Compensation Of Temperature Effects Research Articles

New readout system of the FATIMA detectors based on Silicon Photomultipliers arrays

We present a new readout system based on large area Silicon Photomultipliers arrays coupled with cylindrical 1.5 × 2” LaBr3(Ce) FATIMA-type crystals. This achieves the fast-timing capabilities of such crystals coupled to the usual Photomultiplier Tubes. Energy calibration was measured with 137Cs and 152Eu standard radioactive sources, while the timing performances were investigated with a 60Co radioactive source. We benchmark our results against the corresponding results obtained with the fast R9779 Photomultiplier tubes and highlight the importance of achieving similar energy and timing performances for nuclear structure experiments. The FWHM energy resolution for the 1.5 × 2” LaBr3(Ce) crystal coupled with the SiPM and PMT was found to be 3.31(2)% and 3.85(1)%, respectively, for the 661.6 keV transition of the 137Cs source. The timing resolution was measured between a conical crystal known for its fast response and a cylindrical crystal coupled to a SiPM or PMT readout. We obtain values of FWHM = 230(1) ps and 232(1) ps, respectively, between the 1173.2-1332.5 keV transitions of the 60Co source. In addition, a temperature effect compensation circuit was developed to maintain a good stability of the gain during long measurements, typical for in-beam/off-beam experiments in nuclear physics.

Temperature compensation method for impedance signals of bolt loosening under temperature varying conditions using TransUnet

Abstract Piezoelectric transducer based electro-mechanical impedance technology is an effective and reliable detection method for bolt structure loosening under external load. However, temperature change usually causes some non-loosening factors to change the impedance spectrum of bolt structure. In order to reduce the misjudgment of loosening damage caused by temperature change, it is necessary to construct a temperature compensation model for impedance spectrum. In this paper, the convolutional structure in U-net and Transformer are effectively combined to form a TransUnet deep neural network structure suitable for input and output of one-dimensional data. Using impedance data between 10 °C and 50 °C and temperature as input to the network. After convolution operation, the convolutional block attention module is embedded in the U-net to optimize the encoder transmission characteristics and enhance the performance of the skip connection in the traditional U-shaped structure. The temperature compensation rate (TCR) is defined to measure the effect of temperature compensation. Then the lightweight convolutional neural network structure is used to recognize the bolt loosening damage of the compensated impedance signal. The generalization ability of the TransUnet was tested using impedance data that is not in the training dataset. The results show that the TransUnet proposed in the paper can realize the temperature compensation of multi-peak impedance signals. The TCR and recognition accuracy of bolt loose damage reaches reach 0.003 and 95.7%, respectively, which is 11% higher than that without temperature compensation. At 60 °C, the TCR and the identification accuracy of loosening damage can still reach 0.0055 and 90.2%, respectively, which show that the TransUnet has strong generalization ability.

Effect of temperature compensation on properties and interfacial structure evolution of Al/CFRTP ultrasonic welded joints

Effect of temperature compensation on properties and interfacial structure evolution of Al/CFRTP ultrasonic welded joints

Research and development of corrosion monitoring sensor for bridge cable using electrical resistance probes technique

A cable corrosion monitoring sensor with a temperature compensation probe has been designed and manufactured to monitor the corrosion of high-strength steel wires in the transition zone between the cable body and the anchorage. The influence of temperature and tensile force on the resistance of steel wires was thoroughly investigated. Reliability tests were conducted on the temperature compensation probe, along with salt spray corrosion tests on the corrosion sensor. The research results demonstrated that, compared to the temperature sensor, temperature compensation probe can better reflect the actual temperature of the corrosion sensor and provide effective temperature compensation for the corrosion sensor. Moreover, the developed corrosion sensor can effectively reflect the mass loss rate of the corrosion probe. The sensor is capable of detecting a corrosion level as low as 0.02 % of the complete steel wire mass, which corresponds to an average corrosion depth of 0.412 μm.

Compensation of temperature effects in force-balanced microelectromechanical system accelerometers

The reduction of temperature effect is crucial for high-precision MEMS accelerometers. This study presents an automatic real-time compensation method for reducing the temperature effect on the scale factor of force-balanced MEMS accelerometers. Thermistors with negative temperature coefficient are connected in series to the circuit for counteracting the thermal responses of the accelerometers. The compensation system is theoretically analysed, predicting an optimal working temperature with zero-temperature coefficient that agrees with the experimental results with a confidence level of 99.73 %. The temperature effect on the scale factor is reduced from 419 ppm/°C to ±8 ppm/°C at the working temperature with a variation of ±0.5 °C. Compared with other works, the proposed method has advantages on simplified procedures, high efficiency and improved resource utilization, which is promising to large-scale applications in industrial sensors.

Head surface strain measurement based wireless bolt sensor with self temperature compensating

Bolt loosening detection is crucial for ensuring the safe operation of equipment. Loosened bolts are hard to detect, and if left undetected, it can lead to catastrophic failures, especially for numerous bolts in large-scale structures. Therefore, the development of distributed bolt monitoring method and related sensors is highly necessary. In this paper, a novel bolt preload sensor with self-temperature compensation is proposed, based on the strain distribution of the bolt head end face. This study enhances previous research by conducting a detailed analysis of strain distribution at the edge of the bolt head surface. The finite element analysis results show that the bolt preload has almost no effect on the circumferential strain in the edge region of bolt head surface. Based on this feature, the strain gauge is applied circumferentially along the edge of the bolt head face as a temperature compensation gauge. In this way, the measuring strain gauge and the temperature compensation gauge can be integrated on the surface of the bolt head, thus achieving self-temperature compensation for the sensor. An experimental device has been established and the experimental results show that the designed sensor has excellent linearity to the bolt preload and effective temperature compensation. For the monitoring of numerous bolts with a wide distribution, a wireless sensing network utilizing the proposed sensor has been designed. The proposed wireless bolt sensor is easy to install and replace, without redesigning or changing the existing structure, thus providing a simple and effective way to monitor large number of bolts with wide distribution.

A Miniature Liquid Flowmeter Using All-Fiber Fabry–Perot Cavity for Real-Time Measurement

A miniature and highly sensitive fiber-optic liquid flowmeter based on Fabry–Perot interferometry (FPI) is proposed and demonstrated for fluid-flow micro-channel testing. The diaphragm deformation and pressure of the proposed sensor for flow rate detection are obtained from numerical and finite element method simulations of the theoretical model. The FPI flowmeter can be applied in real time to measure the ultra-wide dynamic range from 0 mL/min to 90 mL/min, with a response time of hundreds of milliseconds, controlling the flow rate with a resolution of 1.08 mL/min, which is 1.2% of the full scale. The quadratic functional relation between dip wavelength shifts and flow rates is verified by the flow calibration curves of the FPI flowmeter under dynamic pressure conditions. In addition, the effective temperature compensation is realized by connecting an FBG temperature sensor for variable temperature flow detection, and the measured error is reduced by nearly 25-times. The proposed sensor has the potential to measure the liquid flow rate in various applications.

The temperature effects on embedded PZT signals in structural health monitoring for composite structures with different thicknesses

Ultrasonics guided waves (GWs) are established as an effective structural health monitoring technique for detecting damage in composite structures. However, for GWs to be applied reliably in service, the effect of temperature needs to be accounted for baseline damage detection approaches. Previous studies have focused on developing temperature compensation methods for surface-mounted transducers. In this paper, an extensive investigation has been carried out to develop an effective temperature compensation method for GWs generated by embedded transducers in different thickness composites. To accomplish this, Laser Doppler Vibrometer experiments were carried out to obtain wavenumbers generated by embedded transducers and to compare them against surface mounted cases. The consistent trend observation of dispersion curves between surface-mounted and embedded PZTs serves as a foundation for conducting analysis of the embedded signals with the effect of temperature. Following that, GW propagation has been studied in three quasi-isotropic composites of 2 mm, 4 mm and 9 mm thicknesses. Based on the established temperature database with measurements from − 50 °C to 70 °C, a temperature compensation methodology has been developed and validated with the temperature difference of 30 °C. It demonstrates that the temperature effect on the embedded PZTs is lower in comparison to surface mounted PZTs, and the temperature compensation of a single thickness composite is scalable to other panels thickness. This novel methodology proves beneficial in reducing the scale of the experimental campaign required, which holds significant value for actual aeronautical structures characterized by variable composite thicknesses across different sections, such as in fuselage panels or wing boxes.

Temperature Compensation of Wind Tunnel Balance Signal Detection System Based on IGWO-ELM.

The wind tunnel balance signal detection system is widely employed in aerospace applications for the accurate and automated measurement of aerodynamic forces and moments. However, measurement errors arise under different environmental temperature. This paper addresses the issue of measurement accuracy under different temperature conditions by proposing a temperature compensation method based on an improved gray wolf optimization (IGWO) algorithm and optimized extreme learning machine (ELM). The IGWO algorithm is enhanced by improving the initial population position, convergence factor, and iteration weights of the gray wolf optimization algorithm. Subsequently, the IGWO algorithm is employed to determine the optimal network parameters for the ELM. The calibration decoupling experiment and high-low temperature experiment are designed and carried out. On this basis, ELM, GWO-ELM, PSO-ELM, GWO-RBFNN and IGWO-ELM are used for temperature compensation experiments. The experimental results show that IGWO-ELM has a good temperature compensation effect, reducing the measurement error from 20%FS to within 0.04%FS. Consequently, the accuracy and stability of the wind tunnel balance signal detection system under different temperature environments are enhanced.

Improving the Electro-Optical Deflection Performance of KTN Crystals Based on the Temperature Compensation Effect

The laser deflector is a crucial device used to change the direction of light beam propagation in various fields, including lithography, lidar, and scanning. In this paper, we conduct a systematic study of two KTa(1–x)NbxO3 (KTN) crystals that use different physical deflection mechanisms. We analyze their dielectric properties, entropy, domain structure, and deflection performance. We also address the drawback of the small deflection angle of the compositional gradient KTN deflector crystal by proposing a new temperature-compensated temperature control strategy to improve its deflection performance. The gradient temperature control mechanism maximizes the dielectric constant in different regions of the KTN crystals, leading to a threefold (10.67 mrad) increase in deflection angle compared to conventional uniform temperature control equipment. This optimized temperature control mechanism can significantly enhance the practical application of KTN crystals, providing a new avenue for achieving a large deflection angle beam deflector.

An enhanced approach for damage detection using the electromechanical impedance with temperature effects compensation

An enhanced approach for damage detection using the electromechanical impedance with temperature effects compensation

Experimental characterization, modelling and compensation of temperature effects in optotunable lenses

Most tunable lenses (TLs) are affected by deviations in optical power induced by external temperature changes or due to internal heating while in use. This study proposes: (1) An experimental characterization method to evaluate the magnitude of the optical power deviations due to internal temperature shifts; (2) three different mathematical models (experimental, polynomial, and optimized) to describe the response of the lens with temperature; (3) predictions of the internal temperature shifts while using the lens in time frames of minutes, seconds, and milliseconds and; (4) a real time optical power compensation tool based on the implementation of the models on a custom voltage electronic driver. The compensation methods were successfully applied to two TL samples in static and dynamic experiments and in hysteresis cycles. After 40 min at a static nominal power of 5 diopters (dpt), the internal temperature exponentially increased by 17 °C, producing an optical power deviation of 1.0 dpt (1.5 dpt when the lens cools down), representing a 20% distortion for heating and 30% for cooling. Modelling and compensation reduced the deviations to 0.2 dpt when heating (0.35 dpt when cooling) and the distortions to 4% and 7%. Similar levels of improvement were obtained in dynamic and hysteresis experiments. Compensation reduced temperature effects by more than 75%, representing a significant improvement in the performance of the lens.

Research on Temperature Compensation of Optical Fiber MEMS Pressure Sensor Based on Conversion Method

The characteristics of optical fiber MEMS pressure sensors are easily affected by temperature, so effective temperature compensation can improve the accuracy of the sensor. In this paper, the temperature characteristics of optical fiber MEMS pressure sensors are studied, and a temperature compensation method by converting the wavelength is proposed. The influence of target temperature and data point selection on the compensation effect is studied, and the effectiveness of the method is verified by the temperature compensation of sensors before and after aging. When the converted target temperature is 25 °C, the pressure measurement accuracy of the sensor is improved from 1.98% F.S. to 0.38% F.S. within the range of 5–45 and 0–4 MPa. The method proposed in this paper can not only improve the accuracy but also make the regular calibration more operable.

Simulation study of a temperature-calibrated double-sided polished optical fiber SPR refractive index sensor.

The temperature of the environment directly affects the accuracy of refractive index (RI) measurement. Therefore, we propose a double-sided polished surface plasmon resonance (SPR) RI fiber sensor, which is available for simultaneous measurement of the RI and temperature in real time. The proposed sensor uses single-mode fiber as a special double-sided polishing structure. The double-sided polishing regions are coated with a gold-silver hybrid film; one side is additionally coated with graphene layers to increase detection sensitivity, and the other side is coated with polydimethylsiloxane on the metal layer for temperature sensing. The simulation result shows that in the range from 1.33 to 1.35, RI sensitivity reaches as high as 2600nm/RIU. In the range from 15°C to 85°C, temperature sensitivity reaches as high as -3.5n m/∘ C. The full width at half maximum is 65nm. Compared with previous studies, the sensitivity is slightly improved, and an excellent temperature compensation effect can be achieved. It is suitable for high-precision measurement of the environment and biochemical aspects.

Temperature compensation methods of spin-exchange relaxation-free co-magnetometer

According to the temperature characteristics of spin-free exchange relaxation (SERF) co-magnetometer, three temperature compensation methods are proposed in this paper, including particle swarm optimization radial basis function (PSO-RBF) neural network, Gaussian regression and least squares support vector basis. The effectiveness of the three compensation methods is verified by experiments and compared with the back-propagation (BP) neural network optimized by a genetic algorithm compensation method. In order to improve the effect of temperature compensation, this paper also conducts correlation and cluster analysis on the different positions temperature and output signals of the SERF co-magnetometer, and selects the data of temperature points that are closely related to signal bias changes for model training. Through experimental comparison with traditional linear compensation and BP neural network compensation methods, it is found that PSO-RBF neural network has advantages in training speed, compensation accuracy and robustness. Experiments show that PSO-RBF neural network temperature compensation algorithm improves the stability of the SERF co-magnetometer by more than 53 at room temperature or under artificially imposed temperature changes.

Design of ring oscillator with temperature compensation effect

In this article, a ring oscillator with Temperature Compensation Effect is proposed in 0.18 μm CMOS. The ring oscillator is composed of 31 stages of inverters in series. The change in ambient temperature will cause the oscillator frequency to deviate. Therefore, this research uses a voltage circuit with a positive temperature coefficient as the power supply for the oscillator circuit, so that the ring oscillator can output stable oscillation center frequency regardless of ambient temperature. The ring oscillator has been verified by simulation and experimental testing. The ambient temperature is within the range of −40°C to 80°C. The output frequency of the ring oscillator is stable at 33 kHz ± 0.50 kHz. The frequency error is within 1.6%. Temperature stability was 120 ppm/°C. At 1 MHz off the carrier, the phase noise is as low as −151.2 dBc/Hz and the total power dissipation is 210 μW. Compared with the previous scheme, the chip area and power consumption are lower. This circuit module can provide a clock signal for the timer when the UWB chip sleeps.

Thermal airflow sensor design and temperature compensation research based on the thermostatic method

PurposeThis paper aims to solve the typical thermal airflow sensor's high power consumption and integration difficulties, based on the FS5 thermal element and constant temperature measurement method, a flow sensor is developed with high measurement accuracy, low power consumption, small size, low cost and easy system integration.Design/methodology/approachA small wind tunnel was used to test and assess the sensor's measurement range, reaction time, stability, repeatability, measurement accuracy and multi-temperature calibration was performed in the temperature range of −10°C to 30°C. The effect of ambient temperature on the sensor's measurement data is investigated, and the coefficient correction method of power function was investigated to implement the sensor's software temperature compensation function.FindingsThe results show that the sensor is stable and repeatable, the output voltage has a power function relationship with the airflow rate, the flow rate measurement range is 0–18 m/s, the response time is less than 3 s, the measurement accuracy at high flow rates is within 0.4 m/s and the temperature-corrected airflow rate measurement error is less than 5%. Setting the temperature calibration interval to 2°C and 5°C has the same temperature compensation effect, reducing the sensor's calibration effort significantly.Originality/valueThis paper demonstrates that a thermostatic method is used to construct a thermal wind speed sensor that delivers accurate measurements in the wind speed measuring range of 0–18 m/s under test conditions. In addition, the sensor's performance is evaluated, and calibration tests for a wide range of temperatures are done. Finally, based on the power function correction method, a temperature compensation algorithm is proposed.

Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability

Global fluctuations in annual land carbon uptake (NEEIAV) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, we quantify regional and seasonal contributions to the correlations of globally-averaged NEEIAV against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEEIAV, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEEIAV and discuss their implications for future carbon–climate feedbacks.

A heat balance model of zinc pot and its application

In this paper, the problem of stripe temperature at the entrance of the zinc pot is addressed in a novel way. Based on in-depth analysis of thermal features of hot-dip galvanization, a generalized heat-balance mode has been established that has wider adaptivity within the production lines. The relationship between the pot load, the galvanization load and the productivity has been re-characterized by introducing a new concept of line-area ratio. Subsequently, the stripe temperature can be estimated based on the model. The effectiveness of the proposed model has been verified by real-time application to the production lines with temperature estimation error within ± 3 °C. As such, effective temperature compensation can be implemented that significantly improves the galvanization quality.

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C.