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A detection and identification method based on CNN for laser point thermal radiation

A detection and identification method based on CNN for laser...

引用

2020 International Conference on Mechatronics Technology and intelligent Manufacturing, ICMTIM 2020

作者： Yang, Haichuan Xie, Ruidong Yi, Yingmin Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an710048 China

Aiming at the high demands of temperature and precision in the aspect of additive manufacturing, a method based on CNN was proposed for estimating measurement. The network was trained through the collected laser thermal radiation images for image recognition and isotherm estimation after modeling a CNN. The experimental conclusion verifies that the isotherm detection and temperature estimation of the laser point can be efficiently implemented in proposed method. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Isotherms

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A semantic segmentation method for UAV image based on improved BiseNetv2 5

A semantic segmentation method for UAV image based on improv...

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5th International Conference on Artificial Intelligence and Computer Science, AICS 2023

作者： Guo, Fengjuan Han, Sen Zhao, Jiahang Han, Jiale Xin, Jing Shaanxi Key Laboratory of Integrated and Intelligent Navigation The 20th Research Institute of China Electronics Technology Corporation Shaanxi Xi’an710068 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Shaanxi Xi’an710048 China

ISBN: (纸本)9781510668621

Aiming at the problem of low semantic segmentation accuracy of tiny targets in UAV aerial images, a bilateral semantic segmentation network T-BiseNetv2 is proposed. The proposed segmentation network is based on BiseNetv2, and the Transformer structure is introduced into semantic branch, and the detail branch and feature fusion module are reconstructed, which improves the network’s capacity to capture both global context information and local semantic information. Several semantic segmentation experiments are conducted on the standard semantic segmentation dataset UAVID, experimental results show that the proposed semantic segmentation network T-BiseNetv2 has a MIoU of 69.52%, which is about 2.2% higher than the original BiseNetv2 network. Especially, for "Human", the IoU of TBiseNetv2 is about 4.3% higher than that of the popular UNetFormer. © 2023 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Improved Kalman Filtering Algorithm Based Multi-Sensor Integration for Silicon Single Crystal Growth Process 7

Improved Kalman Filtering Algorithm Based Multi-Sensor Integ...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Xie, Ruidong Zhu, Pei Ma, Wenle Zhang, Zheqi Yi, Yingmin Guo, Zheng Xi'an University of Technology Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an710048 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9798350363173

The study primarily delves into addressing the data filtering challenge inherent in the silicon single crystal growth process by proposing a multi-sensor integrated detection approach. This approach is designed to alleviate the diminished filtering accuracy resulting from the reliance on a single sensor and the conventional Kalman filtering algorithm. By utilizing an enhanced adaptive Kalman filtering algorithm and the maximum likelihood estimation criterion to incorporate the innovation variance directly into the gain calculation of the Kalman filter, dynamic adjustment of the estimation model is achieved while interference from system noise and measurement noise is reduced. Finally, simulation-based comparative experiments between the adaptive and conventional Kalman filtering algorithms are performed. The results show that the performance of the adaptive Kalman filtering algorithm is superior to that of the conventional Kalman filtering algorithm in terms of accuracy and stability when detecting signals from multiple sensors. The research findings furnish dependable data support for refining the decision-making process in crystal growth technology, augmenting the precision and scientific integrity of crystal safety production scheduling and decision-making endeavors. © 2024 IEEE.

关键词： Kalman filters

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A power optimization control method based on IMC for 3D printer

A power optimization control method based on IMC for 3D prin...

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2020 International Conference on Mechatronics Technology and intelligent Manufacturing, ICMTIM 2020

作者： Xie, Ruidong Yang, Haichuan Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China

Aiming at the effect of selective laser sintering technology used in 3D printing, the recursive least squares method was applied to fitting a control system model for quantification the relationship between laser power and corresponding temperature in this paper. The internal model control method is considered based on the establishing model. The controller is put into the actual 3D printing power control system for controlling the laser power. In the experiment, both internal model controller and the PID controller for the 3D printer are researched and deployed for comparing the their effects in the paper. The experimental result illustrates that the IMC based on the recursive least squares method is of effectiveness. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： 3D printers

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Study of multilevel feature weighted fusion based image classification method for silicon single crystal growth process

Study of multilevel feature weighted fusion based image clas...

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2024 International Conference on Image processing and Artificial Intelligence, ICIPAl 2024

作者： Xie, Ruidong Zhang, Zheqi Zhu, Pei Ma, Wenle Yi, Yingmin Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

ISBN: (纸本)9781510681514

A multi-level feature weighted fusion based image classification method for silicon single crystal growth process has been proposed to address the issue of the long silicon single crystal pulling times at industrial sites, which prevents timely understanding of the crystal growth process. A multi-level feature weighted fusion method was employed to identify and classify the growth process of silicon single crystals. A Czochralski single crystal silicon growth process recognition system was then designed. A comparison of the experimental results obtained from this design with the traditional single image classification method clearly showed that using different levels of silicon single crystal image information simultaneously effectively improved the accuracy of silicon single crystal growth image classification. © 2024 SPIE.

关键词： Image classification

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Optimization design of superconducting cusp magnetic field structure 13

Optimization design of superconducting cusp magnetic field s...

引用

13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

作者： Shangbin, Jiao Dongbin, Hou Ding, Liu Weichao, Huang Natl. and Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China

ISBN: (纸本)9781538637579

Based on the analysis of the Cusp magnetic field suppression convection principle, the simulation model of superconducting Cusp magnetic field is built by the finite element method. In the case of satisfying the magnetic field strength of the crucible wall and giving the excitation current, the number of layers of the superconducting coil is calculated by using the established model. The influence of coil spacing, thickness of shielding thickness, horizontal distance between coil and shielding thickness and longitudinal distance on magnetic induction strength, horizontal distance and longitudinal distance between coil and the shielding are analyzed under the condition that the number of superconducting coils is constant. The influence of the force on the coil, the influence of the thickness of the shielding body on the magnetic leakage strength of the magnetic field. The simulation results show that the optimized Cusp magnetic field structure parameters can be used in the actual design. © 2018 IEEE.

关键词： Finite element method

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Early Forest Fire Recognition Method Based on C-GhostNet Network 5

Early Forest Fire Recognition Method Based on C-GhostNet Net...

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5th International Symposium on Autonomous systems, ISAS 2022

作者： Li, Mengna Zhang, Youmin Mu, Lingxia Xin, Jing Yu, Ziquan Jiao, Shangbin Liu, Han Xie, Guo Yi, Yingmin Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Shaanxi Xi'an710048 China Concordia University Industrial and Aerospace Engineering Department of Mechanical MontrealQCH3G 1M8 Canada Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing211106 China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an Shaanxi 710048 China

ISBN: (纸本)9781665487085

Early forest fire image recognition plays an important role in timely fire fighting. This paper proposes an early forest fire recognition method based on C-GhostNet network. The C-GhostNet network is an improved version of GhostNet, which mainly consists of a series of c-ghost bottlenecks, each c-ghost bottleneck mainly consists of two c-ghost modules. Through the concat operation and channel shuffle, the c-ghost module establishes the relationship between the input data and the output features generated by the original ghost module, so that GhostNet network has the ability to capture contextual features. The experimental results show that the C-GhostNet network achieves better recognition performance than GhostNet without introducing additional computational load, and the running speed reaches about 20FPS, which basically realizes real-time recognition. In addition, like GhostN et, the C-GhostNet network is also a lightweight network. © 2022 IEEE.

关键词： Image recognition

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Research on weak signal detection based on adaptive multi-stable stochastic resonance under α stable noise

Research on weak signal detection based on adaptive multi-st...

引用

Annual Conference of Industrial Electronics Society

作者： Shang-bin Jiao Yi Wang Qing Zhang Le Fan Di Sun Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

In this paper, the influences of system parameters on stochastic resonance output effect is analyzed, which takes the multi-stable stochastic resonance system as the model. That is, the vibration condition of multi-stable stochastic resonance system, and weak signal detection method based on the multi-stable stochastic resonance under α stable noise is investigated. Then considering the real-time detection of weak signals in practical engineering, the multi-stable stochastic resonance system parameters a, b, c are optimized by particle swarm optimization(PSO), which takes the output signal-to-noise ratio(SNR out ) as the fitness function. Finally, multi-frequency weak signals detection with α stable noise is achieved, and the above method is applied to the vibration fault diagnosis of turbine. Both simulation and experiment results show that this method can quickly and effectively detect multi-frequency weak signals submerged in strong noise background, which lays a foundation for its application in engineering practice.

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Assessment and prediction of leakage degree of expansion joints in underground network heating pipe network based on LS-SVM and ARIMA model 13

Assessment and prediction of leakage degree of expansion joi...

引用

13th IEEE Conference on Industrial Electronics and Applications, ICIEA 2018

作者： Shang-Bin, Jiao Le, Fan Peng-Yue, Wu Lei, Qiao Yong-Ze, Jin Qian-Kun, Shen Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China Xi'an Thermal Power Research Institute Co. Ltd Xi'an710054 China

ISBN: (纸本)9781538637579

The study shows that the leakage of the expansion joints in the underground heating primary pipe network will lead to the fluctuation of soil temperature and conductivity around the leakage point. Based on the online monitoring of changes of physical quantities around the expansion joint, this paper established the assessment model of temperature and conductivity as the input parameters and the degree of expansion joints leakage as the output parameters, which took the radial basis function as kernel function and made use of PSO algorithm to achieve the optimization of the kernel function parameters. Then, the temperature and conductivity were predicted based on the ARIMA model, and the LS-SVM assessment of expansion joint leakage was realized according to the prediction results. Both simulation and field experiments show that the prediction model based on ARIMA has higher accuracy, which has identified the foundation for on-line prediction and accurate assessment of the expansion joint leakage in the underground heating primary pipe network. © 2018 IEEE.

关键词： Particle swarm optimization (PSO)

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Nonlinear integral sliding mode variable structure control for two-tank system with input — Limitation

Nonlinear integral sliding mode variable structure control f...

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Annual Conference of Industrial Electronics Society

作者： Hai-Peng Ren Jiao Hu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an Shaanxi CN Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China

To deal with the unsatisfactory transient response of the conventional integral sliding mode control (ISMC), A nonlinear integral sliding mode controller (NISMC) is proposed in this paper, which uses a smooth nonlinear function with “small error amplification and large error saturation” property, meanwhile, takes the limited input into account. The proposed NISMC improves the transient performance, i.e., less controller chattering and less steady error. The two-tank system is usually treated as a paradigm to test the control algorithms. Five kinds of sliding-mode control methods (SMC) are used to control the two-tank liquid level to test the performance. The simulation and experimental results show that the proposed NISMC has the superior performance as compared to the comparison methods.

关键词： Liquids Two dimensional displays Level control Robustness Valves Sliding mode control Transient analysis

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