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APPLICATION OF MULTI-SENSOR DATA FUSION BASED ON FUZZY NEURAL NETWORK IN ROTA TING MECHANICAL FAILURE DIAGNOSIS 被引量:1
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作者 周洁敏 林刚 +1 位作者 宫淑丽 陶云刚 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2001年第1期91-96,共6页
At present, multi-se nsor fusion is widely used in object recognition and classification, since this technique can efficiently improve the accuracy and the ability of fault toleranc e. This paper describes a multi-se... At present, multi-se nsor fusion is widely used in object recognition and classification, since this technique can efficiently improve the accuracy and the ability of fault toleranc e. This paper describes a multi-sensor fusion system, which is model-based and used for rotating mechanical failure diagnosis. In the data fusion process, the fuzzy neural network is selected and used for the data fusion at report level. By comparing the experimental results of fault diagnoses based on fusion data wi th that on original separate data,it is shown that the former is more accurate than the latter. 展开更多
关键词 MULTI-SENSOR data fus ion fuzzy neural network rotating mechanical fault diagnosis grade of members hip
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A REALIZATION OF FUZZY LOGIC BY A NEURAL NETWORK 被引量:1
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作者 杨忠 鲍明 赵淳生 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 1995年第1期104-108,共5页
This paper proposes a Fuzzy Neural Network (FNN) model, which uses a propagation algorithm. A logical operation is defined by a set of weights which are independent of inputs. The realization of the basic And,Or and N... This paper proposes a Fuzzy Neural Network (FNN) model, which uses a propagation algorithm. A logical operation is defined by a set of weights which are independent of inputs. The realization of the basic And,Or and Negation fuzzy logical operations is shown by the fuzzy neuron. A example in fault diagnosis is put forward and the result witnesses some effectiveness of the new FNN model. 展开更多
关键词 fuzzy logic NEURON neural network propagation algorithm fault diagnosis
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INDUCTION MOTOR SPEED CONTROL SYSTEM BASED ON FUZZY NEURAL NETWORK 被引量:1
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作者 徐小增 李叶松 秦忆 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2004年第3期195-199,共5页
A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teachin... A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teaching controller are described. The parameters of the membership function are regulated by an on-line learning algorithm. The speed responses of the system under the condition, where the target functions are chosen as I qs and ω, are analyzed. The system responses with the variant of parameter moment of inertial J, viscous coefficients B and torque constant K tare also analyzed. Simulation results show that the control scheme and the controller have the advantages of rapid speed response and good robustness. 展开更多
关键词 induction motor fuzzy neural network vector control speed control system
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AN INTELLIGENT TOOL CONDITION MONITORING SYSTEM USING FUZZY NEURAL NETWORKS 被引量:3
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作者 赵东标 KeshengWang OliverKrimmel 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2000年第2期169-175,共7页
Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificia... Reliable on line cutting tool conditioning monitoring is an essential feature of automatic machine tool and flexible manufacturing system (FMS) and computer integrated manufacturing system (CIMS). Recently artificial neural networks (ANNs) are used for this purpose in conjunction with suitable sensory systems. The present work in Norwegian University of Science and Technology (NTNU) uses back propagation neural networks (BP) and fuzzy neural networks (FNN) to process the cutting tool state data measured with force and acoustic emission (AE) sensors, and implements a valuable on line tool condition monitoring system using the ANNs. Different ANN structures are designed and investigated to estimate the tool wear state based on the fusion of acoustic emission and force signals. Finally, four case studies are introduced for the sensing and ANN processing of the tool wear states and the failures of the tool with practical experiment examples. The results indicate that a tool wear identification system can be achieved using the sensors integration with ANNs, and that ANNs provide a very effective method of implementing sensor integration for on line monitoring of tool wear states and abnormalities. 展开更多
关键词 tool condition monitoring neural networks fuzzy logic acoustic emission force sensor fuzzy neural networks
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基于FNN优化的AUV姿态控制研究
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作者 张海龙 齐向东 +1 位作者 普勇博 张涛 《舰船科学技术》 北大核心 2025年第5期132-137,共6页
为了满足自主水下潜航器(AUV)快速达到稳定姿态的需求,在传统增量式PID的基础上引入神经网络理论和模糊控制逻辑,提出一种模糊神经网络(FNN)PID姿态控制器。首先建立双坐标系系统,并通过受力分析得到AUV动力学模型,其次融合模糊逻辑和... 为了满足自主水下潜航器(AUV)快速达到稳定姿态的需求,在传统增量式PID的基础上引入神经网络理论和模糊控制逻辑,提出一种模糊神经网络(FNN)PID姿态控制器。首先建立双坐标系系统,并通过受力分析得到AUV动力学模型,其次融合模糊逻辑和人工神经网络的计算模型,设计AUV姿态控制器并搭建Matlab仿真模型,有效解决模糊PID控制过度依赖经验,难以应对水下复杂工况的问题。仿真结果表明,相比于传统的模糊PID控制和BP神经网络,模糊神经网络PID姿态控制器具有更快的响应速度,达到稳定姿态所需时间减少一倍以上,有效改善了AUV姿态控制性能。 展开更多
关键词 自主水下潜航器 模糊PID BP神经网络 控制优化
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Fuzzy neural network control of underwater vehicles based on desired state programming 被引量:6
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作者 LIANG Xiao LI Ye XU Yu-ru WAN Lei QIN Zai-bai 《Journal of Marine Science and Application》 2006年第3期1-4,共4页
Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was pr... Due to the nonlinearity and uncertainty, the precise control of underwater vehicles in some intelligent operations hasn’t been solved very well yet. A novel method of control based on desired state programming was presented, which used the technique of fuzzy neural network. The structure of fuzzy neural network was constructed according to the moving characters and the back propagation algorithm was deduced. Simulation experiments were conducted on general detection remotely operated vehicle. The results show that there is a great improvement in response and precision over traditional control, and good robustness to the model’s uncertainty and external disturbance, which has theoretical and practical value. 展开更多
关键词 underwater vehicle motion control fuzzy neural network desired state programming
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Transient Air-Fuel Ratio Control in a CNG Engine Using Fuzzy Neural Networks 被引量:2
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作者 李国岫 张欣 《Journal of Beijing Institute of Technology》 EI CAS 2005年第1期100-103,共4页
The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) ... The fuzzy neural networks has been used as means of precisely controlling the air-fuel ratio of a lean-burn compressed natural gas (CNG) engine. A control algorithm, without based on engine model, has been (utilized) to construct a feedforward/feedback control scheme to regulate the air-fuel ratio. Using fuzzy neural networks, a fuzzy neural hybrid controller is obtained based on PI controller. The new controller, which can adjust parameters online, has been tested in transient air-fuel ratio control of a CNG engine. 展开更多
关键词 air-fuel (A/F) ratio fuzzy neural network hybrid controller
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Robust stability analysis of Takagi-Sugeno uncertain stochastic fuzzy recurrent neural networks with mixed time-varying delays 被引量:1
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作者 M.Syed Ali 《Chinese Physics B》 SCIE EI CAS CSCD 2011年第8期1-15,共15页
In this paper, the global stability of Takagi-Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered. A novel LMI-based stabili... In this paper, the global stability of Takagi-Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature. 展开更多
关键词 recurrent neural networks linear matrix inequality Lyapunov stability time-varyingdelays TS fuzzy model
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Rough Set Based Fuzzy Neural Network for Pattern Classification 被引量:1
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作者 李侃 刘玉树 《Journal of Beijing Institute of Technology》 EI CAS 2003年第4期428-431,共4页
A rough set based fuzzy neural network algorithm is proposed to solve the problem of pattern recognition. The least square algorithm (LSA) is used in the learning process of fuzzy neural network to obtain the performa... A rough set based fuzzy neural network algorithm is proposed to solve the problem of pattern recognition. The least square algorithm (LSA) is used in the learning process of fuzzy neural network to obtain the performance of global convergence. In addition, the numbers of rules and the initial weights and structure of fuzzy neural networks are difficult to determine. Here rough sets are introduced to decide the numbers of rules and original weights. Finally, experiment results show the algorithm may get better effect than the BP algorithm. 展开更多
关键词 fuzzy neural network rough sets the least square algorithm back-propagation algorithm
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Stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks with mixed delays and the Wiener process based on sampled-data control 被引量:1
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作者 M. Kalpana P. Balasubramaniam 《Chinese Physics B》 SCIE EI CAS CSCD 2013年第7期564-573,共10页
We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete, unbounded distributed delays, and the Wiener process based on sampled-d... We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality (LMI) approach. The Lyapunov–Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions (e.g., time derivative is smaller than one) are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results. 展开更多
关键词 stochastic asymptotical synchronization fuzzy cellular neural networks chaotic Markovian jumping parameters sampled-data control
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Adaptive fuzzy synchronization for a class of fractional-order neural networks 被引量:1
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作者 刘恒 李生刚 +1 位作者 王宏兴 李冠军 《Chinese Physics B》 SCIE EI CAS CSCD 2017年第3期258-267,共10页
In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as sync... In this paper, synchronization for a class of uncertain fractional-order neural networks with external disturbances is discussed by means of adaptive fuzzy control. Fuzzy logic systems, whose inputs are chosen as synchronization errors, are employed to approximate the unknown nonlinear functions. Based on the fractional Lyapunov stability criterion, an adaptive fuzzy synchronization controller is designed, and the stability of the closed-loop system, the convergence of the synchronization error, as well as the boundedness of all signals involved can be guaranteed. To update the fuzzy parameters, fractional-order adaptations laws are proposed. Just like the stability analysis in integer-order systems, a quadratic Lyapunov function is used in this paper. Finally, simulation examples are given to show the effectiveness of the proposed method. 展开更多
关键词 fractional-order neural network adaptive fuzzy control fractional-order adaptation law
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Fuzzy Entropy: Axiomatic Definition and Neural Networks Model 被引量:1
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作者 QINGMing CAOYue HUANGTian-min 《Chinese Quarterly Journal of Mathematics》 CSCD 2004年第3期319-323,共5页
The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy sys... The measure of uncertainty is adopted as a measure of information. The measures of fuzziness are known as fuzzy information measures. The measure of a quantity of fuzzy information gained from a fuzzy set or fuzzy system is known as fuzzy entropy. Fuzzy entropy has been focused and studied by many researchers in various fields. In this paper, firstly, the axiomatic definition of fuzzy entropy is discussed. Then, neural networks model of fuzzy entropy is proposed, based on the computing capability of neural networks. In the end, two examples are discussed to show the efficiency of the model. 展开更多
关键词 neural networks BP networks fuzzy entropy fuzzy set MODEL
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A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system 被引量:1
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作者 Min Ding Zili Tao +3 位作者 Bo Hu Meng Ye Yingxiong Ou Ryuichi Yokoyama 《Global Energy Interconnection》 EI CSCD 2023年第5期554-566,共13页
When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power refer... When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions.Finally,the effectiveness of this method is verified via Simulink simulation. 展开更多
关键词 Maximum wind power tracking fuzzy control neural network
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Intelligent Flow Control Technique of ABR Service in ATM Networks Based on Fuzzy Neural Networks 被引量:7
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作者 Zhang Liangjie Li Yanda Li Qinghua Wang Pu (Dept of Automation, Tsinghua University, Beijing 100084) 《通信学报》 EI CSCD 北大核心 1997年第3期3-9,共7页
InteligentFlowControlTechniqueofABRServiceinATMNetworksBasedonFuzzyNeuralNetworks①ZhangLiangjieLiYandaLiQing... InteligentFlowControlTechniqueofABRServiceinATMNetworksBasedonFuzzyNeuralNetworks①ZhangLiangjieLiYandaLiQinghuaWangPu(DeptofA... 展开更多
关键词 模糊神经网络 流量控制 异步传输网 反馈 可用位率
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Study of Fuzzy Neural Networks Model for System Condition Monitoring of AUV 被引量:3
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作者 WANG Yu-jia, ZHANG Ming-junCollege of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001 ,China 《哈尔滨工程大学学报(英文版)》 2002年第2期42-45,共4页
A structure equivalent model of fuzzy-neural networks for system condition monitoring is proposed, whose outputs are the condition or the degree of fault occurring in some parts of the system. This network is composed... A structure equivalent model of fuzzy-neural networks for system condition monitoring is proposed, whose outputs are the condition or the degree of fault occurring in some parts of the system. This network is composed of six layers of neurons,which represent the membership functions, fuzzy rules and outputs respectively. The structure parameters and weights are obtained by processing off-line learning, and the fuzzy rules are derived from the experience. The results of the computer simulation for the autonomous underwater vehicle condition monitoring based on this fuzzy-neural networks show that the network is efficient and feasible in gaining the condition information or the degree of fault of the two main propellers. 展开更多
关键词 fuzzy neural network CONDITION monitoring AUTONOMOUS UNDERWATER vehicle
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Fuzzy Control Based on Neural Networks for Armored Vehicle Electric Drive System 被引量:1
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作者 马晓军 李华 +1 位作者 张剑 张豫南 《Defence Technology(防务技术)》 SCIE EI CAS 2006年第3期169-172,共4页
关键词 装甲车 电力驱动 模糊控制 神经网络 鲁棒性
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Application of fuzzy neural network to the nuclear power plant in process fault diagnosis
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作者 LIUYong-kuo XIAHong XIEChun-li 《Journal of Marine Science and Application》 2005年第1期34-38,共5页
The fuzzy logic and neural networks are combined in this paper, setting upthe fuzzy neural network (FNN ) ; meanwhile, the distinct differences and connections between thefuzzy logic and neural network are compared. F... The fuzzy logic and neural networks are combined in this paper, setting upthe fuzzy neural network (FNN ) ; meanwhile, the distinct differences and connections between thefuzzy logic and neural network are compared. Furthermore, the algorithm and structure of the FNN areintroduced. In order to diagnose the faults of nuclear power plant, the FNN is applied to thenuclear power planl, and the intelligence fault diagnostic system of the nuclear power plant isbuilt based on the FNN . The fault symptoms and the possibility of the inverted U-tube breakaccident of steam generator are discussed. In order to test the system' s validity, the invertedU-tube break accident of steam generator is used as an example and many simulation experiments areperformed. The test result shows that the FNN can identify the fault. 展开更多
关键词 neural networks fuzzy logic fuzzy neural network (fnn) inverted U-tube nuclear power plant
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Fault Diagnosing System of Steam Generator for Nuclear Power Plant Based on Fuzzy Neural Networks
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作者 Ming-Yu Fu Xin-Qian Bian Ji Shi 《Journal of Marine Science and Application》 2002年第1期41-46,共6页
All kinds of reasons are analysed in theory and a fault repository combined with local expert experiences is establishedaccording to the structure and the operation characteristic of steam generator in this paper. At ... All kinds of reasons are analysed in theory and a fault repository combined with local expert experiences is establishedaccording to the structure and the operation characteristic of steam generator in this paper. At the same time, Kohonen algo-rithm is used for fault diagnoses system based on fuzzy neural networks. Fuzzy arithmetic is inducted into neural networks tosolve uncertain diagnosis induced by uncertain knowledge. According to its self-association in the course of default diagnosis. thesystem is provided with non-supervise, self-organizing, self-learning, and has strong cluster ability and fast cluster velocity. 展开更多
关键词 neural network STEAM GENERATOR fuzzy FAULT diagnosing
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Fuzzy neural network based on a Sigmoid chaotic neuron
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作者 Zhang Yi Wang Xing-Yuan 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第2期175-180,共6页
The theories of intelligent information processing are urgently needed for the rapid development of modem science. In this paper, a novel fuzzy chaotic neural network, which is the combination of fuzzy logic system, a... The theories of intelligent information processing are urgently needed for the rapid development of modem science. In this paper, a novel fuzzy chaotic neural network, which is the combination of fuzzy logic system, artificial neural network system, and chaotic system, is proposed. We design its model structure which is based on the Sigmoid map, derive its mathematical model, and analyse its chaotic characteristics. Finally the relationship between the accuracy of map and the membership function is illustrated by simulation. 展开更多
关键词 CHAOS fuzzy neural network
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Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays
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作者 P.Balasubramaniam M.Kalpana R.Rakkiyappan 《Chinese Physics B》 SCIE EI CAS CSCD 2012年第4期586-596,共11页
Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The ... Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs). Each cell in an FCNN contains fuzzy operating abilities. The entire network is governed by cellular computing laws. The design of FCNNs is based on fuzzy local rules. In this paper, a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated. Mixed delays include discrete time-varying delays and unbounded distributed delays. A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network. By constructing the Lyapunov-Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs. The controller can be easily obtained by solving the derived LMIs. A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method. 展开更多
关键词 asymptotic stability CHAOS fuzzy cellular neural networks linear matrix inequalities SYNCHRONIZATION
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