Temperature Compensation Research Articles

Temperature-compensated optical fiber sensor for urea detection based on the femtosecond laser-inscribed process

This study demonstrates a low crosstalk temperature-compensated fiber-based urea sensor based on the hybridization of surface plasmon resonance (SPR) and Mach-Zehnder interferometer (MZI). In this sensing structure, an inscribed waveguide and a semi-open cavity are processed by a femtosecond laser in an optical fiber to excite an SPR signal sensitive to refractive index (RI) and an MZI signal highly sensitive to temperature. Based on the temperature detected by the MZI, the influence of temperature on the SPR signal’s RI detection can be calculated and compensated for using a sensitivity matrix. Based on this precise RI detection of the SPR signal, we have achieved selective urea detection by bio-functionalizing the sensor surface using the urease self-assembly method. The sensitivity and limit of detection for urea are 7.98 (nm/mmol/L) and 0.13 mmol/L, respectively, which are better than those in previous studies. Compared to previous temperature compensation studies, this SPR + MZI sensing method using femtosecond laser processing significantly improves the temperature sensitivity of the MZI signal, which reduces crosstalk and ensures a sufficient working range for the SPR signal. Therefore, this sensor is crucial for advancing high-precision temperature compensation detection, high-sensitivity biological detection, and the future application of the femtosecond laser technology.

Ultrasensitive optical electric field sensor with temperature compensation for point-wise and quasi-distributed sensing

A point-wise and quasi-distributed optical sensing technique with the Vernier effect is proposed and achieved by multiplexing Fabry–Perot interferometers (FPIs). The FPIs are fabricated by LiNbO3 (LN) crystals of varying lengths to enable simultaneous measurement of electric field (E-field) and temperature. Compared to the traditional bulk-type optical E-field sensors, this innovative sensor enables E-field measurement without being limited by half-wave voltage and effectively avoids the influence of natural birefringence. By an algorithm based on the Fourier transform, sub-FPIs are addressable, and their interference spectra can be demodulated independently, where any two FPIs are paired to generate the fundamental Vernier effect (FVE) or harmonic Vernier effect (HVE). Thus, the measurement sensitivities of FPIs can be significantly improved by monitoring the spectral shift of the envelope in the superimposed spectra. The quasi-distributed sensing experiment is conducted using three cascaded FPIs, yielding E-field sensitivities of 2.84 nm/E (FVE) and 3.37 nm/E (HVE), with a standard deviation (STD) of spectrum variation after temperature compensation below 3.19 × 10−3. The proposed multiplexing method is significant for practical applications of the E-field quasi-distributed measurement.

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.

Bolt loosening status classification via wave energy dissipation measurements with temperature-compensated deep learning by piezoelectric active sensing

Abstract In industrial applications, bolts, serving as crucial components, endure substantial loads and are susceptible to loosening problems exacerbated by intricate external environmental factors. The active sensing method based on wave energy dissipation exhibits pronounced sensitivity to axial load fluctuations in bolts and demonstrates extensive applicability, with its measurement indicators directly applicable for discerning the bolt’s status. However, environmental factors, notably temperature, can significantly influence signal energy measurements, and the oversight of temperature impact may result in erroneous state discrimination. To tackle this challenge, this paper introduces a cascaded model comprising a temperature compensation subnetwork and a bolt state discrimination subnetwork. The temperature compensation subnetwork takes temperature and signal energy as inputs and outputs the temperature-compensated signal energy, and conveys the outcomes to the bolt state discrimination subnetwork for state classification. In model design, we quantitatively analyzed the number of convolutional blocks and training epochs for the temperature compensation subnetwork with the aim of enhancing the model’s generalization ability, ultimately determining the model architecture. By comparing the experimental results between a single-task model and a model incorporating the temperature compensation subnetwork, we verified the effectiveness of the temperature compensation subnetwork. The experimental outcomes demonstrate that the proposed cascaded model achieved a state classification accuracy of 98.6% on over 1300 temperature-generalized data points. To comprehensively assess our approach, we conducted detailed comparisons with other bolt loosening monitoring methods, elucidating the effectiveness based on data trends and model design. Experimental results demonstrate that the proposed temperature compensation cascaded model accurately identifies bolt states amidst complex temperature variations.

A Compact V-Band Temperature Compensation Low-Noise Amplifier in a 130 nm SiGe BiCMOS Process.

This paper presents a compact V-band low-noise amplifier (LNA) featuring temperature compensation, implemented in a 130 nm SiGe BiCMOS process. A negative temperature coefficient bias circuit generates an adaptive current for temperature compensation, enhancing the LNA's temperature robustness. A T-type inductive network is employed to establish two dominant poles at different frequencies, significantly broadening the amplifier's bandwidth. Over the wide temperature range of -55 °C to 85 °C, the LNA prototype exhibits a gain variation of less than 1.5 dB at test frequencies from 40 GHz to 65 GHz, corresponding to a temperature coefficient of 0.01 dB/°C. At -55 °C, 25 °C, and 85 °C, the measured peak gains are 25.5 dB, 25 dB, and 24.4 dB, respectively, with minimum noise figures (NF) of 3.0 dB, 3.5 dB, and 4.2 dB, and DC power consumptions of 22.3 mW, 27.6 mW, and 34.4 mW. Moreover, the total silicon area of the LNA chip is 0.37 mm2, including all test pads, while the core area is only 0.09 mm2.

Effect of Electromagnetic Stirring on Solidification Structure and Central Porosity of Large‐Sized Round Bloom in Continuous Casting

The effect of strand (S‐) and final (F‐) electromagnetic stirring (EMS) on solidification structure characteristic of a φ690 mm continuously cast round bloom has been investigated industrially and theoretically. The newly designed S1‐EMS equipped just below the foot zone takes great effect on both equiaxed ratio and distribution alignment, as well as central porosity. Larger current S1‐EMS leads to higher equiaxed ratio, more symmetrical equiaxed zone, and smaller diameter of central porosity, and the effect is much more obvious than conventional S2‐EMS and F‐EMS. It is also noticed that there should be a saturation effect of S1‐EMS on the promotion of equiaxed dendrite nucleation. The S2‐EMS is beneficial for the expanding of equiaxed zone and improving of central porosity. When S1‐EMS is weak, strong S2‐EMS results in more asymmetrical equiaxed zone. However, when S‐EMS is strong, strong S2‐EMS results in more symmetrical distribution of equiaxed zone. The F‐EMS takes a little impact on the expanding of equiaxed zone in the large‐sized round bloom, and almost no effect on the alignment. The central porosity, however, is improved by F‐EMS with the help of decrease in temperature gradient and compensation of solidification contraction.

Magnetic field measurement with temperature compensation based on a fiber ring microwave photonic filter and Vernier effect.

We proposed, a novel, to the best of our knowledge, magnetic field measurement with temperature compensation based on a fiber ring microwave photonic filter (FR-MPF) and a Vernier effect. The sensing head is made up by attaching the fiber Bragg grating (FBG) on the magnetostrictive material. Based on the wavelength division multiplexing, two FR-MPFs with different optical carriers can eliminate the influence of the temperature. The Linear chirped FBG (LCFBG) in the FR can transfer the magnetic field variation to the time delay change as well as the frequency shift. Two FR-MPFs with close free spectral ranges can implement the Vernier effect, which can improve the sensitivity. The experimental results show the sensitivity is 58.3 kHz/Oe and the magnification factor is 214. The proposed sensor has merits of high resolution, high sensitivity and low cross-sensitivity, which has potential applications requiring high precision detections.

Wavelet neural network algorithm for hybrid GA in infrared CO2 gas sensor

As the economy develops and the environmental impact of the greenhouse effect becomes more apparent, the need for precise measurement of specific gas concentrations in the air has become increasingly pressing. Nevertheless, as a representative of greenhouse gases, CO2 gas detectors are susceptible to environmental temperature fluctuations, which impairs the accuracy of detection. To address this issue, the research team innovatively combined the genetic algorithm (GA) and the wavelet neural network (WNN) to develop a solution for the temperature compensation problem of the infrared CO2 gas sensor. The non-dominant sorted genetic algorithm II (NSGA-II) was integrated into the GA to achieve a balance between the accuracy, complexity, and temperature performance of the model through multi-objective optimization. The results showed that compared with other existing models, the GA-WNN model proposed in this study can significantly reduce the difference between the detected values and the actual environmental values under various temperature conditions when processing data. Especially at an ambient temperature of 49 °C, for a true CO2 concentration of 2000 ppm, the detection value processed by the GA-WNN algorithm was 2046 ppm, with a relative error of only 2.3 %, far lower than the 9.8 % of Faster RCNN algorithm and 11.5 % of WNN algorithm. The contribution of the research is the proposal of a novel temperature compensation method that significantly enhances the precision of infrared CO2 gas sensors. This is of paramount importance for enhancing the accuracy of gas detection in environmental monitoring and industrial control.

A Packaged 54-to-69-GHz Wideband 2T2R FMCW Radar Transceiver Employing Cascaded-PLL Topology and PTAT-Enhanced Temperature Compensation in 40-nm CMOS

A Packaged 54-to-69-GHz Wideband 2T2R FMCW Radar Transceiver Employing Cascaded-PLL Topology and PTAT-Enhanced Temperature Compensation in 40-nm CMOS

A Temperature-Robust Envelope Detector Receiving OOK-Modulated Signals for Low-Power Applications

This paper presents a passive Envelope Detector (ED) to be used for reception of OOK-modulated signals, such as in Wake-Up Receivers employed within Wireless Sensor Networks, widely used in the IoT. The main goal is implementing a temperature compensation mechanism in order to keep the passive ED input resistance roughly constant over temperature, making it a constant load for the preceding matching network and ultimately keeping the overall receiving chain sensitivity constant over temperature. The proposed ED was designed using STMicroelectronics 90 nm CMOS technology to receive 1 kbps OOK-modulated packets with a 433 MHz carrier frequency and a 0.6 V supply. The use of a block featuring a Proportional-to-Absolute Temperature (PTAT) current yields a 5 dB reduction in sensitivity temperature variation across the −40 °C to 120 °C range. Moreover, two different implementations were compared, one targeting minimal mismatch and the other one targeting minimal area. The minimal area version appears to be better in terms of estimated overall chain sensitivity at all temperatures despite a higher sensitivity spread.

Cold-induced degradation of core clock proteins implements temperature compensation in the Arabidopsis circadian clock.

The period of circadian clocks is maintained at close to 24 hours over a broad range of physiological temperatures due to temperature compensation of period length. Here, we show that the quantitative control of the core clock proteins TIMING OF CAB EXPRESSION 1 [TOC1; also known as PSEUDO-RESPONSE REGULATOR 1 (PRR1)] and PRR5 is crucial for temperature compensation in Arabidopsis thaliana. The prr5 toc1 double mutant has a shortened period at higher temperatures, resulting in weak temperature compensation. Low ambient temperature reduces amounts of PRR5 and TOC1. In low-temperature conditions, PRR5 and TOC1 interact with LOV KELCH PROTEIN 2 (LKP2), a component of the E3 ubiquitin ligase Skp, Cullin, F-box (SCF) complex. The lkp2 mutations attenuate low temperature-induced decrease of PRR5 and TOC1, and the mutants display longer period only at lower temperatures. Our findings reveal that the circadian clock maintains its period length despite ambient temperature fluctuations through temperature- and LKP2-dependent control of PRR5 and TOC1 abundance.

A Highly Linear Ultra-Low-Area-and-Power CMOS Voltage-Controlled Oscillator for Autonomous Microsystems.

Voltage-controlled oscillators (VCOs) can be an excellent means of converting a magnitude into a readable value. However, their design becomes a real challenge for power-and-area-constrained applications, especially when a linear response is required. This paper presents a VCO for smart dust systems fabricated by 65 nm technology. It is designed to minimize leakage, limit high peak currents and provide an output whose frequency variation is linear with the input voltage, while allowing rail-to-rail input range swing. The oscillator occupies 592 μm2, operates in a frequency range from 43 to 53 Hz and consumes a maximum average power of 210 pW at a supply voltage of 1 V and 4 pW at 0.3 V. In addition, the proposed VCO exhibits a quasi-linear response of frequency vs. supply voltage and temperature, allowing easy temperature compensation with complementary to absolute temperature (CTAT) voltage.

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.

RFSoC Softwarisation of a 2.45 GHz Doppler Microwave Radar Motion Sensor

Microwave Doppler sensors are used extensively in motion detection as they are energy-efficient, small-size and relatively low-cost sensors. Common applications of microwave Doppler sensors are for detecting intrusion behind a car roof liner inside an automotive vehicle and to detect moving objects. These applications require a millisecond response from the target for effective detection. A Doppler microwave sensor is ideally suited to the task, as we are only interested in movement of a large water-based mass (i.e., a person) (FMCW Radar also detect static objects). Although microwave components at 2.45 GHz are now relatively cheap due to mass production of other Industrial Scientific and Medical application (ISM) devices, they do require tuning for temperature compensation, dielectric, and manufacturing variability. A digital solution would be ideal, as chip solutions are known to be more repeatable, but Application-Specific Integrated Circuits (ASICs) are expensive to initially prototype. This paper presents the first completely digital Doppler motion sensor solution at 2.45 GHz, implemented on the new RFSoC from Xilinx without the need to up/downconvert the frequency externally. Our proposed system uses a completely digital approach bringing the benefits of product repeatability, better overtemperature performance and softwarisation, without compromising any performance metric associated with a comparable analogue motion sensor. The RFSoC shows to give superior distance versus false detection, as the Signal-to-Noise Ratio (SNR) is better than a typical analogue system. This is mainly due to the high gain amplification requirement of an analogue system, making it susceptible to electrical noise appearing in the intermediate-frequency (IF) baseband. The proposed RFSoC-based Doppler sensor shows how digital technology can replace traditional analogue radio frequency (RF). A case study is presented showing how we can use a novel method of using multiple Doppler channels to provide range discrimination, which can be performed in both analogue and in a digital implementation (RFSoC).

A fiber optic refractive index sensor with temperature compensation based on cascaded Mach-Zehnder interference and Intermodal interference

Optical fiber refractive index (RI) sensor with temperature (T) compensation has important application values in biomedicine and environmental monitoring. In order to solve the problem that the detection accuracy of liquid RI is affected by T in practical applications, a T-compensated RI fiber sensor based on cascaded Mach-Zehnder interference (MZI) and multimode interference (IMI) is proposed in this paper. Experimental results showed the proposed sensor achieved a sensitivity of 797.41 nm/RIU for the measurement of RI in the range of 1.3333–1.3640, and a sensitivity of 0.120 nm/°C for the measurement of T in the range of 0–60 °C. The resolution (R) of RI and T measurements reached 2.5 × 10−5 RIU and 0.167 °C, respectively. The detection limits (DL) of RI and T measurements are 3.135 × 10−8 RIU and 1.392 °C, respectively. A matrix is obtained to demodulate the cross-sensitivity in RI and T measurements. The proposed sensor shows the advantages of simple structure, low hysteresis, and good stability.

Achieving superior mechanical and corrosion properties in medium-thickness Ti-6Al-4 V alloy joints by back heating assisted friction stir welding below β-phase transformation temperature

The equiaxed microstructure formed below the β-phase transition point of Ti alloys generally exhibits an excellent balance of mechanical properties and corrosion resistance. However, this desirable microstructure is impossible to be obtained in fusion welded joints but is prospective to be achieved by the solid-state friction stir welding (FSW) technique. Unfortunately, it generally generates bottom defects and severe tool wear in medium-thickness Ti alloy joints when conventional FSW was conducted below the β-phase transition point. In this study, 6 mm thick Ti-6Al-4 V plates were joined by both the conventional FSW and back heating assisted FSW (BHAFSW). Defects caused by significant tool wear and bottom phase transition differences occurred in the conventional FSW. It was found that the hardness difference between the base material (BM) and the tool increased to 35.6 % from 500 °C to 900 °C. The back heating (150 °C) was used to control welding temperatures remaining the 900 °C, thus largely reducing the tool wear by increasing the hardness difference. In addition, the back temperature compensation increased the bottom temperature and controlled the phase transition position from the bottom to the middle of the joint. The shoulder pressure contributed to the compression of the defects, and the defects were eliminated by increasing the pressure at the phase transition position. A significantly refined equiaxed microstructure with an average grain size of ∼0.9 μm was achieved below the β-phase transition temperature in the stir zone via back heating assisted FSW, while a bimodal structure with an average grain size of 3.5 μm was formed near the β-phase transition temperature. Inconspicuous reduction of the strength was detected for the joints (98 % of the BM) which possess equiaxed microstructures, and the corrosion resistance of the joints was enhanced compared to the BM. This superior synergy of mechanical and corrosion properties exceeded the majority of Ti alloy joints previously reported. This study provided an effective method for obtaining medium-thickness Ti alloy joints with ultrafine equiaxial structures with superior mechanical properties and corrosion resistance.

Neuromodulator-induced temperature robustness in a motor pattern: a comparative study between two decapod crustaceans.

While temperature fluctuations pose significant challenges to the nervous system, many vital neuronal systems in poikilothermic animals function over a broad temperature range. Using the gastric mill pattern generator in the Jonah crab, we previously demonstrated that temperature-induced increases in leak conductance disrupt neuronal function and that neuropeptide modulation provides thermal protection. Here, we show that neuropeptide modulation also increases temperature robustness in Dungeness and green crabs. As in Jonah crabs, higher temperatures increased leak conductance in both species' pattern-generating lateral gastric neuron and terminated rhythmic gastric mill activity. Likewise, increasing descending modulatory projection neuron activity or neuropeptide transmitter application rescued rhythms at elevated temperatures. However, decreasing input resistance using dynamic clamp only restored the rhythm in half of the experiments. Thus, neuropeptide modulation increased temperature robustness in both species, demonstrating that neuropeptide-mediated temperature compensation is not limited to one species, although the underlying cellular compensation mechanisms may be distinct.

Temperature self-compensated dual core fiber-optic sensor integrated with moisture sensitive MIL-96(Al) film for breath detection

In this paper, a dual-core fiber optic sensor has been proposed for dynamic monitoring of temperature and humidity. The side core is polished into a D-type optical fiber, and a layer of nano-silver film and a layer of polydimethylsiloxane (PDMS) are deposited to construct a surface plasmon resonance (SPR) temperature compensator. The middle core is constructed as the long-period fiber grating (LPFG) sensing channel. The mode conversion of LPFG is achieved by TiO2 film, and its refractive index (RI) sensitivity is increased by about 4 times. Meanwhile, a layer of moisture sensitive MIL-96(Al) film is grown outside the TiO2 film. Due to the particular pore structure for water molecules, it is possible to change the effective RI of MIL-96(Al) film by absorbing water molecules. Research has shown that the LPFG sensor can achieve a relative humidity sensitivity of −0.411 nm/%RH. Finally, the sensor successfully achieved real-time dynamic monitoring of respiratory rate.

Flexible FPI sensor fabricated by fiber end photopolymerization and integration for high sensitivity gas pressure sensing

This work presents a new design framework for highly sensitive fiber gas pressure sensor. We construct a Flexible Fabry–Perot Interferometer (F-FPI), which consists of three polymer pillars and an end cap, on a fiber end face. A unique fiber-end photopolymerization and integration (FEPI) technique is adopted for fabricating the device. The varied gas pressure in the enclosed space not only changes the refractive index (RI) of the gas but also the length of the pillars. Therefore the difference in the optical path length of the FPI is more sensitive to pressure changes. Experimental results indicate that the F-FPI realizes a gas pressure sensitivity up to 79.0 pm/kPa in the range of 0–200 kPa. In addition, the Vernier effect is introduced to amplify the sensitivity to −409.7 pm/kPa. The temperature compensation is achieved by cascading a Fiber Bragg Grating (FBG) behind the F-FPI. Such a design framework provides a new idea for highly sensitivity gas pressure sensing.

An amplitude-based temperature compensated MEMS resonant pressure sensor with single resonator

Temperature compensation is a common concern of MEMS sensors. This paper presents an amplitude-based temperature compensated MEMS resonant pressure sensor. An AGC (automatic gain control) closed-loop circuit with a constant-amplitude drive was designed, enabling the real-time sampling of resonant frequencies and amplitudes. Under the constant-amplitude drive, the amplitude of the resonator changes monotonously with temperature. Thus, pressure and temperature can be decoupled using a single resonator, achieving high accuracy in pressure measurements. Experimental results demonstrated that the fabricated microsensor achieved high performance with the amplitude-based temperature compensation. Within a pressure range of 10 kPa to 100 kPa and a temperature range of −20℃ to 60℃, the pressure accuracy of the microsensor reached ± 0.012 %FS (full scale), with a repeatability error of 0.009 %FS and a pressure hysteresis error of 0.007 %FS. Based on single resonator, the developed microsensor is expected to reduce device sizes, simplify design and fabrication processes, and decrease the power consumption of the system.