as there is more barren land on the outskirts. Results were compared to ambient temperature sensor that showed good agreement between temperature retrieved from satellite and temperature sensor. The study suggests that urban areas should be developed intermixed with vegetation and plantation and provisions of green belt along the city roads, highways and ring roads. Based on LST and LULC analysis, a green belt of 30 m along both sides of the road would lower the road temperature by 9.3 oC from existing temperature of 44.7 oC. This would help in lowering down the average temperature of the city.