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Reconstruction of Furnace Temperature Field by Ultrasonic Transducer 15

Reconstruction of Furnace Temperature Field by Ultrasonic Tr...

引用

15th IEEE International Conference on Electronic measurement and Instruments, ICEMI 2021

作者： Chao, Fenjin Wang, Shaohong Zhou, Fuqiang Zhao, Zeyi Chen, Lei Xu, Xiaoli Beijing Information Science Technology University Key Laboratory of Modern Measurement Control Technology Ministry of Education Beijing China

ISBN: (纸本)9781665444910

There are many deficiencies in contact temperature measurement, which can not provide a good guarantee for economy, efficiency and safety. Ultrasonic sensor temperature measurement technology has a good effect on the real-time monitoring of complex temperature field. This study takes the boiler furnace as the research object and the reconstruction of the temperature field in the furnace as the research purpose. Based on the finite element method, a single peak symmetrical temperature field model of the furnace is established on COMSOL platform to simulate the propagation of sound waves in the furnace, calculate the flight time according to the cross-correlation algorithm, and restore the temperature field of the furnace temperature field model by using the least square method and interpolation algorithm. The results show that the maximum relative error of flight time and theoretical flight time obtained by cross-correlation algorithm is 0.85%, and the average absolute error of reconstructed temperature field and single peak symmetric temperature field is 31K, which has a good reconstruction effect. © 2021 IEEE.

关键词： Temperature

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HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD REGISTRATION METHOD 10

HAND-TO-EYE CALIBRATION OF A ROBOTIC ARM USING POINT CLOUD R...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Miao, Zhuoran Zuo, Yunbo Hu, Huan Ge, Xiaoliang Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

The objective of this paper is to investigate a hand-eye calibration approach employing an eye-to-hand configuration, focusing on point cloud registration. In the initial segments of the paper, the paper delineate the core principles that underpin hand-eye calibration, as well as the various techniques that are predominantly utilized in this field. Furthermore, the article meticulously analyzes the limitations of the traditional methods and identifies potential areas where improvements can be made. Subsequently, it delves into the hand-eye calibration methodology grounded in 3D point cloud registration. This exploration includes an in-depth analysis of an enhanced version of the Super 4PCS Algorithm-based point cloud registration algorithm, which is a novel and effective method for point cloud registration. Additionally, the article discusses the intricacies of coordinate system transformation and provides a comprehensive explanation of how to solve the hand-eye calibration equation AX=XB using the navy method. Furthermore, the paper empirically validates the efficacy and precision of this method. This validation process involves a comparative analysis with other existing approaches. Lastly, it summarizes the research findings and discusses the strengths and limitations of the proposed method. © The Institution of Engineering & technology 2024.

关键词： Robotic arms

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Sparse Bayesian Learning based on Fast Marginal Likelihood Maximization for Joint User Activity Detection and Channel Estimation in Grant-Free NOMA 15

Sparse Bayesian Learning based on Fast Marginal Likelihood M...

引用

15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2022

作者： Chen, Shuo Cen, Zhigang Li, Haojie Li, Xuehua Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China

ISBN: (数字)9781665488877

ISBN: (纸本)9781665488877

Grant-free non-orthogonal multiple access (GF-NOMA) is a promising solution to solve the massive connectivity problem with low latency and signaling overhead. User activity detection (UAD) and channel estimation (CE) are two enabling technologies in GF-NOMA systems. In this paper, a correlation-enhanced sparse Bayesian learning algorithm based on fast marginal likelihood maximization (CSBL-FM) is proposed, which can improve the performance of the UAD and CE without prior knowledge of channel state information and sparsity. Firstly, a multi-frame sparse model is proposed so as to exploit the correlation and sparsity characteristics of single time slot and among multiple frames. Then, in order to accurately realize signal reconstruction, channel estimation process is described as sparse signal recovery process based on user indicators and training sequences. Next, based on the proposed multi-frame sparse model, the loss function is derived and optimized to detect active users by utilizing fast marginal likelihood maximization. Simulation results show that the proposed CSBL-FM algorithm is practical to be applied in GF-NOMA system by achieving the balance between high reconstruction performance and fast convergence speed. © 2022 IEEE.

关键词： Channel estimation

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FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VARIABLE SPEED AND STRONG NOISE 10

FAULT DIAGNOSIS METHOD BASED ON THE TIMESNET MODEL UNDER VAR...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qiao, Wan Liu, Xiuli Huang, Jinpeng Wu, Guoxin Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

Aiming at the fault diagnosis of rotating machinery in industrial production, which faces the problems of signal noise, variable speed and other interferences that lead to inconspicuous fault features, and the traditional methods rely on manual experience for feature extraction and lack of robustness, the present study introduces a novel fault diagnosis approach utilizing the TimesNet model. This method takes the temporal multi-periodicity as the starting point, and the one-dimensional original signal is divided into multiple two-dimensional signals by different sizes of the period respectively. Subsequently, Inception-Attention modeling is applied to extract intricate time and space information. The experiments use the planetary gearbox dataset to verify the influence of different parameters and structures of TimesNet on the diagnostic effect, and carry out comparative tests with five time-series classification models, which provide some reference value for the application of TimesNet in fault diagnosis. © The Institution of Engineering & technology 2024.

关键词： Epicyclic gears

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RESEARCH ON BUILDING ALGORITHM OF INDOOR DENSE MAP BASED ON ORB-SALM2 9

RESEARCH ON BUILDING ALGORITHM OF INDOOR DENSE MAP BASED ON ...

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9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Zhang, Pengbo Zhang, Zheng Ding, Bingchao Xu, Xiaoyu Wang, Chao Su, Qinghua Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781839538391

The purpose of visual SLAM (Simultaneous Localization and Mapping) technology is building accurate map and estimating correct camera pose. Since the sparse point cloud map generated by the traditional ORB-SLAM2 algorithm can not be directly applied to the 3D path planning for mobile robots due to inability to generate grid maps, this paper proposes a novel method which improves traditional ORB-SLAM2 algorithm for building more detialed 3D map. The ORB (Oriented FAST and Rotated BRIEF) algorithm is used to detect the image feature points in the front end, and the extracted feature points are processed by using the quad tree based homogenization strategy. At the back end, EPnP (Effective Perspective-n-Point) and ICP (Iterative Closest Point) algorithms are comprehensively used to optimize camera pose and to improve the pose estimation accuracy. Based on ORB-SLAM2, the proposed method adds dense mapping threads to build dense 3D point cloud maps. The experimental results show that the method presented in this paper is effective and robust in both common datasets and real scenes, and the root mean square error of the trajectory under two closed-loop datasets is less than 0.1 m, which can be used for robot navigation and path planning. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Mapping

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Construction of an international IT-driven sharing platform for inheriting and communication of Dongba manuscripts

Construction of an international IT-driven sharing platform ...

引用

2014 International Conference on Applied Mechanics, Mechatronics and Intelligent System, AMMIS 2014

作者： Xu, Xiao Li Wu, Guo Xin Wang, Hong Jun Chen, Tao Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University 100192 China

ISBN: (纸本)9783038351757

Dongba hieroglyph among Naxi ethnic minority is the only globally recognized hieroglyph still in use. Dongba ancient manuscripts are registered on the list of Memory of the World by UNESCO. In order to secure the inheritance and communication of Dongba Manuscripts, we analyze the obstacles encountered in the process of inheritance and communication. We apply IT to construct a digital and network-oriented international Dongba Manuscripts information sharing platform to collect, sort out, extract and disseminate digitalized information of Dongba Manuscripts hieroglyph. Environment and technology support should be provided to carry out remote academic research and exchanges through the international sharing platform. Efforts should be made to seek digital channels to rescue and inherit Memory of the World, Dongba Manuscripts. © (2014) Trans Tech Publications, Switzerland.

关键词： Mechanics

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SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT ASSOCIATION 10

SMOKING BEHAVIOR DETECTION BASED ON IMPROVED YOLOV7 OBJECT A...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Chen, Sai Zuo, Yunbo Hu, Huan Zheng, Yifan Li, Haowei Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781837242672

To address the security risks caused by unauthorized individuals smoking in public places, a method for detecting smoking behavior based on an improved YOLOv7 target association is proposed. First, the improved YOLOv7 algorithm is used to detect the people and cigarette targets in the image, and then the distance relationship between the center coordinates of the cigarette target detection frame and the person target detection box is calculated, and the correlation between the two is located to determine whether there is smoking behavior. The improved YOLOv7 algorithm introduces the CBAM attention module to prioritize key areas and diminish background interference. Simultaneously, the SIOU loss function is employed to bolster the precision of the regression outcomes. Experiments conducted on the test dataset reveal that the proposed approach achieves an accuracy of 91.35% and a detection speed of 78 FPS, achieving real-time accurate detection effects. © The Institution of Engineering & technology 2024.

关键词： IMPROVED YOLOV7 OBJECT ASSOCIATION SMOKING BEHAVIOR DETECTION

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Research on Dynamic Characteristics of Confluence Planetary Row under Speed Impact 15

Research on Dynamic Characteristics of Confluence Planetary ...

引用

15th IEEE International Conference on Electronic measurement and Instruments, ICEMI 2021

作者： Yang, Jun Tang, Changliang Wang, Liyong Liu, Xiaobo Su, Bokang Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China

ISBN: (纸本)9781665444910

As an important part of the dual-flow transmission device, the confluence planetary row works under the complex working conditions of high load, high frequency and strong impact, and the problem of vibration and noise is particularly prominent. In this paper, a concentrated parameter model of the confluence planetary gear dynamics is established, and the time-varying meshing stiffness, bearing stiffness, damping, shaft bending stiffness and other factors are comprehensively considered to establish a dynamic model suitable for the confluence planetary gear system under speed shock conditions. The dynamic characteristics of the confluence planetary gear under the speed shock load were numerically calculated, and the speed shock conditions were analyzed. The results show that as the speed increases, the vibration amplitude of each component shows an increasing trend;in the state of rotating speed shock excitation, the order spectrum signal is mainly composed of meshing frequency and high-order frequency doubling components, and the amplitude of each component also increases with the increase of speed. The test results are in good agreement with the numerical analysis. The conclusions obtained provide important theoretical support and engineering value for the vibration reduction, noise reduction and performance optimization of the confluence planetary gear system. © 2021 IEEE.

关键词： Speed

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RESEARCH ON SLAM IMPROVEMENT METHOD BASED ON CARTOGRAPHER 9

RESEARCH ON SLAM IMPROVEMENT METHOD BASED ON CARTOGRAPHER

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9th International Symposium on Test Automation and Instrumentation, ISTAI 2022

作者： Huang, Yuxiang Wu, Guoxin Zuo, Yunbo Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781839538391

Cartographer is a SLAM (simultaneous localization and map building) algorithm based on graph optimization, which is commonly used for building maps of mobile robots in large indoor scenes, but there are problems of point cloud data feature loss and motion distortion caused by low frame rate LIDAR in data processing of LIDAR. In this paper, an improved algorithm based on Cartographer algorithm is proposed to address these problems. First, a voxel filtering method with downsampling of neighboring points is used for k-neighborhood search to improve the map building accuracy and computation rate. Then, a wheeled odometer-assisted algorithm is used to remove motion distortions and reduce the cumulative errors that occur in a large scale environment, thus improving the map building effect. Finally, the two algorithms are tested separately by simulating experiments in the gazebo simulation environment in the robot operating system, and the experimental results show that the improved algorithm builds the map trajectory with less error, thus verifying its effectiveness and feasibility. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Optical radar

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DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CROSS-ATTENTION NETWORK 10

DENSE POINT CLOUD MAP CONSTRUCTION BASED ON ORB-SLAM2 AND CR...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Liu, Yizheng Su, Qinghua Song, Yue Zhang, Pengbo Xie, Zhihao Wang, Liyong Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

In the field of 3D vision technology, binocular vision technology, as a representative of low-cost and high-efficiency methods, has gained widespread attention and holds superior application prospects in the industrial sector. The current state-of-the-art binocular sparse visual SLAM systems can accurately and reliably estimate camera trajectories and landmark positions. However, these sparse maps are solely used for localization and cannot be employed for other tasks such as obstacle avoidance or scene understanding. To address this, this paper proposes a framework for constructing dense point cloud maps in binocular sparse visual SLAM systems. This framework enhances the traditional ORB-SLAM2 algorithm by incorporating depth estimation using a cross-attention network to complete depth information and build dense point cloud maps based on its localization capabilities. For the first-frame image, the proportion of incorrectly predicted pixels in the KITTI dataset is only 1.77%. The proposed method is effective and robust on common datasets, suitable for constructing dense point cloud maps in outdoor large-scale scenes. The output model is overall comprehensive and detailed, holding significant practical value in various outdoor scenarios. © The Institution of Engineering & technology 2024.

关键词： Binoculars

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