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Weighted Multi-sensor Data Level Fusion Method of Vibration Signal Based on Correlation Function 被引量:7
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作者 BIN Guangfu JIANG Zhinong +1 位作者 LI Xuejun DHILLON B S 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2011年第5期899-904,共6页
As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery... As the differences of sensor's precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn't require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor's own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement. 展开更多
关键词 vibration signal multi-sensor data level fusion correlation function weighted value
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An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion 被引量:1
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作者 Xiangyu Xu Mei Wang +2 位作者 Liyan Luo Zhibin Meng Enliang Wang 《Journal of Computer and Communications》 2017年第3期102-115,共14页
For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sens... For existing indoor localization algorithm has low accuracy, high cost in deployment and maintenance, lack of robustness, and low sensor utilization, this paper proposes a particle filter algorithm based on multi-sensor fusion. The pedestrian’s localization in indoor environment is described as dynamic system state estimation problem. The algorithm combines the smart mobile terminal with indoor localization, and filters the result of localization with the particle filter. In this paper, a dynamic interval particle filter algorithm based on pedestrian dead reckoning (PDR) information and RSSI localization information have been used to improve the filtering precision and the stability. Moreover, the localization results will be uploaded to the server in time, and the location fingerprint database will be built incrementally, which can adapt the dynamic changes of the indoor environment. Experimental results show that the algorithm based on multi-sensor improves the localization accuracy and robustness compared with the location algorithm based on Wi-Fi. 展开更多
关键词 multi-sensor fusion INDOOR Localization PEDESTRIAN DEAD Reckoning (PDR) PARTICLE Filter
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STUDY ON THE COAL-ROCK INTERFACE RECOGNITION METHOD BASED ON MULTI-SENSOR DATA FUSION TECHNIQUE 被引量:7
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作者 Ren FangYang ZhaojianXiong ShiboResearch Institute of Mechano-Electronic Engineering,Taiyuan University of Technology,Taiyuan 030024, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2003年第3期321-324,共4页
The coal-rock interface recognition method based on multi-sensor data fusiontechnique is put forward because of the localization of single type sensor recognition method. Themeasuring theory based on multi-sensor data... The coal-rock interface recognition method based on multi-sensor data fusiontechnique is put forward because of the localization of single type sensor recognition method. Themeasuring theory based on multi-sensor data fusion technique is analyzed, and hereby the testplatform of recognition system is manufactured. The advantage of data fusion with the fuzzy neuralnetwork (FNN) technique has been probed. The two-level FNN is constructed and data fusion is carriedout. The experiments show that in various conditions the method can always acquire a much higherrecognition rate than normal ones. 展开更多
关键词 Coal-rock interface recognition (CIR) Data fusion (DF) multi-sensor
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Data Fusion Algorithm for Multi-Sensor Dynamic System Based on Interacting Multiple Model 被引量:3
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作者 陈志锋 蔡云泽 《Journal of Shanghai Jiaotong university(Science)》 EI 2015年第3期265-272,共8页
This paper presents a data fusion algorithm for dynamic system with multi-sensor and uncertain system models. The algorithm is mainly based on Kalman filter and interacting multiple model(IMM). It processes crosscorre... This paper presents a data fusion algorithm for dynamic system with multi-sensor and uncertain system models. The algorithm is mainly based on Kalman filter and interacting multiple model(IMM). It processes crosscorrelated sensor noises by using augmented fusion before model interacting. And eigenvalue decomposition is utilized to reduce calculation complexity and implement parallel computing. In simulation part, the feasibility of the algorithm was tested and verified, and the relationship between sensor number and the estimation precision was studied. Results show that simply increasing the number of sensor cannot always improve the performance of the estimation. Type and number of sensors should be optimized in practical applications. 展开更多
关键词 multi-sensor cross-correlated noises augmented fusion interacting multiple model(IMM)
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A Study of Multi-sensor Data Fusion System Based on MAS for Nutrient Solution Measurement
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作者 Feng Chen Dafu Yang +1 位作者 Bing Wang Xianhu Tan 《稀有金属材料与工程》 SCIE EI CAS CSCD 北大核心 2006年第A03期264-267,共4页
For complementarity and redundancy of multi-sensor data fusion (MSDF) system,it is an effective approach for multiple components measurement.In order to measure nutrient solution on-line,a dynamic and complex system ... For complementarity and redundancy of multi-sensor data fusion (MSDF) system,it is an effective approach for multiple components measurement.In order to measure nutrient solution on-line,a dynamic and complex system under greenhouse environment,sensors should have intelligent properties including self-calibration and self-compensation. Meanwhile,it is necessary for multiple sensors to cooperate and interact for enhancing reliability of multi-sensor system. Because of the properties of multi-agent system (MAS),it is an appropriate tool to study MSDF system.This paper proposed an architecture of MSDF system based on MAS for the multiple components measurement of nutrient solution.The sensor agent's structure and function modules are analyzed and described in detail,the formal definitions are given,too.The relations of the sensors are modeled to implement reliability diagnosis of the multi-sensor system,so that the reliability of nutrient control system is enhanced.This study offers an effective approach for the study of MSDF. 展开更多
关键词 multi-sensor data fusion multi-agent system nutrient solution reliability diagnosis.
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Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems
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作者 薛广月 任雪梅 夏元清 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第10期197-205,共9页
This paper proposes an adaptive discrete finite-time synergetic control (ADFTSC) scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dy... This paper proposes an adaptive discrete finite-time synergetic control (ADFTSC) scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter (EKF), the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach. 展开更多
关键词 adaptive finite-time synergetic control multi-rate sensor fusion mechanical systems
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Multi-Sensor Image Fusion: A Survey of the State of the Art
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作者 Bing Li Yong Xian +3 位作者 Daqiao Zhang Juan Su Xiaoxiang Hu Weilin Guo 《Journal of Computer and Communications》 2021年第6期73-108,共36页
Image fusion has been developing into an important area of research. In remote sensing, the use of the same image sensor in different working modes, or different image sensors, can provide reinforcing or complementary... Image fusion has been developing into an important area of research. In remote sensing, the use of the same image sensor in different working modes, or different image sensors, can provide reinforcing or complementary information. Therefore, it is highly valuable to fuse outputs from multiple sensors (or the same sensor in different working modes) to improve the overall performance of the remote images, which are very useful for human visual perception and image processing task. Accordingly, in this paper, we first provide a comprehensive survey of the state of the art of multi-sensor image fusion methods in terms of three aspects: pixel-level fusion, feature-level fusion and decision-level fusion. An overview of existing fusion strategies is then introduced, after which the existing fusion quality measures are summarized. Finally, this review analyzes the development trends in fusion algorithms that may attract researchers to further explore the research in this field. 展开更多
关键词 multi-sensor Image fusion fusion Strategy Feature Enhancement fusion Performance Assessment
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Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion
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作者 韩宝玲 张天 +2 位作者 罗庆生 朱颖 宋明辉 《Journal of Beijing Institute of Technology》 EI CAS 2016年第4期448-454,共7页
In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was stu... In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4. 6 cm, which meets the application requirements of the robot. 展开更多
关键词 multi-sensor Kalman filter algorithm constant velocity (CV) model STF fusion algo-rithm obstacle avoidance of robot
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Sensor Fusion with Square-Root Cubature Information Filtering 被引量:8
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作者 Ienkaran Arasaratnam 《Intelligent Control and Automation》 2013年第1期11-17,共7页
This paper derives a square-root information-type filtering algorithm for nonlinear multi-sensor fusion problems using the cubature Kalman filter theory. The resulting filter is called the square-root cubature Informa... This paper derives a square-root information-type filtering algorithm for nonlinear multi-sensor fusion problems using the cubature Kalman filter theory. The resulting filter is called the square-root cubature Information filter (SCIF). The SCIF propagates the square-root information matrices derived from numerically stable matrix operations and is therefore numerically robust. The SCIF is applied to a highly maneuvering target tracking problem in a distributed sensor network with feedback. The SCIF’s performance is finally compared with the regular cubature information filter and the traditional extended information filter. The results, presented herein, indicate that the SCIF is the most reliable of all three filters and yields a more accurate estimate than the extended information filter. 展开更多
关键词 KALMAN FILTER Information FILTER multi-sensor fusion Square-Root Filtering
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Application of data fusion on multi-function earth drill
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作者 胡长胜 赵伟民 +3 位作者 李瑰贤 杨春蕾 牛红 胡长军 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2003年第1期89-92,共4页
taking the bucket of multi function earth drill as an example, combining with the conception of multi sensor integration and data fusion, adopting the terrene column chart and digging torque formula as control depende... taking the bucket of multi function earth drill as an example, combining with the conception of multi sensor integration and data fusion, adopting the terrene column chart and digging torque formula as control dependence, the detecting method of the earth drill’s working state is introduced. Multi sensor data fusion is done with the aid of BP neural network in Matlab. The data to be interfused are pre processed and the program of simulation and “point checking” is given. 展开更多
关键词 multi function earth drill multi sensor integration and data fusion normalization preprocessing simulation experiment
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RESEARCH ON THE ACCURACY OF TRACKING LONG RANGE AIRPLANE BY MULTI-SENSOR
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作者 Yang Chunling Liu Guosui Yu Yinglin(Department of Electronic Engineering, South China University of Technology, Guangzhou 510641) (Electro-Photo Collage, Nanjing University of Science and Technology, Nanjing 210094) 《Journal of Electronics(China)》 2000年第4期304-312,共9页
This paper mainly studies the influence of the relative position of target-sensors on the tracking accuracy of long range airplane. From theory analysis and simulation results, it is found that the tracking accuracy o... This paper mainly studies the influence of the relative position of target-sensors on the tracking accuracy of long range airplane. From theory analysis and simulation results, it is found that the tracking accuracy of long-range airplane can be improved greatly if the extant sensors are rationally placed and multi-sensor data fusion technique is used in the case of 展开更多
关键词 multi-sensor TARGET TRACKING Data fusion RELATIVE POSITION of target-sensors
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多传感信息融合下的煤矿钻机状态远程在线监测研究
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作者 王德伟 张灿明 《煤矿机械》 2026年第1期213-219,共7页
针对煤矿井下钻机状态监测中存在的多源传感器数据时空失配、噪声干扰强、故障特征微弱等问题,提出了一种基于多传感信息融合的远程在线监测系统。在硬件层面,设计以ATMEGA128L低功耗微处理器为核心的嵌入式采集节点,集成振动、温度、... 针对煤矿井下钻机状态监测中存在的多源传感器数据时空失配、噪声干扰强、故障特征微弱等问题,提出了一种基于多传感信息融合的远程在线监测系统。在硬件层面,设计以ATMEGA128L低功耗微处理器为核心的嵌入式采集节点,集成振动、温度、转速等多种传感器,通过LoRa与工业以太网实现数据可靠回传;在软件层面,提出时序对齐与一阶加权滑动平均去噪方法,解决数据异步与噪声耦合问题;进一步提取峰值、均值、均方根、波形指标与峭度等多维时域特征,并引入轻量化熵权融合机制,实现对轴承点蚀、齿轮断齿等隐性故障的敏感识别;最后,采用改进的集成学习算法,在边缘侧完成钻机运行状态的实时诊断。现场应用结果表明,该系统一致性指数稳定在0.9~1.0,可识别正常、异常、维修、故障4类状态,平均响应延迟低于200 ms,为煤矿钻机预测性维护提供了可部署、高可靠的一体化解决方案。 展开更多
关键词 钻机 多传感信息融合 嵌入式系统 熵权特征融合 集成学习 远程在线监测
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基于STM32的多传感智能小车控制系统设计
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作者 郭峻宇 白英凯 +1 位作者 方孜儇 吴倩仪 《汽车电器》 2026年第1期54-56,共3页
为满足智能移动机器人在简单环境下的导航需求,本文设计基于STM32F103C8微控制器的智能移动平台控制系统。该系统集成超声波传感器、四路红外传感器及光敏电阻等感知设备,采用TB6612FNG驱动芯片控制四轮直流减速电机,通过蓝牙实现手机... 为满足智能移动机器人在简单环境下的导航需求,本文设计基于STM32F103C8微控制器的智能移动平台控制系统。该系统集成超声波传感器、四路红外传感器及光敏电阻等感知设备,采用TB6612FNG驱动芯片控制四轮直流减速电机,通过蓝牙实现手机远程控制,实现自主避障、红外循迹、光源追踪、蓝牙遥控等功能。测试结果显示,避障成功率达90%,循迹精度控制在5 cm以内,追光响应延迟小于0.5 s,蓝牙控制延迟小于0.3 s。该系统为汽车辅助驾驶系统的环境感知模块开发提供低成本验证平台。 展开更多
关键词 STM32微控制器 多传感器融合 智能控制 嵌入式系统 汽车电子
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煤矿刮板输送机智能化故障诊断系统设计研究
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作者 孔令成 《煤矿机械》 2026年第1期188-192,共5页
刮板输送机作为煤矿综采工作面的核心运输设备,其运行可靠性直接影响煤矿生产效率与作业安全。针对传统刮板输送机故障诊断依赖人工巡检、诊断滞后、准确率低等问题,设计了一种基于多传感器融合与BP神经网络的智能化故障诊断系统。首先... 刮板输送机作为煤矿综采工作面的核心运输设备,其运行可靠性直接影响煤矿生产效率与作业安全。针对传统刮板输送机故障诊断依赖人工巡检、诊断滞后、准确率低等问题,设计了一种基于多传感器融合与BP神经网络的智能化故障诊断系统。首先,分析刮板输送机关键部件的常见故障机理,确定振动、温度、电流为核心监测参数;其次,完成该系统硬件设计,包括传感器选型与布置、数据采集模块及以太网通信模块搭建;最后,通过MATLAB构建BP神经网络故障诊断模型,采用煤矿现场采集的1 200组工况数据对模型进行训练与验证。实验结果表明:该系统对刮板输送机典型故障的诊断准确率达到96.8%,响应时间少于0.5 s,可实现故障的实时监测与精准识别,为煤矿机械的智能化运维提供了技术支撑。 展开更多
关键词 刮板输送机 智能化故障诊断 多传感器融合 BP神经网络 数据采集
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具有全局速度约束的惯性/编码器/视觉/激光融合定位方法:IEVL-Fusion 被引量:9
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作者 武东杰 仲训昱 +2 位作者 崔晓珍 庄明溪 彭侠夫 《机器人》 EI CSCD 北大核心 2022年第4期443-452,共10页
针对卫星拒止环境中移动机器人高精度定位需求,提出一种基于误差状态扩展卡尔曼滤波(ES-EKF)的激光定位子系统/视觉定位子系统/全局速度测量子系统松耦合融合定位方法,并设计了一个误差低漂移的组合定位系统。首先,根据向量加法和矩阵... 针对卫星拒止环境中移动机器人高精度定位需求,提出一种基于误差状态扩展卡尔曼滤波(ES-EKF)的激光定位子系统/视觉定位子系统/全局速度测量子系统松耦合融合定位方法,并设计了一个误差低漂移的组合定位系统。首先,根据向量加法和矩阵乘法对系统状态的误差进行最小表示,建立误差形式的卡尔曼滤波模型,以误差状态的最优估计对系统状态的估计值进行补偿。然后,针对激光和视觉定位子系统位姿不确定度未知的问题,将位姿输出依时间戳转化为位姿增量,并建立位姿增量观测模型。其次,针对组合定位系统缺少全局速度约束的问题,利用姿态航向参考系统(AHRS)和正向运动学模型构建全局速度测量子系统,并建立全局速度观测模型。最后,在街道和野外两个场景中进行测试,本文算法的相对定位误差小于0.4%,相较于仅受局部速度约束的EKF和ES-EKF融合定位算法降低了约40%。实验结果表明,所提出的算法有效提升了定位系统的精度。 展开更多
关键词 卫星拒止 多传感器融合 位姿增量融合 全局速度约束 误差状态扩展卡尔曼滤波 轮式机器人 移动机器人定位
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A Generic Plug-and-Play Navigation Fusion Strategy for Land Vehicles in GNSS-Denied Environment 被引量:3
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作者 LAI Jizhou BAI Shiyu +1 位作者 XU Xiaowei Lü Pin 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2019年第2期197-204,共8页
Achieving accurate navigation information by integrating multiple sensors is key to the safe operation of land vehicles in global navigation satellite system(GNSS)-denied environment.However,current multi-sensor fusio... Achieving accurate navigation information by integrating multiple sensors is key to the safe operation of land vehicles in global navigation satellite system(GNSS)-denied environment.However,current multi-sensor fusion methods are based on stovepipe architecture,which is optimized with custom fusion strategy for specific sensors.Seeking to develop adaptable navigation that allows rapid integration of any combination of sensors to obtain robust and high-precision navigation solutions in GNSS-denied environment,we propose a generic plug-and-play fusion strategy to estimate land vehicle states.The proposed strategy can handle different sensors in a plug-and-play manner as sensors are abstracted and represented by generic models,which allows rapid reconfiguration whenever a sensor signal is additional or lost during operation.Relative estimations are fused with absolute sensors based on improved factor graph,which includes sensors’error parameters in the non-linear optimization process to conduct sensor online calibration.We evaluate the performance of our approach using a land vehicle equipped with a global positioning system(GPS)receiver as well as inertial measurement unit(IMU),camera,wireless sensor and odometer.GPS is not integrated into the system but treated as ground truth.Results are compared with the most common filtering-based fusion algorithm.It shows that our strategy can process low-quality input sources in a plug-and-play and robust manner and its performance outperforms filtering-based method in GNSS-denied environment. 展开更多
关键词 GNSS-denied multi-sensor fusion plug-and-play factor graph LAND vehicles
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Fault diagnosis method of hydraulic system based on fusion of neural network and D-S evidence theory 被引量:3
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作者 LIU Bao-jie YANG Qing-wen WU Xiang 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2016年第4期368-374,共7页
According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system(HDRLSS) , the fault diagnosis method based on the evidence theory and neural network e... According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system(HDRLSS) , the fault diagnosis method based on the evidence theory and neural network ensemble is proposed. In order to overcome the shortcomings of the single neural network, two improved neural network models are set up at the com-mon nodes to simplify the network structure. The initial fault diagnosis is based on the iron spectrum data and the pressure, flow and temperature(PFT) characteristic parameters as the input vectors of the two improved neural network models, and the diagnosis result is taken as the basic probability distribution of the evidence theory. Then the objectivity of assignment is real-ized. The initial diagnosis results of two improved neural networks are fused by D-S evidence theory. The experimental results show that this method can avoid the misdiagnosis of neural network recognition and improve the accuracy of the fault diagnosis of HDRLSS. 展开更多
关键词 multi sensor information fusion fault diagnosis D-S evidence theory BP neural network
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SELF-TUNING WEIGHTED MEASUREMENT FUSION WHITE NOISE DECONVOLUTION ESTIMATOR 被引量:2
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作者 Sun Xiaojun Deng Zili 《Journal of Electronics(China)》 2010年第1期51-59,共9页
For the multi-sensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is obtained using the correlation method.Sub... For the multi-sensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is obtained using the correlation method.Substituting it into the optimal weighted fusion steady-state white noise deconvolution estimator based on the Kalman filtering,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented.By the Dynamic Error System Analysis(DESA) method,it proved that the self-tuning fusion white noise deconvolution estimator converges to the steady-state optimal fusion white noise deconvolution estimator in a realization.Therefore,it has the asymptotically global optimality.A simulation example for the tracking system with 3 sensors and the Bernoulli-Gaussian input white noise shows its effectiveness. 展开更多
关键词 multi-sensor information fusion Self-tuning fuser White noise deconvolution Global optimality CONVERGENCE
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基于Multi-Agent技术的三层信息融合系统研究
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作者 崔东风 黄宇达 +1 位作者 赵红专 王迤冉 《科学技术与工程》 北大核心 2012年第21期5331-5336,共6页
针对传统传感器网络管理复杂,系统信息融合智能化不高、精度低和模式单一、结构不清晰等不足,首先分析了Multi-Agent技术、传感器网络技术以及信息融合技术的独特优势,然后采用计算机网络分层结构思想和基于人工智能本体的知识表达理念... 针对传统传感器网络管理复杂,系统信息融合智能化不高、精度低和模式单一、结构不清晰等不足,首先分析了Multi-Agent技术、传感器网络技术以及信息融合技术的独特优势,然后采用计算机网络分层结构思想和基于人工智能本体的知识表达理念,在信息融合过程中采用改进的SVM分类方法,构建了一种基于Multi-Agent技术的多传感器三层信息融合系统并对其具体融合过程进行了分析。最后对分类过程用MATLAB进行了分析。实验结果表明:系统分类精度较高,一定程度上不仅明显弥补了传统传感器的诸多不足,而且为后期决策提供了较为精准的目标参数。 展开更多
关键词 multi-AGENT技术 传感器网络 信息融合 分层结构 本体表达 SVM分类
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Altitude information fusion method and experiment for UAV 被引量:2
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作者 徐东甫 Pei Xinbiao +3 位作者 Bai Yue Peng Cheng Wu Ziyi Xu Zhijun 《High Technology Letters》 EI CAS 2017年第2期165-172,共8页
Altitude regulation is a fundamental problem in UAV(unmanned aerial vehicles) control to ensure hovering and autonomous navigation performance.However,data from altitude sensors may be unstable by interference.A digit... Altitude regulation is a fundamental problem in UAV(unmanned aerial vehicles) control to ensure hovering and autonomous navigation performance.However,data from altitude sensors may be unstable by interference.A digital-filter-based improved adaptive Kalman method is proposed to improve accuracy and reliability of the altitude measurement information.A unique sensor data fusion structure is designed to make different sensors switch automatically in different environment.Simulation and experimental results show that an improved Sage-Husa adaptive extended Kalman filter(SHAEKF) is adopted in altitude data fusion which means that altitude error is limited to 1.5m in high altitude and 1.2m near the ground.This method is proved feasible and effective through hovering flight test and three-dimensional track flight experiment. 展开更多
关键词 unmanned aerial vehicles(UAV) altitude information fusion multi-sensor adaptive Kalman filter
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