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2021 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS 2021

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

ISBN: (纸本)9781665401159

Fire segmentation is very important for fire rescue. It can make firefighters get the information on fire area, spread direction and so on, and then help them make quick and effective fire-fighting plan. Therefore, this paper proposes an early forest fire segmentation algorithm based on a deep learning model, named F-Unet, which mainly uses the architecture idea of Unet for reference. F-Unet consists of contraction path, feature fusion layer and expansion path. The contraction path is composed of the first 13 layers of VGG16, which is used to obtain feature maps with different scales. In order to improve the segmentation accuracy of the model, the feature fusion network proposed in this paper is added to the Unet architecture to fuse these feature maps with different scales. The expansion path is used for upsampling these feature maps to restore the size of the original input image and obtain the fire segmentation results. The experimental testing results on the FLAME dataset show that F-Unet can significantly improve the fire segmentation precision, and also prove that the proposed feature fusion network is effective to improve the performance of fire segmentation. © 2021 IEEE.

关键词： Deforestation

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A Real-time Fire Segmentation Method Based on A Deep Learning Approach

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IFAC-PapersOnLine 2022年第6期55卷 145-150页

作者： Mengna Li Youmin Zhang Lingxia Mu Jing Xin Ziquan Yu Shangbin Jiao Han Liu Guo Xie Yi Yingmin Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an Shaanxi 710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Quebec H3G 1M8 Canada College of Automation Engineering Nanjing University of Aeronautics and Astronautics (NUAA) Nanjing Jiangsu China

As a kind of the forest “fault”, fire is highly destructive and difficult to rescue. Fire segmentation is helpful for firefighters to understand the fire scale and formulate a reasonable fire-fighting plan. Therefore, this paper proposes a real-time fire segmentation method based on deep learning. This method is an improved version of deeplbav3+, which is an encoder-decoder structure network. Encoder network is composed of deep convolutional neural network and atrous spatial pyramid pooling. Different from deeplabv3+, in order to improve the segmentation speed, this paper uses the lightweight network mobilenetv3 to build a new deep convolutional neural network and does not use atrous convolution, but it will affect the segmentation accuracy. Therefore, in order to compensate for the loss of segmentation accuracy, on the basis of the original decoder network, this paper adds two different shallow features to make the network contain rich fire feature information. Experimental results show that the comprehensive performance of this method is better than the original deeplabv3+, especially the segmentation speed of the network is greatly improved, which is about 59 FPS.

关键词： Forest fire Fire segmentation Atrous spatial pyramid pooling Mobilenetv3 Deeplabv3+

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Temperature prediction of generator carbon brush based on LSTM neural network

Temperature prediction of generator carbon brush based on LS...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Qing Jiao, Tingyang Ma, Yinxing Zhang, Youmin Wu, Xiaohui Wu, Pengyue Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China The Faculty of Computing Science The University of Alberta EdmontonABT6G 2R3 Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi 'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University MontrealQCH3G 1M8 Canada Huaneng Weihai Power Generation Co. Ltd Weihai264200 China Xi 'an Thermal Power Research Institute Co. Ltd Xi'an710048 China

ISBN: (纸本)9781665426473

In order to improve the prediction accuracy of the carbon brush temperature trend of the generator, analyzing the operating state of the generator more accurately, and reduce other accidents like the unplanned outage caused by carbon brush failure of the generator in the power plant. A multi-step temperature prediction model based on the LSTM (Long Short-Term Memory) neural network is proposed. The data comes from real operating carbon brush temperature of Weihai Power Plant in ten days. Then the temperature prediction model is established to achieve an accurate prediction of the carbon brush temperature in the future day. The prediction error is stable within 0.4 °C. By comparing the predicted results of the BP model and Elman model, the error between the predicted results of each model and the actual temperature data is analyzed. By comparing the indicators and analyzing the actual curves, the results show that LSTM neural network has higher accuracy in predicting the temperature of generator carbon brush. This method is of reference significance for the accurate analysis of the operation state of the generator and the load analysis of the excitation system. © 2021 IEEE

关键词： Long short-term memory

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Distributed MPC Algorithm for Linear Discrete systems with Communication Noise

Distributed MPC Algorithm for Linear Discrete Systems with C...

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第40届中国控制会议

作者： Duqiao Zhao Ding Liu Linxiong Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xian University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

In this paper, a distributed MPC algorithm is proposed for linear discrete systems with bounded communication noise and random communication failure. Based on the characteristics of time-varying directed graphs, the convergence of the algorithm is analyzed in the case of communication noise and random communication failure. This algorithm uses the distributed projection dual subgradient algorithm to solve the dual problem and replaces the double stochastic condition of the traditional algorithm with row stochastic condition. The exponential stability of the system is guaranteed. Finally, an example is given to illustrate the performance of the algorithm.

关键词： Distributed MPC Bounded Communication Noise Random Communication Faults Distributed Projection Dual Subgradient Row Stochastic

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ICP algorithm point cloud registration method based on a new improved Harris Hawk algorithm

ICP algorithm point cloud registration method based on a new...

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Chinese Automation Congress (CAC)

作者： Chen Wang Shangbin Jiao Rui Gao Yuxing Li School of Automation and Information Engineering Xi’an University of Technology Xi’an China School of Automation and Information Engineering Xi’an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China School of Electronic & Electrical Engineering Baoji University of Arts and Sciences Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology China

ISBN: (纸本)9781665426480

To address shortcomings of ICP algorithm, which is sensitive to the initial position and easy to fall into local optimum, we propose a Harris Hawks Optimizer (HHO) point cloud registration method combining PCA preprocessing and parallel population initialization. The PCA method is used to align the point clouds with the main axes and perform the main axes correction. Since the six input variables in the population initialization stage of HHO point cloud registration are different and independent, the initial population of HHO algorithm is initialized by the parallel initialization method. The results show that the improved algorithm is able to successfully overwhelm the fault of ICP algorithm, and its global seek performance and optimization accuracy are more advantageous, and the algorithm operates efficiently, with high registration accuracy and robustness.

关键词： Point cloud compression Automation Input variables Sociology Robustness Statistics Optimization

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MOSFET/TFET Mixed Power Clamp Circuit For ESD and Surge Protection

MOSFET/TFET Mixed Power Clamp Circuit For ESD and Surge Prot...

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Design and system (IEDS), international EOS/ESD Symposium on

作者： Zhaonian Yang Yaping Yue Shi Pu Xiaohan Yang Yue Zhang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Shandong Inspur Intelligence Research Institute Co. Ltd. Xi'an China Xi'an Xiangteng Microelectronics Co. Ltd. Xi'an China

ISBN: (数字)9781585373383

ISBN: (纸本)9781665469814

In this paper, a high sensitive voltage detector is proposed and its electrical characteristics are investigated using technology computer-aided design (TCAD) simulation. Germanium (Ge) source and line configuration TFET is adopted to obtain an ultra sensitive detection capability. Corresponding operating principle is explained and the impact of the key parameters on the voltage detector is also discussed. The simulation results show that the new proposed Ge source line TFET based voltage detector has a low leakage current and high detection sensitivity under the electrostatic discharge (ESD) and surge events compared to traditional detectors.

关键词： TFETs Sensitivity Simulation Surge protection Detectors Voltage Germanium

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Effect of Annealing Process Parameters on N-Gaas Ohmic Contacts

SSRN

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SSRN 2021年

作者： Lin, Tao Xie, Jianan Ning, Shaohuan Ma, Zekun Mu, Yan Sun, WanJun Yang, Sha Department of Electronic Engineering Xi'an University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Shaanxi Xi’an710048 China

Ni/Ge/Ni/Au multi-layer metal electrodes were prepared on N-GaAs substrate by electron-beam evaporation to investigate the effect of annealing process parameters on N-GaAs ohmic contacts. In the annealing temperature range of 370 °C to 430 °C, the metal-semiconductor contact was found changing from Schottky contact to ohmic contact as the annealing temperature was above 380 °C. Specific contact resistivity of n-GaAs samples firstly decreased and then increased with the increasing of annealing temperature, and the minimum specific contact resistivity of 3.3×10 -5 Ω·cm 2 was formed at 420 °C annealing for 80 s. Although the specific contact resistivity of the metal-semiconductor contact performed satisfactorily, the surface morphology of the n-GaAs metal electrode was found having metal shrinkage after annealing. The formation mechanism of ohmic contact was qualitatively explained by the elements diffusion under different annealing parameters, which were confirmed by the comparative analysis of SEM and EDX results. © 2021, The Authors. All rights reserved.

关键词： Gallium arsenide

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Optimized Dispatching of Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system

Optimized Dispatching of Seawater Pumping-Storing/Wind/Solar...

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第40届中国控制会议

作者： Yuyu Liu Ding Liu Lu Kang National & Local Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Different power sources in Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system supply power to the island *** order to ensure the reliability of the power supplying and improve the economical efficiency of the island micro-grid system at the same time,the output of each power source in the island micro-grid system needs to be optimized and dispatched according to historical wind power and photo-voltaic *** this paper,the mathematical model of Seawater Pumping-Storing/Wind/Solar Hybrid Power Generating system is established,and the one-time cost,*** the joint system are taken as the objective *** immune particle swarm algorithm is used to figure out the optimal output of each power source in the system after considering the restrictions including power balance of the system,the power constraints of each generator set and the online power of wind power and *** example shows that the optimization result of improved PSO algorithm is better than the original one,and it can also achieve the optimized dispatching of the joint system economically and effectively.

关键词： Seawater pumped-storage power station IPSO Optimized Dispatching

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Echo state network based symbol detection in chaotic baseband wireless communication

arXiv

引用

arXiv 2021年

作者： Yin, Hui-Ping Bai, Chao Ren, Hai-Peng The Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China The Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China

In some internet of Things (IoT) applications, multipath propagation is a main constraint of communication channel. Recently, the chaotic baseband wireless communication system (CBWCS) is promising to eliminate the inter-symbol interference (ISI) caused by multipath propagation. However, the current technique is only capable of removing the partial effect of ISI, due to only past decoded bits are available for the suboptimal decoding threshold calculation. However, the future transmitting bits also contribute to the threshold. The unavailable future information bits needed by the optimal decoding threshold are an obstacle to further improve the bit error rate (BER) performance. Different from the previous method using echo state network (ESN) to predict one future information bit, the proposed method in this paper predicts the optimal threshold directly using ESN. The proposed ESN-based threshold prediction method simplifies the symbol decoding operation by removing the threshold calculation from the transmitting symbols and channel information, which achieves better BER performance as compared to the previous method. The reason for this superior result lies in two folds, first, the proposed ESN is capable of using more future symbols information conveyed by the ESN input to get more accurate threshold;second, the proposed method here does not need to estimate the channel information using Least Square method, which avoids the extra error caused by inaccurate channel information estimation. By this way, the calculation complexity is decreased as compared to the previous method. Simulation results and experiment based on a wireless open-access research platform under a practical wireless channel, show the effectiveness and superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Bit error rate

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Design and Performance Analysis of a Chaotic Pseudo Orthogonal Carriers Multi-Access Communication system

arXiv

引用

arXiv 2021年

作者： Bai, Chao Yao, Jun-Liang Sun, Yu-Zhe Ren, Hai-Peng Xi’an Key Laboratory of Intelligent Equipment Xi’an Technological University Xi’an710021 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China

A Chaotic Pseudo Orthogonal Carriers Multi-Access (CPOCMA) communication based on Chaotic Pseudo Orthogonal Shape-forming Filter (CPOSF) bank, Chaotic Pseudo Orthogonal Matched Filter (CPOMF) bank and Chaotic Pseudo Orthogonal Correlation Filter (CPOCF) bank is proposed in this work. At the transmitter, the multiple CPOSFs are used to generate pseudo orthogonal signals. It provides a good trade-off between spectrum efficiency and high bit transmission rate. At the receiver, the CPOMF bank and CPOCF bank are used to maximize the Signal-to-Noise Ratio (SNR) and extract the received information from each sub-channel, respectively. The received signal is demodulated by averaging the sampled sequence from the matched filter bank output and sorting the sampling sequence from the CPOCF bank output to recover the transmitted information bits. The proposed CPOCMA communication system not only offers multiuser access with high reliability and high data transmission rate, but also achieves higher spectrum efficiency. Analytical Bit Error Rate (BER) expression is derived. The proposed communication system performance has been evaluated in Additive White Gaussian Noise (AWGN) channel and wireless channel by both numerical simulations and experiments based on a Wireless open-Access Research Platform (WARP), the results show the effectiveness and the superiority of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Numerical methods

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