期刊文献+
共找到474篇文章
< 1 2 24 >
每页显示 20 50 100
Disparity estimation for multi-scale multi-sensor fusion
1
作者 SUN Guoliang PEI Shanshan +2 位作者 LONG Qian ZHENG Sifa YANG Rui 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第2期259-274,共16页
The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results ... The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation. 展开更多
关键词 stereo vision light deterction and ranging(LiDAR) multi-sensor fusion multi-scale fusion disparity map
下载PDF
A Heterogeneous Information Fusion Method for Maritime Radar and AIS Based on D-S Evidence Theory
2
作者 Chao Wu Qing Wu +1 位作者 Feng Ma Shuwu Wang 《Engineering(科研)》 2023年第12期821-842,共22页
Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However,... Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However, in practical applications, the information obtained by a single device is limited, and it is necessary to integrate the information of maritime radar and AIS messages to achieve better recognition effects. In this study, the D-S evidence theory is used to fusion the two kinds of heterogeneous information: maritime radar images and AIS messages. Firstly, the radar image and AIS message are processed to get the targets of interest in the same coordinate system. Then, the coordinate position and heading of targets are chosen as the indicators for judging target similarity. Finally, a piece of D-S evidence theory based on the information fusion method is proposed to match the radar target and the AIS target of the same ship. Particularly, the effectiveness of the proposed method has been validated and evaluated through several experiments, which proves that such a method is practical in maritime safety supervision. 展开更多
关键词 D-S Evidence Theory heterogeneous Information fusion Radar Image AIS Message
下载PDF
Progress and Achievements of Multi-sensor Fusion Navigation in China during 2019—2023
3
作者 Xingxing LI Xiaohong ZHANG +12 位作者 Xiaoji NIU Jian WANG Ling PEI Fangwen YU Hongjuan ZHANG Cheng YANG Zhouzheng GAO Quan ZHANG Feng ZHU Weisong WEN Tuan LI Jianchi LIAO Xin LI 《Journal of Geodesy and Geoinformation Science》 CSCD 2023年第3期102-114,共13页
Global Navigation Satellite System(GNSS)can provide all-weather,all-time,high-precision positioning,navigation and timing services,which plays an important role in national security,national economy,public life and ot... Global Navigation Satellite System(GNSS)can provide all-weather,all-time,high-precision positioning,navigation and timing services,which plays an important role in national security,national economy,public life and other aspects.However,in environments with limited satellite signals such as urban canyons,tunnels,and indoor spaces,it is difficult to provide accurate and reliable positioning services only by satellite navigation.Multi-source sensor integrated navigation can effectively overcome the limitations of single-sensor navigation through the fusion of different types of sensor data such as Inertial Measurement Unit(IMU),vision sensor,and LiDAR,and provide more accurate,stable and robust navigation information in complex environments.We summarizes the research status of multi-source sensor integrated navigation technology,and focuses on the representative innovations and applications of integrated navigation and positioning technology by major domestic scientific research institutions in China during 2019—2023. 展开更多
关键词 Simultaneous Localization And Mapping(SLAM) integrated navigation multi-sensor fusion
下载PDF
Research on Optimal Preload Method of Controllable Rolling Bearing Based on Multisensor Fusion
4
作者 Kuosheng Jiang Chengrui Han Yasheng Chang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第6期3329-3352,共24页
Angular contact ball bearings have been widely used in machine tool spindles,and the bearing preload plays an important role in the performance of the spindle.In order to solve the problems of the traditional optimal ... Angular contact ball bearings have been widely used in machine tool spindles,and the bearing preload plays an important role in the performance of the spindle.In order to solve the problems of the traditional optimal preload prediction method limited by actual conditions and uncertainties,a roller bearing preload test method based on the improved D-S evidence theorymulti-sensor fusion method was proposed.First,a novel controllable preload system is proposed and evaluated.Subsequently,multiple sensors are employed to collect data on the bearing parameters during preload application.Finally,a multisensor fusion algorithm is used to make predictions,and a neural network is used to optimize the fitting of the preload data.The limitations of conventional preload testing methods are identified,and the integration of complementary information frommultiple sensors is used to achieve accurate predictions,offering valuable insights into the optimal preload force.Experimental results demonstrate that the multi-sensor fusion approach outperforms traditional methods in accurately measuring the optimal preload for rolling bearings. 展开更多
关键词 multi-sensor information fusion neural network preload force
下载PDF
Weighted Multi-sensor Data Level Fusion Method of Vibration Signal Based on Correlation Function 被引量:7
5
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
下载PDF
Data Fusion in Distributed Multi-sensor System 被引量:7
6
作者 GUOHang YUMin 《Geo-Spatial Information Science》 2004年第3期214-217,234,共5页
This paper presents a data fusion method in distributed multi-sensor system including GPS and INS sensors’ data processing. First, a residual χ 2 \|test strategy with the corresponding algorithm is designed. Then a ... This paper presents a data fusion method in distributed multi-sensor system including GPS and INS sensors’ data processing. First, a residual χ 2 \|test strategy with the corresponding algorithm is designed. Then a coefficient matrices calculation method of the information sharing principle is derived. Finally, the federated Kalman filter is used to combine these independent, parallel, real\|time data. A pseudolite (PL) simulation example is given. 展开更多
关键词 PSEUDOLITE distributed multi-sensor system data fusion federated Kalman filtering
下载PDF
STUDY ON THE COAL-ROCK INTERFACE RECOGNITION METHOD BASED ON MULTI-SENSOR DATA FUSION TECHNIQUE 被引量:7
7
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
下载PDF
A Novel Multi-sensor Data Fusion Algorithm and Its Application to Diagnostics 被引量:2
8
作者 Li Xiong Xu Zongchang Dong Zhiming 《仪器仪表学报》 EI CAS CSCD 北大核心 2005年第z1期788-790,共3页
To Meet the requirements of multi-sensor data fusion in diagnosis for complex equipment systems,a novel, fuzzy similarity-based data fusion algorithm is given. Based on fuzzy set theory, it calculates the fuzzy simila... To Meet the requirements of multi-sensor data fusion in diagnosis for complex equipment systems,a novel, fuzzy similarity-based data fusion algorithm is given. Based on fuzzy set theory, it calculates the fuzzy similarity among a certain sensor's measurement values and the multiple sensor's objective prediction values to determine the importance weigh of each sensor,and realizes the multi-sensor diagnosis parameter data fusion.According to the principle, its application software is also designed. The applied example proves that the algorithm can give priority to the high-stability and high -reliability sensors and it is laconic ,feasible and efficient to real-time circumstance measure and data processing in engine diagnosis. 展开更多
关键词 DIAGNOSTICS multi-sensor DATA fusion ALGORITHM ENGINE
下载PDF
A Spatially Heterogeneous Expert Based (SHEB) Urban Growth Model using Model Regionalization 被引量:4
9
作者 Dimitrios Triantakonstantis Giorgos Mountrakis Jida Wang 《Journal of Geographic Information System》 2011年第3期195-210,共16页
Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban gr... Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models. Instead of applying a single method to the entire study area, we segment the study area into different regions and apply targeted algorithms in each subregion. The working hypothesis is that the integration of appropriately selected region-specific models will outperform a globally applied model as it will incorporate further spatial heterogeneity. We examine urban land use changes in Denver, Colorado. Two land use maps from different time snapshots (1977 and 1997) are used to detect the urban land use changes, and 23 explanatory factors are produced to model urbanization. The proposed Spatially Heterogeneous Expert Based (SHEB) model tested decision trees as the underlying modeling algorithm, applying them in different subregions. In this paper the segmentation tested is the division of the entire area into interior and exterior urban areas. Interior urban areas are those situated within dense urbanized structures, while exterior urban areas are outside of these structures. Obtained results on this model regionalization technique indicate that targeted local models produce improved results in terms of Kappa, accuracy percentage and multi-scale performance. The model superiority is also confirmed by model pairwise comparisons using t-tests. The segmentation criterion of interior/exterior selection may not only capture specific characteristics on spatial and morphological properties, but also socioeconomic factors which may implicitly be present in these spatial representations. The usage of interior and exterior subregions in the present study acts as a proof of concept. Other spatial heterogeneity indicators, for example landscape, socioeconomic and political boundaries could act as the basis for improved local segmentations. 展开更多
关键词 URBAN Growth Models Spatial heterogenEITY MODEL fusion DECISION Trees Denver
下载PDF
Multi-sensor measurement and data fusion technology for manufacturing process monitoring:a literature review 被引量:12
10
作者 Lingbao Kong Xing Peng +2 位作者 Yao Chen Ping Wang Min Xu 《International Journal of Extreme Manufacturing》 2020年第2期1-27,共27页
Due to the rapid development of precision manufacturing technology,much research has been conducted in the field of multisensor measurement and data fusion technology with a goal of enhancing monitoring capabilities i... Due to the rapid development of precision manufacturing technology,much research has been conducted in the field of multisensor measurement and data fusion technology with a goal of enhancing monitoring capabilities in terms of measurement accuracy and information richness,thereby improving the efficiency and precision of manufacturing.In a multisensor system,each sensor independently measures certain parameters.Then,the system uses a relevant signalprocessing algorithm to combine all of the independent measurements into a comprehensive set of measurement results.The purpose of this paper is to describe multisensor measurement and data fusion technology and its applications in precision monitoring systems.The architecture of multisensor measurement systems is reviewed,and some implementations in manufacturing systems are presented.In addition to the multisensor measurement system,related data fusion methods and algorithms are summarized.Further perspectives on multisensor monitoring and data fusion technology are included at the end of this paper. 展开更多
关键词 multi-sensor data fusion process monitoring additive manufacturing laser melting
下载PDF
Applications of state estimation in multi-sensor information fusion for the monitoring of open pit mine slope deformation 被引量:1
11
作者 付华 刘银平 肖健 《Journal of Coal Science & Engineering(China)》 2008年第2期317-320,共4页
The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monito... The traditional open pit mine slope deformation monitoring system can not use the monitoring information coming from many monitoring points at the same time, can only using the monitoring data coming from a key monitoring point,and that is to say it can only handle one-dimensional time series.Given this shortage in the monitoring, the multi-sensor information fusion in the state estimation techniques would be intro- duced to the slope deformation monitoring system,and by the dynamic characteristics of deformation slope,the open pit slope would be regarded as a dynamic goal,the condi- tion monitoring of which would be regarded as a dynamic target tracking.Distributed In- formation fusion technology with feedback was used to process the monitoring data and on this basis Klman filtering algorithms was introduced,and the simulation examples was used to prove its effectivenes. 展开更多
关键词 multi-sensor information fusion the side slope distortion the state estimation Klman filter algorithm
下载PDF
An Indoor Pedestrian Localization Algorithm Based on Multi-Sensor Information Fusion 被引量:1
12
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
下载PDF
Dynamic Modeling of Heterogeneous Spatial Analysis for Energy and Natural Resources in Grid Integration Environment
13
作者 Wei Ji,Xincai Wu Faculty of Information Engineering,China University of Geosciences(Wuhan),Wuhan 430074,China. 《地学前缘》 EI CAS CSCD 北大核心 2009年第S1期287-287,共1页
With the high-tech industrialization of earth observation satellite remote sensing and the implementation of digital earth strategy,the energy and natural resources have been decided to be the key research fields in C... With the high-tech industrialization of earth observation satellite remote sensing and the implementation of digital earth strategy,the energy and natural resources have been decided to be the key research fields in China.In these fields,from the model based on topology data,through simple feature data model to rule-based data model,the basic spatial analysis algorithms have been developed 展开更多
关键词 DYNAMIC modeling of heterogeneous spatial analysis suspended inversion architecture FUNCTION WAREHOUSE FUNCTION POLYMERIZATION FUNCTION fusion operator OVERLOADING
下载PDF
A Study of Multi-sensor Data Fusion System Based on MAS for Nutrient Solution Measurement
14
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.
下载PDF
Adaptive Multi-Feature Fusion for Vehicle Micro-Motor Noise Recognition Considering Auditory Perception 被引量:1
15
作者 Ting Zhao Weiping Ding +1 位作者 Haibo Huang Yudong Wu 《Sound & Vibration》 EI 2023年第1期133-153,共21页
The deployment of vehicle micro-motors has witnessed an expansion owing to the progression in electrification and intelligent technologies.However,some micro-motors may exhibit design deficiencies,component wear,assem... The deployment of vehicle micro-motors has witnessed an expansion owing to the progression in electrification and intelligent technologies.However,some micro-motors may exhibit design deficiencies,component wear,assembly errors,and other imperfections that may arise during the design or manufacturing phases.Conse-quently,these micro-motors might generate anomalous noises during their operation,consequently exerting a substantial adverse influence on the overall comfort of drivers and passengers.Automobile micro-motors exhibit a diverse array of structural variations,consequently leading to the manifestation of a multitude of distinctive auditory irregularities.To address the identification of diverse forms of abnormal noise,this research presents a novel approach rooted in the utilization of vibro-acoustic fusion-convolutional neural network(VAF-CNN).This method entails the deployment of distinct network branches,each serving to capture disparate features from the multi-sensor data,all the while considering the auditory perception traits inherent in the human auditory sys-tem.The intermediary layer integrates the concept of adaptive weighting of multi-sensor features,thus affording a calibration mechanism for the features hailing from multiple sensors,thereby enabling a further refinement of features within the branch network.For optimal model efficacy,a feature fusion mechanism is implemented in the concluding layer.To substantiate the efficacy of the proposed approach,this paper initially employs an augmented data methodology inspired by modified SpecAugment,applied to the dataset of abnormal noise sam-ples,encompassing scenarios both with and without in-vehicle interior noise.This serves to mitigate the issue of limited sample availability.Subsequent comparative evaluations are executed,contrasting the performance of the model founded upon single-sensor data against other feature fusion models reliant on multi-sensor data.The experimental results substantiate that the suggested methodology yields heightened recognition accuracy and greater resilience against interference.Moreover,it holds notable practical significance in the engineering domain,as it furnishes valuable support for the targeted management of noise emanating from vehicle micro-motors. 展开更多
关键词 Auditory perception multi-sensor feature adaptive fusion abnormal noise recognition vehicle interior noise
下载PDF
Multi-sensor Data Fusion by Improved Hough Transformation
16
作者 张鸿宾 《High Technology Letters》 EI CAS 1995年第2期7-11,共5页
In this paper we present an evidence-gathering approach to slove the multi-sensor data fusion problem. It uses an improved Hough transformation method rather than the usual statistical or geometric approach to extract... In this paper we present an evidence-gathering approach to slove the multi-sensor data fusion problem. It uses an improved Hough transformation method rather than the usual statistical or geometric approach to extract the directions and positions of the walls in a room and update the location (orientation and position)of a mobile robot. The simulation results show that the proposed method is of practical importance since it is very simple and easy to implement. 展开更多
关键词 multi-sensor data fusion Hough transformation Mobile robot
下载PDF
Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion
17
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
下载PDF
Multi-Sensor Image Fusion: A Survey of the State of the Art
18
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
下载PDF
A Robust Approach of Multi-sensor Fusion for Fault Diagnosis Using Convolution Neural Network
19
作者 Jiahao Sun Xiwen Gu +3 位作者 Jun He Shixi Yang Yao Tu Chenfang Wu 《Journal of Dynamics, Monitoring and Diagnostics》 2022年第2期103-110,共8页
Multi-sensor measurement iswidely employed in rotatingmachinery to ensure the safety ofmachines.The information provided by the single sensor is not comprehensive.Multi-sensor signals can provide complementary informa... Multi-sensor measurement iswidely employed in rotatingmachinery to ensure the safety ofmachines.The information provided by the single sensor is not comprehensive.Multi-sensor signals can provide complementary information in characterizing the health condition of machines.This paper proposed a multi-sensor fusion convolution neural network(MF-CNN)model.The proposed model adds a 2-D convolution layer before the classical 1-D CNN to automatically extract complementary features of multi-sensor signals and minimize the loss of information.A series of experiments are carried out on a rolling bearing test rig to verify the model.Vibration and sound signals are fused to achieve higher classification accuracy than typical machine learning model.In addition,the model is further applied to gas turbine abnormal detection,and shows great robustness and generalization. 展开更多
关键词 deep learning engineering application fault diagnosis multi-sensor fusion
下载PDF
使用异质集成学习和心电信号异构特征融合的睡眠呼吸暂停分类方法
20
作者 韩亮 罗统军 +2 位作者 蒲秀娟 刘媛 梁国祥 《仪器仪表学报》 EI CAS CSCD 北大核心 2024年第6期320-327,共8页
睡眠呼吸暂停(sleep apnea,SA)会影响睡眠质量,增加心脑血管疾病风险,其准确分类有助于在SA早期阶段及时开展针对性治疗。本文提出一种使用异质集成学习和异构特征融合的SA分类新方法。首先从原始心电信号中提取小波时频谱,使用SE-ResNe... 睡眠呼吸暂停(sleep apnea,SA)会影响睡眠质量,增加心脑血管疾病风险,其准确分类有助于在SA早期阶段及时开展针对性治疗。本文提出一种使用异质集成学习和异构特征融合的SA分类新方法。首先从原始心电信号中提取小波时频谱,使用SE-ResNet作为初级分类器;然后提取RR间期序列和R峰值序列,使用1D CNN-LSTM作为初级分类器;再提取心率变异性特征,使用SVM作为初级分类器。最后采用堆叠法作为异质集成学习的融合策略,再使用另一个SVM作为次级分类器实现SA分类。在Apnea-ECG数据集上进行实验,所提出的SA分类方法的准确率为89.12%。实验结果表明,所提方法有效利用了各初级分类器的多样性和异构特征的互补性,其性能优于传统的SA分类方法。 展开更多
关键词 睡眠呼吸暂停 集成学习 异构特征融合 心电信号 深度学习
下载PDF
上一页 1 2 24 下一页 到第
使用帮助 返回顶部