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Neural-networks-based Modelling and a Fuzzy Neural Networks Controller of MCFC

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High Technology Letters 2002年第2期8卷 76-82页

作者：沈承 cao Guangyi Zhu Xinjian institute of Fuel Cell Department of Automation Shanghai Jiaotong University Shanghai 200030 P.R.China

Molten Carbonate Fuel Cells (MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized. The temperature characters of MCFC stack are briefly analyzed. A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack, and the identification structure, algorithm and modeling training process are given in detail. A fuzzy controller of MCFC stack is designed. In order to improve its online control ability, a neural network trained by the I/O data of a fuzzy controller is designed. The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online. A detailed design of the controller is given. The validity of MCFC stack modelling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.

关键词： Molten Carbonate Fuel Cells (MCFC) Radial Basis Function (RBF) fuzzy neural networks control modelling

Retrieval Snow Depth by Artificial Neural Network Methodology from Integrated AMSR-E and In-situ Data——A Case Study in Qinghai-Tibet Plateau

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Chinese Geographical Science 2008年第4期18卷 356-360页

作者： cao Yungang YANG Xiuchun ZHU Xiaohua Department of Survey Engineering School of Civil Engineering Southwest Jiaotong University Chengdu 610031 China institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 China institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

On the basis of artificial neural network (ANN) model, this paper presents an algorithm for inversing snow depth with use of AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System (EOS)) dataset, i.e., brightness temperature at 18.7 and 36.5GHz in Qinghai-Tibet Plateau during the snow season of 2002-2003. In order to overcome the overfitting problem in ANN modeling, this methodology adopts a Bayesian regularization approach. The experiments are performed to compare the results obtained from the ANN-based algorithm with those obtained from other existing algorithms, i.e., Chang algorithm, spectral polarization difference (SPD) algorithm, and temperature gradient (TG) algorithm. The experimental results show that the presented algorithm has the highest accuracy in estimating snow depth. In addition, the effects of the noises in datasets on model fitting can be decreased due to adopting the Bayesian regularization approach.

关键词： artificial neural network Bayesian regularization snow depth brightness temperature Qinghai-Tibet Plateau

Back-Stepping Control for Flexible Air-Breathing Hypersonic Vehicles Based on Uncertainty and Disturbance Estimator

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Journal of Beijing institute of Technology 2020年第4期29卷 504-513页

作者： Lin cao Dong Zhang Ao Zhang System Engineering institute of Sichuan Aerospace Chengdu 610100China College of Astronautics Northwestern Polytechnical UniversityXi’an 710072China

A theoretical framework of nonlinear flight control for a flexible air-breathing hypersonic vehicle(FAHV)is proposed in this *** order to suppress the system uncertainty and external disturbance,an uncertainty and disturbance estimator(UDE)based back-stepping control strategy is designed for a dynamic state-feedback controller to provide stable velocity and altitude ***,the longitudinal dynamics of FAHV is simplified into a closure loop form with lumped uncertainty and *** the UDE is applied to estimate the lumped uncertainty and disturbance for the purpose of control input *** a nonlinear tracking differentiator is introduced to solve the problem of“explosion of term”in the back-stepping *** stability of the UDE-based control strategy is proved by using Lyapunov stability ***,simulation results are presented to demonstrate the capacity of the proposed control strategy.

关键词： flexible air-breathing hypersonic vehicle(FAHV) uncertainty and disturbance estimator(UDE) back-stepping control

Active learning accelerated Monte-Carlo simulation based on the modified K-nearest neighbors algorithm and its application to reliability estimations

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Defence Technology（防务技术） 2023年第10期28卷 306-313页

作者： Zhifeng Xu Jiyin cao Gang Zhang Xuyong Chen Yushun Wu School of Civil Engineering and Architecture Wuhan Institute of TechnologyWuhan430200PR China School of Mechanical and Electrical Engineering Wuhan Institute of TechnologyWuhan430200PR China Failure mechanics&Engineering Disaster Prevention and Mitigation Key Laboratory of Sichuan ProvinceSichuan UniversityChengdu610065PR China

This paper proposes an active learning accelerated Monte-Carlo simulation method based on the modified K-nearest neighbors *** core idea of the proposed method is to judge whether or not the output of a random input point can be postulated through a classifier implemented through the modified K-nearest neighbors *** to other active learning methods resorting to experimental designs,the proposed method is characterized by employing Monte-Carlo simulation for sampling inputs and saving a large portion of the actual evaluations of outputs through an accurate classification,which is applicable for most structural reliability estimation ***,the validity,efficiency,and accuracy of the proposed method are demonstrated *** addition,the optimal value of K that maximizes the computational efficiency is ***,the proposed method is applied to the reliability estimation of the carbon fiber reinforced silicon carbide composite specimens subjected to random displacements,which further validates its practicability.

关键词： Active learning Monte-carlo simulation K-nearest neighbors Reliability estimation Classification

Fault diagnosis of railway point machines based on wavelet transform and artificial immune algorithm

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Transportation Safety and Environment 2023年第4期5卷 117-126页

作者： Xiaochun Wu Weikang Yang Jianrong cao School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou 730070GansuChina china Railway Rolling Stock Corporation Qingdao Sifang Rolling Stock Research institute Co. LtdQingdao 266000ShandongChina

Aiming at the current problems of high failure rate and low diagnostic efficiency of railway point machines(RPMs)in the railway industry,a short-time method of fault diagnosis is *** the effect of noise on power signals in the data acquisition process of the railway centralized signaling monitoring(CSM)system,this study utilizes wavelet threshold denoising to eliminate *** results show that the accuracy of fault diagnosis can be improved by 4.4% after denoising the power *** in order to attain a lighter weight and shorten the running time of the diagnosis model,Mallat wavelet decomposition and artificial immune algorithm are applied to RPM fault ***,voluminous experiments using veritable power signals collected from CSM are introduced,which show that combining these methods can procure higher precision of RPMs and curtail fault diagnosis *** substantiates the validity and feasibility of the presented approach.

关键词： railway point machines wavelet threshold denoising Mallat wavelet decomposition artificial immune algorithm

22种春季开花的常用行道树种的致敏花粉形态特征

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应用与环境生物学报 2024年第4期30卷 759-766页

作者：宗桦曹芷萌李梦霞唐琪陈文凯李秀西南交通大学风景园林系成都611756 成都市植物园暨成都市公园城市植物科学研究院成都610000

树木花粉是我国春季最常见的致敏花粉原,是诱发市民过敏的最主要原因之一.为揭示致敏园林树种的花粉形态的个性与共性,对成都市常用的22种春季开花且花粉致敏的行道树种展开花粉形态研究.采用光学显微镜和扫描电镜对致敏花粉进行形态观... 详细信息

树木花粉是我国春季最常见的致敏花粉原,是诱发市民过敏的最主要原因之一.为揭示致敏园林树种的花粉形态的个性与共性,对成都市常用的22种春季开花且花粉致敏的行道树种展开花粉形态研究.采用光学显微镜和扫描电镜对致敏花粉进行形态观察与测量,借助主成分分析和聚类分析比较致敏花粉形态上的异同点.结果显示:(1)22个树种的致敏花粉的大小指数(sizeindex,SI)波动于13.43-51.10μm之间,小型和中型花粉合计占比94.45%.其中,池杉(Taxodium distichum ***)和马尾松(Pinus massoniana)花粉的个体大小差异最大,而枫杨(Pterocarya stenoptera)花粉的个体大小最为稳定.(2)22个致敏树种的花粉形状以长球形(占比45.45%)和近球形(占比36.36%)为主且轮廓线流畅而适于飘散,仅有刺柏(Juniperus formosana)的花粉为球形;并且72.73%的花粉为等极类型.(3)22种花粉中,16种花粉具萌发孔结构,其中有超过50%的花粉为3孔沟类型,进化程度均较高.花粉的外壁纹饰差异较大,多为模糊稀疏的颗粒状(36.36%)和瘤状(27.27%),且均没有明显的次级雕纹.银杏(Ginkgo biloba)、刺柏(***)和木麻黄(Casuarina equisetifolia)的花粉外形最为特殊;被子植物中桑(Morus alba)和构(Broussonetia papyrifera)的花粉与裸子植物最为相似.总体而言,22种致敏花粉的形状特征都趋向于形态小、圆润、散播阻力小、3孔沟结构占比高等特点,进化程度很高,以上共性特征可为初步鉴定园林树种的花粉致敏风险提供孢粉学依据.(图7表4参30)

关键词：行道树花粉形态共性特征花粉过敏

基于响应面法和ARO算法的桥梁有限元模型修正

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重庆交通大学学报（自然科学版） 2024年第9期43卷 9-17页

作者：杨宏印姜良维顾箭峰曹鸿猷吴楠昊武汉工程大学土木工程与建筑学院湖北武汉430073 桥梁智能与绿色建造全国重点实验室湖北武汉430034 武汉理工大学土木工程与建筑学院湖北武汉430070

针对桥梁结构模型修正过程中计算量大、全局寻优难等问题,提出一种基于响应面法和人工兔优化算法(artificial rabbits optimization, ARO)的桥梁有限元模型修正方法。该方法通过F检验法明确对结构响应影响显著的参数并建立响应面模型作... 详细信息

针对桥梁结构模型修正过程中计算量大、全局寻优难等问题,提出一种基于响应面法和人工兔优化算法(artificial rabbits optimization, ARO)的桥梁有限元模型修正方法。该方法通过F检验法明确对结构响应影响显著的参数并建立响应面模型作为桥梁有限元模型的代理模型进行迭代计算,然后通过静动力联合修正法基于特征响应的响应面模型计算值和试验值构建目标函数,并通过人工兔优化算法对目标函数进行迭代计算进而获得精确的有限元模型参数。采用该方法对变截面连续刚构黄河特大桥有限元模型进行修正,结果显示:基于显著性分析结果建立的桥梁响应面模型相关系数大于0.98,且平均绝对误差低于0.05;模型修正后主梁关键截面竖向位移最大相对误差由32.97%降至5.72%,平均相对误差由20.67%降至3.61%,桥梁前3阶竖向自振频率平均相对误差仅为0.18%。可见,采用所提方法修正的模型能用于评价桥梁结构实际受力性能。

关键词：桥梁工程变截面连续刚构桥有限元模型修正 F检验法响应面法静动力联合修正法

基于MOOSE平台的西安脉冲反应堆多物理耦合计算研究

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核动力工程 2024年第3期45卷 14-19页

作者：胡田亮姜夺玉张信一王召浩王立鹏曹璐李达陈立新西北核技术研究所强脉冲辐射环境模拟与效应国家重点实验室西安710024 西安交通大学西安710049

反应堆中涉及一系列复杂相互作用的多物理耦合过程,随着高性能计算技术的迅速发展,基于多物理耦合的分析越来越受到重视。基于多物理耦合平台MOOSE开展了西安脉冲反应堆的稳态和瞬态多物理耦合计算研究,综合应用Picard迭代和Jacobian Fr... 详细信息

反应堆中涉及一系列复杂相互作用的多物理耦合过程,随着高性能计算技术的迅速发展,基于多物理耦合的分析越来越受到重视。基于多物理耦合平台MOOSE开展了西安脉冲反应堆的稳态和瞬态多物理耦合计算研究,综合应用Picard迭代和Jacobian Free Newton-Krylov(JFNK)方法处理多物理耦合中的非线性问题,实现了三维中子扩散时空动力学、三维固体导热和一维流体流动传热的多物理耦合计算,计算了西安脉冲反应堆2 MW稳态运行和3.45$(1$表示一个有效缓发中子份额)脉冲运行条件下的反应堆行为,得到了堆芯三维功率和温度分布计算结果,计算结果与实验结果符合较好,证明了多物理耦合的正确性。开发的多物理耦合计算方法具有几何适应性好、耦合灵活等特点,具有应用于其他小型反应堆的潜力。

关键词：多物理耦合西安脉冲反应堆 MOOSE 稳态分析瞬态分析

密贴下穿既有地铁车站的新建通道拆撑影响分析

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铁道标准设计 2024年第2期68卷 158-166页

作者：曹攀章慧健杨宇杰张帅郭宏博西南交通大学交通隧道工程教育部重点实验室成都610031 西南交通大学土木工程学院成都610031 广州地铁设计研究院股份有限公司广州510010

依托成都地铁8号线倪家桥站零距离密贴下穿既有地铁1号线倪家桥车站工程,采用数值模拟方法对比分析“先施作二衬再拆撑”和“先拆撑再施作二衬”对既有和新建结构的力学差异,并基于“先拆撑再施作二衬”工况进一步分析拆撑方案,最后通... 详细信息

依托成都地铁8号线倪家桥站零距离密贴下穿既有地铁1号线倪家桥车站工程,采用数值模拟方法对比分析“先施作二衬再拆撑”和“先拆撑再施作二衬”对既有和新建结构的力学差异,并基于“先拆撑再施作二衬”工况进一步分析拆撑方案,最后通过实测现场实施的“先施作二衬再拆撑”工序下的既有车站底板沉降数据验证相关结论。研究结果表明:“先施作二衬再拆撑”既有车站弯矩及沉降、新建通道初支弯矩及二衬沉降变化不明显;“先拆撑再施作二衬”对于既有车站及新建通道影响则较为显著,一次性全部拆撑后既有及新建结构弯矩沿断面分布形态变化明显,在结构沉降方面,拆撑后既有车站及新建通道初支最大沉降突变量分别达4.86,7.30 mm;“先拆撑再施作二衬”工况下,采用顺序拆撑与跳仓拆撑,最不利部位出现在下穿通道纵向中部,跳仓拆撑引起新建通道初支沉降量大于顺序拆撑,但其施工效率更高,具体拆撑方式应根据施工安全控制标准及经济性要求合理选择。

关键词：地铁车站密贴下穿临时支撑内力分析现场监测拆撑方案