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Indoor Vehicle Positioning Based on multi-sensor data fusion

Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 77-85页

作者：王明阳时良仁李元龙 Department of Automation Shanghai Jiao Tong University、Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai 200240China

This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are *** fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit,we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter,*** then conducted simulations and experiments to examine the performances of the *** the experiment,the Kalman filtering hyperparameters are configured,and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via *** verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.

关键词： indoor vehicle positioning multi-sensor data fusion ultra-wideband linear Kalman filter extended Kalman filter

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Crack propagation characteristics during progressive failure of circular tunnels and the early warning thereof based on multi-sensor data fusion

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GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES 2022年第5期8卷 1-24页

作者： Zhang, Liming Chao, Wenwen Liu, Zhongyuan Cong, Yu Wang, Zaiquan Qingdao Univ Technol Sch Civil Engn Qingdao 266033 Peoples R China Qingdao Univ Technol Cooperat Innovat Ctr Engn Construct & Safety Shan Qingdao 266033 Peoples R China Qingdao Univ Technol Sch Sci Qingdao 266033 Peoples R China

Biaxial compression tests were conducted on circular tunnels that constructed in sandstone to reveal the evolution of macro-cracks, the strain field, and acoustic emission (AE) parameters during deformation of tunnels. An early-warning method for tunnel failure based on multi-sensor data fusion was studied. The results indicate that tensile cracks first initiate at the arch haunch of the tunnel;then shear cracks occur on both sides of the opening, forming two asymmetric V-shaped grooves;finally, tensile-shear cracks on both sides of the tunnel propagate to the vault, triggering brittle failure of the tunnel. The strain concentration zones appear earlier than cracks in the tunnel, and the location and range of strain concentration zones cover the crack-propagation paths. Before the failure of tunnels, a series of precursor events occur, including an AE quiet period, a significant, rapid drop in the AE-based b value, and abrupt increases in AE entropy and covariance of the strain field. The monitoring data of each physical field provide early warning asynchronously: the early-warning time of AE entropy is the earliest while that of the AE quiet period is the latest. Membership functions are constructed taking early-warning results of monitoring data in various physical cases as bodies of evidence, and their critical values are determined using normal distribution. multi-sensor data are fused using the Dempster-Shafer (D-S) evidence theory to realize time-varying prediction and provision of early warning with graded probabilities for tunnel failure based on collaborative multi-sensor data fusion.

关键词： Tunnel Crack propagation Acoustic emission Failure warning multi-sensor data fusion

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multi-sensor data fusion and CNN-LSTM Model for Human Activity Recognition System

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sensorS 2023年第10期23卷 4750-4750页

作者： Zhou, Haiyang Zhao, Yixin Liu, Yanzhong Lu, Sichao An, Xiang Liu, Qiang Beijing Inst Petrochem Technol Acad Artificial Intelligence Beijing 102617 Peoples R China Beijing Acad Safety Engn & Technol Beijing 102617 Peoples R China

Human activity recognition (HAR) is becoming increasingly important, especially with the growing number of elderly people living at home. However, most sensors, such as cameras, do not perform well in low-light environments. To address this issue, we designed a HAR system that combines a camera and a millimeter wave radar, taking advantage of each sensor and a fusion algorithm to distinguish between confusing human activities and to improve accuracy in low-light settings. To extract the spatial and temporal features contained in the multisensor fusion data, we designed an improved CNN-LSTM model. In addition, three data fusion algorithms were studied and investigated. Compared to camera data in low-light environments, the fusion data significantly improved the HAR accuracy by at least 26.68%, 19.87%, and 21.92% under the data level fusion algorithm, feature level fusion algorithm, and decision level fusion algorithm, respectively. Moreover, the data level fusion algorithm also resulted in a reduction of the best misclassification rate to 2%similar to 6%. These findings suggest that the proposed system has the potential to enhance the accuracy of HAR in low-light environments and to decrease human activity misclassification rates.

关键词： human activity recognition multi-sensor data fusion fusion algorithm CNN-LSTM

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Research on Real -Time Fire Prediction System Using multi-sensor data fusion and Teaching Application

Research on Real -Time Fire Prediction System Using Multi-Se...

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2024 Cross Strait Radio Science and Wireless Technology Conference

作者： Shen, Xiaobo Wang, Liuliu Shu, Renyi Zhu, Jiabin Zheng, Yaling Huainan Normal Univ Huainan Anhui Peoples R China Anhui Prov Key Lab Beidou Satellite Nav Technol Hefei Anhui Peoples R China

ISBN: (纸本)9798331507800;9798331507794

Fire is a frequent and heavy loss of disaster, fire early warning is the first line of defense against fire hazards, found that the fire and dispose of timely can significantly reduce fire hazards, reduce property losses and casualties. For the latent period of fire and early warning, it is the goal that people have been exploring. This paper proposes a fire realtime early warning model with combustion sound infrasound, temperature, humidity, smoke, flame, gas concentration of six sensor data fusion, the design of the early warning system hardware and computer applications, cell phone applications, through the system joint test, showed that the fusion system can be able to effectively identify the fire situation, ahead of the rapid response, with a certain degree of reliability. At the same time, the system design process is applied to the course teaching as an engineering case, which plays the role of scientific research to feed the teaching, and the students' engineering awareness and practical skills are enhanced.

关键词： real-time prediction multi-sensor data fusion neural network engineering education

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Design of security monitoring system based on multi-sensor data fusion 36

Design of security monitoring system based on multi-sensor d...

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36th Chinese Control and Decision Conference (CCDC)

作者： Qi, Tao Pang, Zongqiang Yang, Hongji Nanjing Univ Posts & Telecommun Sch Automat & Artificial Intelligence Nanjing Peoples R China

ISBN: (纸本)9798350387780;9798350387797

Aiming at the single monitoring technology of the existing building security monitoring system, a building monitoring system based on IoT and multi-sensor fusion is designed and developed. The system focuses on addressing sensor false alarms and enabling remote real-time monitoring. The main control unit of the system is the STM32F103ZET6 MCU, which collects real-time indoor air quality data through various sensors and captures real-time video streams using a network camera. By utilizing multi-sensor data fusion technology, the system incorporates the ESP8266 wireless communication module, relay module, and infrared module to establish wireless remote linkage monitoring of the building's environment and video on the cloud platform. Additionally, it enables infrared remote control of the equipment within the building. Test results demonstrate the system's effectiveness in avoiding false alarms caused by a single sensor through multi-sensor data fusion technology. Moreover, the system's infrared remote control feature ensures easy operation and effective control of various devices via the cloud platform.

关键词： loT wireless communication multi-sensor data fusion cloud platform infrared remote control

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multi-sensor data fusion for rotating machinery fault detection using improved cyclic spectral covariance matrix and motor current signal analysis

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2023年 230卷

作者： Guo, Junchao He, Qingbo Zhen, Dong Gu, Fengshou Ball, Andrew D. Shanghai Jiao Tong Univ State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China Hebei Univ Technol Sch Mech Engn Tianjin 300401 Peoples R China Univ Huddersfield Ctr Efficiency & Performance Engn Huddersfield HD1 3DH W Yorkshire England

When an abnormal situation occurs in rotating machinery, fault feature information may be scattered on multiple sensors, and fault feature extraction through a single sensor is not enough for fault detection. Moreover, fault detection techniques based on vibration signals are commonly applied to monitor the health of rotating machinery. However, the installation of vibration sensor is inconvenient, which will greatly affect collected signal and thus influence detection effect. This paper proposes a novel method with improved cyclic spectral covariance matrix (ICSCM) and motor current signal analysis, which achieves multi-sensor data fusion for rotating machinery fault detection. Firstly, an improved cyclic spectral is proposed to process multi-sensor signals collected from rotating machinery, which adaptively acquires multi-sensor mode components. Subsequently, sample entropy of acquired mode components is utilized to construct the ICSCM, which can fully preserve the interaction relationship between different sensors. Finally, ICSCM is incorporated into extreme learning machine classifier to identify different fault types for rotating machinery. The merits of the proposed method are validated using two datasets. Analysis results demonstrate that the proposed method has achieved satisfactory results and more reliable diagnosis accuracy than other state-of-the-art algorithms in rotating machinery fault detection.

关键词： multi-sensor data fusion Improved cyclic spectral covariance matrix Motor current signal analysis Rotating machinery Fault detection

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Information security of flowmeter communication network based on multi-sensor data fusion

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ENERGY REPORTS 2022年 8卷 12643-12652页

作者： Lin, Tao Wu, Peng Gao, Fengmei Chongqing Coll Elect Engn Sch Elect & Internet Things Chongqing 401331 Peoples R China Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Chongqing Coll Elect Engn Sch Informat Smart Hlth Chongqing 401331 Peoples R China

With the progress of society, the use of intelligent flowmeters has become more and more widespread. The powerful functions of intelligent flowmeters have made people's production and living more convenient. Still, at the same time, public data, including industry and agriculture privacy and information security, have exposed huge security risks. This paper aims to study the information security of flowmeter communication networks based on multi-sensor data fusion and artificial intelligence-driven. The present study introduces network information security and its development direction, proposes a cloud computing-based network security situation prediction algorithm, uses the cloud model to predict the security situation of the cloud computing network, and gives a cloud computing network security situation assessment system model. At the same time, it analyzes and explores network information security, and explores network security based on multi-sensor data fusion and artificial intelligence driving. The experimental research results show that due to the unique advantages of the universal flowmeter intelligent processing system, such as high resource utilization, uniform standards, and wide application range, it has a lot of room for development. With the development of science and technology and application fields, and the continuous progress and expansion of general flowmeters, the future space of general category flowmeters is huge. The popularity of the Internet is getting faster and faster, and the requirements for information security are getting higher and higher, and the information security issues faced in the future will become more and more complicated. Therefore, it is necessary to speed up the construction of an information security system, and take measures to strictly manage from the aspects of law, management, technology and talents. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http

关键词： multi-sensor data fusion Artificial intelligence drive Network information security Simulation analysis Cloud computing

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multi-sensor data fusion Method Based on ARIMA-LightGBM for AGV Positioning 5

Multi-sensor Data Fusion Method Based on ARIMA-LightGBM for ...

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5th International Conference on Robotics and Automation Sciences (ICRAS)

作者： Che, HongLei China Acad Safety Sci & Technol Beijing Key Lab Metro Fire & Passenger Transporta Beijing Peoples R China

ISBN: (纸本)9780738133119

This paper proposes a novel AGV multi-sensor data fusion method. First, for the problem of multi-sensor error changing with time, use ARIMA time series to process the positioning error data, and establish a time series model of each sensor error as a new feature input of the subsequent regression model. Then, the widely used machine learning regression model LightGBM is used to fuse the positioning data, train two LightGBM models for the coordinate data in two directions, and output the positioning results at the same time. Finally, through comparison experiments, the positioning accuracy can reach 6.5mm, which verifies the superiority of this method.

关键词： multi-sensor data fusion ARIMA time series LightGBM positioning error AGV Positioning

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Autonomous Delivery Vehicle System Based on multi-sensor data fusion

Autonomous Delivery Vehicle System Based on Multi-Sensor Dat...

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2024 International Conference on Intelligent Robotics and Automatic Control

作者： Lei, Runyu Tang, Longbin Guo, Jiaxin Sun, Jie Bu, Qinglei Natl Univ Singapore Suzhou Res Inst Suzhou Peoples R China Xian Jiaotong Liverpool Univ Sch Adv Technol Suzhou Peoples R China

ISBN: (纸本)9798350389814;9798350389807

With the rapid advancement of science and technology, people's yearning for a more convenient life has gradually become concrete, which has given rise to a huge logistics industry chain. At the same time, the ever-increasing labor costs have caused an urgent need for autonomous delivery vehicles. This paper presents the design and integration of an autonomous vehicle system for efficient indoor parcel delivery, addressing the challenges of navigating dynamic indoor environments. This vehicle system leverages a multi-sensor approach, integrating LiDAR, radar, Inertial Measurement Unit (IMU), GPS, and odometer data to provide comprehensive environmental perception and precise localization, which will contribute to the field by providing a practical application of autonomous vehicle technology in a constrained environment, offering a solution for the logistics industry's indoor delivery challenges.

关键词： LiDAR SLAM Autoware.Universe Path Planning multi-sensor data fusion

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Factory Environmental Monitoring System based on Zigbee Technology and multi-sensor data fusion 12

Factory Environmental Monitoring System based on Zigbee Tech...

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12th International Conference on Networks, Communication and Computing (ICNCC)

作者： Feng, Lu Lai, Wugang Yang, Chengyi Li, Jianan Yang, Biyun Chengdu Univ Technol Chengdu Peoples R China

ISBN: (纸本)9798400709265

In the standard Zigbee protocol, there is no design specification for data fusion, so that it can only be used in applications with low data redundancy. For large-scale networks, the data redundancy in the network is large, and data redundancy in the network will cause nodes to frequently compete for channels, increase network latency, and even cause network paralysis. In order to solve this problem, a wireless sensor network based on Zigbee technology is built, and a multi-level adaptive data fusion algorithm is used to reduce data redundancy, improve data accuracy and improve query efficiency, and realize accurate collection and intelligent monitoring of factory environmental data.

关键词： Zigbee technology multi-sensor data fusion Wireless sensor networks

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