Temperature Measurement Error Research Articles

Theoretical and numerical investigation of introduced errors in surface temperature measurements of pistons applied in internal combustion engine

DMP (Differences in Material Properties) often exists between temperature sensors and combustion chamber components of ICE (Internal Combustion Engine), resulting in IEs (Introduced Errors) in the temperature measuring process. In this paper, we present a comprehensive theoretical analysis of the correlation between introduced errors on chamber components and the DMP. The analysis process considers the characteristics of the chamber's heat transfer BC (Boundary Condition). Then, simulations are used to investigate the introduced error of hardness plug and thermocouple sensors on the top surface of an ICE aluminum alloy piston. The theoretical analysis results indicate that heat transfer BC can be segmented into the time-averaged and fluctuation parts, and IEs are linearly superimposed under these two parts of BCs. The heat conductivity impacts the time-averaged error and the product of heat conductivity, density, and heat capacity impacts the fluctuation error. The experimental and simulation results indicate that the max time-average error of the hardness plug on piston is 2.4 °C, with a fluctuation introduced error of 3.6 °C and a total introduced error of 6 °C; and the time-average introduced error of thermocouple sensor is 9.4 °C, with a fluctuation error of 5.8 °C and a total introduced error of 15.2 °C. Finally, a fluctuation error correction method is proposed to reduce error. After correction, the error is reduced by 71 % and 66 % for hardness plug and thermocouple, respectively.

Real-Time Temperature Monitoring of Lithium Batteries Based on Ultrasonic Technology.

Electrochemical energy storage stations serve as an important means of load regulation, and their proportion has been increasing year by year. The temperature monitoring of lithium batteries necessitates heightened criteria. Ultrasonic thermometry, based on its noncontact measurement characteristics, is an ideal method for monitoring the internal temperature of lithium batteries. In this study, temperature and ultrasonic time delay measurement experiments were conducted on 18650 lithium batteries and laminated and wound lithium batteries to obtain the corresponding relationship between temperature and time delay and validate the temperature measurement for the same type of battery. The experimental results show that (1) the ultrasonic temperature measurement technique exhibits a relatively large error when used for 18650 Li-ion batteries under experimental conditions; (2) in the experiments on laminated and wound soft-pack lithium batteries, the relationship between temperature and time delay exhibits a nonlinear characteristic; and (3) under the experimental conditions, the ultrasonic temperature measurement errors were ±1.1 °C for stacked Li-ion batteries and ±1.4 °C for wound Li-ion batteries.

ВПЛИВ УМОВ РОБОТИ НА ТЕМПЕРАТУРНИЙ РЕЖИМ ПІДШИПНИКІВ З МЕТАЛЕВИМИ ТА КЕРАМІЧНИМИ КУЛЬКАМИ

The results of an experimental study of the temperature mode of operation of rolling bearings under different lubrication conditions are presented. Comparative tests of all-metal bearings and similar bearings with rolling elements made of silicon nitride (hybrid bearings) when lubricated with an oil jet and an oil-air mixture in the range of rotor rotation frequencies from 0 to 35000 rpm were carried out. For the experiments, a specially created set was used, which allows you to study the temperature of the bearings and the temperature of the lubricant at the entrance and exit from the bearings. The axial load on the bearings was created with the help of a compression spring, which rested on the outer rings of the bearings. This made it possible to close the load inside the system. During the tests, the load was 0 N, 1000 N, and 2000 N. Tests were carried out for two modes of bearing lubrication: oil jet and oil-air mixture. The method of measuring the temperature of the outer ring of bearings is described. The temperature measurement error was considered as a complex of instrumental error and method error. It was assumed that the temperature error is subject to a normal distribution. The conducted analysis showed that the error of measuring the temperature of the bearing ring was ± 2.8 °C with a confidence probability of 95 %. It has been established that bearings with ceramic balls in the entire studied range behave qualitatively and quantitatively in approximately the same way as with steel ones. The temperature level of hybrid bearings is slightly higher when lubricated with both an oil jet and an oil-air mixture. There is a clear connection between the values of the bearing temperature and the moment of resistance in the bearing: the increase in temperature is observed under the same conditions under which the moment of resistance increases.

A WGM-FP hybrid microcavity for simultaneous measurement of NaCl concentration and temperature

Whispering gallery mode (WGM) resonator is sensitive to the external medium change due to its strong light-matter interaction. However, the temperature sensitivity of silica-based WGM resonators would cause crosstalk, which is a fatal shortcoming for those high-quality (Q) resonators. In this paper, a hybrid microcavity including WGM resonance and Fabry–Pérot (FP) interference is proposed for simultaneous measurement of NaCl concentration and temperature, using the same microcavity in the same system to obtain two types of optical signals. The experimental results indicate that the maximum measurement error of NaCl concentration and temperature without compensation is about ± 0.026 % and ± 1.1 °C, while they would be ± 0.012 % and ± 0.3 °C after compensation. Sharing one microcavity enables temperature compensation to achieve temperature synchronization, and sharing of one system ensures the simplicity and stability of the sensing platform.

Design and implementation of a Li River water quality monitoring and analysis system based on outlier data analysis.

The detection of water quality indicators such as Temperature, pH, Turbidity, Conductivity, and TDS involves five national standard methods. Chemically based measurement techniques may generate liquid residue, causing secondary pollution. The water quality monitoring and data analysis system can effectively address the issues that conventional methods require multiple pieces of equipment and repeated measurements. This paper analyzes the distribution characteristics of the historical data from five sensors at a specific time, displays them graphically in real time, and provides an early warning of exceeding the standard; It selects four water samples from different sections of the Li River, based on the national standard method, the average measurement errors of Temperature, PH, TDS, Conductivity and Turbidity are 0.98%, 2.23%, 2.92%, 3.05% and 3.98%.;It further uses the quartile method to analyze the outlier data over 100,000 records and five historical periods are selected. Experiment results show the system is relatively stable in measuring Temperature, PH and TDS, and the proportion of outlier is 0.42%, 0.84% and 1.24%. When Turbidity and Conductivity are measured, the proportion is 3.11% and 2.92%. In the experiment of using 7 methods to fill outlier, K nearest neighbor algorithm is better than others. The analysis of data trends, outliers, means, and extreme values assists in making decisions, such as updating and maintaining equipment, addressing extreme water quality situations, and enhancing regional water quality oversight.

A correction method for radial distortion and nonlinear response of infrared cameras.

The key feature of non-contact temperature measurement provided by infrared (IR) cameras underpins their versatility. However, the accuracy of temperature measurements with IR cameras depends on imaging quality due to their non-contact nature, such as the lens, body temperature, and measurement environment. This paper addresses the correction of radial distortion and nonlinear response issues in IR cameras. To address radial distortion, we have designed a passive checkerboard calibration board specifically for infrared cameras. This board is used to calibrate the IR camera and derive the necessary camera parameters. Subsequently, these parameters are applied during the actual measurement process to rectify radial distortion effectively. Building on the radial distortion correction method mentioned above, we propose a multi-point segmented calibration approach that considers different temperature ranges and imaging regions. This method alleviates the issue of reduced temperature measurement accuracy due to variations in camera responses by computing gain and offset coefficient matrices for each temperature range. Experimental results demonstrate the effectiveness of the calibration board in correcting radial distortion in IR cameras, with a mean reprojection error of less than 0.16 pixels. Regarding the nonlinear response problem, the introduced method significantly reduces the relative error in temperature measurement. In the verification phase, spanning from 100 to 500 °C, the average relative error in temperature measurement decreases by 0.49% from 1.61% before and after correction, which highlights a substantial improvement in temperature measurement accuracy. This work gives a useful reference to improve the imaging quality and temperature measurement accuracy using infrared cameras.

Intelligent decision-making in healthcare telemonitoring via forward-backward chaining and IoT

Healthcare telemonitoring has emerged as a promising approach to remotely monitor patients remotely, enabling timely intervention and personalized care. Internet of things (IoT) device-generated patient data necessitates innovative solutions for intelligent healthcare decision-making, as current methods struggle to provide timely, context-aware, and data-driven recommendations, resulting in suboptimal patient care. This study aims to develop an intelligent decision-making framework for healthcare telemonitoring by leveraging forward-backward chaining and IoT technology. The research focuses on a system using forward-backward chaining algorithms to analyze real-time patient data from IoT devices. It utilizes machine learning models to adapt to changing conditions and refine decision-making, demonstrating its ability to provide real-time context-aware recommendations. Temperature, blood pressure, oxygen level, and heart rate measurement errors are 2.01%, 1.74 to 2.13%, 0.61%, and 1.45%, respectively. The success rate of early disease diagnosis using an expert system is 81%, with an average application interface responsiveness time of 4.978 s. The integration of IoT data with intelligent decision-making algorithms in healthcare telemonitoring has the potential to revolutionize patient care. However, future work should focus on scalability and interoperability for diverse healthcare settings.

Continuous light-guide control of melts temperature in induction furnaces

The article is devoted to the question of the most effective for the full use of the induction furnaces technological flexibility continuous temperature control. The aim of the work is to create a light-guide technology for continuous temperature control of the processes of induction melting, treatment and pouring of liquid metal in metallurgy of machine building. The investigations of crucible and channel, melting, holding and pouring induction furnaces from the standpoint of light-guide thermometry have been developed. Materials, designs, as well as technologies of manufacturing, mounting and safe operation of the light-guide and auxiliary devices have also been investigated. Using the results of complex studies, the base light-guide thermometry system, general and particular methods of the light-guide temperature measurements have been developed. On the base of the Huygens construction, as well as the laws of geometric and crystal optics, techniques for calculation of the optical characteristics of the light-guide and focusing devices, as well as schemes of their optical joint have been developed. These techniques increase the metrological characteristics of the light-guide thermometry. Standard construction of the secondary part of thermometry system requires classical pyrometry methods application. These methods are acceptable for continuously operated metallurgical aggregates, where stable emissivity of the light-guide operating end takes place. The secondary part of thermometry system has been modernized in order to widen application field of light-guide thermometry on periodically operated metallurgical aggregates where emissivity of light-guide immersion end randomly changes. Modernized secondary part is purposed for spectral (multicolor) pyrometry methods realization. These methods minimize influence of the instability of emissivity of light-guide immersion end on methodical errors of temperature measurements. Research and industrial exploitation, at domestic and foreign enterprises, have shown obvious metrological advantages of the light-guide thermometry technology in comparison with known solutions. Implementation of the light-guide thermometry systems on induction furnaces has high technical-economic efficiency, including by reduction the spoilage of metal products and resource costs for production. Keywords: induction furnace, continuous temperature control, light-guide thermometry, amorphous, poly- and single-crystalline materials, measurement error, Huygens construction, technical-economic efficiency.

Management of thermal drift of bolometric infrared cameras: limits and recommendations

ABSTRACT In this article, the authors propose a general framework for checking the calibration of the A325sc camera and then minimizing the temperature measurement errors due to thermal drift. Thermal drift and non-uniformity affect the measurement accuracy of infrared bolometric cameras and remain a major problem for the reproducibility and repeatability of radiance quantification. Any thermal camera is pre-calibrated at the factory to correct for thermal drift. This pre-calibration was done for specific case temperatures, and variations in these temperatures are a major source of uncertainty. To improve the accuracy of the camera measurements, it’s important to control the housing temperatures. To this end, a cold box was build up. The effectiveness of the thermal drift compensation was examined over the two ranges of the camera. In the [-20°C; 120°C] range, the thermal drift compensation is efficient up to 110°C. The range [0°C; 350°C] highlights two behaviors: for an emitting temperature within [65-225] °C, the thermal drift compensation is made difficult by the self-heating of the measurement chain due to the intensity of the source. Above 225°C, the self-heating of the optics is significant, as it becomes more absorbent. A correction of the thermosignal is suggested.

Non-destructive Thermal Monitoring of Temperature and Flow Rate of the Heat Carrier in a Heating Device

Conducting various calculations for the heating system of a building under operational conditions is impossible without knowledge of the temperature and flow rate of the heat carrier at specific points. Contact measurement means are not always applicable, especially for small-diameter pipelines. Measurement techniques based on the theory of non-destructive thermal inspection allow for remote and timely acquisition of all necessary information. The object of the study is the floor node of the building's heating system. The subject of the study is the temperature and flow rate of the heat carrier passing through the heating device. The research aim is to determine the temperature and flow rate of the heat carrier passing through the heating device under operational conditions. The research method involves the theory of non-destructive thermal inspection, as well as heat balance and heat transfer equations for a vertical flat wall. Research findings reveal that during thermovisual inspection, the temperature of the heat carrier in the supply and return pipelines of the floor node respectively amounted to 51.6 ℃ and 49.6 ℃. The flow rate of the heat carrier through the heating device model MS-140M2-500, with a heat transfer coefficient of 8.5 W/(m²⋅K), was determined to be 195.0 kg/h. Recommendations include utilizing a thermal imager with an absolute measurement error not exceeding ±0.15 ℃ for determining the flow rate of the heat carrier through the heating device. The influence of measurement error of indoor air temperature on the accuracy of determining the heat carrier flow rate is insignificant (not exceeding ±2%). The relative error in determining the heat transfer coefficient of the heating device does not exceed ±1%.

Rayleigh Doppler Lidar Technology Based on a Quadruple Dual-pass Fabry–Perot Interferometer

A novel Rayleigh Doppler lidar technology based on a quadruple dual-pass Fabry–Perot interferometer (FPI) that can accurately measure wind field, temperature and aerosol backscatter ratio from the troposphere to lower stratosphere is proposed. This study aims to analyse the detection principle of wind speed, temperature and aerosol backscatter ratio in detail and obtain their measurement error formulas. The structure of this type of lidar is studied and designed. The FPI consists of two edge channels FPI-1 and FPI-2, aerosol channel FPI-M and locking channel FPI-L. FPI-1, FPI-2 and FPI-M use a dual-pass optical path, whereas FPI-L uses a single-pass optical path. The parameters of FPI are optimised as follows: the free spectral spacing (FSR) is 12 GHz, the FWHM of FPI-1 and FPI-2 are both 2.2 GHz, the peak-to-peak interval of FPI-1 and FPI-2 is 5.8 GHz, the FWHM of FPI-M and FPI-L are both 1.2 GHz, the peak-to-peak interval of FPI-M and FPI-1 is 2.9 GHz and the peak-to-peak interval of FPI-L and FPI-1 is 2.3 GHz. Under simulated atmospheric conditions, for a daytime sky background brightness of 0.3 Wsr−1m−2nm−1 at 355 nm, using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz and a telescope with a 0.45-m aperture, with a vertical range resolution of 30 m at 0–10 km, 100 m at 10–20 km and 500 m at 20–35km, temporal resolution of 30 min, zenith angle of 0° for temperature and aerosol backscatter ratio detection and temporal resolution of 3 min and zenith angle of 30° for radial wind speed detection, the detection performance of the designed Rayleigh Doppler lidar is determined. The simulation results show that the measurement errors of aerosol backscatter ratio, temperature and radial wind speed of the lidar system in the daytime and night-time are less than 4.36 × 10−3 and 3.32 × 10−3 (excluding cirrus cloud area), 4.0 K and 3.0 K and 3.8 m/s and 1.9 m/s, respectively, from an altitude of 0.06 to 35km.

Design and Implementation of Temperature Sensor Based on Dynamic Current Gain Compensation Technology

Complementary metal oxide semiconductor (CMOS) temperature sensors are widely used in on-chip systems for their low cost, high integration and low power consumption. A temperature sensor based on parasitic transistor front-end and dynamic current compensation technology is proposed in this paper, which is used to detect temperature in CMOS bipolar junction transistor. In this paper, the parasitic bipolar junction transistor (BJT) device in CMOS process and its temperature sensing principle are introduced, and a temperature sensor based on BJT temperature sensing front-end and dynamic current compensation technology is proposed. In this scheme, the high-resolution current comparator dynamic current compensation technology is used instead of the large capacitance which is necessary in the traditional current domain temperature sensor, which not only ensures the accuracy of the temperature sensor, but also ensures the accuracy of the temperature sensor, it also saves area and power consumption. The sensor’s control circuit uses a novel bucket search algorithm that allows current measured temperature values to be obtained by comparing as few times as possible. In addition, threshold setting technology is adopted to further improve the temperature sensing accuracy with lower power consumption and area cost. In the end, the test results and analysis are introduced. The CMOS temperature sensor proposed in this paper has been used in the standard 55 nm CMOS process. The test results show that the temperature range from −15 °C to 90 °C, the temperature measurement error is ± 0.5 °C and the area is only 0.021 mm2 after single point calibration.

Numerical simulation of laser heating effect in optical temperature measurement based on Kubelka-Munk theory

The fluorescence intensity ratio (FIR) technique is widely used in many fields as one of the sensing methods of phosphor thermometry. In the gas turbine field, the rare earth ions are often doped to thermal barrier coating (TBC). When excited by laser pulses TBC glows phosphorescent, and it can be utilized for thermometry. The laser energy absorbed by the TBC is not only used to generate the luminescence but also introduces heat into the TBC and causes a temperature rise further increasing optical temperature measurement error. Therefore, it’s essential to predict the temperature rise and the temperature measurement error, and take measures to reduce the error due to the laser heating effect. However, there are few researches concerning this problem, and most of them focus on the relationship between the laser energy and the point temperature measured by the FIR technique. Here we show a method for evaluating the effect of laser heating on temperature fields and optical temperature measurement errors by establishing thermal equivalent model and discrete model of body luminescence, considering laser and phosphorescence scattering in coatings made of YSZ based on Kubelka-Munk theory. We found that continuous pulsed laser heating caused severe temperature rise and significant temperature measurement error. Furthermore, the temperature rise can be decreased to the level of a single pulsed laser heating by decreasing the frequency of laser. In addition, the main influencing factors of the temperature measurement error are the density of laser energy and coating thickness.

Self-Calibration of UAV Thermal Imagery Using Gradient Descent Algorithm

Unmanned aerial vehicle (UAV) thermal imagery offers several advantages for environmental monitoring, as it can provide a low-cost, high-resolution, and flexible solution to measure the temperature of the surface of the land. Limitations related to the maximum load of the drone lead to the use of lightweight uncooled thermal cameras whose internal components are not stabilized to a constant temperature. Such cameras suffer from several unwanted effects that contribute to the increase in temperature measurement error from ±0.5 °C in laboratory conditions to ±5 °C in unstable flight conditions. This article describes a post-processing procedure that reduces the above unwanted effects. It consists of the following steps: (i) devignetting using the single image vignette correction algorithm, (ii) georeferencing using image metadata, scale-invariant feature transform (SIFT) stitching, and gradient descent optimisation, and (iii) inter-image temperature consistency optimisation by minimisation of bias between overlapping thermal images using gradient descent optimisation. The solution was tested in several case studies of river areas, where natural water bodies were used as a reference temperature benchmark. In all tests, the precision of the measurements was increased. The root mean square error (RMSE) on average was reduced by 39.0% and mean of the absolute value of errors (MAE) by 40.5%. The proposed algorithm can be called self-calibrating, as in contrast to other known solutions, it is fully automatic, uses only field data, and does not require any calibration equipment or additional operator effort. A Python implementation of the solution is available on GitHub.

Effect of flame thickness on the temperature measurement error for bare-bead thermocouple in open pool fires with different fuels

Accurately obtaining the temperature distribution of the flame is crucial for a comprehensive understanding of the combustion behavior of the pool fire. The correction method is needed to compensate the measurement error when the temperature is measured by bare-bead thermocouple in the open pool experiment, but the effect of flame thickness is rarely considered in the current method. Thus, this work develops a coupled heat transfer model of bare-bead thermocouples in open pool fires and modifies the flame radiation characteristics based on the fuel type and flame thickness. The control mechanism of measurement error in the model is identified, and then the effects of main parameters such as flame thickness and flame temperature on measurement error are analyzed. The results show that the flame emissivity decreases exponentially with the decrease of flame thickness, the minimum emissivity of gasoline flame is 0.26 when flame thickness is 0.1 m. The decrease of flame thickness leads to a sharp increase of temperature measurement error. The maximum increment of error can reach 227.3 K. On this basis, the flame thickness limit value, considering the correction of temperature measurement error in different hydrocarbon pool fire experiments is proposed.

Temperature sensing technique across a wide range using phosphorescence intensity ratio of Dy3+-Doped YAG/YAP

To address the need for precise temperature measurement across an extended temperature range, we successfully synthesized a temperature-sensitive phosphorescent material using a high-temperature solid-state method. This material involves the incorporation of dysprosium dopant into the yttrium aluminum garnet/yttrium aluminum perovskite (YAG/YAP) phosphor matrix. Our primary objective was to leverage the phosphorescence intensity ratio of Dy3+ energy level transitions (4F9/2 → 6H15/2, 4I15/2 → 6H15/2) in response to temperature fluctuations, enabling temperature measurements within the 100–1300 °C range. Throughout our investigation, we observed shifts in the peak wavelengths “a” and “b” attributable to thermally coupled energy level transitions as temperature increased. Specifically, at 1000 °C, the peak wavelength “a” shifted from 457.4 nm to 457.8 nm, while at 750 °C, peak wavelength “b” shifted from 497.6 nm to 497.2 nm. Subsequently, we assessed the temperature sensitivity and measurement error of the sample. Impressively, the temperature sensitivity remained consistent across various single-pulse excitation powers and even after 50 h of continuous operation. The maximum absolute sensitivity exceeded 11.21 × 10−4 °C−1, and the relative sensitivity surpassed 2.78 × 10−2 %°C−1. The minimum temperature measurement error was approximately ±2 °C. As a result, the phosphorescent YAG/YAP: Dy3+ powder demonstrates significant potential for applications within the 100–1300 °C temperature range.

Fluctuation of Magnetic Field in Magnetic Nano-Particles Thermometer

In this study, some important factors have been identified for the fluctuation of the magnetic field over time, which provides a basis for improving the temperature measurement accuracy and long-term stability of the magnetic nanoparticles thermometer (MNPT). We improved the mathematical model between the relative error of the magnetic induction intensity and the temperature measurement error of MNPT. The simulation founded that when the relative error of the magnetic induction intensity is kept within the range of <0.01%, the temperature measurement error is less than 0.1 K. Then, the multi-physics (magnetic field, temperature field, and thermal stress field) coupling relationship in the Helmholtz coil is established. During the coupling process, the temperature field of the Helmholtz coil affects the resistance of coil wire, and its thermal stress field is affected by the temperature field, which also changes the coil radius. After the temperature field and thermal stress field change, the magnetic field fluctuates immediately. Further simulation found that the problem of coil temperature rise becomes more serious as the size of the Helmholtz coil increases. The method of forced air cooling can make the fluctuation of the large Helmholtz coil magnetic field < 0.01%, and improve the measurement accuracy of MNPT.

Influence of Tilting Angle on Temperature Measurements of Different Object Sizes Using Fiber-Optic Pyrometers.

This article presents a new model of optical power gathered by a fiber-optic pyrometer when there is a tilting angle between the fiber longitudinal axis and the vector perpendicular to the tangent plane of the emitted surface. This optical power depends on the fiber specifications, such as the diameter and the numerical aperture (NA), as well as the object parameters, including its diameter, emissivity, and tilting angle. Some simulations are carried out using other pyrometers from the literature without tilting to validate the model. Additional simulations with different optical fibers, object sizes, and distances at different tilting angles allow us to describe the behavior of the pyrometer when the object is smaller than the optical fiber field of view (the light cone defined by its NA). The results show that for a finite surface object, the power collected by the optical fiber is affected by changes in the tilting angle, greater tilting lesser gathered power, and reaching the maximum power when the field of view of the fiber covers up the entire object, as expected. On the other hand, additional equations are presented to describe the maximum tilting angle, and distance that allow the maximum power gathered for a determined object diameter and fiber, avoiding temperature measurement errors.

Approach to multispectral thermometry with Planck formula and hybrid metaheuristic optimization algorithm.

Accurate temperature measurement has significant implications for product quality, industrial process control, and scientific research. As a non-contact temperature measurement method with broad application prospects, multispectral thermometry still poses significant challenges in data processing. Currently, most multispectral thermometry methods use the Wien approximation equation to construct the objective function. However, the use of the Wien approximation equation is conditional and generally applicable only to low temperatures or short wavelengths. In this paper, what we believe is a new data processing model of multispectral thermometry is established based on the Planck formula; Additionally, a feasible region constraint method is proposed to constrain the emissivity range; By utilizing a hybrid metaheuristic optimization algorithm based on differential evolution (DE) and multi-population genetic (MPG) algorithms, the simulation results of six different models and experimental results of silicon carbide demonstrate that the proposed algorithm achieves an average relative error in temperature measurement within 0.42% and a random relative error within 0.79%. The average computation time for each temperature inversion is approximately 0.26 seconds. The accuracy and efficiency of the algorithm ensure that it can be applied to real-time temperature measurement in industrial field.

A wavelet analysis method to retrieve thermal conductivity and radiative properties of intense extinction and low conductive medium

The accurate acquisition of the physical properties of strongly extinction materials limits their application development. In order to solve the problem of large errors in the high temperature measurement of these materials, this paper constructs an inversion model for the radiative and conductive coupled heat transfer through wavelet decomposition coefficients, and compares it with traditional methods. The radiative and conductive coupled heat transfer model is solved by finite volume method and Monte Carlo method. Daubechies nine wavelet is used for signal wavelet analysis. It has been discovered that the wavelet decomposition parameters of the temperature field are mainly concentrated in the 4–8 wavelet frequency band of wavelet, it can separate from the random error that is mainly concentrated in the 1–3 frequency band of wavelet. Most of physical properties like the heating power, convective heat transfer coefficient, material thermal conductivity, extinction coefficient has a great impact on the waveform and amplitude of wavelet detail coefficient and approximation coefficient, and the change trend of approximation coefficient and detail coefficient amplitude is consistent with the trend of temperature field. However, the effect of scattering albedo on wavelet parameters is tiny. Through inversion, it is found that the inversion model based on wavelet decomposition parameters of 5–7 frequency band has higher accuracy when random error exists.