Temperature Compensation Technique Research Articles

Enhancing Open-Space Gas Detection Limit: A Novel Environmentally Adaptive Infrared Temperature Prediction Method for Uncooled Spectroscopy

Gas cloud imaging with uncooled infrared spectroscopy is influenced by ambient temperature, complicating the quantitative detection of gas concentrations in open environments. To solve the aforementioned challenges, the paper analyzes the main factors influencing detection errors in uncooled infrared spectroscopy gas cloud imaging and proposes a temperature correction method to address them. Firstly, to mitigate the environmental effects on the radiative temperature output of uncooled infrared detectors, a snapshot-based, multi-band infrared temperature compensation algorithm incorporating environmental awareness was developed. This algorithm enables precise infrared radiation prediction across a wide operating temperature range. Validation tests conducted over the full temperature range of 0 °C to 80 °C demonstrated that the prediction error was maintained within ±0.96 °C. Subsequently, temperature compensation techniques were integrated, resulting in the development of a comprehensive uncooled infrared spectroscopy gas cloud imaging detection method. Ultimately, the detection limits for SF6, ethylene, cyclohexane, and ammonia were enhanced by 50%, 33%, 25%, and 67%, respectively.

Temperature Compensation Method for Tunnel Magnetoresistance Micro-Magnetic Sensors Through Reference Magnetic Field.

The sensitivity of Tunnel Magnetoresistance (TMR) sensors is characterized by significant temperature drift and poor sensitivity drift repeatability, which severely impairs measurement accuracy. Conventional temperature compensation techniques are often hindered by low compensation precision, inadequate real-time performance, and an inability to effectively address the issue of poor repeatability in temperature drift characteristics. To overcome these challenges, this paper introduces a novel method for suppressing temperature drift in TMR sensors. In this method, an alternating reference magnetic field is applied to TMR sensors, and the output amplitude at the frequency of the reference magnetic field is calculated to compensate the sensitivity temperature drift in real time. Temperature characteristic tests were conducted in a non-magnetic temperature test chamber, and the results revealed that the proposed method significantly reduced the TMR sensitivity drift coefficient from 985.39 ppm/°C to 59.08 ppm/°C. Additionally, the repeatability of sensitivity temperature characteristic curves was enhanced, with a reduction in root mean square error from 0.84 to 0.21. This approach effectively mitigates temperature-induced sensitivity drift without necessitating the use of a temperature sensor, and has the advantages of real-time performance and repeatability, providing a new approach for the high-precision temperature drift suppression of TMR.

A 60–90 GHz Mixer-First Receiver With Adaptive Temperature-Compensation Technique

A 60–90 GHz Mixer-First Receiver With Adaptive Temperature-Compensation Technique

A comparison of temperature compensation methods in a diaphragm-embedded FBG

This paper presents the comparison of temperature compensation techniques for Fiber Bragg Grating (FBG)-based pressure sensor. Such temperature compensation is obtained through a physical assembly using a continuous FBG pair embedded in a rubber diaphragm through a vulcanization method in conjunction with different signal processing methods. The so-called continuous FBG pair is based on two consecutive FBGs (with different Bragg wavelengths) inscribed with physical separation up to 10 mm. The sensor system is tested as a function of temperature and pressure, where the temperature sensitivities of both FBGs are around 50 pm/°C. Pressure estimation errors around 148.22 Pa/°C were observed when this variation in sensitivity was not taken into account by the compensation technique. Furthermore, there is a comparison between techniques that consider the pressure sensitivity variation, namely multiple linear regression using the response of both FBGs and exponential regression using the sum of FBGs. In this case, the exponential regression indicated a smaller temperature cross-sensitivity (3.07 Pa/°C), higher determination coefficient (0.97) and smaller root mean squared error (0.40 kPa). Therefore, the exponential regression using the response of both FBGs is the suitable technique for temperature compensation when the continuous FBG pair embedded in the diaphragm assembly is considered. The results obtained in this work provide a guideline for the development of diaphragm-embedded sensors with temperature compensation and suitable for large-scale production in practical applications.

Non-bridge NTC thermistor anemometer with programmable sensitivity

This paper presents a programmable constant temperature anemometer (CTA) with a voltage control of the negative temperature coefficient (NTC) thermistor's working temperature. The CTA uses a non-bridge regulating circuit, outputting voltage, current and power dissipation signals. Its operation and sensitivity control are tested for NTC temperatures in a 45 to 85°C range, at wind speeds up to 14m/s. The power sensitivity at 25m/s is improved by NTC temperature increase, estimated to be 6.74mW/(m∙s−1) at 85°C. A qualitative analysis of circuit's stability is derived, providing the guidelines for bandwidth optimization. The NTC's resistance is regulated with error of 0.9% for working temperatures over 60°C. The demonstrated programmability of NTC temperature allows for implementation of known temperature compensation and measurement techniques utilizing a single sensor, while permitting continuous sensitivity control. This makes it suitable for measurements with varying ambient conditions.

An Optimized Temperature Compensated Ring Oscillator with Low Power Consumption and Low Variation

In this paper a low power ring oscillator with three differential delay stages and one output buffer stage is designed for Radio Frequency Identification (RFID) applications. The proposed oscillator is designed with neural network model and its parameters are optimized with Teaching–Learning Based Optimization (TLBO) algorithm. The central frequency of the oscillator becomes independent of the temperature with the help of two temperature compensation techniques. In the first technique, the PMOS load transistor of each stage is connected to the NMOS diode connected - in series - transistor. Since these two transistors work in complement of each other, the temperature variation of each stage’s output voltage is decreased. In the second technique, the current variation of oscillator stages versus temperature is reduced since the diode connected transistor is employed in the current source structure. The simulation is done in 0.18 µm Complementary Metal-Oxide Semiconductor (CMOS) technology with the help of Cadence software and the chip area of the layout designed with this software is 19×25 µm2. The designed oscillator exhibits the following parameters: a central frequency of 7.5 MHz, the power dissipation is 238 nW and the frequency deviation is 210 ppm/̊C in the temperature range of 0 to 120ºC, the noise phase and the period jitter are -87.05 dBc/Hz and 0.578 ns (rms), respectively, at 100 KHz offset frequency and 10000 clock cycle.

Real-Time Structural Damage Detection Using EMI under Varying Load a and Temperature Conditions

Structural Health Monitoring (SHM) is a critical aspect of maintaining the safety and integrity of infrastructure. In recent years, there has been a significant shift towards adopting innovative techniques, and one of the most promising methods is Electromechanical Impedance (EMI). EMI involves the utilization of piezoelectric transducers to assess the health of structures in real-time by examining changes in their electrical characteristics. The presence of load causes a change in structural stiffness, which alters the resonant characteristics of the structure. Understanding how external factors like load and temperature influence the electrical impedance of these sensors is essential for its reliable application in damage detection. This article presents an experimental and numerical study to investigate the effects of load and temperature on the electrical impedance of a piezoelectric sensor used in the electromechanical impedance (EMI) technique. The experimental setup uses an impedance analyzer (Agilent 4294A model) to measure the in-situ EMI of piezoelectric wafer active sensors (PWAS) attached to the monitored structure. The numerical model uses ANSYS software to simulate an aluminum beam at varying temperatures. The results show that the load and temperature have a significant effect on the impedance of the transducer. However, it is shown that it is still possible to detect damage using EMI even under varying load and temperature conditions. The results also show that the accuracy of EMI-based damage detection can be improved by using temperature and load compensation techniques.

Elastomagnetic Sensor-Based Long-Term Tension Monitoring of Prestressed Bridge Member with Temperature Compensation

Continuous monitoring of the prestressed members of a bridge under construction using the free cantilever method (FCM) is crucial for ensuring bridge safety. Temperature-sensitive sensors require special considerations as they may misinterpret the signal and tension. Moreover, the unnecessary and inappropriate use of features obtained from the sensor signal can deteriorate the efficiency of the signal and, therefore, tension analysis. This study proposes a tension estimation method using an embedded elastomagnetic (EM) sensor with a temperature-compensation technique. Changes in the signal due to the tension in the temporary steel rods were analyzed using a full-scale test, and the sensor data were acquired for 15 months via the field application. The temperature effect on the signal could be removed by subtracting the tension from the signal using the thermistor data, reducing the error by 91.99% when considering permeability. Additionally, linear regression (LR) and machine learning (ML) algorithms were adopted to predict the tension. Furthermore, the performances of both algorithms were compared using mean absolute error (MAE) and R2. For the prediction using each feature in magnetic hysteresis, LR surpassed ML and the permeability exhibited the highest prediction performance. Meanwhile, predictions using multiple features were attempted to investigate the applicability of ML. Two cases of prediction were performed using ML: on using all the features and the other using three features excluding coercivity, which showed poor relevance to tension. As a result, the performance of the tension prediction was improved significantly compared to the results obtained by LR. In summary, the obtained results have demonstrated that the utilization of selective features of data with temperature compensation techniques could enhance predictive power.

A 54 µW CMOS Auto-Trimming Bandgap References (ATBGR) Achieving 90 dB PSRR for Artificial Intelligence of Things (AIoT) Chips.

An Auto-Trimming CMOS Bandgap References Circuit (ATBGR) with PSRR enhancement circuit for Artificial Intelligence of Things (AIoT) chips is presented in this paper. The ATBGR is designed with a first-order temperature compensation technique providing a stable reference voltage of 1.25 V in the ranges of input voltages from 1.65 V to 4.5 V. An auto-trimming circuit is integrated into a PTAT resistor of BGR to minimize the influences of the process variations. The four parallel resistor pairs with PMOS switches are connected in series with the PTAT resistor. The reference voltage, VREF, is compared to an external constant value, 1.25 V, through an operational amplifier, and the output of the de-multiplexer is used to configure the PMOS switches. High power supply rejection is achieved through a PSRR enhancement circuit constituting a cascaded PMOS common gate pair. The ATBGR circuit is fabricated in 180 nm CMOS technology, consuming an area of 0.03277 mm2. The auto-trimming method yields an average temperature coefficient of 9.99 ppm/°C with temperature ranges from -40 °C to 125 °C, and a power supply rejection ratio of -90 dB at 100 MHz is obtained. The line regulation of the proposed circuit is 0.434%/V with power consumption of 54.12 µW at room temperature.

A Temperature Compensated Voltage Controlled Relaxation Oscillator for Frequency Modulated DC-DC Charge Pump Regulation

Relaxation oscillators with wide dynamic range are required for low power frequency modulated switch mode DCDC regulator designs. In this brief, a temperature compensation technique with variable threshold control for Voltage Controlled Relaxation Oscillator (VCRO) is presented. The voltage to current conversion circuit reduces the drift in the frequency gain across temperature by introducing a PMOS-NMOS current gain compensation scheme. The current gain circuit also allows absolute control on the minimum value of control voltage after which VCRO starts doing voltage to frequency conversion. This restricts the amplifier to go out of saturation which is inherently generating the control voltage for VCRO. Measurement results show that across temperature range of -40 oC to 150 oC, the oscillator achieves a temperature stability of 187 ppm/oC at 18MHz and 171 ppm/oC at 92.5MHz respectively. Implemented in 90nm process node, it occupies 57μm×32μm area while dissipating 2.61 nW/KHz from a 1.5V supply.

Smart textile embedded with distributed fiber optic sensors for railway bridge long term monitoring

The Structural Health Monitoring (SHM) of large civil infrastructures has become a priority due to economic advantages and early detection of structural failure. Distributed Fiber Optics (DFO) sensors are becoming widely used for SHM due to their immunity to Electromagnetic interference and the ability to collect multiple data points from a single fiber cable. However, its reliability for a long monitoring period is still an area of interest. This paper studied the long-term performance of DFO embedded into textiles for faster installation procedures. The aim was to understand if the textile distributed fiber sensor experience any signal degradation after multiple weather seasons. To perform this investigation a railway bridge was used as a case study. The data was collected using Brillouin Optical Time Domain Reflectometry (BOTDR) and Brillouin Optical Time Domain Amplification (BOTDA). Additionally, a temperature compensation technique was investigated to remove the cross-relation between temperature and strain. The final results show the sensor’s effectiveness for long-term monitoring, where the data quality remained constant with an average standard deviation of 0.455 for the BOTDR and 0.208 for the BOTDA approaches.

Calibration Experiment and Temperature Compensation Method for the Thermal Output of Electrical Resistance Strain Gauges in Health Monitoring of Structures

Electrical resistance strain gauges are widely used in asymmetric structures for measurement and monitoring, but their thermal output in changing temperature environments has a significant impact on the measurement results. Since thermal output is related to the coefficient of thermal expansion of the strain gauge’s sensitive grating material and the measured object, the temperature self-compensation technique of strain gauges fails to eliminate the additional strain caused by temperature because it cannot match the coefficient of thermal expansion of various measured objects. To address this problem, in this study, the principle of the thermal output of electrical resistance strain gauges was analyzed, a calibration experiment for thermal output in the case of a mismatch between the coefficient of linear expansion of the measured object and the strain gauge grating material was conducted, and the mechanism for temperature influence on thermal output was revealed. A method was proposed to obtain the thermal output curves for different materials by using thermostats with dual temperatures to conduct temperature calibration experiments. A linear regression method was used to obtain a linear formula for the thermal output corresponding to each temperature. The thermal output conversion relationship was derived for materials with different coefficients of linear expansion. An in situ temperature compensation technique for electrical resistance strain gauges that separates the measured strain into thermal and mechanical strains was proposed. The results showed that the thermal output curve for the measured object can be calibrated in advance and then deducted from the measured strain, thus reducing the influence of temperature-induced additional strain on the mechanical strain. In addition, a new method was provided for the calculation of the thermal output among materials with similar coefficients of linear expansion, providing a reference for the health monitoring of asymmetric structures.

End-to-End Direct-Current-Based Extreme Fast Electric Vehicle Charging Infrastructure Using Lithium-Ion Battery Storage

An urgent need to decarbonize the surface transport sector has led to a surge in the electrification of passenger and heavy-duty fleet vehicles. The lack of widespread public charging infrastructure hinders this electric vehicle (EV) transition. Extreme fast charging along interstates and highway corridors is a potential solution. However, the legacy power grid based on alternating current (AC) beckons for costly upgrades that will be necessary to sustain sporadic fast charging loads. The primary goal of this paper is to propose a sustainable, low-loss, extremely fast charging infrastructure based on photovoltaics (PV) and co-located lithium-ion battery storage (BESS). Lithium-ion BESS plays a pivotal role in our proposed design by mitigating demand charges and operating as an independent 16–18 h power source. An end-to-end direct current power network with high voltage direct current interconnection is also incorporated. The design methodology focuses on comprehensive hourly EV-load models generated for different types of passenger vehicles and heavy-duty fleet charging. Appropriate PV-BESS sizing, optimum tilt, and temperature compensation techniques based on 15 years of irradiation data were utilized in the design. The proposed grid-independent DC power networks can significantly improve well-to-wheels efficiency by minimizing total system losses for fast charging networks. The network power savings for low, medium, and high voltage use cases were evaluated. Our results demonstrate 17% to 25% power savings compared to the traditional AC case.

Fiber Bragg grating pressure sensors: a review

Fiber Bragg grating (FBG) pressure sensors have the potential to replace conventional voltage sensors due to their compact size, resistance to electromagnetic interference, excellent safety, distributed sensing, and numerous other intrinsic benefits. It is frequently employed in the domains of civil engineering, aerospace, and medicine. Our work examines two types of sensitized FBG pressure sensors, namely FBG pressure sensors with innately improved sensitivity and FBG pressure sensors with extrinsically increased sensitivity. Our work examines microstructured fiber Bragg grating pressure sensors and polymer fiber Bragg grating pressure sensors for FBG pressure sensors with innately heightened sensitivity. Our research examines metal-mechanical FBG pressure sensors and polymer-mechanical FBG pressure sensors for extrinsically sensitized FBG pressure sensors. This report also summarizes the benefits and drawbacks of various FBG pressure sensors and temperature compensation techniques. Finally, the future of FBG pressure sensors is examined.

A transformer matching X-band MMIC power amplifier with temperature compensation technique on 0.25µm GaN process

A transformer matching X-band MMIC power amplifier with temperature compensation technique on 0.25µm GaN process

Evaluation of machine learning techniques for structural health monitoring using ultrasonic guided waves under varying temperature conditions

The implementation of machine learning methods for structural health monitoring applications has proven to be very effective, especially in detecting damage and compensating for environmental and operational conditions. The use of guided waves in this area has also shown to be a powerful tool due to their sensitivity to structural changes in the propagation medium. In this work, two strategies for detecting damage and distinguishing their positions and for dealing with temperature variations without an additional classical temperature compensation technique are investigated. For this purpose, four unsupervised dimensionality reduction learning methods were used and compared: Principal Component Analysis, Kernel Principal Component Analysis, t-distributed stochastic neighbour embedding and Autoencoder. The first strategy (score plot) consists of using the latent dimensions directly to distinguish the data points of different states of the structure, and the second (DI plot) proposes a method to use Q- and T2-statistics, which have been proposed in previous work for PCA, computed using the compressed representation of the monitoring data. To this end, monitoring data from intact and damaged states of a 500x500x2 mm plate of carbon-fibre–reinforced polymer recorded by 12 piezoelectric transducers at different temperatures are examined. As a reversible damage model, a 10 mm thick aluminium disc is placed at four different locations on the plate. The results primarily show the success of the methods used with DI plot in detecting damage regardless of varying temperature. The autoencoder in the first strategy also demonstrates promising performance in detecting and distinguishing the position of the damage, even in the presence of varying temperature conditions.

Ultrasonic-based tensile force estimation for cylindrical rod at various temperature conditions

This study presents the development of a tensile force estimation technique based on the ultrasonic bulk wave for cylindrical rod in a suspension bridge anchor system. Three piezoelectric macro fiber composites (MFC) transducers are installed on the surface of a cylindrical rod specimen for the generation and sensing of ultrasonic bulk waves. Ultrasonic responses are obtained at various tensile force levels and temperature conditions, and the relationship between the time lag of the ultrasonic response and the tensile force is established. In particular, the temperature effect on the tensile force estimation is theoretically derived and compensated for field applications. The originality of this study includes (1) theoretical derivation and investigation of the relationship between an applied tensile force level and the time lag of an ultrasonic response considering the variations of temperature, density, and elastic modulus, (2) development of a tensile force estimation and temperature compensation technique without temperature measurement, and (3) application to the tensile force estimation of the rod structure commonly used in a suspension bridge anchor system. The performance of the developed tensile force estimation technique was examined based on mock-up experiments of the rod structure of a real suspension bridge anchor system.

Improving Electromechanical Impedance Damage Detection Under Varying Temperature

The field of structural health monitoring has seen a fundamental shift in recent years, as researchers strive to replace conventional non-destructive evaluation techniques with smart material-based techniques. Perhaps the most promising of smart material techniques for developing structural health monitoring (SHM) systems is electromechanical impedance (EMI) which can be used for real-time structural damage assessment. In EMI, mechanical resonances of structure can be seen in electrical characteristics of piezoelectric transducers due to electromechanical coupling of transducer with the structure. Existence of damage will cause a structural stiffness change and therefore the resonant characteristics of the structure will be altered. This article presents an experimental and numerical study to investigate the effects of notch damage with temperature on the electrical impedance of the piezoelectric sensor used in the EMI technique. The practical implementation of the compact EMI method utilizes as its main apparatus an impedance analyser (Model Agilent 4294A) that reads the in-situ EMI of piezoelectric wafer active sensors (PWAS) attached to the monitored structure. The finite element modelling used ANSYS software three-dimensional (3D) capability to simulate an aluminium beam at varying temperatures. Real-time monitoring of the structure is achieved based on harmonic measurements. The results conclusively showed that the proposed temperature compensation technique eliminates the results ambiguity and enabled the EMI system to detect small damages that were otherwise indiscernible.

Design of a Broadband MMIC Driver Amplifier with Enhanced Feedback and Temperature Compensation Technique

This paper presents a broadband GaN pseudo high-electron-mobility transistor (pHEMT) two-stage driver amplifier based on an enhanced feedback technique for a wideband system. Through well-designed parameter values of the feedback and the matching structure of the circuit, a relatively flat frequency response was obtained over a wide frequency band. Simultaneously, in order to reduce the fluctuation of current caused by the environmental temperature, a bias circuit with quiescent current temperature compensation was designed. The driver power amplifier, which was implemented in the form of a monolithic microwave integrated circuit (MMIC), was designed to drive a broadband high-power amplifier. The designed broadband driver amplifier for the 6 GHz to 20 GHz frequency band had a very small die size of 1.5 × 1.2 mm2 due to the use of an optimized impedance matching structure. It exhibited a small-signal gain of 12.5 dB and output power of 26 dBm. The flatness of this driver amplifier for gain and output power was achieved as ±2.5 dB and ±1 dB over the entire frequency band, respectively. The experimental results showed up to 35 dBm in the OIP3, and the current variation range was ±5 mA after using the temperature compensation bias circuit.

Simultaneous measurements of velocity, gas concentration, and temperature by way of thermal-anemometry-based probes

Many natural and engineering flows transport more than one scalar. Moreover, to study the scalar mixing therein, knowledge of the velocity field is also essential. For this reason, the present work describes the development of a three-wire thermal-anemometry-based probe to simultaneously measure velocity, helium concentration, and temperature in turbulent flows. It is first demonstrated, both theoretically and experimentally, that the temperature measured by a cold-wire thermometer is effectively insensitive to helium concentration. Then, building on recent work by Hewes and Mydlarski (2021 Meas. Sci. Technol. 32 105305), which pertains to the design of interference probes (i.e. thermal-anemometry-based probes used to measure velocity and gas concentration), a novel temperature compensation technique is proposed to extend their use to non-isothermal flows. The performance of the compensation technique is validated in turbulent coaxial jets by combining the cold-wire thermometer and interference probe to form a three-wire probe. Given that the three-wire probe can be employed to obtain simultaneous measurements of velocity and multiple scalars, it can therefore be used investigate phenomena such as multi-scalar mixing, including differential diffusion.