Accurate Temperature Measurements Research Articles

Design Implementation of a Logger-Based Digital Thermometer

LM35 temperature sensor is a widely used 3-terminal sensor known for its precise temperature measurement capabilities without the need for external calibration circuitry. With a sensitivity of 10mV/°C, it operates within a temperature range of -55°C to 150°C, with an error margin of 0.5°C. This paper presents the development and testing of a logger-based digital thermometer using LM35 sensor, integrated with a dsPIC30F4013 digital signal processing controller, an LCD, a real-time clock (DS1307), and other essential components. The methodology involves the analysis of the sensor's sensitivity and its response under both stress and non-stress temperature conditions. The findings indicate that the sensor's output closely follows the theoretical sensitivity, with a negligible offset, ensuring accurate temperature measurements. Comparative analysis with a standard laboratory thermometer suggests that the digital sensor provides superior precision, with an error margin of ±0.01°C. The results confirm LM35's suitability for accurate ambient temperature monitoring and validation of environmental temperature fluctuations.

Printed Thick Film Resistance Temperature Detector for Real-Time Tube Furnace Temperature Monitoring.

Accurately acquiring crucial data on tube furnaces and real-time temperature monitoring of different temperature zones is vital for material synthesis technology in production. However, it is difficult to achieve real-time monitoring of the temperature field of tube furnaces with existing technology. Here, we proposed a method to fabricate silver (Ag) resistance temperature detectors (RTDs) based on a blade-coating process directly on the surface of a quartz ring, which enables precise positioning and real-time temperature monitoring of tube furnaces within 100-600 °C range. The Ag RTDs exhibited outstanding electrical properties, featuring a temperature coefficient of resistance (TCR) of 2854 ppm/°C, an accuracy of 1.8% FS (full scale), and a resistance drift rate of 0.05%/h over 6 h at 600 °C. These features ensured accurate and stable temperature measurement at high temperatures. For demonstration purposes, an array comprising four Ag RTDs was installed in a tube furnace. The measured average temperature gradient in the central region of the tube furnace was 5.7 °C/mm. Furthermore, successful real-time monitoring of temperature during the alloy sintering process revealed approximately a 20-fold difference in resistivity for silver-palladium alloys sintered at various positions within the tubular furnace. The proposed strategy offers a promising approach for real-time temperature monitoring of tube furnaces.

Infrared photodetection in graphene-based heterostructures: bolometric and thermoelectric effects at the tunneling barrier

Graphene/hBN/graphene tunnel devices offer promise as sensitive mid-infrared photodetectors but the microscopic origin underlying the photoresponse in them remains elusive. In this work, we investigated the photocurrent generation in graphene/hBN/graphene tunnel structures with localized defect states under mid-IR illumination. We demonstrate that the photocurrent in these devices is proportional to the second derivative of the tunnel current with respect to the bias voltage, peaking during tunneling through the hBN impurity level. We revealed that the origin of the photocurrent generation lies in the change of the tunneling probability upon radiation-induced electron heating in graphene layers, in agreement with the theoretical model that we developed. Finally, we show that at a finite bias voltage, the photocurrent is proportional to either of the graphene layers heating under the illumination, while at zero bias, it is proportional to the heating difference. Thus, the photocurrent in such devices can be used for accurate measurements of the electronic temperature, providing a convenient alternative to Johnson noise thermometry.

Evaluating the Agreement between Oral, Armpit, and Ear Temperature Readings during Physical Activities in an Outdoor Setting.

Accurate body temperature measurement is essential for monitoring and managing safety during outdoor activities. Physical activities are an essential consideration for public health, with sports taking up an important proportion of these. Athletes' performances can be directly affected by body temperature fluctuations, with overheating or hypothermia posing serious health risks. Monitoring these temperatures allows coaches and medical staff to make decisions that enhance performance and safety. Traditional methods, like oral, axillary, and tympanic readings, are widely used, but face challenges during intense physical activities in real-world environments. This study evaluated the agreement, correlation, and interchangeability of oral, axillary, and tympanic temperature measurements in outdoor exercise conditions. Systems developed for specific placements might generate different sensor readouts. Conducted as an observational field study, it involved 21 adult participants (11 males and 10 females, average age 25.14 ± 5.80 years) that underwent the Yo-Yo intermittent recovery test protocol on an outdoor court. The main outcomes measured were the agreement and correlation between temperature readings from the three methods, both before and after exercise. The results indicate poor agreement between the measurement sites, with significant deviations observed post-exercise. Although the Spearman correlation coefficients showed consistent temperature changes post-exercise across all methods, the standard deviations in the pairwise comparisons exceeded 0.67 °C. This study concluded that widely used temperature measurement methods are challenging to use during outdoor exercises and should not be considered interchangeable. This variability, especially after exercise, underscores the need for further research using gold standard temperature measurement methods to determine the most suitable site for accurate readings. Care should thus be taken when temperature screening is done at scale using traditional methods, as each measurement site should be considered within its own right.

Dual lanthanide Complexes-Loaded ratiometric nanothermometer for elucidating intracellular variations of temperature and calcium transport

Herein, we report a ratiometric nanothermometer to study the correlation of heat/temperature and intracellular calcium transport. Firstly, poly(methyl methacrylate)-based copolymeric nanoparticles (NPs) from nanoprecipitation encapsulates two lanthanide complexes (Eu(DNPD)3Phen and Sm(DBM)3Phen) to enhance fluorescence of lanthanide ions (Ln3+). NPs were thereafter coated with an amphiphilic block copolymer pluronic F-127 to prevent nonspecific interaction between NPs and proteins, which ensures internalization of the nanothermometer into living cells. The back energy transfer (BET) from the excited state of Ln3+ to the triplet energy levels of ligand endows the temperature dependence on ratiometric fluorescence of Eu3+ and Sm3+. This nanothermometer has excellent anti-interference ability, ensuring accurate cell temperature measurement within a range of 29.0–40.0℃. It exhibits a maximum relative thermal sensitivity of 1.9 % ℃-1 at 29.0℃ and a minimum temperature resolution of 0.1℃ at 39.0℃ in live HeLa cells. The nanothermometer was applied for studying temperature or heat induced intracellular Ca2+ transport. It illustrated that free cytoplasmic Ca2+ concentration ([Ca2+]i) increased only when the cell temperature reached a certain threshold under photothermal stimulation, and the rise of temperature corresponds to the increase of [Ca2+]i. Furthermore, Ca2+ burst induced Ca2+ transport from cytoplasm to endoplasmic reticulum, which promoted ATP hydrolysis along with the rise of intracellular temperature. 200 s stimulation with FCCP enhanced ca. 1.7℃ of intracellular temperature along with 2.2 folds increment of [Ca2+]i, as FCCP induces Ca2+ efflux from mitochondria by increasing proton concentration therein. These results indicate that a close relationship between intracellular temperature and Ca2+ transport, which is of great significance for further understanding the role of temperature in signaling pathways and neurotransmitter release events.

Leaf Temperature Measurement Using Low-Resolution Thermal Camera Based on Thresholding and Clustering Techniques

Leaf temperature can indicate photosynthetic rates, leaf water status, and stomata conductance. Leaf temperature can be measured using thermal resistance sensors, thermocouple devices, infrared thermometers, or infrared thermal imaging devices. Additionally, measuring leaf temperature using a thermal camera is simple and efficient. Therefore, the research proposes a leaf temperature measurement method using AMG8833, a low-resolution (64 pixels) thermal camera. The proposed system adopts an image segmentation technique to extract the leaf area from a thermal image. The leaf temperature is then calculated by averaging the temperature values on the leaf area. The proposed system aims to utilize a low-cost and low-resolution thermal camera for measuring the leaf temperature. The proposed approach is evaluated using real images of the Dieffenbachia plant, a popular ornamental plant that can be easily planted. In the experiments, fourteen segmentation methods consisting of eight thresholding techniques and six clustering techniques are evaluated. The experimental findings on the Dieffenbachia plant indicate that the most accurate leaf temperature measurements are obtained using local thresholding with an absolute error of 0.0109 and k-means clustering with an absolute error of 0.0134. The proposed method provides a simple, effective, and low-cost leaf temperature measurement system compared to the existing systems which employ high-cost commercial thermal cameras and complex measurement methods.

Novel Entropy for Enhanced Thermal Imaging and Uncertainty Quantification.

This paper addresses the critical need for precise thermal modeling in electronics, where temperature significantly impacts system reliability. We emphasize the necessity of accurate temperature measurement and uncertainty quantification in thermal imaging, a vital tool across multiple industries. Current mathematical models and uncertainty measures, such as Rényi and Shannon entropies, are inadequate for the detailed informational content required in thermal images. Our work introduces a novel entropy that effectively captures the informational content of thermal images by combining local and global data, surpassing existing metrics. Validated by rigorous experimentation, this method enhances thermal images' reliability and information preservation. We also present two enhancement frameworks that integrate an optimized genetic algorithm and image fusion techniques, improving image quality by reducing artifacts and enhancing contrast. These advancements offer significant contributions to thermal imaging and uncertainty quantification, with broad applications in various sectors.

Review of the Capacity to Accurately Detect the Temperature of Human Skin Tissue Using the Microwave Radiation Method.

Microwave radiometry (MWR) is instrumental in detecting thermal variations in skin tissue before anatomical changes occur, proving particularly beneficial in the early diagnosis of cancer and inflammation. This study concisely traces the evolution of microwave radiometers within the medical sector. By analyzing a plethora of pertinent studies and contrasting their strengths, weaknesses, and performance metrics, this research identifies the primary factors limiting temperature measurement accuracy. The review establishes the critical technologies necessary to overcome these limitations, examines the current state and prospective advancements of each technology, and proposes comprehensive implementation strategies. The discussion elucidates that the precise measurement of human surface and subcutaneous tissue temperatures using an MWR system is a complex challenge, necessitating an integration of antenna directionality for temperature measurement, radiometer error correction, hardware configuration, and the calibration and precision of a multilayer tissue forward and inversion method. This study delves into the pivotal technologies for non-invasive human tissue temperature monitoring in the microwave frequency range, offering an effective approach for the precise assessment of human epidermal and subcutaneous temperatures, and develops a non-contact microwave protocol for gauging subcutaneous tissue temperature distribution. It is anticipated that mass-produced measurement systems will deliver substantial economic and societal benefits.

Design of a Negative Temperature Coefficient Temperature Measurement System Based on a Resistance Ratio Model.

In this paper, a temperature measurement system with NTC (Negative Temperature Coefficient) thermistors was designed. An MCU (Micro Control Unit) primarily operates by converting the voltage value collected by an ADC (Analog-to-Digital Converter) into the resistance value. The temperature value is then calculated, and a DAC (Digital-to-Analog Converter) outputs a current of 4 to 20 mA that is linearly related to the temperature value. The nonlinear characteristics of NTC thermistors pose a challenging problem. The nonlinear characteristics of NTC thermistors were to a great extent solved by using a resistance ratio model. The high precision of the NTC thermistor is obtained by fitting it with the Hoge equation. The results of actual measurements suggest that each module works properly, and the temperature measurement accuracy of 0.067 °C in the range from -40 °C to 120 °C has been achieved. The uncertainty of the output current is analyzed and calculated with the uncertainty of 0.0014 mA. This type of system has broad potential applications in industry fields such as the petrochemical industry.

Infrared-based temperature measurement in three dimensions

A highly accurate and low-cost mobile platform for multiple object temperature measurement in 3D coordinate positions is introduced. The key idea relies on not only a combination of a 3D optical depth sensor and the 2D infrared thermal imager but also a determined distant-dependent compensation model. As a result, a cost-effective yet wider (>100.0∘C) temperature measurement range under the fluctuation of working distant shift is realized with a low standard deviation of 0.16°C at the working distance of 1.0 m. Accurate temperature measurement at different positions of objects along the suitable working distance is also demonstrated.

Improvement of Temperature Measurement Accuracy of Hot Airflow Using Ultrafine Thermo-Sensitive Fluorescent Wires of Lumisis Phosphor.

In this study, the fluorescence properties of Lumisis, a phosphor that can be easily applied to ultrafine wires, were evaluated. By evaluating the wavelength characteristics of Lumisis phosphor, we investigated the possibility of applying it to a dual-wavelength laser-induced fluorescence (LIF) measurement system and evaluated the accuracy of temperature measurements. The difference between the decrease in the percentage intensities of the red and green fluorescence of Lumisis phosphors showed that two-color LIF was possible. The Lumisis phosphor-mixture ratio was optimized as 1:1.25, and the average measurement error of the fluorescent wire was 0.20 K, as evaluated through uncertainty analysis. Finally, the application of this measurement method to hot air jet phenomena showed that this method accurately captures the temperature changes in hot air, thus proving its validity.

Sweat and Deformation‐Resistance Graphite/PVDF/PANI‐Based Temperature Sensor for Real‐Time Body Temperature Monitoring

AbstractBody temperature is critical indicator of human health, and its real‐time monitoring is crucial for assessing body status and disease diagnosis. In this work, a flexible temperature sensor is presented that employs a graphite/polyvinylidene fluoride (PVDF)/polyaniline composite and demonstrates a negative temperature coefficient (NTC). This sensor exhibits high sensitivity (−0.832%/ °C), rapid response time (11.05 s), and excellent linearity (R2 = 0.98). Its integration with a self‐adhesion PDMS‐PEG substrate layer ensures close skin contact, enhancing the accuracy of temperature measurements. Notably, the sensor's stability and resistance to sweat and deformation ensure continuous, reliable temperature monitoring, even during extensive exercise. This sensor thus represents a significant advancement in flexible and waterproof temperature sensing technologies.

Enhancing Microwave Photonic Interrogation Accuracy for Fiber-Optic Temperature Sensors via Artificial Neural Network Integration

In this paper, an application of an artificial neural network algorithm is proposed to enhance the accuracy of temperature measurement using a fiber-optic sensor based on a Fabry–Perot interferometer (FPI). It is assumed that the interrogation of the FPI is carried out using an optical comb generator realizing a microwave photonic approach. Firstly, modelling of the reflection spectrum of a Fabry–Perot interferometer is implemented. Secondly, probing of the obtained spectrum using a comb-generator model is performed. The resulting electrical signal of the photodetector is processed and is used to create a sample for artificial neural network training aimed at temperature detection. It is demonstrated that the artificial neural network implementation can predict temperature variations with an accuracy equal to 0.018 °C in the range from −10 to +10 °C and 0.147 in the range from −15 to +15 °C.

Design of a hemispherical shell shaped natural ventilation temperature observation instrument.

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations. A neural network model was employed to develop a temperature error correction model that can be targeted for multi-variable changes. This model provides accurate correction data when the influencing factors change continuously. Finally, field experiments were performed. The experimental data analysis indicates that the mean temperature error and the maximum error of the instrument before correction are 0.08 and 0.25 °C, respectively. The root mean square error, the mean absolute error, and the correlation coefficient between measured temperature errors from experiments and corrected temperature errors from the correction model are 0.099, 0.016, and 0.952 °C, respectively. By utilizing a temperature error correction model, the measuring error of the instrument can be minimized to a range between -0.05 and 0.04 °C. Consequently, the instrument is anticipated to enhance temperature measurement accuracy to ∼0.1 °C.

High-precision and wide-range temperature measurement and control system of satellite-borne calibration blackbody

The accurate measurement and control of blackbody temperature can play an important role in radiometric calibration. A novel circuit suitable for the aerospace environment is designed to measure and control the temperature of the blackbody. A coarse-fine measurement method considering the wire resistance and self-heating effect of the platinum resistance is presented to calculate the resistance values of the platinum resistors. The precision of temperature measurement is improved using a line fitting algorithm with error calibration and temperature drift error compensation. A fuzzy self-adaptive PID controller is designed to improve the temperature control effect. The performances of the developed system are implemented on an FPGA/A3PE3000-FG484I controller board. The test results show that the device temperature measurement precision can reach ±0.03K for the entire temperature range 238 K to 367 K, the temperature stability is better than 0.02 K/20 s, and the temperature uniformity is better than 0.1 K.

Performance Enhancement in a Few-Mode Rayleigh-Brillouin Optical Time Domain Analysis System Using Pulse Coding and LMD Algorithm

Rayleigh Brillouin optical time domain analysis (BOTDA) uses the backscattered Rayleigh light generated in the fiber as the probe light, which has a lower detection light intensity compared to the BOTDA technique. As a result, its temperature-sensing technology suffers from a low signal-to-noise ratio (SNR) and severe sensing unreliability due to the influence of the low probe signal and high noise level. The pulse coding and LMD denoising method are applied to enhance the performance of the Brillouin frequency shift detection and temperature measurement. In this study, the mechanism of Rayleigh BOTDA based on a few-mode fiber (FMF) is investigated, the principles of the Golay code and local mean decomposition (LMD) algorithm are analyzed, and the experimental setup of the Rayleigh BOTDA system using an FMF is constructed to analyze the performance of the sensing system. Compared with a single pulse of 50 ns, the 32-bit Golay coding with a pulse width of 10 ns improves the spatial resolution to 1 m. Further enhanced by the LMD algorithm, the SNR and temperature measurement accuracy are increased by 5.5 dB and 1.05 °C, respectively. Finally, a spatial resolution of 1.12 m and a temperature measurement accuracy of 2.85 °C are achieved using a two-mode fiber with a length of 1 km.

Integrated micro thermoelectric devices with self-power supply and temperature monitoring: Design and application in power grid early warning

The Internet of Things (IoT) and wearable technology have led to the development of wireless sensors at an unprecedented pace. Within the IoT framework, smart grid systems require real-time temperature monitoring of various switch contacts. Especially in the process of power transformation (China: ultra-high voltage → 10 kV → 380 / 220 V), poor switch contact will lead to overheating, resulting in equipment damage and major safety accidents. Micro-thermoelectric devices (micro-TEDs) exhibit a significantly greater thermoelectromotive force than metal-based thermocouples. By establishing two bivariate first-order equations for hot-end and cold-end temperatures, accurate detection of both temperatures and simultaneous self-power supply can be achieved. In this work, we observe that the Seebeck coefficient of hot extruded n-type Bi2Te2.7Se0.3 and p-type Bi0.5Sb1.5Te3 thermoelectric couple exhibits slight fluctuations around 435 μV/K, while its resistivity follows an almost linear trend with temperature from room temperature to 120 °C. By utilizing these two bivariate first-order equations, the temperatures at both the hot and cold ends can be determined. Based on this, we have fabricated a micro-TED (size: 14 × 6 × 2.5 mm3, TE leg: 0.8 × 0.8 × 1.6 mm3) with a temperature measurement accuracy of up to ± 0.1 °C and a power density of 10.12 mW/cm2 under a temperature difference of 30 °C. Furthermore, we used thirteen micro-TEDs and one circuit board to build a self-power supply temperature monitor. When this TE sensor device was deployed on the plum blossom connector surface and conducted online assessments for the 10 kV substation over a span of approximately 200 h, it continuously outputs a temperature signal and the power supply maintained normalcy, exhibiting no aberrations. This temperature monitoring system can be extended to other fields that require all-weather wireless temperature monitoring, which provides a new direction for the development of micro-TEDs.

A combined theoretical, computational, and experimental investigation to evaluate performance of suitable thermocouple for microwave processing

Accurate temperature measurement during any microwave processing of material is a contentious issue. While thermocouples are routinely utilized in conventional heat furnaces, their presence in microwave cavities may cause complications such as localized distortion of electromagnetic field, heat dissipation, thermal instabilities, microwave breakdown, and significant inaccuracies in temperature measurement. Therefore, in the present investigation thermocouple effects are discussed by providing the results of temperature estimation by various thermocouples for microwave cladding systems. The present study theoretically and experimentally explored the impact of multiple thermocouples on temperature measurements during microwave heating. COMSOL simulation models were developed to explore microwave and thermocouple interaction during microwave heating. Simulation models were used to assess the effects of the microwave power intensity, thermocouple orientation, and geometry on temperature measurement. The investigation outcomes can be utilized as a guide for selecting appropriate thermocouples in the applications of microwave cladding and other microwave-based manufacturing processes.

High precision temperature measurement for cryogenic temperature sensors based on deep learning technology

Nonlinear error compensation is a significant factor that affects the measurement accuracy of temperature sensors. Cryogenic temperature sensors require a precise calibration technique to achieve accurate temperature measurements. BP (Back Propagation) neural networks are not suitable for sensor temperature prediction due to slow convergence and poor learning ability. In this study, a Chebyshev polynomial-based BiLSTM (Bi-directional Long Short-Term Memory) algorithm (C-BiLSTM) is proposed to improve the accuracy of measurement. Firstly, we demonstrate vacuum packaged temperature sensors based on zirconium oxynitride (ZrOxNy) thin films with ultra-high sensitivity at cryogenic temperatures. Secondly, a dataset consisting of sensor resistance and temperature values was obtained from five above-mentioned sensors, which contains 29 calibration points in the temperature range of 16 K-300 K measured by the Calibration System. Then, the dataset was divided into two temperature ranges (16 K-54.358 K and 40 K-300 K). In the range 16–54.358 K, 14 set-points are selected as training set and 3 set-points as testing set. In the range 40–300 K, 12 set-points are selected as training set and 2 set-points as testing set. Thirdly, a neural network model was built and trained using the TensorFlow framework. By comparing C-BiLSTM we proposed with the BP neural network and BiLSTM, the results show that the C-BiLSTM model converges faster and greatly improves the prediction accuracy after adding Chebyshev polynomial features. The fitting error and prediction error are less than 1 mK in the temperature range of 16 K-40 K. They can also keep less than 10 mK even at the wide temperature range of 40 K-300 K, which is a significant improvement respect to improving the accuracy of temperature measurement.

Comparative study on fluorescence intensity ratio and chromatic coordinate temperature measurement using CsPbBr3-Eu3+ co-doped glass

We have fabricated CsPbBr3-Eu3+ co-doped glass for optical temperature measurement. Photoluminescence (PL) spectra, PL excitation (PLE) spectra and PL decay have been measured. The CsPbBr3 and Eu3+ show distinguishable PL spectra and different temperature dependences. Fluorescence intensity ratio (FIR) and chromatic coordinate temperature measurements are investigated. Absolute sensitivity (Sa), relative sensitivity (Sr) and temperature measurement accuracy (UT) are analyzed. For the FIR method, the Sa and Sr are better in comparison with other temperature sensing materials. The chromatic coordinate is calculated by using PL spectra. Comparing with FIR method, the chromatic coordinate method has smaller Sa and Sr, but better UT due to small uncertainty Ur(x). In addition, the chromatic coordinate method has linear temperature dependence, good compatibility and universality. Both FIR mode and chromatic coordinate mode have excellent temperature cycle characteristics..