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Analysis of the 3-D Evolution Characteristics of Ionospheric Anomalies During a Geomagnetic Storm Through fusion of GNSS and COSMIC-2 data

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2022年 60卷 1页

作者： Wang, Yang Yao, Yibin Kong, Jian Zhai, Changzhi Chen, Xuanxi Shan, Lulu Wuhan Univ Sch Geodesy & Geomat Wuhan 430079 Peoples R China Wuhan Univ Key Lab Geospace Environm & Geodesy Minist Educ Wuhan 430079 Peoples R China Wuhan Univ Chinese Antarctic Ctr Surveying & Mapping Wuhan 430079 Peoples R China Hohai Univ Sch Earth Sci & Engn Nanjing 210098 Peoples R China

To solve the ill-posed and accuracy problems experienced by global navigation satellite system (GNSS) computerized ionosphere tomography (CIT), this study proposes the use of the ionospheric profile data of COSMIC-2 as the initial scale factor to constrain GNSS data. At present, studies are lacking on long-term data volume statistics and accuracy assessment of COSMIC-2 ionospheric profile products. Therefore, we calculated the data volume statistics and assessed the ionospheric quality of the COSMIC-2 data for the whole year of 2020. We used incoherent scattering radar (ISR) and ionosonde data to evaluate the quality of the COSMIC-2 ionospheric profile data. To verify the accuracy and reliability of the CIT algorithm for COSMIC-2 ionosphere profile-constrained GNSS data, the American region was selected. On the plane, the tomographic results were superimposed and compared with the global ionospheric map (GIM). The root mean square (rms) of the vertical total electron content (VTEC) difference in the six periods was 0.68, 0.97, 0.63, 0.86, 0.76, and 0.82 total electron content unit (TECU), respectively. In the vertical direction, the scale factor that was not involved in the CIT was compared with the ratio of total electron contents (TECs) in each layer to the total TEC. The average difference of the ratio factors in the four periods was 3.72%, 2.79%, 1.80%, 3.05%, 1.99%, and 2.37%, respectively. Finally, an intermediate-level geomagnetic storm that occurred on July 25, 2020, was selected for analysis, and the 3-D ionospheric morphological changes and evolution characteristics of the Australian region during this geomagnetic storm were studied.

关键词： Global navigation satellite system Ionosphere Geomagnetic storms Satellites Tomography Harmonic analysis Global Positioning System Computerized ionosphere tomography (CIT) COSMIC-2 data fusion algorithm geomagnetic storm global navigation satellite system (GNSS) total electron content (TEC)

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Analysis of Situational Awareness in Substation Equipment Health Management

International Core Journal of Engineering

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International Core Journal of Engineering 2023年第6期9卷 278-286页

作者： Hongsen Song Xingzhong Xiong

Situation awareness has been widely applied in disaster warning, equipment detection, monitoring and other scenarios. Its data fusion and analysis methods have developed in a diversified way. For the health management of substation equipment, there is still room for improvement in order to effectively integrate information from multiple sites, analyze the operating status of multiple devices, detect and locate faults, and predict the overall situation. This paper discusses the concept of situation awareness, analyzes its role in the automation and intelligence process of substations, and summarizes the commonly used algorithms for data processing, situation evaluation, and prediction in recent years.

关键词： Situation Awareness Equipment Health Management Substation data fusion algorithm

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Rotational speed monitoring of brushed DC motor via current signal

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MEASUREMENT 2021年 184卷 109890-109890页

作者： Zhang, Qi Wen, Bin He, Yongling Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China

Sensor-less speed estimation of brushed DC motor is preferred for dynamic control and state monitoring. Ripplebased and model-based methods are widely applied for sensor-less speed estimation. This paper firstly offers a ripple-based technique, analyzes their features and performance, then presents a modified Kalman filter to fuse the ripple-base and model-based results. The two source data are fused through modification of the noise covariance matrices of the conventional Kalman filter. Experimental validates the proposed algorithm. Test shows that the proposed method reduces speed estimation to less 3% and owns roughly 8 times of accuracy comparing with conventional ripple-based and model-based methods. The proposed method is suitable for speed monitoring of industrial applications involving brushed DC motor.

关键词： Brushed DC motor Sensor-less speed estimation Kalman filter Noise covariance data fusion algorithm

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Design of 2D LiDAR and camera fusion system improved by differential evolutionary PID with nonlinear tracking compensator

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INFRARED PHYSICS & TECHNOLOGY 2021年 116卷 103776-103776页

作者： Xu, Xiaobin Zhao, Minghui Lu, Yonghua Ran, Yingying Tan, Zhiying Luo, Minzhou Hohai Univ Coll Mech & Elect Engn Changzhou 213022 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Mech & Elect Engn Nanjing 210016 Peoples R China Changzhou Changgong Elect Technol Co Ltd Changzhou 213001 Jiangsu Peoples R China

An improved 2D LiDAR and camera fusion system is proposed for the 3D reconstruction of unknown environments. It combines the advantages of dense 2D point cloud and rich color image, adopting a differential evolutionary nonlinear tracking PID to control the pitching motion of LiDAR and camera accurately. The quadratic polynomial transition function is used to optimize the pitching trajectory. The environment was scanned by the system and converted into a 3D colored point cloud by the data fusion algorithm. The experimental results show: the proposed PID control algorithm can accurately control the pitching motion with a small average error (0.0267 degrees) and significantly reduce the point cloud inhomogeneity (0.00698);the processing time for converting each 2D point cloud into the 3D point cloud is about 0.6 ms;combined with the data fusion algorithm, the system can obtain the dense colored 3D point cloud;compared with binocular camera, depth camera and 3D LiDAR under the condition of strong light interference, the fusion system outperforms, with the reconstruction object errors of distance, length and width of 0.23%, 0.17% and 0.46% respectively. In conclusion, the system can obtain homogeneous, and dense colored 3D point cloud in real time while ensuring stable refresh frame rate.

关键词： 2D LiDAR Color camera data fusion algorithm Differential evolutionary nonlinear tracking PID

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An Online Calibration Method Based on n-Tuple and Opportunistic Communication for Mine Mass Portable Gas Sensors

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SENSORS 2021年第7期21卷 2451-2451页

作者： Wang, Gang Zhao, Yang Ding, Zeheng Zhao, Xiaohu China Univ Min & Technol IoT Percept Mine Res Ctr Xuzhou 221000 Jiangsu Peoples R China Natl Joint Engn Lab Internet Appl Technol Mines Xuzhou 221000 Jiangsu Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221000 Jiangsu Peoples R China

Due to the increasing deployment of the Internet of Things (IoT) in the mining industry, portable gas monitoring devices have been widely used. Sensor calibration of large-scale portable gas monitoring devices is becoming an urgent problem to be solved. An online sensor calibration algorithm based on n-tuple and opportunistic communication is proposed based on the specific characteristics (i.e., 'single-sensor, multi-position' and 'multi-sensor, single-position') of each portable gas monitoring device employed. In this paper, data collected from portable and fixed sensors were defined as multi-dimensional data points and gas monitoring data pairs, respectively. The cluster-based self-adaptive weighted data fusion algorithm and multi-period single sensor reliability fusion algorithm were proposed and used for overall judging. The overall judgments were broadcast to each wireless access point by network, and the reliability of the calibration information transmission was enhanced by opportunistic communications. The simulation results revealed that efforts required for the calibration of portable sensors were reduced significantly, and their reliability was improved.

关键词： data fusion algorithm gas monitoring data pairs multi-dimensional data points underground coal mine

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Using data monitoring algorithms to physiological indicators in motion based on Internet of Things in smart city

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SUSTAINABLE CITIES AND SOCIETY 2021年 67卷 102727-102727页

作者： Tian, Jian Gao, Lulu Henan Univ Sch Phys Educ Kaifeng 475000 Henan Peoples R China Henan Univ Sch Phys Educ Minsheng Coll Kaifeng 475000 Henan Peoples R China

This article discusses the monitoring of physiological indicators during exercise, combined with the data fusion algorithm of the smart city Internet of Things health. We use the hash value of the tuple key to the corresponding data block of the node, use the data block record to obtain the response of the target node, and output the data tuple. It is used as a measure of the load balance of health data streams to determine whether load migration is needed and to determine the way and amount of migration tasks to make migration decisions. The simulation experiments show that the method has good computational performance and dynamic load balancing. A series of mean arterial pressure and heart rate of patients and non-stationary health data, and a series of blood pressure and heart rate of health individuals in different postures are selected to perform experiments to analyze the transfer function and power spectra in the model, validating that the model can be used to reveal the changes associated with severe systemic response syndrome (SIRS), providing a hypothesis for the decomposition of autoregulation of physiological control under health and disease conditions.

关键词： Internet of Things data fusion algorithm Physiological indicators Monitoring Smart city

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Anode effect prediction method based on local effect detection

Anode effect prediction method based on local effect detecti...

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Chinese Automation Congress (CAC)

作者： Cui, Jiarui Zhang, Shuai Cao, Bin Li, Qing Huang, Ruoyu Yang, Xu Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing Peoples R China Guiyang Aluminum Magnesium Design & Res Inst Co L Guiyang Guizhou Peoples R China

ISBN: (纸本)9781728176871

In view of the situation that the current anode effect prediction methods can not cover all types of anode effects, or the anti-interference ability is poor, or the prediction advance is very small, this paper proposes a method to predict the global anode effect based on the local effect detection, that is, by using the local signal before forming the global anode effect instead of the cell voltage of the whole cell, the local or local anode effect can be detected Anode effect in local anode. Therefore, based on the internal structure of aluminum reduction cell, we divide the area. Then, the potential periodicity of anode current is obtained by analyzing the power spectrum of anode current. Finally, a local effect detection model based on data fusion method is used to predict the occurrence of global effects. The effectiveness of the algorithm is illustrated by the anode current data measured on-line during the actual operation of aluminum electrolysis.

关键词： Local effect power spectrum data fusion algorithm

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A Highly Accurate and Reliable data fusion Framework for Guiding the Visually Impaired

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IEEE ACCESS 2018年 6卷 33029-33054页

作者： Elmannai, Wafa M. Elleithy, Khaled M. Univ Bridgeport Dept Comp Sci & Engn Bridgeport CT 06604 USA

The world has approximately 253 million visually impaired (VI) people according to a report by the world health organization (WHO) in 2014. Thirty-six million people are estimated to be blind. According to WHO, 217 million people are estimated to have moderate to severe visual impairment. An important factor that motivated this research is the fact that 90% of VI people live in developing countries. Several systems were designed to improve the quality of the life of VI people and support their mobility. Unfortunately, none of these systems are considered to be a complete solution for VI people and these systems are very expensive. We present in this paper an intelligent framework for supporting VI people. The proposed work integrates sensor-based and computer vision-based techniques to provide an accurate and economical solution. These techniques allow us to detect multiple objects and enhance the accuracy of the collision avoidance system. In addition, we introduce a novel obstacle avoidance algorithm based on the image depth information and fuzzy logic. By using the fuzzy logic, we were able to provide precise information to help the VI user in avoiding front obstacles. The system has been deployed and tested in real-time scenarios. An accuracy of 98% was obtained for detecting objects and 100% accuracy in avoiding the detected objects.

关键词： Assistive wearable devices computer vision systems data fusion algorithm obstacle detection and obstacle collision avoidance sensor-based networks visual impairment blindness mobility limitation

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Multi-sensor fusion for robust target tracking in the simultaneous presence of set-membership and stochastic Gaussian uncertainties

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IET RADAR SONAR AND NAVIGATION 2017年第4期11卷 621-628页

作者： Lu, Kelin Zhou, Rui Beihang Univ Sch Automat Sci & Elect Engn Beijing Peoples R China

This study proposes a novel data fusion algorithm in sensor networks with simultaneous presence of set-membership and stochastic Gaussian measurement uncertainties. The proposed method is grounded in the marriage of ellipsoidal calculus theory and data compression algorithm. The point-valued measurement and the set-valued measurement are compressed into a uniform framework during the estimation. An optimal Kalman gain is obtained that minimises the upper bound of the mean square error of the estimation set. The proposed algorithm is applied to the target tracking problem and the estimation results show that the proposed algorithm improves the tracking performance.

关键词： sensor fusion target tracking set theory Gaussian processes stochastic processes calculus data compression Kalman filters estimation theory target tracking problem estimation set mean square error upper bound minimization optimal Kalman gain set-valued measurement point-valued measurement ellipsoidal calculus theory data compression algorithm stochastic Gaussian measurement uncertainty sensor networks data fusion algorithm set-membership robust target tracking multisensor fusion

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Magnetic orientation system based on magnetometer, accelerometer and gyroscope

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CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY 2017年第4期2卷 166-172页

作者： Chu, Zhiwei Chen, Chilai Liu, Youjiang Wang, Yingxian Lin, Xinhua Chinese Acad Sci Hefei Inst Phys Sci State Key Lab Transducer Technol Hefei 230031 Peoples R China Univ Sci & Technol China Sch Informat Sci & Technol Dept Automat Hefei 230026 Peoples R China Chinese Acad Sci Hefei Inst Phys Sci Key Lab Biomimet Sensing & Adv Robot Technol Anhu Hefei 230031 Peoples R China

Magnetic orientation systems have widely been used by measuring the earth magnetic field and provide a pervasive source of directional information. However, to obtain the high precision, orientation systems must be compensated prior to use for the various errors of magnetometers such as the bias, misalignment and inconsistence in sensitivity, and the pitch and roll angles, especially in dynamic state. In this study, magnetic orientation system mainly consist of three single-axis magnetometers, a tri-axis accelerometer and a tri- axis gyroscope were developed. An error-separation method was introduced to calibrate magnetometers. data from magnetometers, accelerometer and gyroscope were fused based on Kalman filtering. In addition, accelerometer and gyroscope were also calibrated before data fusion. Experimental results showed the heading error of magnetic orientation system was about 0.1 degrees in a static state, and <3 degrees in a dynamic state, which proved the effectivities of the calibration methods and data fusion algorithm.

关键词： error compensation triaxis gyroscope Kalman filtering calibration methods accelerometers gyroscopes data fusion algorithm magnetic orientation system single-axis magnetometers calibration error-separation method earth magnetic field measurement sensor fusion triaxis accelerometer magnetometers Kalman filters

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