Ambient Temperature Variations Research Articles

Temperature compensation for piezoresistive pressure sensor based on deep learning on graphs

With the escalating demand for precision in piezoresistive pressure sensors to cater to a wide spectrum of applications, a significant challenge emerges due to the material properties of these sensors, which induce a substantial temperature coefficient. This limitation restricts the operational temperature range and is further exacerbated by ambient temperature variations, resulting in pronounced nonlinearity in sensor responses. To address these challenges, A new method using Graph Neural Networks (GNNs) is introduced to address nonlinearity and temperature drift in piezoresistive pressure sensors. GNNs improve the sensors’ accuracy and reliability across different temperatures, expanding their applicability. Test results show a notable accuracy enhancement, with a maximum full-scale error below 0.05% and even lower in specific ranges (under 0.04%). This precision makes the method ideal for industrial pressure sensor applications and production, offering significant benefits.

A Novel Temperature Drift Error Estimation Model for Capacitive MEMS Gyros Using Thermal Stress Deformation Analysis.

Because the conventional Temperature Drift Error (TDE) estimation model for Capacitive MEMS Gyros (CMGs) has inadequate Temperature Correlated Quantities (TCQs) and inaccurate parameter identification to improve their bias stability, its novel model based on thermal stress deformation analysis is presented. Firstly, the TDE of the CMG is traced precisely by analyzing its structural deformation under thermal stress, and more key decisive TCQs are explored, including ambient temperature variation ∆T and its square ∆T2, as well its square root ∆T1/2; then, a novel TDE estimation model is established. Secondly, a Radial Basis Function Neural Network (RBFNN) is applied to identify its parameter accurately, which eliminates local optimums of the conventional model based on a Back-Propagation Neural Network (BPNN) to improve bias stability. By analyzing heat conduction between CMGs and the thermal chamber with heat flux analysis, proper temperature control intervals and reasonable temperature control periods are obtained to form a TDE precise test method to avoid time-consuming and expensive experiments. The novel model is implemented with an adequate TCQ and RBFNN, and the Mean Square Deviation (MSD) is introduced to evaluate its performance. Finally, the conventional model and novel model are compared with bias stability. Compared with the conventional model, the novel one improves CMG's bias stability by 15% evenly. It estimates TDE more precisely to decouple Si-based materials' temperature dependence effectively, and CMG's environmental adaptability is enhanced to widen its application under complex conditions.

Optimization of Ampacity in High-Voltage Underground Cables with Thermal Backfill Using Dynamic PSO and Adaptive Strategies

This article addresses challenges in the design of underground high-voltage transmission lines, focusing on thermal management and cable ampacity determination. It introduces an innovative proposal that adjusts the dimensions of the backfill to enhance ampacity, contrasting with the conventional approach of increasing the core cable’s cross-sectional area. The methodology employs a particle swarm optimization (PSO) technique with adaptive penalization and restart strategies, implemented in MATLAB for parameter autoadaptation. The article emphasizes more efficient solutions than traditional PSO, showcasing improved convergence and precise results (success probability of 66.1%). While traditional PSO is 81% faster, the proposed PSO stands out for its accuracy. The inclusion of thermal backfill results in an 18.45% increase in cable ampacity, considering variations in soil thermal resistivity, backfill properties, and ambient temperature. Additionally, a sensitivity analysis was conducted, revealing conservative values that support the proposal’s robustness. This approach emerges as a crucial tool for underground installation, contributing to continuous ampacity improvement and highlighting its impact on decision making in energy systems.

Trend Decomposition for Temperature Compensation in a Radar-Based Structural Health Monitoring System of Wind Turbine Blades

The compensation of temperature is critical in every structural health monitoring (SHM) system for achieving maximum damage detection performance. This paper analyses a novel approach based on seasonal trend decomposition to eliminate the temperature effect in a radar-based SHM system for wind turbine blades that operates in the frequency band from 58 to 63.5 GHz. While the original seasonal trend decomposition searches for the trend of a periodic signal in its entirety, the new method uses a moving average to determine trends for each point of a periodic signal. The points of the seasonal signal no longer need to have the same trend. Based on the determined trends, the measurement signal can be corrected by temperature effects, providing accurate damage detection results under changing temperature conditions. The performance of the trend decomposition is demonstrated with experimental data obtained during a full-scale fatigue test of a 31 m long wind turbine blade subjected to ambient temperature variations. For comparison, the well-known optimal baseline selection (OBS) approach is used, which is based on multiple baseline measurements at different temperature conditions. The use of metrics, such as the contrast in damage indicators, enables the performance assessment of both methods.

Structural damage identification under ambient temperature variations based on CNN and normalized modal flexibility-autoregressive coefficients hybrid index

This study proposes a novel method to identify structural damage considering ambient temperature variations. In this method, the normalized modal flexibility based index (nMFBI) and autoregressive (AR) coefficients are combined to form the nMFBI-AR hybrid index, and convolutional neural networks (CNN) are exploited to locate and quantify the damage. Moreover, the effects of ambient temperature variations and measurement noise are not considered in the training dataset, which is preferable in practical engineering. To verify the effectiveness of the proposed method, firstly, a numerical structure of a simply supported beam is investigated, and the performance of the nMFBI-AR index is evaluated by making a comparison with the nMFBI and AR indexes. Then, the proposed method is further verified by a test model of a three-story frame and a practical engineering example of a continuous rigid frame bridge. The results demonstrate that although the influence of ambient temperature variations and measurement noise are only considered in the test datasets, this approach has the best performance in locating and quantifying structural damage, and the errors are less than 16%, which is promising. In addition, this paper provides a guideline and a new idea for the study of damage index based on time-frequency hybrid information.

A conceptual model of polyoxymethylene dimethyl ether 3 (PODE3) spray combustion under compression ignition engine-like conditions

As one of the most popular synthetic fuels (E-fuels), Polyoxymethylene dimethyl ethers(PODEX) have garnered significant attention among researchers in the compression ignition engine field. This work aims to provide an exhaustive analysis of the combustion characteristics of PODE3, which typically constitutes the primary component of PODEX. This research seeks to deepen our understanding of the flame structure of PODE3, particularly in relation to ambient temperature variation, and unravel the underlying mechanisms driving the observed trends. To achieve this aim, a range of optical techniques was employed within a high-temperature high-pressure combustion vessel to quantify various general combustion parameters and assess OH* chemiluminescence, formaldehyde, and soot distribution. Two additional reference fuels, pure n-dodecane and a blend of 50 % vol n-dodecane and 50 % vol PODE3 were also tested. Additionally, some analysis from chemical kinetics and 1D spray model calculations were used to substantiate the experimental observations. The findings reveal that the flame structure of PODE3 differs significantly from traditional diffusion flames associated with diesel-like sprays. The flame lift-off length (LOL) of PODE3 aligns closely with that of n-dodecane, and maintains the two-lobe structure under high-temperature conditions. In contrast, under low ambient temperatures, the LOL of PODE3 significantly extends, accompanied by a concentration of OH* radicals at the spray center. The notable sensitivity of PODE3 flames to temperature variation is related to the chemical kinetics of formaldehyde and CO. As a result of the analysis, conceptual models of PODE3 flames under varying temperatures were proposed in the end.

Temperature drift suppression for micro‐electro‐mechanical system gyroscope based on vibrational‐displacement control with harmonic amplitude ratio

AbstractMicro‐electro‐mechanical system gyroscope detection output is susceptible to drift due to ambient temperature variations. Furthermore, the drive‐mode vibration amplitude is affected by the signal pickup circuit and structural parameters, which significantly influence the temperature drift of the bias and scale factor (SF). This study proposes a vibration amplitude control method based on harmonic amplitude sideband‐ratio (SBR), namely SBR‐AGC, which characterizes the vibration amplitude using the harmonic amplitude ratio of the vibrational electrical signal. The constancy of vibration amplitude is maintained via closed‐loop control to suppress bias and SF temperature drift. The experimental results on cobweb‐like disk resonator gyroscope reveal that the temperature coefficient of bias in the SBR‐AGC mode lies within −20 to 60°C and decreases by 36%, and the temperature coefficient of the SF lies within −10 to 50°C and decreases by 49.7%. Therefore, the environmental adaptability of the gyroscope is effectively improved.

High performance efficiency of optical networking infrastructure characteristics with maximum speed of commercial fiber optic line cables employment

Abstract Fiber optic communications have made great strides, and it is now the foundation of our telecommunications and data networking infrastructures. Due to its beneficial characteristics, including low attenuation, a large bandwidth, and immunity to electromagnetic interference, optical fiber is frequently acknowledged as a superior transmission medium. Optical fibers have been widely used to create high speed lines that can transmit either a single wavelength channel or many wavelength channels using wavelength division multiplexing due to their special features (WDM). The maximum speed of commercial fiber-optic cables was only 2.5 Gb/s and can be extended to 1 Tb/s for short and medium distance. The study clarifies the possible transmission distance for different transmission media silica/plastic optical fibers with various optical fiber window transmissions versus environmental ambient temperature variations. The study demonstrated the bad effects of the temperature effects on the optical fiber transmission media (silica/plastic fibers) for various transmission windows.

Ambient temperature variations and AIDS-related mortality: A time-stratified case-crossover study in 103 counties, China

BackgroundClimate change, characterized by the steady ascent of global temperatures and the escalating unpredictability of climate patterns, poses multifaceted challenges to public health worldwide. However, vulnerable groups, particularly the population affected by HIV/AIDS, have received little attention. ObjectivesWe aimed to examine the impacts of temperature variations on AIDS-related mortality. MethodsData on individuals with HIV/AIDS were collected from the HIV/AIDS Comprehensive Response Information Management System between 2013 and 2019. Temperature variation metrics were constructed by diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV0-t). Time-stratified case-crossover design with conditional logistic regression models was used to investigate the associations between ambient temperature variations and AIDS-related mortality. ResultsEach 1 °C elevated in DTR was linked with a 5.28 % [95 % confidence intervals (CIs): 1.61, 9.08] increment in AIDS-related mortality at a lag of 0–6 days. Stronger associations between DTR and AIDS-related mortality were observed in the married than in single, with corresponding excess ORs (%) of 5.33 (95 % CIs: 0.29, 10.62) versus 4.79 (95 % CIs: −0.50, 10.36) for 1 °C increased in DTR at lag 0–6 days. Additionally, we noticed the impact of DTR was more pronounced in the warm season, leading to a 7.32 % (95 % CIs: 0.57, 14.51) elevation in the risks of AIDS-related mortality for 1 °C increase in DTR at lag 0–6 days, while the effect value decreased to 5.16 % (95 % CIs: 0.71, 9.81) in the cold season. ConclusionsOur findings indicated that DTR might be a significant risk factor for AIDS-related deaths among ambient temperature variation indicators, and underscored the importance of considering temperature variability in public health interventions aimed at mitigating this risk of AIDS-related mortality.

Does the expensive brain hypothesis apply to amphibians and reptiles?

Vertebrate brains show extensive variation in relative size. The expensive brain hypothesis argues that one important source of this variation is linked to a species’ ability to generate the energy required to sustain the brain, especially during periods of unavoidable food scarcity. Here we ask whether this hypothesis, tested so far in endothermic vertebrates, also applies to ectotherms, where ambient temperature is an additional major aspect of energy balance. Phylogenetic comparative analyses of reptiles and amphibians support the hypothesis. First, relative brain size increases with higher body temperature in those species active during the day that can gain free energy by basking. Second, relative brain size is smaller among nocturnal species, which generally face less favorable energy budgets, especially when maintaining high body temperature. However, we do not find an effect of seasonal variation in ambient temperature or food on brain size, unlike in endotherms. We conclude that the factors affecting energy balance in ectotherms and endotherms are overlapping but not identical. We therefore discuss the idea that when body temperatures are seasonally very low, cognitive benefits may be thwarted and selection on larger brain size may be rare. Indeed, mammalian hibernators may show similarities to ectotherms.

Effect of Mn on the ZnBiMnO varistor ceramics sintered at a low-temperature of 875 °C

The effect of Mn on ZnO–Bi2O3 (ZnBiO) based varistor ceramics sintered below 900 °C has not been fully understood due to the conventional ZnBiO-based varistor ceramics usually being sintered at temperatures higher than 900 °C. Therefore, (99.5-x) ZnO+0.5Bi2O3+xMnCO3 (x = 0, 1, 2, and 3; all in mole ratio) ceramics were prepared by solid-state sintering at 875 °C for 3 h to study the effect of Mn on the microstructure, electrical nonlinear properties and their stability within the range of 25–100 °C. The results show that doping MnCO3 results in the formation of Mn3O4 and Bi12MnO20 secondary phases within the sintered samples. Mn3O4 mainly exists at grain boundary as particle phase, restricting the growth of ZnO grains during sintering. The presence of Bi12MnO20 indicates MnCO3 may enhance the sintering of ZnBiMnO ceramics by increasing the amount of Bi-rich liquid phase. MnCO3 effectively improves the electrical nonlinear properties of ZnBiMnO varistor ceramic and their stability against the variations in ambient temperature. The 2 mol% MnCO3 doped ZnBiMnO varistor ceramic shows the best electrical nonlinearity, with a nonlinear coefficient, a breakdown voltage and a leakage current density of 53.61, 503.11 V/mm, and 2.85 μA/cm2 respectively. This study may improve our understanding of the effect of Mn on the low-temperature sintered ZnBiO based varistor ceramics, and provide a promising candidate material for manufacturing low-cost ZnO based varistor.

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. This study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

Thermal conductivity-based hydrogen in argon detector (HAD): Design, development of instrumentation, and performance evaluation.

The Hydrogen in Argon Detectors (HADs) working on the principle of thermal conductivity difference between argon (reference) and argon + H2 (sample) in the cover gas of a sodium-cooled fast breeder reactor using the Wheatstone bridge circuit. The output of HAD is very sensitive to the gas flow rate and to the variation in ambient temperature. The RMSnoise of current was brought within ±1 µA by a constant current source across the bridge. The temperature correction factor fed in the processor brought down the RMSnoise in the HAD signal within ±2.4 mV than the uncorrected one having RMSnoise of ±230 mV. The filtered noise of HAD facilitates enhancing the detection limit of HAD down to 30 ppm (3σ) of hydrogen in argon.

Ambient temperature and seasonal variation in inpatient mortality from respiratory diseases: a retrospective observational study.

The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain. We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation. The study analysed 1710012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure. Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season. European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

Seasonal Association With Hypothermia inCombat Trauma.

Hypothermia increases mortality in trauma populations and frequently occurs in military casualties due to the nature of combat environments. The association between hypothermia and the time of year when injured remains unclear. We sought to determine the association between seasonal changes in temperature and hypothermia among combat casualties. This observational study was a secondary analysis of a previously described Department of Defense Trauma Registry dataset which included U.S. military and Coalition casualties who received prehospital care from January 2007 to March 2020 in Afghanistan and Iraq. We tested for associations between hypothermia (<36.2°C) and seasonal ambient temperatures by constructing multivariable logistic regression models. Summer was defined as June through August and winter as December through February. We assumed that the combat operations occurred in the area near the point of first contact with the deployed military treatment facilities. This study was determined to be exempt from Institutional Review Board oversight. There were 5,821 that met inclusion for this study. Within the multivariable logistic regression model, we adjusted for injury severity score, mechanism of injury, and imputed transport time, finding that combat casualties were 2.28 (odds ratio, 95% confidence interval 1.93-2.69) times more likely to develop hypothermia in the winter versus summer. When using temperature as a continuous outcome, casualties had a lower emergency department temperature during the winter (parameter estimate -0.133°C, P < 0.001) after adjusting for confounders. In casualties experiencing hypothermia, mortality was higher (4% versus 1%, P < 0.001), and composite median injury severity score values were higher (10 versus 5, P < 0.001). Among hypothermic casualties, serious injuries were significantly more common (all P < 0.001) to the head (15% versus 7%), thorax (15% versus 7%), abdomen (9% versus 6%), extremities (35% versus 22%), and skin (4% versus 2%). We found a seasonal variation in the occurrence of hypothermia in a large cohort of trauma casualties. Despite adjustment for multiple known confounders, our findings substantiate probable ambient temperature variations to trauma-induced hypothermia. Furthermore, our findings, when taken in the context of other studies on the efficacy of current hypothermia prevention and treatment strategies, support the need for better methods to mitigate hypothermia in future cold-weather operations.

Effect of ambient high-temperature on real driving emission tests of a light-duty gasoline vehicle

In real driving emission (RDE) test procedures, the extended high-temperature conditions of 30–35 °C are set to correct for the effect of ambient high-temperature on RDE tests. However, direct test data supporting or explaining the rationality of this provision remains lacking. To understand the impact of high-temperature environmental conditions on the RDE tests, ten RDE tests of a light-duty gasoline vehicle were conducted in an ambient temperature range of approximately 10–40 °C with the same driver and driving route. From the sample data of the ten RDE tests, the RDE tests were more affected by the non-temperature test conditions of trip dynamic, route topography, etc., than by the ambient temperature test conditions. The CO2, CO, NOx, and PN emissions were not sensitive to the variations in ambient temperature except for very few cases in urban CO2 and CO emissions. The ambient high-temperature conditions did not necessarily lead to severe pollutant emissions in the ten RDE tests. Extending the upper limit of the moderate temperature conditions upwards to a higher ambient temperature in the RDE test procedures should be considered.

Significance of slight ambient temperature variation on the electrocatalyst performance toward oxygen evolution reaction

Hundreds of oxygen evolution reaction (OER) electrocatalysts have been developed over the past few decades, and their performances are evaluated and compared at ambient temperature. However, the effect of ambient temperature variation on OER electrocatalyst performance has received less attention, which may play a remarkable role in the electrocatalytic activity. In this work, we systematically investigated the influence of ambient temperature variation on electrocatalyst performance toward OER. The results show that the slight ambient temperature variation has a significant effect on OER catalyst performance based on the changes of overpotential (10 mA cm−2) and Tafel slope. Both remarkable chances are observed on transition metal (Ni) and noble metal (IrO2) electrocatalysts, and the overpotentials decrease around 81 mV with a temperature increase by 20 °C (from 10° to 30°C) for both Ni and IrO2 electrocatalysts with the Tafel slope drops of 36.9 and 29.5 mV dec−1, respectively. A similar trend is also found in the electrochemically active surface (ECSA) normalized performance and the charge transfer resistance. This study demonstrates that reporting the actual operating temperature for OER is not only recommended but also necessary to evaluate and compare electrocatalyst activities from different materials systems properly, and neglecting the ambient temperature variation effect can highly mislead conclusions.

Hydrogen production using hybrid six-step copper-chlorine thermochemical cycle: Energy and exergy analyses

The hybrid thermochemical copper-chlorine (Cu–Cl) cycle for water splitting, developed as a novel approach to produce green hydrogen, has gained greater attention. A series of close-loop reactions makes the process environmentally friendly. A newly developed hybrid six-step Cu–Cl cycle consists of thermochemical, electrochemical, and a unit operation of spray drying. The present paper analyzes the configuration of the six-step Cu–Cl cycle thermodynamically. Studies on many factors are carried out to determine the cycle's total energy and exergy efficiency. The modeling and simulation of the six-step process was done by Aspen Plus. The six-step cycle was found to have an energy and exergy efficiency of 38.94 % and 52.74 %, respectively. The effect on exergetic efficiency with ambient temperature and cycle temperature variation was also investigated. The enhancement in the effectiveness of six steps Cu–Cl cycle could be possible from the current study analysis using thermal recovery and minimizing exergy destructions.

D-Band Thin-Film Resistive Line Bolometer as Transfer Standard

A bolometric thin-film-based transfer standard with a novel structure for absolute power detection in D-band (110–170 GHz) is reported. It uses a resonance-type matching technique with thin-film resistive lines. The same line functions as the sensing element. The change in the resistivity of the line under the incident wave is calibrated to measure the absolute RF power in the D-band. This article presents the analysis using equivalent circuit models, the full-wave electromagnetic design, the fabrication, and the comprehensive characterization of the device. The comparison between a single and a folded-line matching structure is performed, showing the wideband capability of the latter. The transfer standard consists of two sensors in one waveguide housing for RF power measurement, as well as for monitoring and calibrating out the ambient temperature variation. It has shown a very good short-term time response with only <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula> 0.19% deviation in a given time interval, which is very close to a commercial PM5 sensor with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula> 0.27% deviation. The long-term time response is also impressive, with a deviation of less than 0.6%, similar to a commercial PM5 sensor. The fast response time, good thermal isolation, and ambient compensation ability make it suitable for transfer/working standards, which can be used in ambient temperature environments.

Optimization of power feedback control system for HCN interferometer on EAST Tokamak

The Hydrogen Cyanide (HCN) interferometer stands as an indispensable diagnostic tool, designated to measure the line-integrated electron density on the Experimental Advanced Superconducting Tokamak (EAST), thereby offering essential density feedback signals for EAST operation. The HCN laser used in the interferometer is a continuous glow discharge gas laser. However, owing to variations in external ambient temperature, the HCN laser exhibits output power instability. The current power automatic feedback control system for the HCN laser interferometer exhibits low actuator adjustment precision, thereby limiting its ability to achieve maximum output power. Moreover, the system may cause a temporary power drop to zero during adjustment, while EAST operation requires the HCN laser interferometer to maintain high power continuously. In order to solve the issues, this paper developed an innovative actuator that ingeniously amalgamates the virtues of piezoelectric ceramic and stepper motor. This novel actuator, demonstrating a broad adjustment range and high precision, is intended to replace the present one in the HCN interferometer power control system. While the stepper motor executes coarse adjustment, the piezoelectric ceramic enables precise adjustment, thus enhancing the adjustment accuracy of the automatic power control system to a sub-micrometer level and an adjustment range greater than 5 mm. Accurate determination of the regulator's adjustment direction can significantly improve the efficiency of adjustment. The slope of the laser output power peak decreases as it approaches the maximum value, and increases as it moves away from the maximum value. Therefore, this system replaces the original threshold algorithm with a slope algorithm. By correctly judging the adjustment direction, the efficiency of adjustment is improved. Furthermore, this algorithm can keep the output power stable on a power peak. There will be no instances of zero power output during the adjustment, allowing the power to remain stable above the set threshold for a long time. Currently, this system has been successfully applied to the HCN interferometer, and testing has found that the system can maintain stability for at least 16 hours. Furthermore, even when the laser output power was intentionally reduced to below the set threshold, the system was able to respond quickly and adjust the output, rapidly restoring it to above the predefined threshold. Multiple tests have shown the strong robustness of the system, indicating it meets the stringent demands of the EAST's complex environment.