Robust distributed fixed-time cooperative hunting control for multi-quadrotor with obstacles avoidance.

This paper addressed the robust distributed fixed-time cooperative hunting problem of multiple quadrotors subject to disturbances in obstacles environment. To handle the underactuated issue inherent in quadrotor dynamics, an inner-outer (attitude-position) loop cascade control configuration is proposed to achieve the cooperative flight control of quadrotors. For position subsystem, as the information of target cannot be accessible to all quadrotors, a distributed fixed-time observer is devised to estimate the target's information. To improve the system's robustness, a fixed-time extended state observer is designed to reject disturbances actively. Based on two observers, the sliding mode position encirclement control protocol with repulsive force is presented to avoid obstacles and encircle the target within a fixed time. For attitude subsystem, a sliding mode attitude tracking control protocol is proposed such that tracking errors can converge to zero even under disturbances. The stability analysis is performed to show the stabilization of the whole closed-loop system with fixed-time convergence. Finally, two sets of comparison simulation are provided to show the superiority of the developed control strategy.

Simulation Study and Optimization Strategies for Vacuum Infusion of GFRP Hoses Based on Resin Time-Viscosity Variables.

During the infusion process of a glass-fiber-reinforced thermosetting composite hose, the viscosity of its resin matrix undergoes temporal variations. Consequently, if the impact of resin viscosity changes over time on the internal resin fluidity is not considered during the infusion process, this may result in the incomplete impregnation of the hose, characterized by the presence of numerous voids. This phenomenon adversely affects the quality of the pipe's curing and forming process. Therefore, based on the characteristic variations in resin viscosity, this paper considers the changes in fluidity caused by the resin's temporal evolution within the material. We establish a finite element simulation model to calculate and analyze the overall infusion effects of resin viscosity changes during the hose infusion process. Furthermore, based on the predicted analysis, a variable parameter infusion strategy is proposed to increase resin impregnation in the hose, thereby reducing internal void content and subsequently improving the quality of material curing and forming.

Space dynamic target tracking method based on five-frame difference and Deepsort.

For the problem of space dynamic target tracking with occlusion, this paper proposes an online tracking method based on the combination between the five-frame difference and Deepsort (Simple Online and Realtime Tracking with a Deep Association Metric), which is to achieve the identification first and then tracking of the dynamic target. First of all, according to three-frame difference, the five-frame difference is improved, and through the integration with ViBe (Visual Background Extraction), the accuracy and anti-interference ability are enhanced; Secondly, the YOLOv5s (You Look Only Once) is improved using preprocessing of DWT (Discrete Wavelet Transformation) and injecting GAM (Global Attention Module), which is considered as the detector for Deepsort to solve the missing in occlusion, and the real-time and accuracy can be strengthened; Lastly, simulation results show that the proposed space dynamic target tracking can keep stable to track all dynamic targets under the background interference and occlusion, the tracking precision is improved to 93.88%. Furthermore, there is a combination with the physical depth camera D435i, experiments on target dynamics show the effectiveness and superiority of the proposed recognition and tracking algorithm in the face of strong light and occlusion.

Research on the Heating Process of CFRP Circular Tubes Based on Electromagnetic Induction Heating Method.

Based on the electromagnetic induction heating method, heating and curing of Carbon Fiber Reinforced Polymer (CFRP) have the advantages of high energy utilization and no pollution. However, in the heating process, both the material weaving structure and mold material can affect the temperature field. Therefore, in this study, an electromagnetic heating finite element analysis model for CFRP circular tubes was established based on the equivalent electromagnetic thermal characteristics of CFRP. The study investigated the temperature rise mechanism of the material weaving structure under the magnetic field, and explored in-depth the influence of molds made of 45# steel and glass fiber-reinforced plastic (FRP) on the heating process of CFRP. The CFRP circular tubes with weaving structures of 89-degree winding angle, 45-degree winding angle, and plain weave were studied. The study found that when the metal mold was heated, the CFRP structure had almost no effect on the temperature distribution. However, when the glass fiber-reinforced plastic mold was heated, the temperature field changed with the CFRP structure, and the more fiber cross points, the more uniform the temperature field. The accuracy of the finite element model was verified through experiments. The aim of this research is to provide theoretical guidance for actual industrial production.

Research and Application of Contactless Measurement of Transformer Winding Tilt Angle Based on Machine Vision.

In the process of producing winding coils for power transformers, it is necessary to detect the tilt angle of the winding, which is one of the important parameters that affects the physical performance indicators of the transformer. The current detection method is manual measurement using a contact angle ruler, which is not only time-consuming but also has large errors. To solve this problem, this paper adopts a contactless measurement method based on machine vision technology. Firstly, this method uses a camera to take pictures of the winding image and performs a 0° correction and preprocessing on the image, using the OTSU method for binarization. An image self-segmentation and splicing method is proposed to obtain a single-wire image and perform skeleton extraction. Secondly, this paper compares three angle detection methods: the improved interval rotation projection method, quadratic iterative least squares method, and Hough transform method and through experimental analysis, compares their accuracy and operating speed. The experimental results show that the Hough transform method has the fastest operating speed and can complete detection in an average of only 0.1 s, while the interval rotation projection method has the highest accuracy, with a maximum error of less than 0.15°. Finally, this paper designs and implements visualization detection software, which can replace manual detection work and has a high accuracy and operating speed.

Particle Swarm Optimization and Salp Swarm Algorithm for the Segmentation of Diabetic Retinal Blood Vessel Images.

In recent years, the incidence of diabetes has been increasing year by year. Since most of the fundus lesions are located near blood vessels, the image information is complex, and the end vessels are difficult to identify. So, a new segmentation method of diabetic retinal vessel images based on particle swarm optimization and salp swarm algorithm is proposed. This paper uses a Gaussian filter to enhance the main blood vessels, and a top-bot hat transform is used to strengthen the end vessels. The preprocessing process is completed by combining and reconstructing the two images through a normalization operation. The improved particle swarm optimization and salp swarm algorithms perform multi-threshold segmentation on the preprocessed vessel images. The best fit value, Structural Similarity Index Measure, Peak Signal to Noise Rati, feature similarity index measure, sensitivity, accuracy, regional consistency, Dice coefficient, Jaccard similarity, and Shannon entropy are selected for comprehensive evaluation and analysis. The results showed that this paper's improved particle swarm-salp swarm algorithm for segmenting diabetic retinal blood vessel images is more efficient, and the threshold is better. The vascular segmentation method in this paper is applied in medical image processing, which improves the accuracy of medical image processing and reduces the computational effort.

Network Security Situation Prediction Model Based on EMD and ELPSO Optimized BiGRU Neural Network.

In order to improve the accuracy of network security situation prediction and the convergence speed of prediction algorithm, this paper proposes a combined prediction model (EMD-ELPSO-BiGRU) based on empirical mode decomposition (EMD) and improved particle swarm optimization (ELPSO) to optimize BiGRU neural network. Firstly, the network security situation data sequence is decomposed into a series of intrinsic mode function by EMD. Then, a particle swarm optimization algorithm (ELPSO) based on cooperative update of evolutionary state judgment and learning strategy is proposed to optimize the hyper-parameters of BiGRU neural network. Finally, a network security situation prediction model based on EMD-ELPSO-BiGRU is constructed to predict each intrinsic mode function, respectively, and the prediction results are superimposed to obtain the final network security situation prediction value. Simulation results show that ELPSO has better optimization performance, and EMD-ELPSO-BiGRU model has higher prediction accuracy and significantly improved convergence speed compared with other traditional prediction methods.

Research on Subdivision System of Sin-Cos Encoder Based on Zero Phase Bandpass Filter.

A novel high-precision subdivision system for high-speed encoders is designed in this work. The system is designed with an arc second of Sin-Cos Encoder (SCE) based on zero phase bandpass filter. The system collects the analog output signals of an encoder with a high-speed data acquisition system (DAS); the noise of a digital signal can be effectively eliminated by zero phase bandpass filter with appropriate prior parameters. Finally, the actual rotation angle of the encoder is calculated by the software subdivision technique in the system. The software subdivision technique includes two methods, which are the Analog Pulse Counter (APC) and the Arc Tangent Subdivision (ATS). The APC method calculates the encoder angle by counting the analog pulses acquired by the arc tangent signal. The ATS method calculates the encoder angle by computing the arc tangent results of each point. The accuracy and stability of the system are first verified with a simulated signal; second, the real signals of an SCE are acquired by a high speed DAS on a test bench of a precision reducer, which is employed in industrial robots. The results of the proposed system are compared. The experimental results show that the system can significantly improve the accuracy of the encoder angle calculation, with controllable costs.