Temperature Compensation Method Research Articles

Sliding Window Dynamic Time-Series Warping-Based Ultrasonic Guided Wave Temperature Compensation and Defect Monitoring Method for Turnout Rail Foot.

Temperature changes are a major challenge in outdoor guided wave structural health monitoring of rails. Temperature variations greatly impact the waveform of guided wave signals, making it challenging to diagnose and characterize defects. Traditional temperature compensation methods, such as signal stretch and scale transform, are restricted to use in regular structures, such as plates and pipes. To solve the temperature compensation problem in long rails with serious mode conversion and complex structure echo, we propose a temperature compensation and defect monitoring method, namely, sliding window dynamic time-series warping (SWDTW), which overcomes the challenges of mass computation and overcompensation of dynamic time-series warping (DTW). The basic idea of SWDTW is to utilize sliding windows to accelerate the computation and identify defects from subsequence scales. Then, an index, window subsequence Teager energy (WSTE), is used to indicate the local abnormality of guided wave signals, and a sliding window net (SWnet) is devised to monitor the occurrence of defects automatically. Outdoor monitoring of turnout rails showed that the proposed method can effectively reduce the temperature noise and recognize an artificial defect with 1.16% and 0.36% cross-sectional change rates (CSCRs) on the switch and stock rails, respectively, at different temperatures; moreover, the defect signals processed by SWDTW showed better defect identification performance than those processed by scale transform and DTW.

Fiber Bragg Grating Array for Shape Reconstruction in Structural Elements.

This paper presents the development, analysis and application of a fiber Bragg grating (FBG) array for two-dimensional (2D) shape reconstruction in a cantilever beam. The structural elements made of Pinus wood and Nylon 6.0 were numerically analyzed using the finite element method for the strain distribution when constant loading is applied at the free end of the beam. In addition, the temperature compensation method is proposed to decouple the temperature cross-sensitivity in the deflection analysis. In this case, the temperature sensitivities of all sensing elements of the 5-FBG array were obtained. An additional FBG was encapsulated in a silicone mold for increased sensitivity and positioned in the clamping point in which deflection was negligible. Temperature compensation was achieved considering the temperature measured by the silicone-embedded FBG (sensitivity of 27.78 pm/°C) and the sensitivity of all five FBGs of the deflection-sensing array (9.14 pm/°C ± 0.33 pm/°C). In the deflection experiments, the sensors presented a high linearity, in which a determination coefficient (R2) higher than 0.995 was obtained in all of the analyzed cases. Furthermore, the 2D shape construction using the proposed sensor approach resulted in the elastic line estimation for all analyzed beams, where the experimental results were in agreement with the theoretical and numerical analysis with a R2 higher than 0.99 in all of the analyzed cases. Therefore, the proposed sensor array is a feasible approach for real-time shape reconstruction of structural elements with the advantages related to the possibility of direct embedment in the measured structure.

Energy Saving Control of District Heating System Based on MATLAB

In order to offset the lag and delay in the heating process and solve the problem of excessive heating in the heating season, an energy-saving control method of district heating system based on MATLAB is proposed. Based on MATLAB/SIMULINK software, the simulation model of district heating system is established to study its dynamic characteristics. The short-term load forecasting method is introduced to guide the system to conduct centralized regulation and observe the dynamic response of indoor temperature and operating energy consumption. Compared with the constant water supply temperature and the outdoor temperature compensation method, the results show that the proposed method can reduce the indoor temperature fluctuation range to 20 ± 1°C, and the energy saving rate of the whole heating season can reach 14.5% compared with the conventional regulation method.

Research on Temperature Compensation of Multi-Channel Pressure Scanner Based on an Improved Cuckoo Search Optimizing a BP Neural Network.

A multi-channel pressure scanner is an essential tool for measuring and acquiring various pressure parameters in aerospace applications. It is important to note, however, that the pressure sensor of each of these channels will drift significantly with the increase in the temperature range of the pressure measurement, and the output voltage of each of these channels will show nonlinear characteristics, which will constrain the improvements in the accuracy of the measurement. In the regression fitting process, it is difficult to fit nonlinear data with the traditional least-squares method, which leaves pressure measurement accuracy unsatisfactory. A temperature compensation method based on an improved cuckoo search optimizing a BP neural network for a multi-channel pressure scanner is proposed in this paper to improve pressure measurement accuracy in a wide temperature range. Using the chaotic simplex algorithm, we first improved the cuckoo search algorithm, then optimized the connection weights and thresholds of the BP neural network, and finally constructed an experimental calibration system to investigate the temperature compensation of the multi-channel pressure scanning valves in the −40 °C to 60 °C temperature range. The compensation test results show that the algorithm has a better compensation effect and is more suitable for the temperature compensation of multi-channel pressure scanners than the traditional least-squares method and the standard RBF and BP neural networks. The maximum full-scale error of all 32 channels is 0.02% FS (full-scale error) and below, which realizes its high-accuracy multi-point pressure measurement in a wide temperature range.

An FBG-Based 3-DOF Force Sensor With Simplified Structure for Retinal Microsurgery

Retinal microsurgery, which requires surgeons to perform precise operations on delicate tissue in a tiny eye, is considered one of the most technically demanding operations. Lack of force perception is one of the major problems faced during retinal microsurgery. In order to solve the problem of lack of force sensing, many 3 degree of freedom (DOF) force sensing instruments have been developed. However, they all adopt complex structures, and the accuracy of axial force still has room for improvement. In this paper, we presented a 3-DOF force sensor based on fiber Bragg grating (FBG) sensors for retinal microsurgery. An improved FBG configuration which simplifies the structure of the force sensor and the corresponding temperature compensation method was designed. Two optical fibers with single FBG sensor and an optical fiber with dual FBG sensors are longitudinally attached along the grooves of a stainless steel tube. The calibration method used in the force sensor is a combination of linear calibration method and the least squares support vector regression (LSSVR), which can effectively reduce the influence of linear and nonlinear errors. The results of calibration experiment demonstrate that the hybrid calibration method has better accuracy than using linear or nonlinear method alone. Verification experiment and temperature compensation experiment show that the 3-DOF force sensor proposed has the ability to provide accurate and stable estimation of 3 dimensional forces in a temperature changing environment.

태양광모듈의 전력 측정 개선을 위한 온도 보정법에 대한 연구

Nowadays, solar energy is major energy source. New amount of solar system installation are estimated as about 200GW globally in 2021. Solar module has each original IV characteristics by the types of products. These informations contain Voc, Isc, Vmp, Imp, Pmax, F.F, Rs, Rsh and etc. These information reveal us voltage, current, power, resistance of PV module. Thus, precise measurement of IV characteristics of PV module is important for quality control, performance evaluation, and safety enhancement. In this paper, temperature compensation method is applied to PV module IV characteristics curve measurement under continuous solar simulator condition. These improved IV measurement method will attribute IV measurements of PV module easily and precisely.

A Temperature Compensation Method for aSix-Axis Force/Torque Sensor Utilizing Ensemble hWOA-LSSVM Based on Improved Trimmed Bagging.

The performance of a six-axis force/torque sensor (F/T sensor) severely decreased when working in an extreme environment due to its sensitivity to ambient temperature. This paper puts forward an ensemble temperature compensation method based on the whale optimization algorithm (WOA) tuning the least-square support vector machine (LSSVM) and trimmed bagging. To be specific, the stimulated annealing algorithm (SA) was hybridized to the WOA to solve the local entrapment problem, and an adaptive trimming strategy is proposed to obtain the optimal trim portion for the trimmed bagging. In addition, inverse quote error (invQE) and cross-validation are employed to estimate the fitness better in training process. The maximum absolute measurement error caused by temperature decreased from to of full scale after being compensated by the proposed method. The analyses of experiments illustrate the ensemble hWOA-LSSVM based on improved trimmed bagging improves the precision and stability of F/T sensors and possesses the strengths of local search ability and better adaptability.

High-accuracy ultrasonic method for in-situ monitoring of oil film thickness in a thrust bearing

The ultrasonic method has been widely applied to measure the oil film thickness – a critical variable that reflects lubrication conditions. However, due to the thermal dependence of ultrasonic signals, significant deviations in film thickness measurements are introduced, hindering the in-situ application of the ultrasonic technique. To address this issue, a real-time temperature compensation method that can accurately obtain the frequency domain information of the reference signal is proposed. Specifically, the reflection from the substrate-coating interface compensates for the thermal effect on the phase increment and amplitude attenuation – this is noted as “self-calibration”. An extra experimental test with a substrate-coating-air structure is performed to calibrate the thermal effect on the coating-induced phase shift – this part is denoted as “pre-calibration”. The combination of “self-calibration” and “pre-calibration” enables the overall temperature compensation strategy. After the effectiveness validation with a temperature-controlled experiment, the proposed method is implemented in a thrust bearing in a heavy-duty hydropower generator with full running conditions, including loading and unloading, normal speed and shut-down. The largely ranged oil film thickness (3–330 μm) is ultrasonically measured and compared with the theoretical value, showing a higher measurement accuracy than the eddy current method.

Application of Temperature Compensation Combined with Neural Network in Infrared Gas Sensor

Due to the state of the gas to be measured, the detection mechanism of the pyroelectric detector and the temperature drift of the peripheral circuit components and the detection of the ambient temperature will interfere with the measurement accuracy of the nondispersive infrared gas sensor from many aspects. This paper proposes a temperature compensation method based on the BP neural network. The compensation function of the gas sensor is realized by programming the various functional parameters in the neural network through the program provided in the Matlab neural network toolbox. Experimental simulation results show that the proposed method effectively reduces the influence of external temperature on the gas sensor output and improves its accuracy and stability.

A dual LC resonant circuit integrated wireless passive force and temperature sensor for harsh-environment applications

This paper proposes a dual inductor-capacitor (LC) circuit integrated wireless and passive force and temperature sensor for the simultaneous measurement of force and temperature in high-temperature environments. The sensor is fabricated by a two-step process: the preparation of the Al2O3 substrate and the fabrication of the dual LC sensor with Ag paste using screen-printing technology and metallization. The variation in ambient force and temperature can be detected wirelessly by extracting the resonant frequencies of the antenna. The sensor can work in the force range of 0–10 N and temperature range of 25–500 °C with a maximum force sensitivity of 107 kHz/N at 500 °C and temperature sensitivity of 21.7 kHz/°C. To precisely measure the force, the temperature compensation method is proposed. The sensor has the advantages of low cost, simple fabrication and test, and high stability and repeatability, which are promising for the force and temperature application on the engine turbine blade in high-temperature environments.

A data processing method on infrared temperature measurement of non-lambert body in a non-uniform environment

Ambient temperature is one of the most important factors influencing the accuracy of infrared temperature measurement when detecting temperatures near the ambient ones. Starting from the classical ambient temperature compensation method, a data processing method on the infrared temperature measurement of a non-lambert body in a non-uniform environment is proposed. Experiments were conducted to compare the temperature measurement accuracy of the classical method and the one proposed in this paper, in a non-uniform environment. Data processing of the experiments involves parameters fitting, object emissivity measurement, and measurement of each temperature source in the environment. The experiments demonstrated the effectiveness of the proposed method, which can effectively solve the ambient interference problems when the non-lambert body (such as aluminum and steel) are present.

Experimental and numerical study on the laminar burning velocities of n-decane/toluene/air mixtures at elevated temperatures

The laminar burning velocities (LBVs) of n-decane/toluene/air mixtures were measured at elevated temperatures using externally heated diverging channel (EHDC) method. The effects of initial temperature (up to 650 K), toluene blending ratio (RC7H8 = 0 to 1.0 by liquid volume) and equivalence ratio (ϕ = 0.6 to 1.4) on the LBVs of n-decane/toluene/air mixtures have been investigated. Numerical computation with a detailed reaction mechanism was used to further analyze the effects of potential interactions between n-decane and toluene. It was observed that the LBVs of n-decane/toluene/air mixtures increase with the increase of initial temperature, while the LBVs decrease with the increase of toluene blending ratio. The effects of toluene on the LBVs through chemical reactions, heat and mass transfer were analyzed in detail. Moreover, the temperature compensation method, which separates the effect of adiabatic flame temperature and contribution from chemical and disunion, was used in analysis. The effects of the toluene blending on the LBV is mainly attributed to chemical term, and the thermal effect have a second order importance. The reaction pathways and sensitivity analysis show that the LBVs of stoichiometric mixtures is less sensitive to kinetic coupling. The distinct flame propagation properties of the n-decane/toluene blended fuels are determined by the distributions of reaction rates of the crucial intermediate species and radicals.

Temperature variation compensated damage classification and localisation in ultrasonic guided wave SHM using self-learnt features and Gaussian mixture models

Conventional damage localisation algorithms used in ultrasonic guided wave-based structural health monitoring (GW-SHM) rely on physics-defined features of GW signals. In addition to requiring domain knowledge of the interaction of various GW modes with various types of damages, they also suffer from errors due to variations in environmental and operating conditions (EOCs) in practical use cases. While several machine learning tools have been reported for EOC compensation, they need to be custom-designed for each combination of damage and structure due to their dependence on physics-defined feature extraction. In this work, we propose a convolutional neural network (CNN)-based automated feature extraction framework coupled with Gaussian mixture model (GMM) based temperature compensation and damage classification and localisation method. Features learnt by the CNNs are used for damage classification and localisation of damage by modelling the probability distribution of the features using GMMs. The Kullback–Leibler (KL) divergence of these GMMs with respect to corresponding baseline GMMs are used as signal difference coefficients to compute damage indices (DIs) along various GW sensor paths, and thus for damage localisation. The efficacy of the proposed method is demonstrated using FE generated GW-data for an aluminium plate with a network of six lead zirconate titanate (PZT) sensors, for three different types of damages (rivet hole, added mass, notch) at various temperatures (from 0 ∘C to 100 ∘C), with added white noise and pink noise to incorporate errors due to EOCs. We also present experimental validation of the method through characterisation of notch damage in an aluminium panel under varying and non-uniform temperature profiles, using a portable custom-designed field programmable gate array based signal transduction and data acquisition system. We demonstrate that the method outperforms conventional temperature compensation method using GMM with physics-defined features for damage localisation in GW-SHM systems prone to EOC variations.

Establishment and optimization of temperature compensation model for benzoic acid detection based on terahertz metamaterial

To regulate the use of food additives is of great significance to human health, for the excessive use of food additives can cause damage to human body so serious as organ failure and even cancers. Benzoic acid (BA) is a widely used food preservative, and it is of great importance to achieve high-sensitive detection of it. Conventional THz detection method can obtain the fingerprint spectrum of the sample in the terahertz band, it can only detect a sample to be detected at a milligram level, and it is not suitable for the micro or trace analysis of the sample. In this paper, an enhanced terahertz (THz) micro-nano structure of metamaterial based on electromagnetic theory was designed to achieve enhanced detection of benzoic acid additives by THz technology. THz spectroscopy is more sensitive to temperature changes than other spectroscopic detection techniques, so it is particularly important to find out a method of spectral temperature compensation to minimize the inference caused by temperature variations in the detection of samples with variable temperature. To this end, based on the enhanced technology of THz metamaterial, an optimized compensation method for external temperature variations was explored in this paper. Firstly, the THz spectra of seven samples with different concentrations under six different temperatures were collected. Secondly, smoothing and baseline correction methods were used to preprocess the spectra to study the better spectral pretreatment methods. To reduce the influence of the change of external temperature on the detection, the External Parameter Orthogonalization (EPO) and Generalized Least Squares Weighting (GLSW) methods were introduced to compensate the temperature change. These two aforementioned methods were compared with the method without temperature compensation, respectively. Then, Uninformative Variable Elimination (UVE), principal component analysis (PCA),successive projections algorithm (SPA) and Competitive Adaptive Reweighted Sampling (CARS) were used to explore the optimal terahertz band selection method. Finally, Partial Least Squares (PLS) and Least square support vector machine (LS-SVM) models were established, respectively, to realize the enhanced detection of benzoic acid additives. The LS-SVM model combined with SPA and GLSW has the best effect, with the Rp2 of 0.9892, the RMSEP of 3.8412 × 10−5 and the LOD of 1.158 × 10−4 g/mL. The LOD of the model is nearly three times higher than that of the mixed global model. The results show that the GLSW method exhibited a better compensation effect on the THz spectra of benzoic acid solution samples at different temperatures. Therefore, this study can be applied to other temperature-compensated models and can also provide reference for the detection of samples with variable temperature.

On-machine measurement and temperature compensation method of NURBS surface interpolation for semicircular narrow neck thickness based on ultra-precision machine tool

Flexible joint is a typical low-rigidity micro part, which has four narrow neck structures evenly distributed around its central axis. In the ultra-precision machining process, it is crucial to control the dimensional accuracy of the narrow necks to improve stiffness consistency. However, the limited space of the neck structures and the high accuracy requirements bring extremely difficulties to the measuring process. In this paper, a novel on-machine measurement method for the semicircular narrow necks was presented and a measuring device was developed based on the combination of high linearity incremental measurement method and on-machine measurement technology. Moreover, the uncertainty of measurement error was analyzed in detail. In view of the measurement error caused by temperature drift, a compensation method based on non-uniform rational B-spline surface interpolation was used to enhance the measurement accuracy. The experimental results showed that the measurement accuracy enhanced over 30% after compensation, which met the measuring requirement of flexible joint.

Cold Starting Temperature Drift Modeling and Compensation of Micro-Accelerometer Based on High-Order Fourier Transform.

The traditional temperature modeling method is based on the full heating of the accelerometer to achieve thermal balance, which is not suitable for the cold start-up phase of the micro-accelerometer. For decreasing the complex temperature drift of the cold start-up phase, a new temperature compensation method based on a high-order Fourier transform combined model is proposed. The system structure and repeatability test of the micro digital quartz flexible accelerometer are provided at first. Additionally, we analyzed where the complex temperature drift of the cold start-up phase comes from based on the system structure and repeatability test. Secondly, a high-order temperature compensation model combined with K-means clustering and the symbiotic organisms search (SOS) algorithm is established with repeatability test data as training data. To verify the proposed temperature compensation model, a test platform was built to transmit the measured values before and after compensation with the proposed Fourier-related model and the other time-related model, which is also a model aiming at temperature compensation in the cold start-up phase. The experimental results indicate that the proposed method achieves better compensation accuracy compared with the traditional temperature compensation methods and the time-related compensation model. Furthermore, the compensation for the cold start-up phase has no effect on the original accuracy over the whole temperature range. The stability of the accelerometer can be significantly improved to about 30 μg in the start-up phase of different temperatures after compensation.

Temperature Compensation of an Eddy-Current Displacement Sensor Using an Improved Sparrow Search Algorithm Method

Eddy-current displacement sensor (ECS) has been applied widely to the production of modern industry by reason of its characteristics of high sensitivity, good reliability, powerful anti-interference capacity, and noncontact measurement. However, it cannot be used when severe temperature drift occurs at high temperature. Some traditional compensation methods are difficult to achieve good performance with neglecting the nonlinearity. Hence, it is essential to propose a better method for temperature compensation. A novel temperature compensation approach for ECS problem using an improved sparrow search algorithm (ISSA) and radial basis function neural network (RBFNN) is proposed in this article. In the ISSA, a chaos strategy is introduced in the algorithm for avoiding local optimal point, and an elite opposition-based learning strategy is integrated to promote global search ability of ISSA with high efficiency. RBFNN is elected to model the temperature drift, and its parameters are determined by the proposed ISSA. The proposed method compensates the significant deterministic errors caused by temperature variation within a wide temperature range. The experimental schemes were designed to the effectiveness of the proposed method according to data fusion technology. The various test results obtained confirm the potential and effectiveness of the proposed approach compared to some other traditional temperature compensation methods presented in the literatures.

A High Reliability Damage Imaging Method Under Environmental Temperature Variations

Abstract In Lamb wave-based structural health monitoring (SHM), the environmental temperature variations can easily affect Lamb wave monitoring signals and seriously reduce the reliability of final damage detection results. To resolve the temperature effect problem, a temperature compensation method of improved baseline signal stretch (IBSS) is presented and applied for high reliability damage imaging under large environmental temperature variations in this paper. After the basic principle of IBSS is analyzed, the realization of IBSS is discussed. Then, a IBSS-based high reliability damage imaging method under temperature variation situation is developed. An experimental study is finally arranged.

Gas Flow Measurement Method with Temperature Compensation for a Quasi-Isothermal Cavity

Pneumatic transmission is a technology that uses compressed air as a power source to drive and control various mechanical equipment to realize the mechanization and automation of production processes. With the development of industrial mechanization and automation, pneumatic technology, represented by pneumatic muscle, is increasingly becoming more widely used in various fields. The current standards for research are more complex for the measurement of flow without a flowmeter, some of them do not consider the influence of temperature change on flow measurement, and some of them are simplified as adiabatic or isothermal models, which are inaccurate measurement methods in actual practical application. This paper describes a method to determine flow rate by measuring the pressure change in the process of gas tank inflation. This study used the method of temperature compensation to eliminate the influence of temperature in the isothermal formula. The measurement structure was simple and the calculation was accurate, which has a certain practical significance. Based on this method, charging experiments were carried out with a gas tank that had a volume of 3 L or 5 L with or without copper wire filling, and the experimental results were used in the processed research. The temperature compensation parameters were identified with or without an isothermal environment and in different sizes of tanks. This method identified the different parameters of the 5 L tank and 3 L tank. Finally, the flow compensation was completed for the gas tank filled with copper wire. After verification, the results of the quasi-isothermal calculation formula and temperature compensation formula were close to those measured by a high-precision flow sensor in the experiment. The method introduced in this study is a novel flow calculation method that is simple in structure and accurate in calculation compared with the conventional isothermal calculation method; furthermore, it can be used in real world situations without the need for a high-precision flow sensor.

A CMOS bandgap reference based on switched capacitor with temperature compensation method

A CMOS bandgap reference based on switched capacitor with temperature compensation method