Method For Arrays Research Articles

A parameterized model of center-symmetric space deployable arrays inspired by Miura and five-crease origami

Thick-panel origami has gained significant attention for its potential applications in the design of space deployable arrays. However, existing origami structures often fail to meet the stringent constraints imposed by various spacecraft in terms of connectivity and space efficiency, limiting the achievement of optimal folding ratios and compact transportation. To address these challenges, we propose a parameterized geometric model and design method for center-symmetric thick-panel space deployable arrays for varying scales and functions, integrating five-crease vertices with Miura origami. A planar four-bar linkage mechanism is applied to coordinate the motion between the five-crease vertices and Miura origami, ensuring one-degree-of-freedom (one-DOF) motion. The proposed model is validated through a case study on a space exposure experiment platform, with a scaled-down prototype fabricated for testing. The resulting space deployable arrays can be compactly placed within a rectangular prism, offering central symmetry, one-DOF motion, high volume efficiency and folding ratio, and enhanced design flexibility and adaptability.

Distributed planning method for detection array of UAV formation with bearing-only sensor network

Abstract Unmanned aerial vehicle (UAV) formations for bearing-only passive detection are increasingly important in modern military confrontations, and the array of the formation is one of the decisive factors affecting the detection accuracy of the system. How to plan the optimal geometric array in bearing-only detection is a complex nondeterministic polynomial problem, and this paper proposed the distributed stochastic subgradient projection algorithm (DSSPA) with layered constraints to solve this challenge. Firstly, based on the constraints of safe flight altitude and fixed baseline, the UAV formation is layered, and the system model for bearing-only cooperative localisation is constructed and analysed. Then, the calculation formula for geometric dilution of precision (GDOP) in the observation plane is provided, this nonlinear objective function is appropriately simplified to obtain its quadratic form, ensuring that it can be adapted and used efficiently in the system model. Finally, the proposed distributed stochastic subgradient projection algorithm (DSSPA) combines the idea of stochastic gradient descent with the projection method. By performing a projection operation on each feasible solution, it ensures that the updated parameters can satisfy the constraints while efficiently solving the convex optimisation problem of array planning. In addition to theoretical proof, this paper also conducts three simulation experiments of different scales, validating the effectiveness and superiority of the proposed method for bearing-only detection array planning in UAV formations. This research provides essential guidance and technical reference for the deployment of UAV formations and path planning of detection platforms.

A fast calibration and testing method for large-scale phased array

A fast calibration and testing method for large-scale phased array

Sparse loudspeaker array design for wideband frequency-invariant beamforming with multiple targets.

Beamforming technology using loudspeaker arrays is widely used in sound applications, but current sparse array design methods focus on optimizing a single beam for a single target direction, limiting their applicability to multi-channel sound systems. This paper presents a design method for sparse loudspeaker line arrays to generate wideband frequency-invariant beams in multiple target directions. A model based on tapped delay lines is developed and a two-stage design approach is proposed. In the first stage, a compressive sensing framework combined with an extended fast iterative shrinkage-thresholding algorithm is employed to determine the optimal locations of active drivers. In the second stage, the excitations of the active drivers are calculated using the least squares method. Numerical simulations show a 32.3% reduction in the number of drivers compared to that of traditional uniform linear loudspeaker arrays while maintaining frequency-invariant properties. The proposed algorithm exhibits considerable computational efficiency, rendering it highly suitable for addressing large-scale optimization problems and substantially reducing the design time. This design method is applicable to sound projection scenarios and can be extended to other multi-channel beamforming systems to achieve reliable beam performance and reduce system costs.

A real-time signal space separation method for a 32-channel planar sensor array

A real-time signal space separation method for a 32-channel planar sensor array

Dual-Wavelength Synchronous Control Method for Liquid Crystal Optical Phased Array

Dual-Wavelength Synchronous Control Method for Liquid Crystal Optical Phased Array

Liquid Chromatography Column Screening for the Analysis of Corrosion Inhibitor Molecules Using Derringer Desirability Functions.

Corrosion inhibitors (CIs) are extensively employed in the oil and gas industry, yet their analysis remains a challenge. To develop a suitable liquid chromatography method for a wide array of CIs, a column screening was conducted. Nine different chromatographic conditions were tested across eight RPLC and mixed-mode columns (Accucore C18, CORTECS Shield RP18, Acquity HSS T3, Acquity Premier HSS T3, Accucore 150-C4, Accucore PFP, Synergi Polar RP, and Acclaim WCX-1). Seven model mixtures representative of CIs, which included quaternary ammoniums, imidazolines, and phosphoric esters, were considered to probe the columns. Each column exhibited unique analytical performances, peak shape, and separation profiles. To find a compromise to analyze all the mixtures with one method, Derringer desirability functions were used. Shielding of residual silanols proved to be a critical factor. The trifunctional grafting of the Acquity HSS T3 columns appeared to be a promising strategy to minimize residual silanol effects. However, it was the Premier technology, which protects the column's inner walls and frits against parasitic adsorption, which delivered the best overall results. Based on the desirability study, the Acquity Premier HSS T3 column was selected and the gradient was optimized, which enabled the separation of the molecules present in the model mixtures.

Research on Fault Diagnosis Method for Photovoltaic Array Based on XGBoost Algorithm

INTRODUCTION: Photovoltaic (PV) energy sources frequently experience issues, including fragmentation, open-circuit, short-circuiting, and other common and hazardous problems. The current focus of PV research is on fault detection within solar arrays. Traditional models encounter challenges in identifying errors due to uncertainties in panel settings and the complex nature of the actual PV structure.OBJECTIVES: This study aims to introduce a novel Extreme Gradient Boosting (XGBoost) approach for fault diagnosis in PV arrays.METHODS: The XGBoost algorithm is trained using collected PV array defect data samples. Data preprocessing is performed to manage missing values and remove noisy data. Feature extraction is conducted using Linear Discriminant Analysis (LDA) to improve detection accuracy. To further enhance XGBoost’s performance, the World Cup Optimization (WCO) approach is applied to select optimal features from the extracted data. Fault detection is then conducted using the XGBoost algorithm on the processed data. Various indicators are utilized for performance assessment within the Python environment.RESULTS: The comparative analysis demonstrates that this research improves fault detection efficiency in PV arrays compared to existing methodologies.CONCLUSION: The study presents an effective method for enhancing fault detection in PV systems, showcasing the advantages of the XGBoost and WCO-based approach over conventional methods.

Parameters Estimation and Curves Analysis for Faults Evaluation of a Degraded Photovoltaic Module

In the present work, a fault evaluation method for photovoltaic arrays based on fault parameters identification and curves analysis is proposed for diagnosing the state of photovoltaic generators. An overview of the components, the modelling of the photovoltaic generator and the meaning of the parameters is established for relating parameters to photovoltaic components and environmental conditions. The analysis and investigation of the relationship between the maximum power points and the parameters variations are performed. Investigation on how degradations and failure on photovoltaic systems can affect parameters, is established. In this context, the methodology for diagnosing and monitoring defects based on photovoltaic estimated parameters is developed; the optimization technique maximum likelihood, is used for extracting health and faults parameters from the measured curves of the photovoltaic array. From residual vectors, the parameters which vary more are the series resistance, the shunt resistor, and the current of photon. The maximum power also changes and decreases from its reference value. The validation results prove deviations on parameters, which means that there are degradations and failures on the ARCO Solar M75 array after 20 years of outdoors operation. So, at the end of this analysis, it is recommended to act on the PV system through junction box, cell edges, wiring, busbars, and connectors.

A Novel Near-Field Calibration Method for Linear Array Based on Plane Wave Expansion

A Novel Near-Field Calibration Method for Linear Array Based on Plane Wave Expansion

Reduced-dimension STAP method for conformal array based on sequential convex programming

Compared with the uniform arrays, the conformal array can effectively reduce the radar cross section and improve the utilization of the limited space in the aircraft. However, the special array structure aggravates the non-stationarity of the clutter, and the typical blocking matrix construction method in the space–time adaptive processing (STAP) is not appropriate any more. To address these issues, a reduced dimension STAP algorithm based on penalty sequential convex programming in the generalized sidelobe cancellation structure is proposed. The blocking matrix, channel selection vector and STAP weights can be optimized simultaneously in the algorithm framework. To tackle the resultant nonconvex problem, we formulate the original optimization function as a quasi-convex form and solve these parameters alternately within an iterative framework. Numerical simulations are provided to validate the proposed method and demonstrate its high performance.

Saving energy resources during operation of rolling stock of underground electrified transport

Purpose. To analyze the energy saving reserves under the conditions of implementation and integration of the system in order to find rational driving modes in the general system of managing underground electrified transport. Methodology. The work presents the method for processing data arrays obtained experimentally with the help of a measuring system and theoretically with the use of the “Rational Trajectory” software. Findings. Experimental studies were carried out using a testing system created on the basis of a refurbished train with energy recovery system. Theoretical studies were carried out using the “Rational Trajectory” software, which is based on the principle of solving a multi-criteria problem by the method of the main criterion. The minimum amount of electricity consumption from the overhead contact line was chosen as the main criterion. The software was developed in the LabVIEW graphical programming environment in order to determine the rational modes of driving rolling stock and energy indicators in a given area of its operation. The amount of electricity consumed for traction and the amount of electricity generated by the train during regenerative braking were determined based on the results of experimental and theoretical studies, respectively, under typical and rational modes of driving the train for given identical operating conditions. Originality. Further research on the analysis of energy saving reserves on the rolling stock of underground electrified transport was achieved due to the introduction of a system for finding a rational driving mode. Practical value. It has been established that the implementation and incorporation of the “Rational Trajectory” software into the train control system will save up to 14.7 % of the amount of electricity consumed for traction, compared to typical modes operation on a given track section.

An RD-Domain Virtual Aperture Extension Method for Shipborne HFSWR

High-frequency surface wave radar (HFSWR) is widely used for detecting sea surface or low-altitude targets due to its all-weather operation and over-the-horizon detection capability. To further enhance the maneuverability and detection range of HFSWR, shipborne HFSWR has been developed. However, compared to shore-based platforms, shipborne platforms face challenges such as a small array aperture and reduced Direction of Arrival (DOA) estimation performance due to their limited size. The traditional time–domain virtual aperture extension method, based on the principle of space-time equivalence, aims to improve the array aperture but has limitations when used for HFSWR background or multiple targets with different speeds. To address these issues, this paper proposes a range-Doppler domain (RD-domain) virtual aperture extension method for the uniform linear array, based on the uniform motion model. The contributions of this work include (1) a continuous motion model for shipborne HFSWR, (2) a virtual aperture processing flowchart for shipborne HFSWR, and (3) an RD-domain aperture extension method suitable for HFSWR background or multiple targets with varying speeds. Through simulation and experimental data, we validate the proposed method and analyze its performance.

Decoupling for microstrip antenna array based on characteristic mode analysis

AbstractA new decoupling method for microstrip antenna arrays has been proposed in this paper, which is based on characteristic mode analysis. This method works by suppressing the nonworking mode that contributes the most to mutual coupling. An eight‐element microstrip antenna array is designed as the reference antenna, and for this antenna, mode suppression is achieved by etching gaps on the patch and adding metal columns between the patch and the ground. The antenna array after the mode suppression is fabricated and measured. The results show that the measured S34 after the mode suppression is below −21 dB, whereas the simulated S34 of the reference antenna array is about −15 dB. This indicated a 7–10.5 dB reduction in coupling across the band. Additionally, the measured ActiveS3 after the mode suppression is still below −11 dB. Besides, the measured and simulated normalized array patterns after the mode suppression agree well at different frequencies.

Research on optimization of flatness evaluation method for antenna array of a radar vehicle

Abstract Radar vehicles play an important role in providing radar services in the aviation field. The flatness of the antenna array is one of the key factors in ensuring the detection accuracy of radar vehicles for airborne targets. In this paper, the mechanical structure of a new type of radar antenna truck is designed, the stress analysis under various working conditions is carried out, the mechanical performance of the whole vehicle is checked, and the evaluation method of the flatness of the antenna array is discussed. Using ANSYS to carry out static finite element analysis and using the deformation results of each element node in ANSYS, the evaluation method based on the multiple regression function is applied to the calculation scheme of antenna array flatness. The final results show that the safety factor of the radar vehicle structure can reach more than 1.75 under extreme working conditions and more than 2.0 under other working conditions. It can work safely. Through the optimization of the shape evaluation method, the accuracy of the final shape calculation result is less than 10mm. The precision of shape error processing is improved.

Research on the vector DOA estimation method with limited number of snapshots

The number of sample snapshots of array signals directly affects the performance of direction of arrival (DOA) estimation methods, and smaller snapshots often cannot represent all the features of array signals. However, in practical applications, owing to short-time abrupt changes, low intensity, large noise interference, and other factors of the target signal, the acoustic vector array sometimes cannot obtain sufficient signal data, making it difficult to achieve accurate DOA estimation. Therefore, this study proposes a transfer-learning-based DOA estimation method for acoustic vector arrays. This method extracts the spatial–temporal features of existing signal data by constructing a pre-trained network model based on a convolutional neural network (CNN) and long short-term memory (LSTM), and transfers the trained model to scenes with limited snapshot data through model fine-tuning, achieving the goal of improving the DOA estimation accuracy under a small number of snapshots. Simulation experiments show that the accuracy and RMSE of the proposed DOA estimation method are superior to those of traditional methods when only 1% of the target data are used. This indicates that the pre-training model based on LSTM and CNN can preserve the effective information of signal data and provides a new solution for the real-time prediction of acoustic vector arrays in scenes with a limited number of snapshots through transfer learning.

Large-scale sub-5-nm vertical transistors by van der Waals integration

Vertical field effect transistor (VFET), in which the semiconductor is sandwiched between source/drain electrodes and the channel length is simply determined by the semiconductor thickness, has demonstrated promising potential for short channel devices. However, despite extensive efforts over the past decade, scalable methods to fabricate ultra-short channel VFETs remain challenging. Here, we demonstrate a layer-by-layer transfer process of large-scale indium gallium zinc oxide (IGZO) semiconductor arrays and metal electrodes, and realize large-scale VFETs with ultra-short channel length and high device performance. Within this process, the oxide semiconductor could be pre-deposited on a sacrificial wafer, and then physically released and sandwiched between metals, maintaining the intrinsic properties of ultra-scaled vertical channel. Based on this lamination process, we realize 2 inch-scale VFETs with channel length down to 4 nm, on-current over 800 A/cm2, and highest on-off ratio up to 2 × 105, which is over two orders of magnitude higher compared to control samples without laminating process. Our study not only represents the optimization of VFETs performance and scalability at the same time, but also offers a method of transfer large-scale oxide arrays, providing interesting implication for ultra-thin vertical devices.

Femtosecond laser fabrication of nanopillar arrays for Surface-Enhanced Raman scattering substrates

This work presents a femtosecond laser fabrication method for precision-engineered nanopillar arrays, applicable for surface-enhanced Raman scattering (SERS) substrates. The proposed method consists of two steps: (1) fabrication of nanopillar arrays using femtosecond laser-induced two-photon polymerization (TPP) technology; and (2) deposition of Ag nanoparticles on the fabricated nanopillar arrays. Nanopillar arrays of the proposed SERS substrates are optimized with geometrical parameters of diameter, height, spacing, and arrangement. A limit of detection (LOD) down to 10-7 mol/L for Rhodamine 6G solution is achieved and the enhancement factor is estimated to be up to 2 × 103. The experimental results indicate that the proposed SERS substrates have potential applications in biomedical detection, food safety monitoring, and quality control.

A Temperature Monitoring Method for Sensor Arrays Based on Temperature Mapping and Improved Mask R-CNN

A Temperature Monitoring Method for Sensor Arrays Based on Temperature Mapping and Improved Mask R-CNN

A high-precision positioning method for deep-towed multichannel seismic arrays

A high-precision positioning method for deep-towed multichannel seismic arrays