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A sliding-window based signal processing method for characterizing particle clusters in gas-solids high-density CFB reactor

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CHEMICAL ENGINEERING JOURNAL 2023年第Part1期452卷

作者： Wang, Chengxiu Luo, Mengjie Su, Xin Lan, Xingying Sun, Zeneng Gao, Jinsen Ye, Mao Zhu, Jesse China Univ Petr State Key Lab Heavy Oil Proc Beijing 102249 Peoples R China Univ Western Ontario Dept Chem & Biochem Engn London ON N6A 5B9 Canada Chinese Acad Sci Dalian Inst Chem Phys 457 Zhongshan Rd Dalian 116023 Peoples R China

Particle clusters in CFB risers were identified from the instantaneous solids holdup signals by a new sliding -window based signal processing method. By shifting the time window and calculating the mean and the stan-dard deviation within it, a non-linear threshold curve for identifying the clusters was derived instead of the conventional constant threshold. The optimal sliding window size was determined as Wb = 1024 data points by the bisection method on the entire piece of signals. Using the proposed method, a more realistic characterization of the particle clusters in both HDCFB and LDCFB was obtained by considering the bulk fluctuation of the gas -solids flow. The clusters in HDCFB have higher solids holdup and lower velocity than that in the LDCFB. The HDCFB is also found to have a greater number of loose clusters for better gas-solids contacting and exchanges in the center of the riser.

关键词： High-density Circulating fluidized bed sliding window algorithm Cluster Signal processing

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Efficient Lane Detection and Keeping for Autonomous Vehicles in Real-World Scenarios 26

Efficient Lane Detection and Keeping for Autonomous Vehicles...

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26th International Conference on Computer and Information Technology, ICCIT 2023

作者： Azad, Farhana Islam, Yumna Ruslan, Ch Zakauddin Md Aye Mong Marma, C. Kalpoma, Kazi A. Ahsanullah University of Science and Technology Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

In this study, we developed an auto-lane-keeping assist system to contribute to autonomous driving. The system will keep the vehicle in its designated lane to reduce road accidents. The main challenge of this research is to make the system suitable for real-world road conditions. To achieve an efficient lane-keeping system, we detected the lane lines automatically using canny edge detection and a sliding window algorithm. The proposed lane-keeping system has another stage: lane-keeping. The lane-keeping task includes the calculation of the offset value, meaning how much the vehicle deviates from its lane or if the vehicle is in the center line of the lane, and the steering angle correction of the vehicle to be in the lane. We use the sliding window algorithm for the offset value calculation, which makes the detection of curved lane lines more accurate than the previous works and also performs well in various weather and lighting conditions. The proposed system's performance is evaluated using the IROADS dataset in this work. We implemented lane keeping in both software and hardware models, introducing the AURIX TC-375 microcontroller for hardware integration, which enhances overall lane-keeping system output through the integration of detection and keeping processes. © 2023 IEEE.

关键词： AURIX TC-375 Micro-controller Automotive ECU Lane Detection Lane Keeping sliding window algorithm

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Feature-Based Lane Detection algorithms for Track Following: A Comparative Study 8

Feature-Based Lane Detection Algorithms for Track Following:...

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8th International Conference on Mechatronics and Robotics Engineering (ICMRE)

作者： Hashem, Ahmed Schlechter, Thomas Univ Appl Sci Upper Austria Wels Austria

ISBN: (纸本)9781665483773

Autonomous driving has been gaining momentum in recent years and is today one of the hottest areas of research and development in the mobility sector. One of the basic tasks to cover in the field of a utonomous d riving i s l ane detection. Considering that lane keeping and controlled lane change are low level autonomy tasks, those tasks are essential to any project aiming to achieve a reasonable level of autonomous driving. As a students' playground, the University of Applied Sciences Upper Austria - along with its partners - is currently establishing a model car based future mobility race event. To make this happen, a ROS based model car is equipped with various known and newly to be developed algorithms enabling certain capabilities. Given the described topical context, in this paper two featurebased lane detection algorithms, namely Hough Line Transform algorithm and sliding window algorithm, are developed, tested and compared.

关键词： Lane Detection Hough Line Transform sliding window algorithm Future Mobility Cup

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A Vision-based Navigation System for an Agricultural Autonomous Tractor 7th

A Vision-based Navigation System for an Agricultural Autonom...

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7th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture (AGRICONTROL)

作者： Saha, Sristi Morita, Tsuyoshi Ospina, Ricardo Noguchi, Noboru Hokkaido Univ Grad Sch Agr Sapporo Hokkaido Japan Hokkaido Univ Res Fac Agr Sapporo Hokkaido Japan

RTK-GNSS (Real-time Kinematic-Global Navigation Satellite System) signal is necessary for the safe navigation of an autonomous tractor. However, the main problem associated with this type of precise GNSS is that the RTK correction signal might not be available at all geographical locations. Tree canopies present close to the tractors' vicinity obstruct satellite signals and degrade the position accuracy. This can lead the autonomous tractor to travel outside of its predetermined path, which is unsafe. To avoid such situations, this study aims to develop a vision-based road detection system, which does not rely on RTK-GNSS. This system aims to detect both paved and unpaved roads in rural farm areas. It takes the RGB images obtained from an HD onboard camera and segments the road surface and road edges. The segmentation is performed by using several image filters, the sliding window method, and a set of rules that are determined manually Finally, the lateral error obtained from the machine vision system is transmitted to the tractor's automatic navigation system. Experimental runs performed at the experimental farm of Hokkaido University showed that the lateral error calculated by this system is less than 0.2 m for unpaved roads and 0.4 m for paved roads. This shows that the system can detect both paved and unpaved roads. Future work addresses considerations to make the system more robust. Copyright (C) 2022 The Authors.

关键词： Image segmentation sliding window algorithm lateral error robot navigation robot vision road edge detection precision agriculture

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Increasing Measuring Area of Deformed Solid by Digital Image Correlation

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RUSSIAN PHYSICS JOURNAL 2021年第4期64卷 599-604页

作者： Kibitkin, V. V. Solodushkin, A. I. Russian Acad Sci Siberian Branch Inst Strength Phys & Mat Sci Tomsk Russia

Knowledge of mechanisms of deformation and fracture of constructional materials allows optimizing their composition and microstructure. The digital image correlation technique is used for this purpose due to its high accuracy and simplicity in data processing. Physical processes at the meso-level are studied by optical microscopy, which, however, reduces the measuring area. The paper presents a short description of approaches allowing to increase the measuring area without loss in accuracy. It is shown that this problem can be solved by stitching the overlapping fields of view or separate displacement fields to obtain a combined displacement field. Another solution of the problem is associated with a decrease in the optical magnification, while the invariance of the absolute error at the given level is provided by the calculation of sub-pixel accuracy. In this paper, this approach is applied to the welding joint under fatigue loading conditions.

关键词： strain displacement vector digital image correlation sliding window algorithm sub-pixel accuracy

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sliding and Adaptive windows to Improve Change Mining in Process Variability

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INFORMATION 2024年第8期15卷 445页

作者： Hmami, Asmae Sbai, Hanae Baina, Karim Fredj, Mounia Mohammed V Univ Rabat Natl Higher Sch Comp Sci & Syst Anal ENSIAS AlQualsadi Res Team Rabat 8007 Morocco Univ Hassan II Casablanca Fac Sci & Technol Mohammadia 20650 Morocco

A configurable process Change Mining approach can detect changes from a collection of event logs and provide details on the unexpected behavior of all process variants of a configurable process. The strength of Change Mining lies in its ability to serve both conformance checking and enhancement purposes;users can simultaneously detect changes and ensure process conformance using a single, integrated framework. In prior research, a configurable process Change Mining algorithm has been introduced. Combined with our proposed preprocessing and change log generation methods, this algorithm forms a complete framework for detecting and recording changes in a collection of event logs. Testing the framework on synthetic data revealed limitations in detecting changes in different types of variable fragments. Consequently, it is recommended that the preprocessing approach be enhanced by applying a filtering algorithm based on sliding and adaptive windows. Our improved approach has been tested on various types of variable fragments to demonstrate its efficacy in enhancing Change Mining performance.

关键词： adaptive window algorithm configurable business process change mining filtering preprocessing process variability sliding window algorithm

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Ship collision avoidance behaviour recognition and analysis based on AIS data

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OCEAN ENGINEERING 2022年 245卷 110479-110479页

作者： Rong, H. Teixeira, A. P. Soares, C. Guedes Univ Lisbon Ctr Marine Technol & Ocean Engn CENTEC Inst Super Tecn Av Rovisco Pais P-1049001 Lisbon Portugal

A novel approach is proposed to automatically identify the ship collision avoidance behaviour from ship trajectories based on an improved sliding window algorithm. The approach has three main stages: (1) determining the ships' obligations according to the Convention on the International Regulations for Preventing Collision at Sea (COLREGs);(2) assessing the rudder angle according to the true bearing of the target ship;(3) identifying the corresponding ship handling behaviour from the ship trajectory taking into account the Rate of Turn and its derivative based on the sliding window algorithm. Four typical encounter scenarios are studied to demonstrate the feasibility and effectiveness of the proposed method. The approach is then applied to near collision scenarios identified in the maritime traffic off the continental coast of Portugal, which allowed the characterization of the relative and spatial distributions of the locations at which the ships take evasive manoeuvres. The results show that the approach can be applied to accurately detect the ship collision avoidance behaviour from Automatic Identification System trajectory data, and the characterization of the collision avoidance behaviour can potentially be used by situational awareness systems and as the basis for ship collision avoidance decision-making.

关键词： Ship evasive manoeuvring Collision avoidance sliding window algorithm Near collision scenario

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Prediction of COVID-19 spread by sliding mSEIR observer

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Science China(Information Sciences) 2020年第12期63卷 166-178页

作者： Duxin CHEN Yifan YANG Yifan ZHANG Wenwu YU Jiangsu Key Laboratory of Networked Collective Intelligence School of Mathematics Southeast University School of Information Science and Engineering Southeast University

The outbreak of COVID-19 has brought unprecedented challenges not only in China but also in the whole world. Thousands of people have lost their lives, and the social operating system has been affected seriously. Thus, it is urgent to study the determinants of the virus and the health conditions in specific populations and to reveal the strategies and measures in preventing the epidemic spread. In this study, we first adopt the long short-term memory algorithm to predict the infected population in China. However,it gives no interpretation of the dynamics of the spread process. Also the long-term prediction error is too large to be accepted. Thus, we introduce the susceptible-exposed-infected-removed(SEIR) model and further the metapopulation SEIR(mSEIR) model to capture the spread process of COVID-19. By using a sliding window algorithm, we suggest that the parameter estimation and the prediction of the SEIR populations are well performed. In addition, we conduct extensive numerical experiments to show the trend of the infected population for several provinces. The results may provide some insight into the research of epidemics and the understanding of the spread of the current COVID-19.

关键词： epidemic spread prediction sliding window algorithm COVID-19

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A Vision-based Navigation System for an Agricultural Autonomous Tractor

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IFAC-PapersOnLine 2022年第32期55卷 48-53页

作者： Sristi Saha Tsuyoshi Morita Ricardo Ospina Noboru Noguchi

RTK-GNSS (Real-time Kinematic-Global Navigation Satellite System) signal is necessary for the safe navigation of an autonomous tractor. However, the main problem associated with this type of precise GNSS is that the RTK correction signal might not be available at all geographical locations. Tree canopies present close to the tractors’ vicinity obstruct satellite signals and degrade the position accuracy. This can lead the autonomous tractor to travel outside of its predetermined path, which is unsafe. To avoid such situations, this study aims to develop a vision-based road detection system, which does not rely on RTK-GNSS. This system aims to detect both paved and unpaved roads in rural farm areas. It takes the RGB images obtained from an HD onboard camera and segments the road surface and road edges. The segmentation is performed by using several image filters, the sliding window method, and a set of rules that are determined manually. Finally, the lateral error obtained from the machine vision system is transmitted to the tractor's automatic navigation system. Experimental runs performed at the experimental farm of Hokkaido University showed that the lateral error calculated by this system is less than 0.2 m for unpaved roads and 0.4 m for paved roads. This shows that the system can detect both paved and unpaved roads. Future work addresses considerations to make the system more robust.

关键词： Image segmentation sliding window algorithm lateral error robot navigation robot vision road edge detection precision agriculture

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A New Approach for the Development of Grid Models Calculating Tropospheric Key Parameters over China

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REMOTE SENSING 2021年第17期13卷 3546-3546页

作者： Zhu, Ge Huang, Liangke Liu, Lilong Li, Chen Li, Junyu Huang, Ling Zhou, Lv He, Hongchang Guilin Univ Technol Coll Geomat & Geoinformat Guilin 541004 Peoples R China Nat Resources Informat Ctr Guangxi Zhuang Autonom Beidou Nav Dept Nanning 530028 Peoples R China

Pressure, water vapor pressure, temperature, and weighted mean temperature (T-m) are tropospheric parameters that play an important role in high-precision global navigation satellite system navigation (GNSS). As accurate tropospheric parameters are obligatory in GNSS navigation and GNSS water vapor detection, high-precision modeling of tropospheric parameters has gained widespread attention in recent years. A new approach is introduced to develop an empirical tropospheric delay model named the China Tropospheric (CTrop) model, providing meteorological parameters based on the sliding window algorithm. The radiosonde data in 2017 are treated as reference values to validate the performance of the CTrop model, which is compared to the canonical Global Pressure and Temperature 3 (GPT3) model. The accuracy of the CTrop model in regards to pressure, water vapor pressure, temperature, and weighted mean temperature are 5.51 hPa, 2.60 hPa, 3.09 K, and 3.35 K, respectively, achieving an improvement of 6%, 9%, 10%, and 13%, respectively, when compared to the GPT3 model. Moreover, three different resolutions of the CTrop model based on the sliding window algorithm are also developed to reduce the amount of gridded data provided to the users, as well as to speed up the troposphere delay computation process, for which users can access model parameters of different resolutions for their requirements. With better accuracy of estimating the tropospheric parameters than that of the GPT3 model, the CTrop model is recommended to improve the performance of GNSS positioning and navigation.

关键词： GNSS positioning GNSS meteorology MERRA-2 sliding window algorithm tropospheric parameters GNSS

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