Search Results (68)

Articulated arm coordinate measuring machines are designed for in situ use directly in manufacturing environments, enabling efficient dimensional control outside of climate-controlled laboratories. This study investigates the influence of ambient temperature variation on the accuracy of length measurements performed with the Hexagon Absolute Arm 8312. The experiment was carried out in a laboratory setting simulating typical shop floor conditions through controlled temperature changes in the range of approximately 20–31 °C. A calibrated steel gauge block was used as a reference standard, allowing separation of the influence of the measuring system from that of the measured object. The results showed that the gauge block length changed in line with the expected thermal expansion, while the articulated arm coordinate measuring machine exhibited only a minor residual thermal drift and stable performance. The experiment also revealed a constant measurement offset of approximately 22 µm, likely due to calibration deviation. As part of the study, an uncertainty budget was developed, taking into account all relevant sources of influence and enabling a more realistic estimation of accuracy under operational conditions. The study confirms that modern carbon composite articulated arm coordinate measuring machines with integrated compensation can maintain stable measurement behavior even under fluctuating temperatures in controlled environments. Full article

This paper presents the design and implementation of a high-efficiency, full silicon carbide (SiC)-based center-tapped phase-shifted full-bridge (PSFB) converter for NiCd battery charging applications in railway systems. The converter utilizes SiC MOSFET modules on the primary side and SiC diodes on the secondary side, resulting in significant efficiency improvements due to the superior switching characteristics and high-temperature tolerance inherent in SiC devices. A nanocrystalline-cored center-tapped transformer is optimized to minimize voltage stress on the rectifier diodes. Additionally, the use of a nanocrystalline core provides high saturation flux density, low core loss, and excellent permeability, particularly at high frequencies, which significantly enhances system efficiency. The converter also compensates for temperature fluctuations during operation, enabling a wide and adjustable output voltage range according to the temperature differences. A prototype of the 10-kW, 50-kHz PSFB converter, operating with an input voltage range of 700–750 V and output voltage of 77–138 V, was developed and tested both through simulations and experimentally. The converter achieved a maximum efficiency of 97% and demonstrated a high power density of 2.23 kW/L, thereby validating the effectiveness of the proposed design for railway battery charging applications. Full article

The radial magnetic bearing system is an open-loop, unstable, strong nonlinear system with a high rotor speed, predisposition to jitter, and poor interference immunity. The system is subjected to the main interference generated by gravity, and rotor imbalance and sensor runout seriously affect the system’s rotor position control performance. A plug-in repetitive control method based on equivalent-input-disturbance (EID) is presented to address the issue of decreased control accuracy of the magnetic bearing system caused by disturbances from gravity, rotor imbalance, and sensor runout. First, a linearized model of the magnetic bearing rotor containing parameter fluctuations due to the eddy current effect and temperature rise effect is established, and a plug-in repetitive controller (PRC) is designed to enhance the rejection effect of periodic disturbances. Next, an EID system is introduced, and a Luenberger observer is used to estimate the state variables and disturbances of the system. The estimates of the EID are then used for feedforward compensation to address the issue of large overshoot in the system. Finally, simulations are conducted for comparison with the PID control method and PRC control method. The plug-in repetitive controller method assessed in this paper improves control performance by an average of 87.9% and 57.7% and reduces the amount of over-shooting by an average of 66.5% under various classes of disturbances, which proves the efficiency of the control method combining a plug-in repetitive controller with the EID theory. Full article

Heating, ventilation, and air conditioning (HVAC) systems and microgrids have garnered significant attention in recent research, with temperature control and renewable energy integration emerging as key focus areas in urban distribution power systems. This paper proposes a robust predictive temperature control (RPTC) method and a microgrid control strategy incorporating asymmetrical challenges, including uneven power load distribution and uncertainties in renewable outputs. The proposed method leverages a thermodynamics-based R-C model to achieve precise indoor temperature regulation under external disturbances, while a multisource disturbance compensation mechanism enhances system robustness. Additionally, an HVAC load control model is developed to enable real-time dynamic regulation of airflow, facilitating second-level load response and improved renewable energy accommodation. A symmetrical power tracking and voltage support secondary controller is also designed to accurately capture and manage the fluctuating power demands of HVAC systems for supporting operations of distribution power systems. The effectiveness of the proposed method is validated through power electronics simulations in the Matlab/Simulink/SimPowerSystems environment, demonstrating its practical applicability and superior performance. Full article

This paper solves the challenge of precise dual-frequency laser control in Airborne Coherent Doppler LiDAR systems by implementing an innovative laser driver architecture, which integrates compact hardware design with cascade Proportional-Integral-Derivative (PID) control and a frequency–temperature compensation mechanism. The experimental results demonstrate eminent performance with long-term temperature fluctuation below 0.007 °C, temperature stabilizing time under 4 s and long-term power fluctuation of the linear constant current source being <1%. The system enables wide-range temperature–frequency adjustment for individual lasers and dynamically adjusts the dual-laser beat frequencies between −1 GHz and +2 GHz, achieving the frequency difference fluctuation within 3 MHz. These achievements greatly enhance LiDAR performance and create possibilities for broader applications in dynamic environmental sensing, atmospheric monitoring, deep-space exploration, and autonomous systems. Full article

Lithium-ion batteries are the core energy storage technology for electric vehicles and energy storage systems. Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. This review systematically examines the research progress on SOC estimation techniques over a wide temperature range, focusing on two mainstream approaches: model improvement and data-driven methods. The model improvement method enhances temperature adaptability through temperature compensation and dynamic parameter adjustment. Still, it has limitations in dealing with the nonlinear behavior of batteries and accuracy and real-time performance at extreme temperatures. In contrast, the data-driven method effectively copes with temperature fluctuations and complex operating conditions by extracting nonlinear relationships from historical data. However, it requires high-quality data and substantial computational resources. Future research should focus on developing high-precision, temperature-adaptive models and lightweight real-time algorithms. Additionally, exploring the deep coupling of physical models and data-driven methods with multi-source heterogeneous data fusion technology can further improve the accuracy and robustness of SOC estimation. These advancements will promote the safe and efficient application of lithium batteries in electric vehicles and energy storage systems. Full article

Complex scenarios pose challenges to tasks in computer vision, including image fusion, object detection, and image-to-image translation. On the one hand, complex scenarios involve fluctuating weather or lighting conditions, where even images of the same scenarios appear to be different. On the other hand, the large amount of textural detail in the given images introduces considerable interference that can conceal the useful information contained in them. An effective solution to these problems is to use the complementary details present in multi-modal images, such as visible-light and infrared images. Visible-light images contain rich textural information while infrared images contain information about the temperature. In this study, we propose a multi-modal registered dataset for complex scenarios under various environmental conditions, targeting security surveillance and the monitoring of low-slow-small targets. Our dataset contains 30,819 images, where the targets are labeled as three classes of “person”, “car”, and “drone” using Yolo format bounding boxes. We compared our dataset with those used in the literature for computer vision-related tasks, including image fusion, object detection, and image-to-image translation. The results showed that introducing complementary information through image fusion can compensate for missing details in the original images, and we also revealed the limitations of visual tasks in single-modal images with complex scenarios. Full article

The quartz flexible accelerometer (QFA) is a critical component in navigation-grade strapdown inertial navigation systems (SINS) due to its bias error, which significantly impacts the overall navigation accuracy of SINS. Temperature variations induce dynamic changes in the bias and scale factor of QFA, leading to a degradation of the navigation accuracy of SINS. To address this issue, this paper proposes a temperature error compensation method based on a non-uniform mutation strategy genetic algorithm (NUMGA) and a polynomial curve model (PCF). Firstly, the temperature bias mechanism of QFA output is analyzed, and a polynomial temperature error model is established. Then, the NUMGA is utilized to identify the model parameters using the −20–40 °C test data, seeking the optimal parameters for the polynomial. Finally, the compensation parameters are used for cold start static test verification. The results demonstrate that the temperature compensation model based on NUMGA-PCF can automatically select the optimal parameters, which enable the model to exhibit a stable decreasing trend on the adaptation curve without multiple fluctuations. Compared to the traditional GA temperature compensation model, the compensation errors in the three axes of QFA in SINS are reduced by 612.24 μg, 60.82 μg, and 875.82 μg, respectively. Before the 20th generation, there are no decrease in convergence speed observed with the in-crease of population diversity. Within the −20–40 °C temperature range, the average values and standard deviations of QFA for the three optimized axes can be maintained below 0.1 μg by using this compensation model. Full article

Sustainability is becoming increasingly important in the world we live in, because of the rapid global population growth and climate change (drought, extreme temperature fluctuations). People in developing countries need more sustainable protein sources instead of the traditional, less sustainable meat, fish, egg, and dairy products. Alternative sources (plant-based, such as grains (wheat, rice sorghum), seeds (chia, hemp), nuts (almond, walnut), pulses (beans, lentil, pea, lupins), and leaves (duckweed), as well as mycoproteins, microalgae, and insects) can compensate for the increased demand for animal protein. In this context, our attention has been specifically focused on duckweed—which is the third most important aquatic plant after the microalgae Chlorella and Spirulina—to explore its potential for use in a variety of areas, particularly in the food industry. Duckweed has special properties: It is one of the fastest-growing plants in the world (in freshwater), multiplying its mass in two days, so it can cover a water surface quickly even in filtered sunlight (doubling its biomass in 96 hours). During this time, it converts a lot of carbon dioxide into oxygen. It is sustainable, environmentally friendly (without any pesticides), and fast growing; can be grown in indoor vertical farms and aquaculture, so it does not require land; is easy to harvest; and has a good specific protein yield. Duckweed belongs to the family Araceae, subfamily Lemnoideae, and has five genera (Lemna, Spirodela, Wolffia, Wolffiella, Landolita) containing a total of approximately 36–38 recognised species. Duckweed is gaining attention in nutrition and food sciences due to its potential as a sustainable source of protein, vitamins, minerals, and other bioactive compounds. However, there are several gaps in research specifically focused on nutrition and the bioaccessibility of its components. While some studies have analysed the variability in the nutritional composition of different duckweed species, there is a need for comprehensive research on the variability in nutrient contents across species, growth conditions, harvesting times, and geographic locations. There has been limited research on the digestibility, bioaccessibility (the proportion of nutrients that are released from the food matrix during digestion), and bioavailability (the proportion that is absorbed and utilised by the body) of nutrients in duckweed. Furthermore, more studies are needed to understand how food processing (milling, fermentation, cooking, etc.), preparation methods, and digestive physiology affect the nutritional value and bioavailability of the essential bioactive components in duckweed and in food matrices supplemented with duckweed. This could help to optimise the use of duckweed in human diets (e.g., hamburgers or pastas supplemented with duckweed) or animal feed. More research is needed on how to effectively incorporate duckweed into diverse cuisines and dietary patterns. Studies focusing on recipe development, consumer acceptance, palatability, and odour are critical. Addressing these gaps could provide valuable insights into the nutritional potential of duckweed and support its promotion as a sustainable food source, thereby contributing to food security and improved nutrition. In summary, this article covers the general knowledge of duckweed, its important nutritional values, factors that may affect their biological value, and risk factors for the human diet, while looking for technological solutions (covering traditional and novel technologies) that can be used to increase the release of the useful, health-promoting components of duckweed and, thus, their bioavailability. This article, identifying gaps in recent research, could serve as a helpful basis for related research in the future. Duckweed species with good properties could be selected by these research studies and then included in the human diet after they have been tested for food safety. Full article

Optically pumped magnetometers (OPMs) functioning in the spin-exchange relaxation-free (SERF) regime have emerged as attractive options for measuring weak magnetic fields, owing to their portability and remarkable sensitivity. The operation of SERF-OPM critically relies on the ambient magnetic field; thus, a magnetic field compensation device is commonly employed to mitigate the ambient magnetic field to near zero. Nonetheless, the bias of the OPM may influence the compensation impact, a subject that remains unexamined. This paper introduced an innovative bias calibration technique for OPMs. The sensitivity of the OPM was altered by adjusting the cell temperature. The output of the OPM was then documented with varying sensitivity. It is assumed that the signal exhibits a linear correlation with the environmental magnetic field, and the statistical characteristics of the magnetic field are identical for both measurements, upon which the bias of the OPM is assessed. The bias was subsequently considered in the feedback magnetic field compensation mechanism. The results indicate that this technique might successfully reduce environmental magnetic fluctuations and enhance the sensitivity of the OPM. This technique measured the magnetic field produced by the human heart, confirming the viability of the ultra-weak biomagnetic field measurement approach. Full article

High-voltage cables are widely used in power transmission and distribution systems, and their accessories (such as connectors, terminals, and insulators) are key parts to ensure the safe and reliable operation of power systems. These accessories may be affected by factors such as temperature, humidity, and mechanical stress during long-term operation, resulting in performance degradation or failure. In high-voltage environments, performance monitoring of cable accessories is crucial. The reference voltage circuit can withstand the influence of temperature changes and power supply fluctuations, support accurate current and voltage measurement, and thus detect potential faults in time to ensure the safe and stable operation of the power system. However, the traditional reference voltage circuit has a low-temperature curvature loss, which results in an inaccurate reference voltage, resulting in equipment damage. Therefore, in order to solve the problem of curvature loss in this part, this paper proposes a curvature compensation circuit, which realizes a high-precision reference voltage circuit through a high-temperature curvature compensation circuit, thereby meeting the current reference voltage requirements for cable accessory monitoring. Full article

Microwave radiometers are passive remote sensing devices that provide important observational data on the state of the oceanic and terrestrial atmosphere. Temperature retrieval accuracy is crucial for radiometer performance. However, inversions during strong convective weather or seasonal phenomena are short-lived and spatially limited, making it challenging for neural network algorithms trained on historical data to invert accurately, leading to significant errors. This paper proposes a long short-term memory (LSTM) network forecast correction model based on the temperature inversion phenomenon to resolve these large temperature inversion errors. The proposed model leverages the seasonal periodicity of atmospheric temperature profiles in historical data to form a circumferential background field, enabling the prediction of expected background profiles for the forecast day based on temporal and spatial continuity. The atmospheric profiles obtained using the radiometer retrieval are compensated with the forecast temperature inversion vector on the forecast day to obtain the final data. In this study, the accuracy of the forecast correction model was verified utilizing meteorological records for the Taizhou area from 2013 to 2017. Using a hierarchical backpropagation network based on the residual module for comparison, which had a forecast accuracy error of 0.0675 K, the error of our new model was reduced by 34% under the temperature inversion phenomenon. Meanwhile, error fluctuations were reduced by 33% compared with the residual network algorithm, improving the retrieval results’ stability in the temperature inversion state. Our results provide insights to improve radiometer remote sensing accuracy. Full article

The development and calibration of a measurement system designed for assessing the performance of the avalanche photodiodes (APDs) used in the Compton scattering polarimeter of the CUSP project is discussed in this work. The designed system is able to characterize the APD gain $G_{APD}$ and energy resolution across a wide range of temperatures T (from −20 °C to +60 °C) and bias voltages $V_{bias}$ (from 260 V to 410 V). The primary goal was to experimentally determine the $G_{APD}$ dependence on the T and $V_{bias}$ in order to establish a strategy for stabilizing $G_{APD}$ by compensating for T fluctuations, acting on $V_{bias}$. The results demonstrate the system capability to accurately characterize APD behavior and develop feedback mechanisms to ensure its stable operation. This work provides a robust framework for calibrating APDs for space environments. It is essential for the successful implementation of spaceborne polarimeters such as the Compton scattering polarimeter foreseen aboard the CUbeSat Solar Polarimeter (CUSP) mission under development to perform solar flare X-ray polarimetry. Full article

Continual climate change strongly influences temperature conditions worldwide, making ectothermic animals as suitable species for studying the potential impact of climate change on global biodiversity. However, the study of how lizards distributed at different latitudes respond to climate change at the transcriptome level is still insufficient. According to the Climatic Variability Hypothesis (CVH), the range of climate fluctuations experienced by terrestrial animals throughout the year increases with latitude, so individuals at higher latitudes should exhibit greater thermal plasticity to cope with fluctuating environments. Mitochondria, as the energy center of vertebrate cells, may indicate species’ plasticity through the sensitivity of gene expression. In this study, we focused on the changes in transcript levels of liver mitochondrial protein-coding genes (PCGs) in skinks from the genus Plestiodon (P. capito and P. elegans) and the genus Scincella (S. modesta and S. reevesii) under low-temperature conditions of 8 °C, compared to the control group at 25 °C. Species within the same genus of skinks exhibit different latitudinal distribution patterns. We found that the two Plestiodon species, P. elegans and P. capito, employ a metabolic depression strategy (decreased transcript levels) to cope with low temperatures. In contrast, the two Scincella species show markedly different patterns: S. modesta exhibits significant increases in the transcript levels of six genes (metabolic compensation), while in S. reevesii, only two mitochondrial genes are downregulated (metabolic depression) compared to the control group. We also found that P. capito and S. modesta, which live at mid-to-high latitudes, exhibit stronger adaptive responses and plasticity at the mitochondrial gene level compared to P. elegans and S. reevesii, which live at lower latitudes. We suggest that this enhanced adaptability corresponds to more significant changes in a greater number of genes (plasticity genes). Full article

This paper presents the design of a strain-sensitive, dual ball-shaped tunable zone (DBT) taper structure for light intensity modulation. Unlike conventional tapered optical fibers, the DBT incorporates a central light field modulation zone within the taper. By precisely controlling the fusion parameters between single-mode fiber (SMF) and polarization-maintaining fiber (PMF), the ellipticity of the modulation zone can be finely adjusted, thereby optimizing spectral characteristics. Theoretical analysis based on polarization mode interference (PMI) coupling confirms that the DBT structure achieves a more uniform spectral response. In cantilever beam strain tests, the DBT exhibits high sensitivity and a highly linear intensity–strain response (R² = 0.99), with orthogonal linear polarization mode interference yielding sensitivities of 0.049 dB/με and 0.023 dB/με over the 0–244.33 με strain range. Leveraging the DBT’s light intensity sensitivity, a temperature-compensated intensity difference and ratio calculation method is proposed, effectively minimizing the influence of light source fluctuations on sensor performance and enabling high-precision strain measurements with errors as low as ±6 με under minor temperature variations. The DBT fiber device, combined with this innovative demodulation technique, is particularly suitable for precision optical sensing applications. The DBT structure, combined with the novel demodulation method, is particularly well-suited for high-precision and stable measurements in industrial monitoring, aerospace, civil engineering, and precision instruments for micro-deformation sensing. Full article