High Precision Temperature Control Research Articles

Development path of digital cultural industry by integrating proportional integral and differential algorithm from the perspective of cultural innovation

The digital culture business benefits from quick technical updates, digital manufacturing, communication networks, and customized consumption, which promotes new supply and consumption. The innovation and development of the digital cultural industry cannot be separated from the physical industry. The efficient production of the physical industry can ensure the innovative development of digital cultural industry. Therefore, to improve the production efficiency of physical industry, this research proposes a temperature control model combining whale optimization algorithm and fuzzy proportional integral differential algorithm based on the traditional temperature control in ceramic firing and wine making process. Firstly, fuzzy control theory is used to improve the proportional integral differential algorithm, and a fuzzy proportional integral differential model with adaptive adjustment function is established. On this basis, to quickly confirm the optimal parameters of the proportional integral differential model, the whale optimization algorithm is introduced to further optimize its weight factors. It was verified that the temperature control adjustment model combining whale optimization algorithm and fuzzy proportional integral differential model was 2.77 s, which was shortened by 1.11 s, 2.37 s and 3.13 s, respectively than the other three models. Therefore, the constructed temperature control model can effectively realize high-precision intelligent temperature control in industrial production, laying the cornerstone for promoting the innovative development of digital culture industry. The proposed model can improve the production efficiency of physical industries, promote digital transformation, and optimize the innovative development of digital cultural industries.

Simplified decoy-state quantum key distribution based on planar lightwave circuit integration module

The BB84 protocol with decoy states for quantum key distribution (QKD) has generated significant interest due to its theoretical unconditional security. Presently, the most of QKD systems demonstrated rely on bulk optics. Nevertheless, in upcoming large-scale commercial availability, it is imperative to have highly integrated, consistently performing, and cost-effective systems. Photonic integrated circuits (PICs) based on silica planar lightwave circuits (PLCs) play a crucial role in QKD due to its mature manufacturing process, excellent stability, low loss, and high integration level. We develop a simplified BB84 time-bin QKD experiment system that can significantly improve the key rate because it does not require time basis decoding. And two silica PLC asymmetric Mach-Zehnder interferometer (AMZI) module are used with a high-precision temperature control system (±0.01 °C). Three quantum states |ψ0⟩, |ψ1⟩ and |ψ+⟩ are encoded and decoded with the module. The system achieves an estimated key rate about 3.4 Mbps using an analytical model with one decoy state at a clock repetition rate of 1.25 GHz. Finally, we experimentally obtain a key rate of 531 kbps over a 20 km single-mode fiber (SMF) at a clock repetition rate of 156.25 MHz.

High-precision and wide-range temperature measurement and control system of satellite-borne calibration blackbody

The accurate measurement and control of blackbody temperature can play an important role in radiometric calibration. A novel circuit suitable for the aerospace environment is designed to measure and control the temperature of the blackbody. A coarse-fine measurement method considering the wire resistance and self-heating effect of the platinum resistance is presented to calculate the resistance values of the platinum resistors. The precision of temperature measurement is improved using a line fitting algorithm with error calibration and temperature drift error compensation. A fuzzy self-adaptive PID controller is designed to improve the temperature control effect. The performances of the developed system are implemented on an FPGA/A3PE3000-FG484I controller board. The test results show that the device temperature measurement precision can reach ±0.03K for the entire temperature range 238 K to 367 K, the temperature stability is better than 0.02 K/20 s, and the temperature uniformity is better than 0.1 K.

Temperature-Automated Calibration Methods for a Large-Area Blackbody Radiation Source.

High-precision temperature control of large-area blackbodies has a pivotal role in temperature calibration and thermal imaging correction. Meanwhile, it is necessary to correct the temperature difference between the radiating (surface of use) and back surfaces (where the temperature sensor is installed) of the blackbody during the testing phase. Moreover, large-area blackbodies are usually composed of multiple temperature control channels, and manual correction in this scenario is error-prone and inefficient. At present, there is no method that can achieve temperature-automated calibration for a large-area blackbody radiation source. Therefore, this article is dedicated to achieving temperature-automated calibration for a large-area blackbody radiation source. First, utilizing two calibrated infrared thermometers, the optimal temperature measurement location was determined using a focusing algorithm. Then, a three-axis movement system was used to obtain the true temperature at the same measurement location on a large-area blackbody surface from different channels. This temperature was subtracted from the blackbody's back surface. The temperature difference was calculated employing a weighted algorithm to derive the parameters for calibration. Finally, regarding experimental verification, the consistency error of the temperature measurement point was reduced by 85.4%, the temperature uniformity of the surface source was improved by 40.4%, and the average temperature measurement deviation decreased by 43.8%. In addition, this system demonstrated the characteristics of strong environmental adaptability that was able to perform temperature calibration under the working conditions of a blackbody surface temperature from 100 K to 573 K, which decreased the calibration time by 9.82 times.

Thermally stable Peltier controlled vacuum chamber for electrical transport measurements.

The design, manufacture, and characterization of an inexpensive, temperature-controlled vacuum chamber with millikelvin stability for electrical transport measurements at and near room temperature is reported. A commercially available Peltier device and a high-precision temperature controller are used to actively heat and cool the sample space. The system was designed to minimize thermal fluctuations in spintronic and semiconductor transport measurements, but the general principle is relevant to a wide range of electrical measurement applications. The main issues overcome are the mounting of a sample with a path of high thermal conductivity through to the Peltier device and the heat sinking of the said Peltier device inside a vacuum. A copper slug is used as the mount for a sample, and a large copper block is used as a thermal feedthrough before a passive heat sink is used to cool this block. The Peltier device provides 20W of heating and cooling power, achieving a maximum range of 30K below and 40K above the ambient temperature. The temperature stability is within 5 mK at all set points with an even better performance above the ambient temperature. A vacuum pressure of 10-8 hPa is achievable. As a demonstration, we present experimental results from current-induced electrical switching of a CuMnAs thin film. Transport measurements with and without the Peltier control emphasize the importance of a constant temperature in these applications. The thermal lag between the sample space measurement and the sample itself is observed through magnetoresistance values measured during a temperature sweep.

Intelligent control of electric vehicle air conditioning system based on deep reinforcement learning

The existing AC system of EVs consumes a lot of energy in summer, resulting in reduced range. Additionally, the cabin temperature (Tcabin) fluctuates due to varying driving conditions. In this paper, an innovative cooling strategy is designed to address the above drawbacks using deep reinforcement learning algorithms. The primary objective of this strategy is to achieve high-precision temperature control while concurrently minimizing the energy consumption of the AC system. The strategy combines compressor speed (Ncompressor) and blower airflow (Bairflow) control to optimize the AC system's performance. The RL controller minimizes energy consumption by reducing Ncompressor while increasing Bairflow, thus ensuring a constant cooling capacity (Q). And it effectively reduces temperature fluctuations within the cabin. Finally, the RL control strategy was compared with on/off control and proportional integral differential (PID) control. The results showed that RL control performed well in the multi-objective optimization of the AC system. In terms of temperature control, it effectively reduces the amount of overshooting, and the minimum temperature fluctuation achieved through RL control is merely 0.07 °C, exhibiting an 84.4 % and 86.5 % decrease compared to traditional control methods. The average absolute temperature error stands at 0.06–0.07℃, maintaining a remarkable precision in preserving the target temperature. Furthermore, RL control not only ensures superior energy efficiency but also reduces energy consumption by up to 5.98 % and 7.65 % compared with traditional control methods.

Modeling temporal dual variations for return air temperature prediction of mK-level temperature-controlled clean chamber

Clean chamber with mK-level temperature stability is required for precision manufacturing and optical equipment to achieve nanoscale manufacturing tolerances and measurement accuracy, however, the equipped precision air conditioning system cannot respond immediately to temperature fluctuation in the chamber due to large time delay. Predicting the future return air temperature gives the control module a prescient ability to act in advance, thus aiding in temperature regulation. To this end, this paper deals with the mK-level temperature prediction problem under a high-precision temperature control situation, and a novel prediction network model dubbed TDVNet is designed based on convolutional neural network (CNN) and gated recurrent unit (GRU), where Temporal Dual Variations of time series data, namely variations-between-phases and variations-across-periods, are modeled to achieve a higher accuracy of return air temperature prediction. Utilizing chamber temperature data collected on-site for model training and evaluation, the experimental results show that capturing data change patterns from dual perspectives has reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) of the TDVNet model by 21.4% and 24.3%, respectively, compared to the model only capturing the variations-between-phases. Under a signal sampling interval of 10 s and a temperature fluctuation of (66.9 ± 25.8) mK@10min, the TDVNet model can accurately predict the return air temperature change in the next 5 min, and the proportion of prediction errors within 15 mK in the test set can reach over 90.1%.

Temperature control of atomic gas chamber using a nonmagnetic heating chip fabricated on quartz substrate

Nonmagnetic electrical heating and temperature sensing chip fabricated on quartz substrate is developed, and a high-precision digital temperature control system is designed based on this chip. The heating resistance and temperature sensing resistance are prepared by depositing two layers of Ti/Pt alloy electrodes on quartz substrate through magnetic field cancellation design. The temperature coefficient of fabricated Ti/Pt temperature sensing resistance is +0.197%/℃. The simulation results show that the residual magnetic field generated by the heating current in the atomic gas chamber closely adjacent to the chip is less than 0.1 nT. Temperature control in the range of 100~150 ℃ is realized, and the temperature stability is about 0.02 ℃. Due to the high light transmittance of quartz glass, this heating chip has significant advantages for optical integration and miniaturization of atomic magnetometers.

DEVELOPMENT OF METHANE CARBON ISOTOPE BASED ON MID-INFRARED ABSORPTION SPECTRUM TECHNOLOGY APPLIED IN LOGGING PLATFORM

To meet the requirements of rapid measurement of oil and gas methane isotopes in offshore logging platforms, a methane carbon isotope measurement system based on mid-infrared TDLAS technology was proposed in this paper. The measuring system adopted a mid-infrared compact-linear optical structure, including an interband cascade laser (central wavelength at 2963.25 cm-1), long optical path multi-pass cell (effective optical path is 24 m) and mercury cadmium telluride detector (response wavelength is from 2 μm to 5 μm). Combining two 13CH4/12CH4 absorption lines, 2963.25 cm-1 and 2963.34 cm-1, with a high precision temperature control system using an integral separation PID control method, a temperature fluctuation within 100 mK can be achieved. In the experiment, CH4 gases with five different concentrations were configured to calibrate the measurement system, and the response linearity was more than 99%. When the integration time is 121s, the precision of isotope measurement was as low as 0.83 ‰. The average isotopic abundance of methane gas measured by the system was -10.2 ‰, and the error fluctuation was about ±0.5 ‰. It was verified that the system can rapidly measure oil and gas methane isotopes.

Fuzzy control of temperature in gas flow control system based on mixed cold and hot gases

This study proposes a novel high-temperature gas flow temperature simulation system based on the mixing of cold and hot gas flow. The outlet gas flow temperature is controlled by adjusting the flow rate of the cold gas flow. To achieve consistent control of high-precision and wide-range temperature control of the system. The system mathematical model was constructed and the system characteristics were analyzed. However, traditional PID control suffers from inconsistencies in control performance at high and low temperatures, as well as inconsistent responses during temperature increasing and decreasing processes. To address these issues, fuzzy PID control was introduced, but its parameter tuning proved challenging, resulting in poor consistency of control performance. To expand the adaptability of fuzzy control, a function-based and fuzzy inference-based variable universe fuzzy PID controller was proposed. Experimental and simulation results demonstrate that the fuzzy inference-based variable universe fuzzy PID controller exhibits good dynamic and static performance under different operating conditions. The max settling time and static error are 16.5 s and ± 4 K, respectively. Compared with PID controller, the settling time and static error are reduced by 56.2% and 67.5% respectively. The fuzzy inference-based variable universe fuzzy PID controller overcomes the performance discrepancies during temperature increasing and decreasing processes, different operate temperatures, and various step amplitudes. Consequently, highly accurate simulation of system outlet gas flow temperature is realized. This methodology can be widely applied to control systems with strong nonlinearity and asymmetry, improving the consistency of the system control performance.

A two-degree-of-freedom controller for a high-precision air temperature control system with multiple disturbances

The key equipment to prevent precision machinery such as lithography from being influenced by air temperature fluctuation is a high-precision air temperature control (ATC) system. The ATC system developed for a lithography immersion testing platform suffers from the difficulties of multiple disturbances, large inertia and time delay. However, seldom have control methods can solve these problems systematically. A two-degree-of-freedom (2DOF) controller is proposed in this paper for this system, where model predictive control (MPC) is developed to overcome large inertia and time delay in the main control loop, and the measurable disturbance from the inlet air is compensated; based on the loop shaping approach, the controller in the disturbance rejection control loop is designed to attenuate the load disturbance; a Kalman filter is designed to reduce the influence of noise having no stable frequency characteristic. The experimental results show that the MPC controller and Kalman filter can effectively avoid the system oscillation, and the disturbance rejection control loop can significantly attenuate the load disturbance in the frequency range from 0.01 to 0.02 rad/s. Therefore, the 1σ precision is increased by 3.3 mK to 8.7 mK by the 2DOF controller when the system is influenced by the load disturbance with different fluctuation amplitudes.

Photonic millimeter-wave transfer with balanced dual-heterodyne phase noise detection and cancellation.

We report on the realization of long-haul and high-precision millimeter-wave (mm-wave) transfer through a fiber-optic link based on balanced dual-heterodyne phase noise detection. The balanced dual-heterodyne detection is achieved by detecting the fiber phase noise superimposed two intermediate frequency (IF) signals without requiring a local synchronization signal and its output is used to compensate the fiber-induced phase noise by actuating the frequency of the one optical carrier. The proposed scheme can effectively get rid of the effect of the local reference, largely simplifying the configuration at the local site. Additionally, we model and experimentally study the noise contribution coming from the out-of-band, which can be effectively suppressed to the below of the system noise floor with a fractional frequency instability of 1.9 × 10-17 at 10,000 s by designing and implementing a high-precision temperature control module with a peak-to-peak temperature fluctuation of no more than 0.002 K. We experimentally demonstrate that a 100 GHz mm-wave signal to be transmitted over a 150 km fiber-optic link can achieve the fractional frequency instabilities of less than 3.4 × 10-14 at 1 s and 3.5 × 10-17 at 10,000 s.

Experimental research on muffle furnace dynamic properties

Purpose. To develop the method and software for building empirical models of muffle furnaces with two heating elements. Methodology. The method for processing experimental data according to the improved algorithm, which is based on the areas method, is used for constructing empirical models of the muffle furnace. Experimental research of the muffle furnace dynamic is conducted using the following methodology. The muffle furnace is cooled to the room temperature and then the lower heater is turned on and temperatures at the furnace output are fixed using the experimental two-channel temperature controller MIC-344. The second cycle of the experimental research began by cooling the furnace to the room temperature with turning on the upper heater. Observations based on the results of the experiment are conducted until the temperature is stabilized at the two outputs of the muffle furnace. Archiving of temperature trends is carried out using the RS485/Ethernet interface and the SmartReview software (a product of private limited company “Microl”). Findings. The developed software can be used for iteratively selection of the optimal empirical model based on the criterion of the root mean square deviation of the calculated and experimental data. The calculating method for the acceleration curve based on the transfer functions coefficients with a variable discreteness step is improved in order to compare the experimental data with the empirical modeling results. Twelve empirical models were tested for four signal transmission channels in the process of experimental research. It has been established that only four of them are stable (have left-hand roots of the characteristic equation). Among the selected sustainable models, the model with the numerator polynomial equaled to two and denominator polynomial equaled to three has been established as the best model (according to the established criterion). A structural diagram is created based on the synthesized empirical model of the muffle furnace, which includes four transfer functions and cross connections. Originality. For the first time, the empirical model of a muffle furnace with two electrical energy sources has been developed, which describes its dynamic properties as the object of automatic control with high accuracy, which enables to reveal the presence of internal cross-connections, that significantly complicate the controlling process of the object. Practical value. The created empirical models with two electric sources (tens) can be used for the synthesis of the high-precision automatic temperature control system of the muffle furnace.

An Innovative System of Deep In Situ Environment Reconstruction and Core Transfer

The reconstruction of deep in situ environment up to 95 °C and 70 MPa using water is critical for the fidelity testing of deep Earth rocks. The temperature and pressure of the water have strong coupling in such an environment, which makes the control of temperature and pressure very difficult. The paper firstly presents the design of the system of deep in situ environment reconstruction and core transfer (SERCT); secondly, for the problem of high temperature and pressure control, a pressure-temperature (P-T) interpolation control algorithm based on the iso–density P-T curves of water is proposed. A P-T coupling control path is decomposed into two independent interpolation paths: an iso–thermal pressure control and an iso–mass temperature control, which realizes the decoupling control of temperature and pressure. Then, a fuzzy-PID dual mode method is adopted for the pressure control after decoupling, which reduces the overshoot and the dynamic response time of the system. For temperature control, a segmented and grouped electric heating mode is designed to improve the uniformity of the temperature field. A fuzzy PID temperature control algorithm based on grey prediction is proposed to achieve high precision temperature control with small overshoot. Finally, the effectiveness of the proposed methods is verified by experiments.

Ultra-Stable Temperature Controller-Based Laser Wavelength Locking for Improvement in WMS Methane Detection.

In the wavelength modulation spectroscopy (WMS) gas detection system, the laser diode is usually stabilized at a constant temperature and driven by current injection. So, a high-precision temperature controller is indispensable in every WMS system. To eliminate wavelength drift influence and improve detection sensitivity and response speed, laser wavelength sometimes needs to be locked at the gas absorption center. In this study, we develop a temperature controller to an ultra-high stability level of 0.0005 °C, based on which a new laser wavelength locking strategy is proposed to successfully lock the laser wavelength at a CH4 absorption center of 1653.72 nm with a fluctuation of fewer than 19.7 MHz. For 500 ppm CH4 sample detection, the 1σ SNR is increased from 71.2 dB to 80.5 dB and the peak-to-peak uncertainty is improved from 1.95 ppm down to 0.17 ppm with the help of a locked laser wavelength. In addition, the wavelength-locked WMS also has the absolute advantage of fast response over a conventional wavelength-scanned WMS system.

The prediction of the soil freezing characteristic curve using the soil water characteristic curve

Soil-water characteristic curve (SWCC) and soil freezing characteristic curve (SFCC) describe the water-holding characteristics of the soil during drying (or wetting) and freezing (or thawing), respectively. However, the relationship between SWCC and SFCC remains unclear. In order to clarify their relationship, a theoretical model is established based on the Clapeyron equation, which is further examined by laboratory test results for several soils. The results demonstrate that the newly proposed theoretical model has wide adaptability to various soils. With this model, prediction of SWCC from SFCC can be easily achieved, and the problem of time-consuming can also be addressed. In addition, the prediction of SFCC from SWCC can also be achieved, overcoming the difficulty in accurately measuring SFCC for coarse soil (i.e., sand or gravel) due to the lack of high-precision temperature control methods.

Application Test of Curing Equipment with Built-in Planetary Rotating Device

In order to improve the curing quality of composite cylindrical parts, a new curing equipment with built-in planetary rotating device was selected. In the process of equipment installation, commissioning and acceptance inspection, the equipment has been improved and applied. The test results show that the planetary rotating device in the furnace can realize the rotation around its own axis line and the revolution in the annular space in the furnace at the same time; Properly increasing the rotation speed of cylindrical parts during curing is conducive to improving the appearance quality of products; It is an effective way to improve the quality and reliability of composite cylindrical parts and meet the requirements of consistency of curing quality of high performance and high quality products by applying the new curing equipment with planetary rotary device, high precision temperature control system and furnace gas circulation system.

Temperature dependence of hydrogen isotope effect in LaNi5-H(D) system

To study inverse effect of hydrogen isotopes in LaNi5 for hydrogen isotope separation at ambient temperature, temperature dependence of hydrogen isotope effect in LaNi5－H(D) system was investigated in the temperature range -70 °C to 3 °C. Isotherms of hydrogen isotopes were tested in an automated Sieverts apparatus with a thermostat, and pressure differences were studied between H2 and D2. Isotope exchange process was carried out and H2－HD－D2 equilibrium was judged by online chromatography, separation factors were calculated to investigate the thermodynamic isotope effect. In the H2, D2 isotherms, average time interval (0.5h) between each equilibrium point was relatively short due to high precision temperature control. From the plateau pressures at a constant hydrogen (or deuterium) concentration in LaNi5 (2D or 2H atoms/mole of LaNi5) the partial molar enthalpies, ⊿H, and entropies, ⊿S of formation were calculated. ⊿H and ⊿S kept good accordance with the values from references, which indicated good performance of the Sieverts apparatus. The isotope exchange equilibrium was reached within 1h. The results showed that ratio between H2 pressure and D2 pressure, r(H－D) = P(D2)/P(H2), dropped as temperature decreased and the inverse effect was found (r(H－D)<1.0) below -5 °C according to the absorption branch of isotherms, whereas the effect was estimated to appear below 60 °C from the desorption branch. The separation factor of the H2－HD－D2 mixture, decreased as temperature increased and the inverse effect happened below -20 °C. The inverse effect was affected by the isotherm hysteresis and HD existence.

An advanced control strategy for engine thermal management systems with large pure time delay

Stable and precise temperature control can effectively improve the engine’s fuel consumption and emissions. An advanced engine thermal management system (AETMS) composed of electric actuators has great potential in increasing the temperature tracking control accuracy and decreasing the system energy consumption. Time-varying disturbance and pure time delay in the system make it challenging to harmoniously control multiple actuators to ensure efficient temperature tracking performance. In addition, a reasonable power distribution of the actuators is beneficial to reduce the parasitic energy consumption of the system and further improve the system efficiency. In this article, an adaptive optimization control strategy consisting of a state predictor, a disturbance estimator, an energy consumption optimization block and a state tracking controller is proposed for the temperature tracking and energy consumption optimization of AETMS. Experimental verification was performed on a range extender bench of an extended-range electric vehicle, and the results show that the system achieves high-precision temperature control and energy consumption near the theoretical optimal value under changing working conditions. The temperature steady-state error is within 0.3 oC, and the temperature adjustment time is within 100 s after the first overshoot.

Numerical Study of Heat Transfer in a Two-Dimensional Rarefied Hydrogen Gas Moved Jet Impingement Using Direct Simulation Monte Carlo-Finite Difference Coupled Method

Temperature control is an important indicator for the lithography. However, the factors causing temperature fluctuation in lithography remain unclear under a low-pressure environment. In this work, in order to study the jet impingement heat transfer of hydrogen under rarefied conditions, the direct simulation Monte Carlo (DSMC) method and the finite difference method (FDM) are coupled. The heat exchange capacity in the jet impingement obtained using DSMC method is treated as a boundary condition for substrate. The difference of impingement heat transfer of rarefied hydrogen jet under different conditions of inlet absolute pressure, impingement distance and jet aperture are studied. The temperature of substrate is calculated by FDM. Results show that heat exchange capacity of the jet impingement rises with an increasing the inlet absolute pressure and pipe diameter, drops with reducing impact distance. The temperature control requirements can be met when the heat exchange capacity exceeds 380 W/(m2·K), the structural parameters satisfying the temperature control requirement are demarcated. The aforementioned findings can provide design ideas for high-precision temperature control devices.