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The images captured by a plane-array type infrared detector, formed by integrating a large-scale probe array and readout circuits via interconnection, is distorted by two types of superimposed nonuniform noises caused by the probe and readout circuitry. These nonuniform noises arise from the detector's constituent materials, fabrication processes, and other defects. In addition, the output response of an infrared detector is limited by the dynamic range of the circuit, the low and high ends of the output signal exhibit strong nonlinearities. To overcome the impact of detector response nonlinearity and achieve simultaneous correction for two different types of nonuniformities in infrared images, in this study, we proposed a novel correction method. First, the pixel points of all images are reordered according to their pixel values to provide a uniform reorganisation data. Then, the linear correlated region based on the recombined data is extracted using a judgment algorithm that processes the linear correlations of multiple regions to simulate the detector's response curve and find the nonuniformity correction coefficient of each pixel. Experiments on simulated noisy and real images show that our method accurately eliminates nonuniform IR noise without causing blurring and provides optimal peak signal-to-noise ratio and structural similarity.

Dung beetle leg joints exhibit a remarkable capacity to support substantial loads, which is a capability significantly influenced by their surface microstructure. The exploration of biomimetic designs inspired by the surface microstructure of these joints holds potential for the development of efficient self-locking structures. However, there is a notable absence of research focused on the surface microstructure of dung beetle leg joints. In this study, we investigated the structural characteristics of the surface microstructures present in dung beetle leg joints, identifying the presence of fish-scale-like, brush-like, and spike-like microstructures on the tibia and femur. Utilizing these surface microstructural characteristics, we designed a self-locking structure that successfully demonstrated functionality in both the rotational direction of the structure and self-locking in the reverse direction. At a temperature of 20 °C, the biomimetic closure featuring a self-locking mechanism was capable of generating a self-locking force of 18 N. The bionic intelligent joint, characterized by its unique surface microstructure, presents significant potential applications in aerospace and various engineering domains, particularly as a critical component in folding mechanisms. This research offers innovative design concepts for folding mechanisms, such as those utilized in satellite solar panels and solar panels for asteroid probes. [ABSTRACT FROM AUTHOR]

Electrodes or sensors based on silver nanowires (AgNWs) are gaining increasing value in diverse fields such as health monitoring, smart devices, body movement monitoring, and biomedical applications. However, pure AgNWs tend to degrade over time when exposed to an ambient atmosphere, severely limiting the mechanical and electrical performances of AgNW-based electrodes. Here, we take AgNWs and poly-(dimethylsiloxane) (PDMS) as the basic research materials and employ a simple displacement reaction and spin-coating process to prepare one-dimensional platinum-coated AgNWs/PDMS (Pt-AgNWs/PDMS) flexible electrodes. The as-prepared electrodes display comparable electrical conductivity (∼1.65 S/cm), stability (40 min of continuous ultrasound), and flexibility (2500 repetitions of cyclic stretching) compared to pure AgNWs/PDMS electrodes. The resistance even remains consistent at the initial state after 12000 s in a H2SO4 etching medium, indicating that the anticorrosive property of Pt can further enhance the durability and stability of the electrodes. Moreover, the low contact impedance (33.1 kΩ at 1 kHz) of Pt-AgNWs/PDMS electrodes facilitates the capture of various physiological signals, including electrooculogram (EOG), electrocardiogram (ECG), and electromyogram (EMG), which is suitable for applications requiring stable long-term recording. Thus, the proposed strategy shows potential, and Pt-AgNWs are expected to be an ideal material for the fabrication of next-generation high-performance epidermal electrophysiological electrodes. [ABSTRACT FROM AUTHOR]

In this paper, we propose the gradient-oriented prioritization meta-learning (GOPML) algorithm, a new approach for few-shot fault diagnosis in industrial systems. The GOPML algorithm utilizes gradient information to prioritize tasks, aiming to improve learning efficiency and diagnostic accuracy. This method contrasts with conventional techniques by considering both the magnitude and direction of gradients for task prioritization, which potentially enhances fault classification performance in scenarios with limited data. Our evaluation of GOPML's performance across varied fault conditions and operational contexts includes extensive testing on the Tennessee Eastman Process (TEP) and Skoltech Anomaly Benchmark (SKAB) datasets. The results indicate a consistent level of performance across different dataset divisions, suggesting its utility in practical industrial settings. The adaptability of GOPML to specific task characteristics, particularly in environments with sparse data, represents a notable contribution to the field of meta-learning for industrial fault diagnosis. GOPML shows promise in addressing the challenges of few-shot fault diagnosis in industrial systems, contributing to the growing body of research in this area by offering an approach that balances accuracy and generalization with limited data. [ABSTRACT FROM AUTHOR]

Infrared small target detection is critical in remote sensing, military, and other fields. However, the low resolution of most infrared images and the lack of texture and detailed information could cause the target to be lost in a relatively noisy background. Therefore, in recent years, researchers have paid particular attention to the problem of small infrared target detection. In this paper, we propose a double-layer feature fusion convolutional neural network for infrared small target detection (DLFF), consisting of a simultaneous upsampling two-layer network module and a 'T'-type fusion structure. First, the upsampling double-layer network module shares detection information while synchronizing detection, suppressing the background noise and enhancing the detection of the target. In addition, for the small target detection task, since the direct fusion of shallow spatial information and deep semantic information may lose only some small target features, we propose a 'T'-type fusion structure to solve this problem. Furthermore, we collate an infrared small target dataset (MDFA_SIRIST) and design a pre-processing method for pre-detection images. The experimental results show that our network outperforms the other six state-of-the-art methods in combined evaluation metrics ( F 1 -score) and mean intersection ratio (mIou). [ABSTRACT FROM AUTHOR]

Considering a great deal of wind turbine gear failure cases, it is shown that the oxide inclusion has been one of the main reasons for the failure of the gear shaft under fatigue loading condition. In this paper, the fatigue behaviour of gears involving oxide inclusion under real operating condition is investigated. A three‐dimensional finite element model for helical gear pair applied in the middle stage of wind power increasing gearbox is established, and the fatigue life of nonmetallic inclusion zone of middle gear shaft is predicted using Miner's theory and real load spectrum of wind power growth gearbox. Then, the effects of several factors (such as the size and position of oxide inclusion and residual stress induced by manufacturing) on the fatigue life of gears with inclusion are studied. The results show that both inclusion size and position have great influence on the fatigue life of gears, and the compress residual stress will prolong the fatigue life of gears. Furthermore, the critical safety line and safety region of gears with oxide inclusion have been obtained for three representative inclusion positions. The present work is expected to provide a guidance for the engineering design and life safety evaluation of wind turbine gears. [ABSTRACT FROM AUTHOR]