Accurate Temperature Monitoring Research Articles

TEMPERATURE CORRECTION METHOD OF RADIATION THERMOMETER BASED ON THE NONLINEAR MODEL FITTED FROM SPECTRAL EMISSIVITY MEASUREMENTS OF Ni-BASED ALLOY

Accurate temperature monitoring of heat transfer tube is crucial for safe and efficient operation of nuclear power plants, and radiation thermometer is a common method used for this purpose. This paper thoroughly introduces the measurement principle of the radiation thermometer with an operation wavelength range of 8-14 μm. The spectral emissivity of Ni-based alloy DD6 under argon condition is measured using an emissivity measurement setup equipped with a Fourier-transform infrared (FTIR) spectrometer. By integrating the spectral emissivity in the working wavelength range, the spectral band emissivity can be calculated to enhance the accuracy of calculation results obtained by radiation thermometer. And curve of the spectral band emissivity with temperature can be accurately described by the nonlinear model. The radiation and corrected temperatures are compared with the temperatures obtained by a K-type thermocouple to verify the availability of the spectral band emissivity obtained by fitting the nonlinear model. The temperature comparison results demonstrate that the corrected temperatures are closer to the true temperature than the radiation temperature, with a maximum temperature deviation of only 4.38°C. The combined relative uncertainty of true temperature measurement by the radiation thermometer at temperatures of 200, 300, 400, and 500°C is less than 3.60%.

Precise Synergistic Photothermal Therapy Guided by Accurate Temperature‐Dependent NIR‐II Fluorescence Imaging

AbstractPhotothermal therapy (PTT) is considered a promising treatment strategy for solid tumors. However, local hyperthermia (over 45°C) during PTT can cause severe side effects in neighboring healthy tissues. PTT with accurate temperature feedback is a compelling strategy to ablate tumors and reduce side effects, but it still faces challenges. Here, a new kind of phototheranostic nanoparticle, namely 17‐RF@Ag2Se is developed, enabling in vivo NIR‐II fluorescence tracking, PTT and fluorescence nanothermometry as well as synergistic heat‐shock protein (HSP) inhibition. Precise PTT with high spatiotemporal resolution is achieved with the help of the designed NIR‐II fluorescence imaging‐photothermal therapy linkage apparatus. Upon intravenous injection, 17‐RF@Ag2Se is specifically accumulated in tumors targeted by the overexpressed integrin αvβ3, which is monitored by NIR‐II fluorescence imaging of Ag2Se QDs. Further, the release of HSP inhibitor, tanespimycin (17‐AAG), enhances the thermosensitivity of tumor cells. Subsequently, the internal temperature of the tumor is precisely monitored and adjusted during PTT via the temperature‐dependent NIR‐II fluorescence feedback of Ag2Se QDs and the linkage apparatus calibration, thereby achieving efficient and safe tumor PTT. Also, the results present a new method for accurate temperature monitoring and control in vivo, which can be applied to other biomedical studies.

A Multifaceted Exploration of Atmospheric Turbulence and Its Impact on Optical Systems: Structure Constant Profiles and Astronomical Seeing

This study emphasizes the importance of conducting a comprehensive analysis considering the Cn2 atmospheric parameter for a reliable assessment of the seeing value. It highlights the use of the ECMWF ERA5 model to simulate pressure, temperature, and humidity profiles, enabling the evaluation of optical degradation. Accurate modeling and monitoring of temperature and humidity variables are emphasized for precise data in optical communication and astronomical observations. It also discusses the significance of optical turbulence models in understanding the impact of atmospheric turbulence on optical system performance. The validation of the selected Cn2 models is thoroughly analyzed. To evaluate the impact of the boundary layer on seeing conditions, three factors are considered. First, ERA5 data is used to simulate surface Cn2 values using the PAMELA model. Second, typical Cn2 values for specific dates in Redu are obtained. Finally, the thickness of the boundary layer, denoted as hbl, is calculated. This finding highlights the significant influence of the boundary layer on atmospheric seeing conditions and by incorporating Ibl into the models, a more accurate representation of the effects of the boundary layer on seeing quality is achieved.

Pathways toward precise monitoring and low-carbon sustainability in fruit cold chain logistics: A solution enabled by flexible temperature sensing

Cold chain logistics (CCL) technology plays an irreplaceable role in the supply chain of fresh and perishable fruits. However, the rigidity and inflexibility of traditional temperature sensors limit the accurate monitoring of fruit temperature, resulting in temperature abuse, fruit quality degradation, and excessive energy consumption issues. In this paper, we proposed a flexible temperature sensing solution, which could provide efficient cold chain food quality control and reduce cold chain carbon emissions. The fruit cold chain experiment and temperature field simulation results show that the flexible precise temperature sensing solution can achieve approximately 20 % reduction in refrigeration carbon emissions due to the unique benefit of conformal monitoring. This paper has verified that the precise flexible temperature sensing technology could be combined with the intelligent cold chain control strategies. The energy consumption of refrigeration equipment can be greatly reduced, thereby promoting the development of sustainable and precise cold chain logistics technology.

Optimization of the Monitoring of Coal Spontaneous Combustion Degree Using a Distributed Fiber Optic Temperature Measurement System: Field Application and Evaluation

Coal spontaneous combustion (CSC) in gob not only leads to wasted resources and casualties, but also produces a lot of waste gas that pollutes the underground environment. Mastering the degree of CSC helps ensure that timely and effective control measures are taken. The real-time and accurate monitoring of temperature, as the primary indicator of the extent of CSC, is difficult due to the harsh and hidden environment of gob, resulting in a reduced ability to anticipate and prevent CSC. In this work, a complete distributed optical fiber temperature sensing system (DTSS) set with strong anti-damage ability was developed. The optical cable is protected by internal parallel steel cables and external protective pipes, which greatly improve the system’s reliability and integrity when used in gob. During its application in the Wangyun Coal Mine, an abnormal temperature rise in gob was discovered in time, and the effect of inhibitor spraying was monitored and evaluated. The degree of CSC in the gob was accurately identified, which shows that the work of coal mining can be targeted. This work is expected to improve early warning capability to prevent the risk of CSC in gob, and has promising applications.

Communication performance optimization of coal mine goaf LoRa AD hoc network sensor system based on tree topology

Real-time accurate monitoring of goaf gas, temperature, and other parameters is of key significance for the prevention and control of spontaneous coal combustion in the goaf. In this paper, a tree network and communication protocol for LoRa technology are proposed to solve the problems of small communication coverage and short endurance of the traditional goaf wireless monitoring system. In this paper, a geometric topology structure is designed for wireless sensor nodes to find relay nodes through the path loss model, and an energy-saving optimization algorithm routing scheme is designed. In addition, LoRa AD hoc network experiment platform and upper computer system are developed and designed. Through numerical analysis and experimental results in coal mines, it is proved that the proposed method significantly reduces the energy consumption of the whole network. The coverage radius is increased by 300% compared with the traditional star wireless sensor system, which makes the endurance time and communication quality have higher reliability.

Integrated photothermal agents with fluorescence intensity ratio/lifetime dual-mode temperature sensing

Non-invasive photo-thermal therapy (PTT) has been proposed as a powerful method for cancer treatment, in which accurate temperature monitoring is necessary to prevent ineffective therapy or damage to normal cells during the process of PTT. This promotes the design and development of photothermal agents (PTAs) with real-time temperature control and excellent photothermal conversion. Here, the designed dual-function photothermal agents YVO4: Nd3+, Yb3+@IR-780 were obtained, while the temperature detection behavior based on the fluorescence intensity ratio (FIR) of Nd3+ (4F3/2 → 4I11/2) to Yb3+ (2F5/2 → 2F7/2) and the temperature-dependent Yb3+ lifetime were investigated in detail. The advantages of fluorescence lifetime thermometry in the biological field were confirmed by the internal temperature detection of pork tissue through comparison with fluorescence intensity ratio technology. The photo-thermal conversion efficiency of samples YVO4: Nd3+, Yb3+@IR-780 reached about 34.3% and its potential application was also evaluated by the sterilization of E. coli and S. aureus, which shows that IR-780 coated nano-materials have excellent photo-thermal conversion performance. Results illuminated that the present photothermal agents with temperature self-monitoring had a bright future in the process of photothermal therapy.

A Continuously Worn Dual Temperature Sensor System for Accurate Monitoring of Core Body Temperature from the Ear Canal.

The objective of this work was to develop a temperature sensor system that accurately measures core body temperature from an ear-worn device. Two digital temperature sensors were embedded in a hearing aid shell along the thermal gradient of the ear canal to form a linear heat balance relationship. This relationship was used to determine best fit parameters for estimating body temperature. The predicted body temperatures resulted in intersubject limits of agreement (LOA) of ±0.49 °C over a range of physiologic and ambient temperatures without calibration. The newly developed hearing aid-based temperature sensor system can estimate core body temperature at an accuracy level equal to or better than many devices currently on the market. An accurate, continuously worn, temperature monitoring and tracking device may help provide early detection of illnesses, which could prove especially beneficial during pandemics and in the elderly demographic of hearing aid wearers.

Highly cascaded first-order sapphire optical fiber Bragg gratings fabricated by a femtosecond laser.

This Letter reports an innovative technique for fabricating large-scale, highly cascaded first-order sapphire optical fiber Bragg gratings (FBGs) using a femtosecond laser-assisted point-by-point inscription method. For the first time, to the best of our knowledge, this study successfully demonstrates a distributed array of 10 FBGs within highly multimode sapphire crystal fiber, made possible by employing a high-power laser technique to generate larger reflectors with a Gaussian intensity profile. These first-order FBGs offer advantages such as enhanced reflectivity, shorter fabrication time, and simplified spectral characteristics, making them easier to interpret compared with high-order FBGs. The FBGs' resilience and effectiveness are analyzed by subjecting them to temperature tests, proving their capacity for accurate temperature monitoring up to 1500°C-a testament to their suitability for harsh environments. This novel approach broadens the scope for sensing and communication applications in sapphire fibers, particularly under challenging conditions. The novelty of our work lies in successfully overcoming the limitations of previous designs by integrating a cascade of 10 FBGs in sapphire fibers, thereby enhancing multiplexing capabilities, minimizing overlapping of FBG peaks, and ensuring reliable temperature monitoring in industries and applications with thermal gradients.

Automatic Temperature Detection System at the Entrance

Ensuring public health and safety has grown to be a top priority as a result of the ongoing COVID-19 outbreak. This abstract describes a novel system that makes use of an Arduino Uno, an infrared temperature sensor, an ultrasonic sensor, and a servo motor to automate temperature detection at entry to public places. The central processing unit of the suggested system is an Arduino Uno microcontroller. It is not necessary to make physical touch to monitor body temperature because an infrared temperature sensor is used. The risk of potential contagion is decreased because of this sensor's ability to precisely measure human body temperature at a secure distance. An ultrasonic sensor is added to the system to improve functionality by determining how far away the person is from the door. This maximizes accuracy and efficiency by ensuring that temperature sensing only happens when a person is inside the appropriate range. The system activates the servo motor, which smoothly regulates the movement of a physical barrier, such as a gate or door when it detects a human within the predetermined distance range. Automated access control is made possible by this technology, prohibiting anyone with unusual body temperatures from entering. The system's brain, the Arduino Uno, is responsible for digesting sensor data and producing the right control signals for the servo motor. In the event of an abnormal temperature reading, it can also be configured to sound an alarm or notify authorized persons. The suggested system has several benefits, including accurate distance measurement, contactless operation, and real-time temperature monitoring. To provide efficient screening and stop the transmission of infectious illnesses, it can be applied at a variety of entrance points, including workplaces, educational institutions, medical facilities, and hubs for public transit. The Automatic Temperature Detection System at Entrance, which is demonstrated in this abstract, offers a reliable method for automating temperature screening procedures.

Fiber Bragg Grating Sensor Networks Enhance the In Situ Real-Time Monitoring Capabilities of MLI Thermal Blankets for Space Applications.

The utilization of Fiber Bragg Grating (FBG) sensors in innovative optical sensor networks has displayed remarkable potential in providing precise and dependable thermal measurements in hostile environments on Earth. Multi-Layer Insulation (MLI) blankets serve as critical components of spacecraft and are employed to regulate the temperature of sensitive components by reflecting or absorbing thermal radiation. To enable accurate and continuous monitoring of temperature along the length of the insulative barrier without compromising its flexibility and low weight, FBG sensors can be embedded within the thermal blanket, thereby enabling distributed temperature sensing. This capability can aid in optimizing the thermal regulation of the spacecraft and ensuring the reliable and safe operation of vital components. Furthermore, FBG sensors offer sev eral advantages over traditional temperature sensors, including high sensitivity, immunity to electromagnetic interference, and the ability to operate in harsh environments. These properties make FBG sensors an excellent option for thermal blankets in space applications, where precise temperature regulation is crucial for mission success. Nevertheless, the calibration of temperature sensors in vacuum conditions poses a significant challenge due to the lack of an appropriate calibration reference. Therefore, this paper aimed to investigate innovative solutions for calibrating temperature sensors in vacuum conditions. The proposed solutions have the potential to enhance the accuracy and reliability of temperature measurements in space applications, which can enable engineers to develop more resilient and dependable spacecraft systems.

Advanced Radio Frequency Applicators for Thermal Magnetic Resonance Theranostics of Brain Tumors

Thermal Magnetic Resonance (ThermalMR) is a theranostic concept that combines diagnostic magnetic resonance imaging (MRI) with targeted thermal therapy in the hyperthermia (HT) range using a radiofrequency (RF) applicator in an integrated system. ThermalMR adds a therapeutic dimension to a diagnostic MRI device. Focused, targeted RF heating of deep-seated brain tumors, accurate non-invasive temperature monitoring and high-resolution MRI are specific requirements of ThermalMR that can be addressed with novel concepts in RF applicator design. This work examines hybrid RF applicator arrays combining loop and self-grounded bow-tie (SGBT) dipole antennas for ThermalMR of brain tumors, at magnetic field strengths of 7.0 T, 9.4 T and 10.5 T. These high-density RF arrays improve the feasible transmission channel count, and provide additional degrees of freedom for RF shimming not afforded by using dipole antennas only, for superior thermal therapy and MRI diagnostics. These improvements are especially relevant for ThermalMR theranostics of deep-seated brain tumors because of the small surface area of the head. ThermalMR RF applicators with the hybrid loop+SGBT dipole design outperformed applicators using dipole-only and loop-only designs, with superior MRI performance and targeted RF heating. Array variants with a horse-shoe configuration covering an arc (270°) around the head avoiding the eyes performed better than designs with 360° coverage, with a 1.3 °C higher temperature rise inside the tumor while sparing healthy tissue. Our EMF and temperature simulations performed on a virtual patient with a clinically realistic intracranial tumor provide a technical foundation for implementation of advanced RF applicators tailored for ThermalMR theranostics of brain tumors.

Numerical study on the start-up strategy of cylindrical tubular receiver filled with nickel foam

A cylindrical tubular receiver filled with nickel foam (CTRNF) appears to be a promising receiver concept due to its capability to provide temperatures over 900 °C at a high pressure. Nevertheless, CTRNF is challenged by the unsteadiness and high intensity of radiant flux may cause inaccurate start-up time predictions, providing unrealistic and unstable outlet temperatures. In this article, these matters are addressed by a numerical model coupling the Monte Carlo ray tracing (MCRT) method and discrete coordinate (DO) radiative transfer model. The model considers the cold, semi-cold, semi-hot, and hot start-up strategies on the CTRNF using N2 and Ar as the working medium. Three preheating methods and their influence on the thermal characteristic of the CTRNF are proposed. Temperature and equivalent stress distribution of internal heat absorber is simulated and analyzed. The results indicate that the duration for four start-up strategies takes 1711 s, 2189 s, 1212 s and 1032 s as the outlet temperature reaches to 1200 K, respectively, when Ar is used as the working medium (10 g/s) and radiative power of 10.5 kW incidents on the solar receiver. Compared with the 68.44 kg Ar consumption of cold start-up strategy, the Ar working medium consumption decrease by 24.44 kg, 51.68 kg, and 63.16 kg for semi-cold start-up, semi-hot start-up, and hot start-up strategy. However, the maximum equivalent stress of the CTRNF under the hot start-up strategy is 100 MPa higher than under the cold start-up strategy, which requires accurate monitoring of the cavity temperature in solar receiver.

Greenland-Ice-Sheet Surface Temperature and Melt Extent from 2000 to 2020 and Implications for Mass Balance

Accurate monitoring of surface temperature and melting on the Greenland Ice Sheet (GrIS) is important for tracking the ice sheet’s mass balance as well as global and Arctic climate change. Using a moderate-resolution-imaging-spectroradiometer (MODIS)-derived land-surface-temperature (LST) data product with a resolution of 1 km from 2000 to 2020, the temporal and spatial variations of annual and seasonal ‘clear-sky’ surface temperature were evaluated. We also monitored summer surface melting and studied the relationship between the mass balance of the ice sheet and changes in surface temperature and melting. The results show that the mean annual LST during the study period is −24.86 ± 5.46 °C, with the highest of −22.48 ± 5.61 °C in 2010 and the lowest temperature of −26.49 ± 5.30 °C in 2015. With the change of season, the spatial variation of the ice-sheet surface temperature changes greatly. 2012 and 2019 experienced the warmest summers (−5.92 ± 4.01 °C and −6.51 ± 3.93 °C), with extreme cumulative melting detected on the ice-sheet surface (89.9% and 89.7%, respectively), and 2002 also experienced a greater extent of melting. But short period of melt in 2002 and 2019 (30.6% and 31.4%, respectively), accounted for a larger proportion, with neither the duration nor intensity of the melt reaching that of 2012. There is a strong correlation between the GrIS surface temperature and its mass balance. By fitting the relationship between surface temperature and mass balance, it was found that 93.83% (6.17%) of the ice-sheet response to surface-temperature change was via surface-mass balance (discharge and basal-mass balance).

A Temperature Monitoring Method For Power Electronic Converter Based on Infrared Image and Object Detection Algorithm

Power electronic converters are more and more widely used, and abnormal temperature of converter components is the most important factor in converter failure. To improve the reliability of the converter design, it is necessary to monitor the temperature of key components in the converter during the prototype test stage. The temperature measurement method of infrared thermal images has rich temperature information, wide detection range, and does not affect the original circuit design. However, in the current automatic temperature measurement methods, it is necessary to manually establish a standard matching template for the infrared thermal image of the circuit to be tested, which indicates a large workload and poor versatility. This paper proposes a method for fully automatic temperature monitoring of converter components. This method is based on a deep learning object detection algorithm, which can automatically identify the type of converter components, obtain partial infrared thermal images of components through heterogeneous image registration, achieve accurate component temperature monitoring and facilitate the converter state monitoring and fault detection. The advantages of this method are: 1) there is no need to manually establish a standard template for each converter; 2) it can monitor the converter temperature without manual intervention; 3) combining the temperature information and circuit prior knowledge, the state monitoring and fault diagnosis can further be realized. The experimental results also verify the feasibility and accuracy of this method.

Total variation denoising and Euclidean distance based distributed temperature monitoring in Brillouin optical time-domain analysis sensors

The performance of Brillouin optical time domain analysis (BOTDA) sensors is largely deteriorated due to the poor signal-to-noise ratio (SNR) of Brillouin gain spectra (BGSs) collected from the BOTDA experiment. The fast monitoring of distributed temperature using BOTDA sensors is also vital for many longdistant applications. To cope with these requirements, this paper proposes total variation denoising (TVD) and Euclidean distance-based pattern recognition (TEPR) for high-performance BOTDA sensors. The performances of TEPR are analyzed explicitly, and rigorous comparisons have been made with traditional nonlinear least squares fitting (NLSF). The experimentally demonstrated results signify that the proposed TEPR can improve the measurement uncertainty by up to ~55% compared to NLSF without worsening the experimental spatial resolution. The signal processing for using TEPR is also ~4 times faster than that for using NLSF. Hence, the proposed technique is an efficient and reliable alternative for the fast and accurate monitoring of distributed temperature in BOTDA sensors. J. Bangladesh Acad. Sci. 46(2); 193-202: December 2022

Application of Low-Cost Sensors for Accurate Ambient Temperature Monitoring

In structures with reduced monitoring budgets, the high cost of commercial metering devices is always an obstacle for monitoring structural health. This might be an issue when temperatures must be measured for both structural and environmental reasons. To fill this gap, in this paper, a novel monitoring system is proposed for the accurate measurement of indoor temperature in buildings. This protocol is characterized by its generality, as it can be easily adapted to measure any structural or environmental parameters on site. The proposed monitoring system uses from one to eight low-cost sensors to obtain multiple measurements of the ambient temperatures. The accuracy ranges of the developed monitoring systems with different numbers of sensors are statistically analysed. The results indicate that the discrepancy of the measurements decreases with the increase in the number of sensors, as the maximum standard deviation of 10 sensors (0.42) decreases to 0.32 and 0.27 for clusters of 20 and 30 sensors, respectively.

Improving the Accuracy of Constant Temperature Monitoring of Open-Air Stereo Stages

Background: Temperature regulation and monitoring is critical in IVF laboratories. Constant temperature monitoring of open-air stereo stages has proven to be a difficult feat, as probes are exposed to ambient air, making readings irreflective of actual temperature within media. Aim: To determine the substrate that most accurately reflects the temperature of culture media on an open stereo-stage. Method: Media under oil was temperature logged on a stereo stage simultaneously with six different dish setups, each fitted with a temperature probe: empty dish, large steel spheres (5mm), small steel spheres (2mm), ultrasound gel, silicone mold and ceramic balls. The dish set up that most consistently reflected media temperature was further assessed to determine how closely it mimicked the warming rate of media, measured in 1-minute intervals over a 20-minute period. Results: The media logged an average temperature of 36.99°C with a tight range of 36.9°C−37.1°C. The commonly used empty dish recorded an average temperature of 35.44°C with a range of 35.06°C−35.81°C. The tested substrates, listed in ascending order of efficacy, measured as follows: ceramic balls −33.65°C (33.01°C−33.97°C), large steel spheres −33.16°C (35.03°C−35.31°C), silicone mold −35.67°C (35.40°C−36.01°C) and ultrasound gel −36.24°C (36.5°C−36.41°C). The small steel spheres replicated the media temperature most accurately, with an average temperature of 36.48°C and the least variation (36.38−36.60°C). When warmed from room temperature to 37.0°C, the small steel spheres were closely comparable to the warming rate of the media, with rates of 0.94°C per minute and 1.1°C per minute, respectively. Both reached range within 12-minutes. Conclusion: Small steel spheres can substitute for culture media during temperature monitoring, allowing accurate constant monitoring of open-air stage temperature, and are closely comparable to the warming rate of media.

Mild-temperature photothermal treatment method and system based on photoacoustic temperature measurement and control

As a non-invasive technology for tumor treatment, photothermal therapy (PTT) is increasingly applied during clinical treatment. However, due to the lack of non-invasive temperature measurement methods, excessive therapeutic light dose will damage the healthy tissue around the lesion. Monitoring and control the therapy temperature during PTT application is necessary to ensure effective therapy while minimizing thermal damage to adjacent tissue. In order to ensure that the therapy temperature in PTT is stable in the mild range (below 43 °C), it is necessary to design a mild-temperature PTT method and system that can detect and control the temperature in real-time. A mild-temperature photothermal treatment method and system based on photoacoustic temperature measurement and control is proposed in this paper. On the basis of reference temperature, the relative temperature change is measured based on the photoacoustic information, and the treatment temperature of the target area is precisely controlled in real time using the closed-loop temperature control algorithm. Based on the experimental results of agar-based phantoms and pig liver tissue, the proposed system can achieve temperature imaging in real time, and the control steady-state error and overshoot are 0.62 °C and 0.3 % respectively. The results show that our method has the potential for accurate temperature monitoring and closed-loop temperature control during PTT.

POD-Kalman filtering for improving noninvasive 3D temperature monitoring in MR-guided hyperthermia.

BackgroundDuring resonance frequency (RF) hyperthermia treatment, the temperature of the tumor tissue is elevated to the range of 39–44°C. Accurate temperature monitoring is essential to guide treatments and ensure precise heat delivery and treatment quality. Magnetic resonance (MR) thermometry is currently the only clinical method to measure temperature noninvasively in a volume during treatment. However, several studies have shown that this approach is not always sufficiently accurate for thermal dosimetry in areas with motion, such as the pelvic region. Model‐based temperature estimation is a promising approach to correct and supplement 3D online temperature estimation in regions where MR thermometry is unreliable or cannot be measured. However, complete 3D temperature modeling of the pelvic region is too complex for online usage.PurposeThis study aimed to evaluate the use of proper orthogonal decomposition (POD) model reduction combined with Kalman filtering to improve temperature estimation using MR thermometry. Furthermore, we assessed the benefit of this method using data from hyperthermia treatment where there were limited and unreliable MR thermometry measurements.MethodsThe performance of POD–Kalman filtering was evaluated in several heating experiments and for data from patients treated for locally advanced cervical cancer. For each method, we evaluated the mean absolute error (MAE) concerning the temperature measurements acquired by the thermal probes, and we assessed the reproducibility and consistency using the standard deviation of error (SDE). Furthermore, three patient groups were defined according to susceptibility artifacts caused by the level of intestinal gas motion to assess if the POD–Kalman filtering could compensate for missing and unreliable MR thermometry measurements.ResultsFirst, we showed that this method is beneficial and reproducible in phantom experiments. Second, we demonstrated that the combined method improved the match between temperature prediction and temperature acquired by intraluminal thermometry for patients treated for locally advanced cervical cancer. Considering all patients, the POD–Kalman filter improved MAE by 43% (filtered MR thermometry = 1.29°C, POD–Kalman filtered temperature = 0.74°C). Moreover, the SDE was improved by 47% (filtered MR thermometry = 1.16°C, POD–Kalman filtered temperature = 0.61°C). Specifically, the POD–Kalman filter reduced the MAE by approximately 60% in patients whose MR thermometry was unreliable because of the great amount of susceptibilities caused by the high level of intestinal gas motion.ConclusionsWe showed that the POD–Kalman filter significantly improved the accuracy of temperature monitoring compared to MR thermometry in heating experiments and hyperthermia treatments. The results demonstrated that POD–Kalman filtering can improve thermal dosimetry during RF hyperthermia treatment, especially when MR thermometry is inaccurate.