Real-time Temperature Measurement Research Articles

Thermographic imaging of mouse across circadian time reveals body surface temperature elevation associated with non-locomotor body movements.

Circadian clocks orchestrate multiple different physiological rhythms in a well-synchronized manner. However, how these separate rhythms are interconnected is not exactly understood. Here, we developed a method that allows for the real-time simultaneous measurement of locomotor activity and body temperature of mice using infrared video camera imaging. As expected from the literature, temporal profiles of body temperature and locomotor activity were positively correlated with each other. Basically, body temperatures were high when animals were in locomotion. However, interestingly, increases in body temperature were not always associated with the appearance of locomotor activity. Video imaging revealed that mice exhibit non-locomotor activities such as grooming and postural adjustments, which alone induce considerable elevation of body temperature. Noticeably, non-locomotor movements always preceded the initiation of locomotor activity. Nevertheless, non-locomotor movements were not always accompanied by locomotor movements, suggesting that non-locomotor movements provide a mechanism of thermoregulation independent of locomotor activity. In addition, in the current study, we also report the development of a machine learning-based recording method for the detection of circadian feeding and drinking behaviors of mice. Our data illustrate the potential utility of thermal video imaging in the investigation of different physiological rhythms.

Laser-Induced Breakdown Spectroscopy (LIBS) For The Characterization Of Methane-Air Laminar Diffusion Flame

Laser-induced breakdown spectroscopy (LIBS) was applied for the characterization of the methane-air laminar diffusion flame, revealing the spatial distribution of its composition. From the measurement, it was found that distribution of the atomic and ionic N emissions produced by the flame had obvious differences, which were mainly distributed in the air area and flame area, respectively. A comparison of the LIBS spectra of air, methane gas, and methane-air laminar diffusion flame showed that the atomic N emissions were mainly produced by the excitation of N2, and the ionic N emissions were more related to the N-containing combustion products. In addition, the correlation between typical emissions and the flame temperature measured by thermocouple was estimated to show that the tendency of the changes in temperature can be characterized by C2 emission intensities. This work provides a new method for real-time online flame temperature measurement, and also provides a reference for revealing the formation process and conversion pathway of each component in the flame.

Assessment of the thermal outcome during steam-pulse ablation for sheep tissue

Thermal ablation has attracted attention as a minimally invasive tissue ablation treatment. Steam flow was recently introduced as a novel ablation procedure. This work aimed to assess the applicability of pulsated steam flow for tumor ablation. Ex vivo ablation was performed using liver, muscle, and fat tissues of sheep. Three experimental protocols of pulse number were administered to these tissues, while computational simulation was conducted according to the ex vivo tests for each tissue. Real-time measurements of temperature revealed heat propagation during and subsequent to ablation. The peak temperature was achieved after ablation. The time to reach the peak (highest temperature) increased with the distance from the thermal sensor to the steam needle according to thermal conductivity, except for steam leakage along to gap between the tissue and blood vessel. A cross-section of the ablated specimen clearly revealed the boundaries of cell defects. The ablated area was droplet shaped up to the steam needle. Computational simulations revealed that the ablated area was consistent with the area with the highest temperature. Though several limitations still remain such as no blood circulation, pulsated steam flow can ablate diverse animal tissues.

Real-time temperature measurement of living cells exposed to microwaves using a temperature-dependent fluorescent dye

Real-time measurement of temperature in living cells exposed to microwaves is challenging because of the low spatial resolution of conventional temperature probes. Here, we established a noninvasive method by using a temperature-dependent fluorescent dye, Rhodamine B (Rho-B) to stain living cells that were exposed to a customized microwave exposure device. The relationship between Rho-B fluorescence and the temperature of living cells, and between Fluo4/AM and the inward inflow of Ca2+ were established. The results showed that the fluorescence intensity changed by 7.9%/°C as the temperature rose from 25 °C to 37 °C. The spatial resolution and temporal resolution of this method were 225 × 225 µm 2 and 1.5 s, respectively. In conclusion, the real-time temperature measurement technique is simple to use and requires no specialized equipment beyond a LSCM. This method can provide real-time information of the temperature changes in cells simultaneously with the investigation of calcium concentration.

Identification of butt welded joint penetration based on infrared thermal imaging

In the gas metal arc welding (GMAW) process, the intense arc light and high temperature conditions bring great difficulties to the online identification of welded joint penetration. At present, visual sensing method and arc sound detection method are mainly used to identify the welded joint penetration, there are few reports about using welding temperature field to identify welded joint penetration. In this paper, a method of using infrared thermal imaging to identify the welded joint penetration was proposed, a single infrared thermal imager was used to monitor the welding temperature field in real time, the solidified weld area outside the weld pool area was selected as the region of interest (ROI) for real-time temperature measurement. The temperature field distribution features of ROI were extracted, taking these features as input and welded joint penetration as output, the identification model for welded joint penetration was established based on artificial neural network (ANN). The identification accuracy and generalization ability of the identification model were verified by a variety of butt welding experiments, the experimental results show that the identification accuracy of the established model for three penetration states of welded joint is higher than 96%, which can be applied in the online identification of welded joint penetration.

Fatigue reliability evaluation of Q460 welded joints using fracture fatigue entropy method

In this paper, the fracture fatigue entropy (FFE) was used to evaluate the fatigue reliability of Q460 welded joints during high-cycle fatigue. The Q460 butt welded joint fatigue tests were conducted under different loads. Meanwhile, the real-time temperature measurement, monitored by an infrared thermal scanner, was completed. The fatigue limit can be well estimated according to the cumulative damage entropy production rate in Phase II, and compared with the fatigue limit prediction value by the traditional staircase method, a good consistency is achieved. Furthermore, the P-S-N curves of 5%, 50%, and 95% survival probability rate are well predicted, which is consistent with the experimental data. Therefore, based on this, the accurate fatigue reliability evaluation based on the proposed method has been achieved.

Multi-wavelength radiometric thermometry data processing algorithm based on the BFGS algorithm.

Multi-wavelength radiometric thermometry has a wide application prospect in many fields. However, due to unknown emissivity, the data processing algorithm remains a difficult problem. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is proposed to inverse true temperature and spectral emissivity without assuming the emissivity model. The BFGS algorithm can automatically identify the emissivity models of different trends. These simulation results show that given different initial emissivity has no significant influence on the inverse temperature and emissivity. Then, we select 0.5 as the initial emissivity and carry out the simulation experiments at 800 and 900 K, respectively. The maximum absolute error of temperature is less than 3.5 K and the computation time is less than 0.2 s. Thus, the algorithm has high precision and efficiency. Finally, the verification experiment indicates that the BFGS algorithm is effective and reliable. The proposed method can be applied to real-time temperature measurement in many industrial processes.

Development of experimental methodology for estimation of thermo-physical properties of engineering materials using inverse method

In the present article, a novel experimental methodology is proposed for the simultaneous estimation of unknown thermal conductivity (k) and specific heat capacity (cp) of engineering materials. The experimental method involves radiative heating of the test sample and measuring its temperature response at two different locations. Proper arrangements have been made to realize one-dimensional heat conduction within the test sample. The one-dimensional heat conduction equation with convection-radiation heat loss boundary condition is considered as the forward model as it best mimics the experimental heat transfer. The inverse problem is formulated as a parameter estimation problem, and solved using Levenberg-Marquardt algorithm. First, numerical estimations were carried out with synthetic temperature data. It was found that the time-dependent heat flux boundary condition is more suitable to estimate the properties of higher thermal conductivity materials. Then, real-time temperature measurements were carried out on Stainless Steel (SS), Mild Steel (MS), Brass (BS), Aluminium (Al), and Copper (Cu) test samples. The estimated k of SS, MS, BS, Al, and Cu in (W/(m K)) is 14.03, 54.63, 103.21, 221.53 and 379.89, respectively. And, the estimated cp of SS, MS, BS, Al, and Cu in (J/(kg K)) is 500.44, 460.84, 395.01, 939.58, and 398.43 respectively. The estimated thermal properties are also validated against experimentally measured values obtained using the Modified Transient Plane Source (MTPS) sensor. It was found that the estimated k and cp in case of SS has a deviation of 7% and 4%, respectively.

Research on hot spot temperature monitoring technology of transformer winding

A temperature monitoring system based on fiber grating is designed to realize real-time measurement of the hot spot temperature of transformer windings. This paper introduces the principle of fiber grating temperature measurement, and use the Maxwell and Fluent modules in ANSYS to simulate and analyze the electromagnetic field-fluid field-temperature field of the transformer to obtain specific information about hot spots so that the fiber grating can be placed reasonably. Through the fiber grating wavelength demodulation system based on volume phase grating, the center wavelength value of the grating is obtained, and the quantitative relationship between the center wavelength and temperature is found, which proves the feasibility of the system.

A Comparative Studyon Characteristics of Inconel-625 Joints Developed through Microwave Hybrid Heating and Tungsten Inert Gas Welding

In recent years, microwave welding has received attention for joining of similar and dissimilar metals due to its major advantages like volumetric heating, selective heating of target materials, energy saving and sustainability. In the present work, the microstructural characteristics and mechanical properties of Inconel-625-welded joints developed through microwave hybrid heating and those produced by TIG welding have been compared. Welding through microwave hybrid heating (MHH) was carried out using Inconel-625 interface filler powder of 50 μm size, while TIG welding was carried out using ERNiCrMo-3 filler wire of 2.5 mm diameter which had a composition similar to that of Inconel-625 alloy. The welded samples were characterized in terms of microstructural observations and tensile and microhardness properties. The study reveals that the joining of bulk metals through MHH has potential in manufacturing industries in the near future. TIG-welded joints exhibit superior strength compared to MHH joints because of fine grain structure, lower amount of segregation in the weld zone and also smaller width of the weld zone in joints developed through MHH. The hardness in the weld zone of welded joints in both the cases is observed to be almost the same. Use of a finer interface filler of 20–25 μm particle size may further contribute to improving the mechanical properties of the joints developed through MHH. Furthermore, the use of industrial microwave furnace may improve the strength of MHH-welded joints as the process may be integrated with real-time temperature measurement of the joint zone so as to achieve better control over the process.

Real-time measurement method for the skin temperature of the human arm via large lateral shearing interferometry.

This paper presents a real-time measurement method for the skin temperature of the human arm. In this method, the air temperature close to the arm skin is measured via large lateral shearing interferometry, thus avoiding the possible influences of the different physical characteristics of different people, while maintaining the advantages of optical measurement, including its noncontact, noninvasive, and rapid features. The method captures the real-time fringe patterns generated using a parallel-sided plate when a collimated laser light beam transfers through the air surrounding the arm to be measured. Additionally, the phase difference distribution caused by the temperature difference is calculated in combination with the background fringe patterns. The phase difference in the light close to the arm skin is then estimated via a linear fitting method. Accordingly, based on the size parameters of the arm cross section and the ambient temperature monitored in real time, the air temperature close to the arm skin, which is considered equal to the arm skin temperature, is determined while considering the heat conduction effect. Experimental measurements of the temperature of human arm skin were conducted using the proposed method, and the axillary temperatures of the same person before and after the experiments were also measured using an electronic thermometer and a mercury thermometer. Good agreements were found, verifying the reliability of the proposed method. Moreover, based on this method, the possibility for the construction of a real-time body temperature measurement system is also discussed.

A thermal-driven method based on Brillouin fiber-optic sensors for the quantitative identification of subsurface cavities in concrete-filled steel tube structures

In the composite structure of a concrete-filled steel tube (CFST), because the concrete is concealed inside the steel tube, subsurface cavities can occur and are difficult to identify. In this study, a thermal-driven method based on Brillouin fiber-optic sensors (BFOSs) was proposed to quantitatively identify subsurface cavities in CFSTs. By performing a thermodynamic analysis of subsurface cavities in CFSTs, a thermal model related to the relationship between the subsurface cavity size and the temperature rise at the top surface of the CFST was established for the first time. Then, a sensing scheme based on the BFOS was proposed, and its feasibility was evaluated through an experimental program. The experimental program involved the use of an active heating layer for inputting heat flow into the CFST structure and BFOSs for the distributed measurement of temperature to identify subsurface cavities in CFSTs. The experimental results indicated that the BFOSs can achieve real-time distributed measurements of the surface temperature of the CFSTs. According to the temperature anomalies in the temperature rise curves of the CFSTs, the subsurface cavities can be accurately located in the longitudinal direction of the CFST, and its length can be quantified. There is an obvious linear relationship between the temperature rise and the square root of the heating time, from which the equivalent heat absorption coefficient (EHAC) can be determined. Furthermore, according to the relationship between the subsurface cavity height and the EHAC in the thermodynamic theoretical analysis, the subsurface cavity height can be obtained quantitatively.

Analysis of hygrothermal performance of low-energy house in Nordic climate

Analyses of hygrothermal conditions in low-energy houses is important because of their likely sensitivity for excessive moisture. The presented work deals with real-time measurement of temperature and relative humidity at multiple locations inside a low-energy house envelope. The measured data allows diagnosing approaches towards building design and understanding and evaluating the house performance. Suitability and accuracy of numerical computation was analysed. The Finnish mould growth model was used to monitor risk and extent of mould growth under measured and computed conditions. The measured conditions represent more favourable environment to avoid mould growth than the design values recommended by national and international guidelines. There was no mould growth indicated at any monitored points of the envelope. Monitoring the hygrothermal conditions provides valuable information about the performance of structural elements, building material and the house envelope and it helps to predict moisture related risks during the building’s service life.

Real-time Face Mask-Wearing Detection and Temperature Measurement based on a Deep Learning Model

In the context of the COVID-19 outbreak in a global scenario, mandatory mask-wearing and temperature control can effectively prevent its spread and realize self-protection. Therefore, real-time face-mask wearing and temperature measurement technology is of greater importance against the background of infectious disease prevention and control. The present study adopted MobileNet as the backbone of the single-stage RetinaFace framework for real-time face detection and mask-wearing detection. Moreover, the focal loss function of α dynamic value was adopted to avoid the class imbalance problem and improve the classification accuracy in the training stage. Regarding face temperature measurement technology, non-contact and uncooled temperature-sensitive elements were used for temperature measurement, but it was easily affected by environmental variables. Therefore, an SVR model was employed for temperature calibration with the constant temperature blackbody as reference. The alignment errors for the accuracy of face detection, mask wearing detection and temperature correction were 89.58%, 97.84% and 4.85%, respectively. The parameter quantity of the face mask wearing detection model reached 0.42 M, while the computation quantity arrived at 2.039 GFLOPs. The detection model proposed in this study combines real-time mask-wearing detection with face temperature measurement, which can help to quickly measure the body temperature and detect whether one wears face masks properly in the context of COVID-19, so as to reduce the risk of epidemic spread.

Flexible temperature sensors made of aligned electrospun carbon nanofiber films with outstanding sensitivity and selectivity towards temperature.

Continuous real-time measurement of body temperature using a wearable sensor is an essential part of human health monitoring. Electrospun aligned carbon nanofiber (ACNF) films are employed to assemble flexible temperature sensors. The temperature sensor prepared at a low carbonization temperature of 650 °C yields an outstanding sensitivity of 1.52% °C-1, high accuracy, good linearity, fast response time and excellent long-term durability. Moreover, it exhibits high discriminability towards temperature amidst other unwanted stimuli and maintains its original performance even after repeated stretch/release cycles because of highly-aligned structures. The correlation between the atomic structure and the temperature sensing performance of ACNF sensors is established. Contrary to conventional highly conductive temperature sensors, the ACNF sensor with a low electrical conductivity prepared at a low carbonization temperature ameliorates the temperature sensing performance. This anomaly is explained by (i) the smaller and more disordered sp2 carbon crystallites yielding a high negative temperature coefficient, (ii) a larger number of defects, and (iii) a higher pyridinic-N content generating abundant entrapped and localized electrons which are activated once sufficient thermal energy is available. Flexible ACNF sensor's overall performance is among the best-known carbon material-based flexible temperature sensors, demonstrating potential applications in emerging healthcare and flexible electronics technologies.

Method for Real-Time Temperature Measurement of Optical Fiber Link in Loopback Time Service System to Deduce One-Way Delay

Method for Real-Time Temperature Measurement of Optical Fiber Link in Loopback Time Service System to Deduce One-Way Delay

Development of an Apparatus for Testing of High-Temperature Static Seals

A test apparatus is described that evaluates the performance of static aviation seals under an environment similar to the lubrication system in gas turbine engines. The seals can be tested at operating temperatures as high as 400 °C in a static seal rig (SSR). Incorporating an air–oil mist generating system, the test facility exposes the seals to degraded oil, which can deteriorate the performance of seals through chemical attack. The test rig provides representative operating conditions to test four piston and four face seals at the same time. Throughout the aging process of seals, the rig carries out pressure decay leak tests at regular intervals and monitors temperature and pressure at several locations in the test chamber. The capabilities of the rig are demonstrated by presenting the results of durability testing with five types of seals. The results obtained with both successful and failed seals indicate that regular leak testing along with real-time measurement of temperature at the outlet of the low-pressure cavity can provide adequate information as to the operating status of the seals at different stages of testing and operating conditions.

A Positioning Method of Temperature Sensors for Monitoring Dam Global Thermal Field

During the concrete pouring process of a dam construction, timely and accurate temperature monitoring is of great significance to reveal the thermal distribution characteristics and evolution process, and control concrete cracking. In this study, a positioning method of temperature sensors (PMTS) in a concrete dam is developed to determine the arrangement of temperature sensors quantitatively. The proposed positioning method is related to the restructured thermal field based on the natural neighbor interpolation algorithm, and the cross-validation. Based on the method, thermometers, distributed optical fibers and infrared thermal imagers are optimally installed in a super-high arch dam for real-time measurement of concrete temperature. The results show that the PMTS is reasonable and reliable for obtaining the dam global thermal field. The on-site temperature monitoring data indicate that the time and space temperature distribution law of the restructured thermal field is consistent with the actual situation of the super-high arch dam. In addition, the cons and pros, and improvement of the PMTS are further discussed. The proposed PMTS is a valuable method to monitor the global thermal field of concrete dams.

Real-Time Predictive Temperature Measurement in Oil Pipeline: Modeling and Implementation on Embedded Wireless Sensing Devices

In pipeline management, the advent of Internet of Things (IoT) technology enables effective pipeline maintenance with the deployment of embedded sensing units, the basic requirement of which is to make accurate and real-time measurement. Practically, it is impossible to directly measure the internal temperature of the pipe by laying conventional sensors in the oil. This work proposed a novel indirect testing framework to perform real-time and accurate temperature monitoring in oil pipes by solving the inverse problem based on pipe wall's temperature field. The contribution includes three aspects: 1) A rigorous theory was developed to validate the principle of equivalence for heat transfer in pipes. A single-layer boundary-equivalent diffusion model with effective thermal parameters exhibited excellent performance in predicting temperature change in a multilayer structure by simulation. 2) We established a microprocessor-enabled predictive temperature measurement modality to precisely determine the time-dependent temperature evolution in a multilayer composite pipe based on explicit analytical expressions. 3) The correctness and applicability of the modality were verified experimentally on a real oil pipe and a commercial device. The results show that precision of the predictive measurement modality reaches 0.3 K and 0.002 K/s for stable and linear-rising internal fluid temperature, respectively.

Exploring the utility of EDA and skin temperature as individual physiological correlates of motion sickness

Motion sickness (MS) is known to be a potentially limiting factor for future self-driving vehicles – specifically in regards to occupant comfort and well-being. With this as a consideration comes the desire to accurately measure, track and even predict MS state in real-time. Previous research has considered physiological measurements to measure MS state, although, this is mainly measured after an MS exposure and not throughout exposure(s) to a MS task. A unique contribution of this paper is in the real-time tracking of subjective MS alongside real-time physiological measurements of Electrodermal Activity (EDA) and skin temperature. Data was collected in both simulator-based (controlled) and on-road (naturalistic) studies. 40 participants provided at total of 61 data sets, providing 1603 min of motion sickness data for analysis. This study is in agreement that these measures are related to MS but evidenced a total lack of reliability for these measures at an individual level for both simulator and on-road experimentation. It is likely that other factors, such as environment and emotional state are more impactful on these physiological measures than MS itself. At a cohort level, the applicability of physiological measures is not considered useful for measuring MS accurately or reliably in real-time. Recommendations for further research include a mixed-measures approach to capture other data types (such as subject activity) and to remove contamination of physiological measures from environmental changes.