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Distributed energy-efficient wireless sensing and information fusion via event-driven and state-rank activation

WIRELESS NETWORKS 2024年第4期30卷 2697-2711页

作者： Fu, Juteng Ma, Xiang Yu, Hang Dai, Keren Nanjing Univ Sci & Technol Sch Mech Engn Nanjing 210094 Peoples R China

The dynamic management of sensor nodes and advanced information fusion are necessary technologies to enhance the comprehensive performance of sensor networks. This paper presents a cascaded sensor dynamic activation and information fusion algorithm to simultaneously optimize the energy and sensing performance of wireless sensing networks. The proposed algorithm dynamically activates nodes that are most suitable for the current sensing task through a joint event-driven and state ranking activation algorithm that achieves a better sensing performance with lower energy costs. In addition, it further utilizes the sensing information of all the activated nodes with maximum efficiency, through an improved distributed kalman information fusion, which achieves an extra improvement in sensing accuracy as measured by the minimum variance. Finally, the superiority of the proposed cascaded algorithm is verified by a simulation comparison, achieving almost zero dead nodes in terms of energy, and a 62.1% decrease in average error in terms of sensing.

关键词： Wireless sensor network Energy autonomous operation Event-driven activation State-rank activation kalman filtering algorithm Finite time convergence

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A generalized model and solution algorithm for estimation of the dynamic freeway origin-destination matrix

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2007年第5期41卷 554-572页

作者： Lin, Pei-Wei Chang, Gang-Len Univ Missouri Dept Civil & Mech Engn Kansas City MO 64110 USA Univ Maryland Dept Civil & Environm Engn College Pk MD 20742 USA

This study presents a generalized model for estimating the dynamic freeway O-D distribution, based on measurable time series of mainline and ramp flows, and estimated travel time distributions. The proposed model captures the speed discrepancy among drivers, due either to their desired speeds or responses to congestion, with an embedded travel time distribution function and the identified interrelations between time-varying ramp and mainline flows. With the employed mainline information and travel time function, the proposed system equation has increased its observability with less parameters. The proposed model with a specially designed algorithm offers the potential for use in a network of realistic size, such as the 1-95 freeway corridor between the Maryland 1-695 and 1-495 beltways. Extensive numerical analyses with respect to the sensitivity of both input measurement errors and the selection of initial parameters on the estimation results have revealed that the proposed model is sufficiently robust for real-world applications. Published by Elsevier Ltd.

关键词： dynamic origin-destination estimation kalman filtering algorithm

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A Comprehensive Detection System for Track Geometry Using Fused Vision and Inertia

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2021年 70卷 1-15页

作者： Peng, Lele Zheng, Shubin Li, Peixing Wang, Yuling Zhong, Qianwen Shanghai Univ Engn Sci Sch Urban Railway Transportat Shanghai 201620 Peoples R China Shanghai Aerosp Equipment Mfg Gen Plant Res & Dev Shanghai 200245 Peoples R China

The track line suffers from track irregularity, subgrade settlement, rail surface defects, and gauge distortion. Measuring the track geometry quality plays an important role in rail administrations to safe operation and track maintenance. In order to meet the requirements of track daily inspection, this article describes a comprehensive detection system for the track geometry, which is designed by four cameras, an inclinometer, and an inertial measurement unit. Moreover, the detection system has the characteristics of simple structure, automatic detection, and multiple measurement parameters. First, to measure track alignment and irregularity, a multisensing calibration method is established to fuse visual sensors and inertial sensors. An accelerometer and a kalman filter are used to eliminate accumulated unrealistic drifts of accelerometer and gyroscope. Second, to measure the rail surface defects and gauge, the model of laser and machine vision is deduced to obtain the coordinate values in a unified coordinate system, and an improved iterative closest point method is developed to improve the matching accuracy. Finally, a series of experiments is carried out to validate the measuring performance. The results indicate that the proposed method can accurately measure the track geometry, with the maximum deviations of track alignment, track irregularity, rail defects, and gauge that are less than 0.5, 0.4, 0.3, and 0.1 mm, respectively. The detection system is not only simple in structure but also has multiple detection parameters, which is especially suitable for track daily maintenance.

关键词： Inertial measurement iterative closest point (ICP) method kalman filtering algorithm machine vision multisensor fusion rail gauge rail surface defects track alignment track geometry track irregularity

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Designing an intelligent image detection and transmission system for the Internet of Things

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WIRELESS NETWORKS 2023年第3期29卷 1213-1222页

作者： Zhang, Jingya West Anhui Univ Coll Elect & Informat Engn Lu An 237158 Anhui Peoples R China

The Internet of Things (IoT) aims to meet the needs of smart services by combining multiple information intelligence tools and network technologies. In terms of technology, management, cost, policy, and security, the development of the IoT still faces many challenges. This study proposes an intelligent image detection and transmission system based on IoT communication, with the following primary objectives: First, this study aims to provide an early warning model based on kalman filtering Fast Fourier Transform Support Vector Machine (KF-FFT-SVM). It delivers early warning signals by analyzing and extracting historical features from surface motion data for a given period. The step size for spectrum analysis is determined by the signal frequency and is used to create a training dataset and train the SVM model. The use of a trained model for early warning can improve the accuracy of early warning evaluation. Second, the forward line of the video image is used as the necessary information in the content symbol retrieval process, and the information required for the structure is used to improve the quality as much as possible. Because of the search and influence of the transmission quality of digital components, the important data in the digital transmission space is used to ensure the accuracy of digital components while transmitting a small amount of energy. Third, when the device is connected to the network, other users can obtain information about the device via security breaches. The data must be transmitted by both parties using their own identities, which increases transmission security. The design idea of ZigBee technology follows the method of distributing information, such as food space through a zigzag-shaped dance, and low power consumption with low cost. Finally, to increase system efficiency, non-orthogonal multiple access technologies realize and transmit data from multiple users in time, frequency, and code zones while using various channels for each use

关键词： Internet of Things Communication Image transmission Intelligent image detection kalman filtering algorithm ZigBee technology

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Monitoring of subsynchronous oscillation in a series-compensated wind power system using an adaptive extended kalman filter

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IET RENEWABLE POWER GENERATION 2020年第19期14卷 4193-4203页

作者： Shair, Jan Xie, Xiaorong Yuan, Liang Wang, Yanhui Luo, Yongzhi Tsinghua Univ State Key Lab Power Syst Beijing 100084 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia State Grid East Inner Mongolia Elect Power Supply Hohhot 010000 Peoples R China

The characteristics of subsynchronous oscillation (SSO) in series-compensated wind power systems are significantly affected by the system's operating condition. Besides the variation in the magnitude and frequency of the SSO during an SSO event, the fundamental frequency may also deviate from its nominal value. This study aims at capturing the dynamics of both subsynchronous and fundamental frequency components simultaneously. This work first explores the strengths and weaknesses of various kalman filtering based frequency tracking algorithms for joint tracking of the fundamental and SSO components. Then, it proposes a novel adaptive extended kalman filtering (AEKF) algorithm, in which the process noise covariance is updated online by maximising the probability density function of the predicted error. The process noise covariance factor changes to positive non-zero value whenever the frequency of the fundamental component deviates. Thus, the proposed AEKF extracts the time-varying subsynchronous component while also tracking the small variations in the fundamental frequency. The tracking performance of the AEKF is validated on computer-generated test signals as well as on the electromagnetic transient simulation model of an actual wind power system facing SSO. The captured fundamental and subsynchronous dynamics can be used for designing monitoring, protection, and control schemes for the SSO.

关键词： nonlinear filters oscillations wind power plants kalman filters adaptive kalman filters adaptive filters fundamental frequency AEKF actual wind power system captured fundamental dynamics subsynchronous dynamics subsynchronous oscillation series-compensated wind power system adaptive extended kalman filter SSO event kalman filtering based frequency tracking algorithms joint tracking fundamental SSO kalman filtering algorithm process noise covariance factor changes fundamental component deviates time-varying subsynchronous component

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Vehicle rear end collision warning method based on MeanShift and kalman filter tracking

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INTERNATIONAL JOURNAL OF VEHICLE DESIGN 2024年第1-2期95卷 1-21页

作者： Fang, Bin Hunan Police Acad Dept Traff Adm & Engn Changsha 410138 Peoples R China

To reduce the false alarm rate and alarm rate of vehicle rear end warning, and improve the accuracy of warning, a vehicle rear end warning method based on MeanShift and kalman filter tracking is proposed. Determine the rear end warning area, use a high-speed camera to capture the driving video image of the target vehicle, and perform image denoising and enhancement;detect the target vehicle through inter frame difference method, and combine the MeanShift algorithm with the kalman filter algorithm to complete the tracking and positioning of the target vehicle;Determine the position of the target vehicle and the relationship between the warning areas to achieve rear end warning. The experimental results show that the method proposed in this paper can effectively reduce the false alarm rate and alarm rate, with a false alarm rate always below 2% and an alarm rate of 98%. It has good application performance.

关键词： rear end collision of vehicles collision warning MeanShift algorithm kalman filtering algorithm warning area

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Calibration and evaluation of a combined fracture model of microvoid growth that may compete with shear in the polycrystalline microstructure by means of evolutionary algorithms

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COMPUTATIONAL MATERIALS SCIENCE 2009年第1期45卷 133-149页

作者： Jackiewicz, J. Univ Technol & Life Sci Dept Mech Engn PL-85796 Bydgoszcz Poland

Changes of stress or strain ratios during an operation can have an effect on cracking during metalworking processes. Therefore, there is a substantive interest of the aluminum and steel industries of the manufacturing sectors in numerical simulations of the fracture processes of typical structural materials. In this paper, a calibration procedure of material parameters for a combined fracture model of microvoid growth that may compete with shear in the polycrystalline microstructure is described. The paper then proceeds to evaluating the probability of structural failure on the basis of the combined fracture model according to the calibrated material parameters. An assessment of the probability of structural failure is important to improve the quality of manufacturing processes, but also to reduce their costs. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Phenomenological fracture criteria Micromechanical models for the simulation of ductile fracture kalman filtering algorithm Assessment of the joint probability density function Searching the extremum of the objective function with the evolution strategy

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FUZZY PREDICTION OF CHAOTIC TIME SERIES BASED ON FUZZY CLUSTERING

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ASIAN JOURNAL OF CONTROL 2011年第4期13卷 576-581页

作者： Wang, Hongwei Lian, Jie Dalian Univ Technol Sch Control Sci & Engn Dalian Liao Ning Peoples R China

The main purpose of this paper is to study a new method to model and predict a chaotic time series using a fuzzy model. First, the GK fuzzy clustering method is used to confirm the input space of the fuzzy model. The goal is to divide the training patterns into representative groups so that patterns within one cluster are more similar than those belonging to other clusters. Then, the kalman filtering algorithm with singular value decomposition is applied to estimate the consequent parameters of the fuzzy model in order to avoid error delivery and error accumulation. The effectiveness of the proposed method is evaluated through simulated examples, including Mackey-Glass time series and Lorenz chaotic systems. The results show that the proposed method provides effective and accurate prediction.

关键词： Singular value decomposition kalman filtering algorithm GK fuzzy clustering chaotic time series

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AN ESTIMATION METHOD FOR THE SEEMINGLY UNRELATED REGRESSION-MODEL WITH CONTEMPORANEOUS COVARIANCES BASED ON AN EFFICIENT RECURSIVE algorithm

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 1987年第3期16卷 689-698页

作者： BOLSTAD, WM Department of Mathematics University of Waikato Hamilton New Zealand

This paper develops an iterative estimation procedure for estimating both the parameters and covariances of the seemingly unrelated regression model with contemporaneous covariances. The method is based on the use of an efficient recursive estimation algorithm for the SUR model with known contemporaneous covariances. The components of each observation vector are used one at a time to simultaneously estimate the parameters using a Bayesian “state vector” approach. This is computationally efficient, since the only matrix inversion required is one by one. The covariances are estimated using the residuals from the fitted model. The procedure iterates between estimating the parameters and estimating the covariances until convergence. The algorithm yields the parameter estimator and an estimator for its distribution, thus providing a sound basis for inferential procedures on the parameters.

关键词： Seemingly unrelated regressions kalman filtering algorithm state vector state vector estimator

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A Small Flow Point Signal Processing and Measurement Method for Ultrasonic Gas Meter

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MAPAN-JOURNAL OF METROLOGY SOCIETY OF INDIA 2022年第2期37卷 251-259页

作者： Li, Y-Z Liu, G-Q Zhu, P-X Zhang, Y-H Li, M. East China Univ Technol Sch Mech & Elect Engn Nanchang 330013 Jiangxi Peoples R China

Due to the advantages of no loss of pressure and wide range, ultrasonic gas meter is becoming a hot research and application at home and abroad. For low power ultrasonic gas meter, a key problem is to improve the precision and stability of the small flow point measurement with the impact of circuit and environment and the influence of turbulence and pulsating flow. In this paper, the ultrasonic propagation time values and their difference values are achieved by using the method of threshold value and the one-half VCC "zero" point detection. The feature point of the arrival time is defined by the threshold value of the echo, which is the zero-crossing point of the next echo period. Propagation time and the differences can be obtained from several feature points that satisfy the threshold of echo. The measurement value at each time is obtained through the average filter process of these difference values. By using the improved kalman filtering algorithm in flow measurement data processing and adjusting the values of Q and R, the measuring accuracy and stability are improved, respectively, in the small flow point affected by the disturbance and pulsating flow. The latest application circuit introduced by TI company has been used in the ultrasonic gas meter circuit and system design, and the calibration experiment of ultrasonic gas meter has been completed. The experimental results show that the measurement accuracy and repeatability can meet the requirements of the application.

关键词： Small flow point Measurement method Ultrasonic gas meter kalman filtering algorithm

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