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Early Forest Fire Segmentation Based on Deep Learning

Early Forest Fire Segmentation Based on Deep Learning

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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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Operating Health State Prediction and Evaluation of Excitation Unit Based on GMM and LSTM 3rd

Operating Health State Prediction and Evaluation of Excitati...

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3rd China intelligent Robotics Annual Conference, CCF CIRAC 2022

作者： Ma, Yinxing Yang, Peihao Lv, Gang Deng, Shibin Jiao, Shangbin Li, Yujun Wu, Xiaohui Zhang, Jing 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 Huaneng Weihai Power Generation Co. Ltd. Wei’hai264200 China

ISBN: (纸本)9789819903009

The excitation unit is the weak link in the generator operation since it produces internal deterioration under long-term operation. To evaluate the health condition of the key excitation unit and generate warning information in advance, this work proposes a health assessment method based on the Gaussian mixture model (GMM) and LSTM neural network. Firstly, the weights of each type of data will be determined by obtaining the electrical parameter data of the generator excitation unit from the SIS system, using the infrared image data of carbon brush and excitation transformer based on infrared image acquisition system, and the correlation between each electrical parameter data and temperature on account of the MIC correlation analysis method. On the top of it, LSTM neural network prediction model is established. And establish a GMM-based health benchmark model based on the data collected in the field during healthy operation, and design the health decline index HDI using the Marxist distance for evaluating the health status and deterioration degree of the unit. Finally, the method of this paper is validated by the 2022 operation data of a thermal power plant in Weihai, which proved that this method can provide a basis for regular maintenance and early identification of faults in the power plan and quantifying the degradation degree of the excitation unit under long-term operation and making early warning before the abnormal occurrence of the unit. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deterioration

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Modelling and Optimization of Heating Dispatch in Thermal Power Plant

Modelling and Optimization of Heating Dispatch in Thermal Po...

引用

第28届中国控制与决策会议

作者： Lixia Xie Yali Wu Xianyong Peng Lei Li Fan Yi School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Emerson Process Management Co.Ltd.

ISBN: (纸本)9781467397155

With the addition of heating in thermal power *** to lack of guidance for heating scheduling in traditional scheduling mode,it has been unable to satisfy the current costs for energy conservation and saving of thermal power *** load distribution(especially heat load dispatch) is an important subject in the operation optimization of a thermal power *** model of heat load dispatch on the condition of economic power dispatch is established and linear programming for optimized heat load distribution among units based on LINGO is *** average distribution and linear programming distribution are contrasted in a thermal power *** is obviously shown by simulation and calculation that linear programming distribution gets more optimal results than current average *** has important significance to reduce energy consumption and save costs.

关键词： Heating Dispatch Thermal Power Plant LINGO

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Temperature prediction of generator carbon brush based on LSTM neural network

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

引用

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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Robust Platoon control of Industrial Heavy-Load Autonomous Vehicles 12

Robust Platoon Control of Industrial Heavy-Load Autonomous V...

引用

12th International Conference on CYBER Technology in Automation, control, and intelligent systems, CYBER 2022

作者： Liu, Zhe Li, Xiang Wang, Hesheng MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University China School of Mechanical Engineering and Electronic Information China University of Geosciences China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Platoon control of autonomous industrial vehicles contributes to improving the safety and reliability of cargo transportation in complex industrial scenarios, increasing traffic efficiency and saving energy. The platoon control of autonomous heavy-load industrial vehicles is much harder, as the high robustness requirements, low hardware ability and complex un-structural environments. This paper considers the platoon control task from the view-point of practical industrial applications. Firstly, the longitudinal dynamic model of the heavy-load industrial vehicle is transferred into a first-order damping acceleration response model by introducing the low-level feedback linearization control and compensations. Secondly, the synchronization control concept is introduced and a fully distributed control law is presented, which only requires the coupling information of the two nearest neighbors. In particular, in order to ensure the practical applicability, the information processing delays, data samplings and external control disturbances are explicitly modelled and the global stability analysis approach is presented. Finally, we provide real experiments using full-scale industrial heavy-load vehicles to demonstrate our effectiveness and robustness. © 2022 IEEE.

关键词： Accident prevention

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UAV Trajectory Generation Based on Integration of RRT and Minimum Snap Algorithms

UAV Trajectory Generation Based on Integration of RRT and Mi...

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Chinese Automation Congress (CAC)

作者： Bohui Shi Youmin Zhang Lingxia Mu Jing Huang Jing Xin Yingmin Yi Shangbin Jiao Guo Xie Han Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an Shaanxi China Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Aiming at the problems that carrying out forest fire monitoring and fighting missions by using the Rapidly-exploring Randomized Tree (RRT) algorithm to plan paths cannot adapt to the autonomous movement of an Unmanned Aerial Vehicle (UAV) and that high-order dynamic characteristics may mutate during the mission, this paper investigates a trajectory generation algorithm based on the integration of the RRT algorithm and the minimum snap algorithm. First, the RRT algorithm is used to generate the initial path, then the minimum snap algorithm is used to smooth the initial path and obtain a trajectory suitable for the actual flight of the UAV. However, because the UAV is considered as a particle in the simulation, during the actual flight, this trajectory may not guarantee the safe flight of the UAV and may cause the UAV to collide with an obstacle or other nearby UAVs in the cases of formation flight. To solve this problem, flight corridor concept is used to limit the UAV's flight trajectory for ensuring the safe flight of the UAV. Simulation results show that the algorithm can effectively ensure the safety, smoothness, feasibility, and trajectory of unmanned aerial vehicles.

关键词： Vegetation Forestry Path planning Unmanned aerial vehicles Heuristic algorithms Trajectory optimization Safety

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Diameter Detection of Silicon Single Crystal Based on Brain Storm Optimization Algorithm Hough Transform

Diameter Detection of Silicon Single Crystal Based on Brain ...

引用

第三十八届中国控制会议

作者： Lu Kang Ding Liu National and Local Joint 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

In order to improve the speed and accuracy of silicon single crystal diameter detection, this paper proposes an ellipse detection method based on brain storm optimization algorithm Hough transform, this method uses brain storm optimization algorithm to search ellipse parameters that make the accumulator obtains the maximum value after using Hough transform, then the accurate measurement value of silicon single crystal diameter is obtained. The proposed algorithm is simulated on the complete ellipse with Gaussian white noise and silicon single crystal diameter detection engineering experiments, and the results are compared with other intelligent optimization algorithms. Experimental results show that the proposed algorithm can effectively improve the speed and accuracy of ellipse detection with Hough transform, thereby verify the feasibility and effectiveness of the proposed algorithm, and improve the speed and accuracy of silicon single crystal diameter detection.

关键词： Silicon single crystal Diameter detection Ellipse detection Brain storm optimization algorithm Hough transform

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Silicon Melt Liquid Level Detection Based on Improved Laser Trigonometry

Silicon Melt Liquid Level Detection Based on Improved Laser ...

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第37届中国控制会议

作者： Xinyu Zhang Ding Liu Simi Wang Xiaoguo Zhao Lei Jiang National & Local Joint 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

In order to improve the robustness of laser triangulation to detect the liquid level of silicon melt, this paper firstly proposes a method of calculating the laser spot coordinates based on the voting mechanism. The vote is taken according to the coordinates of small laser spots, which are formed by the effect of liquid surface fluctuation on the line laser in the liquid level measurement image. Secondly, the Kalman filter method is used to correct the liquid level measurement data and compensate the missing data. Then the linear conversion is performed to obtain the liquid level value. Finally, the experimental results show that this method can effectively improve the robustness of the liquid level measurement by the laser triangulation method, and avoid the generation of impulse noise. The introduction of the Kalman filter can accurately correct the level measurement data and compensate for missing data.

关键词： Single crystal furnace Liquid level detection Coordinate calculation Voting mechanism Kalman filter

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Asynchronous Algorithm for Distributed Multi-agent Convex Optimization

Asynchronous Algorithm for Distributed Multi-agent Convex Op...

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第三十九届中国控制会议

作者： Duqiao Zhao Ding Liu Xia Zhang National & Local Joint 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

This paper proposes an asynchronous algorithm for distributed optimization problem(Asy-DOP) in multi-agent network with gradient *** algorithm can be implemented in an asynchronous distributed *** objective function of the algorithm is the sum of the local functions of multiple nodes in the network,each node only knows its own local objective function and can exchange information with its *** addition,the algorithm is based on the undirected connected graph and requires the objective function is Lipschitz *** step-size of the proposed algorithm is homogeneous and when the step-size is in a suitable range,it is proved that the convergence rate of the proposed algorithm is O(1/(?)),where the k is the number of iterations.

关键词： asynchronous algorithm distributed optimization multi-agent gradient method

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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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