检索结果-南通市图书馆

Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen hongli dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang hongli dong Yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission *** multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary *** attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance *** this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented ***,we analyze statistical properties of augmented noises as well as high-order moments of certain random *** the aid of two well-defined matrix difference equations,we not only obtain upper bounds on filtering error covariances,but also minimize those bounds via carefully designing gain ***,an example is presented to explain the effectiveness of this newly established quadratic filtering algorithm.

关键词： filtering quadratic bounds

Distributed Platooning Control of Automated Vehicles Subject to Replay Attacks Based on Proportional Integral Observers

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1954-1966页

作者： Meiling Xie Derui Ding Xiaohua Ge Qing-Long Han hongli dong Yan Song Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318the Heilongjiang Provincial Key Laboratory of Networking and Intelligent ControlNortheast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China

Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security *** paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of ***,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay *** light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed ***,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability *** controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication ***,a simulation example is provided to illustrate the effectiveness of the proposed control strategy.

关键词： Automated vehicles platooning control proportional-integral-observers(PIOs) replay attacks time-delays

Protocol-Based Non-Fragile State Estimation for Delayed Recurrent Neural Networks Subject to Replay Attacks

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 249-251页

作者： Fan Yang hongli dong Yuxuan Shen Xuerong Li dongyan Dai the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Sanya 572025China IEEE

Dear Editor, This letter focuses on the protocol-based non-fragile state estimation problem for a class of recurrent neural networks(RNNs). With the development of communication technology, the networked systems have ... 详细信息

关键词： network communication estimation

Scalable Distributed State Estimation over Binary Sensor Networks with Energy Harvester

在线全文

学校读者我要写书评

暂无评论

Guidance, Navigation and Control 2024年第2期4卷 163-193页

作者： Fei Han Longkang Ma Yanhua Song hongli dong State Key Laboratory of Continental Shale Oil Northeast Petroleum University Daqing 163318 P.R.China Arti¯cial Intelligence Energy Research Institute Northeast Petroleum University Daqing 163318 P.R.China School of Electrical and Information Engineering Northeast Petroleum University Daqing 163318 P.R.China Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University Daqing 163318 P.R.China

This paper deals with distributed state estimation problem for discrete time-varying systems over binary sensor networks,where every binary sensor is equipped with an energy *** input of every binary sensor considers the randomly occurring missing *** differences between the real and estimated inputs of binary sensor are employed to derive useful information in order to address the insufficient information for estimation *** information from neighboring nodes is transmitted only if its energy level is positive,where a random variable is introduced to formulate the energy *** means of the available information,distributed estimator is constructed for each binary sensor and the desirable performance constraints is given for the dynamic characteristics of estimation errors within anite time *** conditions are established for the existence of desired distribution estimation quantities through local performance analysis ***,the desired distributed estimator gains are calculated recursively,which means the desirable ***,the viability and efficiency of the distributed scheme are exhibited through a practical illustration.

关键词： Binary sensor network energy harvesting distributed estimation local analysis method

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

基于特征强化U⁃Net的地震速度反演方法

石油地球物理勘探 2024年第2期59卷 185-194页

作者：张岩孟德聪宋利伟董宏丽东北石油大学计算机与信息技术学院黑龙江大庆163318 东北石油大学人工智能能源研究院黑龙江大庆163318 东北石油大学物理与电子工程学院黑龙江大庆163318

基于深度神经网络的地震速度反演方法面临的挑战是:时间域地震数据与空间域模型信息间语义映射的弱对应关系导致多解性;神经网络将地震数据映射到速度模型过程中缺少有效引导,易受噪声干扰,影响反演精度。为此,提出一种基于特征强化U‑Ne... 详细信息

基于深度神经网络的地震速度反演方法面临的挑战是:时间域地震数据与空间域模型信息间语义映射的弱对应关系导致多解性;神经网络将地震数据映射到速度模型过程中缺少有效引导,易受噪声干扰,影响反演精度。为此,提出一种基于特征强化U‑Net的地震速度反演方法。首先,通过多炮地震数据特征叠加使输入网络的地震时间序列信号与对应速度模型之间的空间关系更加明确;其次,基于多尺度特征融合的思想设计具有不同尺寸卷积核的模块,以增强网络对有效特征的学习能力;然后,利用注意力门引导网络,增强网络重点关注的特征;最后,结合瓶颈残差和预激活的思想,在网络中加入预激活瓶颈残差,避免梯度消失和网络退化。实验表明,该方法在地震速度反演方面具有更高的精度,并在抗噪声测试中效果较好,具有一定的泛化能力。

关键词：地震速度反演深度学习注意力多尺度特征融合特征强化

吴门医派验方通窍止痛方对偏头痛模型大鼠的改善作用及机制研究

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

中医药信息 2024年第5期41卷 13-18页

作者：范浩浩董宏利南京中医药大学附属苏州市中医医院江苏苏州215009

目的:通过观察吴门医派验方通窍止痛方对偏头痛大鼠模型血清一氧化氮(NO)、降钙素基因相关肽(CGRP)、内皮素-1(ET-1)、神经递质多巴胺(DA)、去甲肾上腺素(NE)及5-羟色胺(5-HT)含量的影响探讨其作用机制。方法:将SD大鼠随机分为空白组、... 详细信息

目的:通过观察吴门医派验方通窍止痛方对偏头痛大鼠模型血清一氧化氮(NO)、降钙素基因相关肽(CGRP)、内皮素-1(ET-1)、神经递质多巴胺(DA)、去甲肾上腺素(NE)及5-羟色胺(5-HT)含量的影响探讨其作用机制。方法:将SD大鼠随机分为空白组、模型组、西比灵组和通窍止痛方组,每组8只,连续灌胃给予相应药物7 d,末次灌胃30 min后,除空白组外,其余各组以10 mg/kg剂量在颈部皮下注射硝酸甘油(GTN)的方式制备偏头痛大鼠模型。观察大鼠2 h内(以30 min为间隔)挠头次数,记录其行为学变化;造模4 h后,采用酶联免疫吸附实验(ELISA)检测大鼠血清中NO、CGRP、ET-1及脑组织中DA、NE、5-HT水平。结果:与空白组比较,模型组大鼠不同时间段挠头次数显著增多(P<0.01),血清中NO、CGRP水平显著升高(P<0.01),ET-1水平明显下降(P<0.01);脑组织中DA、NE、5-HT水平均显著降低(P<0.01);与模型组比较,西比灵组、通窍止痛方组大鼠不同时间段挠头次数均显著降低(P<0.05,P<0.01),血清中NO、CGRP水平显著降低(P<0.01,P<0.05),ET-1水平显著升高(P<0.05,P<0.01);脑组织中DA、NE、5-HT水平明显升高(P<0.01,P<0.05)。结论:通窍止痛方对偏头痛大鼠模型的改善作用可能与调节血清NO、CGRP、ET-1水平及脑组织神经递质DA、NE、5-HT含量有关。

关键词：偏头痛通窍止痛方大鼠行为学作用机制

基于贝叶斯单源域领域泛化算法的天然气管道故障智能诊断

在线全文

学校读者我要写书评

暂无评论

天然气工业 2024年第9期44卷 27-37页

作者：董宏丽商柔汪涵博王闯陈双庆管闯东北石油大学三亚海洋油气研究院东北石油大学人工智能能源研究院黑龙江省网络化与智能控制重点实验室东北石油大学石油工程学院

基于深度学习算法的故障智能诊断模型已被广泛应用于天然气管道运输安全领域,然而管道通常处于准稳态,使得训练集中的故障样本量受限。为此,针对天然气管道故障诊断中因训练集故障样本量有限,导致难以准确诊断的问题,提出了一种基于贝... 详细信息

基于深度学习算法的故障智能诊断模型已被广泛应用于天然气管道运输安全领域,然而管道通常处于准稳态,使得训练集中的故障样本量受限。为此,针对天然气管道故障诊断中因训练集故障样本量有限,导致难以准确诊断的问题,提出了一种基于贝叶斯单源域领域泛化(BSDG)算法,部署了一种攻击防御策略,通过在攻击阶段明确伪目标域增强路径,并在防御阶段引导模型参数的后验分布向伪域样本得分更高的方向调整,增强模型在面对不同域扰动时的适应性和鲁棒性。研究结果表明:(1)基于贝叶斯网络建立的非定向攻击模型确保伪域样本既保留了与源域的相关性,又引入了足够的域差异来模拟潜在的目标域,由此提升了多源域和单源域设置下的领域泛化诊断准确率;(2)测试结果显示,BSDG算法在多源域泛化任务及两项单源域泛化任务中,相较于性能最优的对比算法,其准确率分别提高了9.79%、5.09%和27.98%;(3)裕度差异损失通过在学习决策边界的过程中引入不确定性,令分类器可以灵活且有效应对频繁的分布变化,显著性测试结果表明BSDG算法在多数场景下显著优于先进对比算法;(4)贝叶斯神经网络通过在权重上引入不确定性,有效提升了BSDG算法的泛化稳定性。结论认为,BSDG算法通过使用基于贝叶斯推理的攻击防御策略,有效扩展了源域模型的决策边界,解决了实际场景数据匮乏导致的深度神经网络泛化能力差的问题,为样本受限情形下的天然气管道故障诊断模型设计提供了理论支撑。

关键词：天然气管道故障智能诊断迁移学习贝叶斯神经网络小样本问题泛化能力

基于MobileViT的岩石薄片图像岩性识别方法研究

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

地质通报 2024年第6期43卷 938-946页

作者：王琼杨杰霍凤财董宏丽任伟建于涛东北石油大学电气信息工程学院黑龙江大庆163318 东北石油大学人工智能能源研究院黑龙江大庆163318 黑龙江省网络化与智能控制重点实验室黑龙江大庆163318 东北石油大学三亚海洋油气研究院海南三亚572000 大庆油田有限责任公司第四采油厂工艺研究所黑龙江大庆163511

岩石薄片图像中包含了大量肉眼无法观察到的地质特征信息,对岩石薄片图像的岩性识别结果为后续的石油勘探和开发奠定了基础。针对岩性识别数据集不均衡、识别模型参数多等问题,提出一种改进的轻量化MobileViT模型,该模型针对涵盖了90%... 详细信息

岩石薄片图像中包含了大量肉眼无法观察到的地质特征信息,对岩石薄片图像的岩性识别结果为后续的石油勘探和开发奠定了基础。针对岩性识别数据集不均衡、识别模型参数多等问题,提出一种改进的轻量化MobileViT模型,该模型针对涵盖了90%以上常见岩性的岩石薄片图像进行建模分析。首先,为使模型更好地学习到每类岩石薄片图像中所包含的独特特征,对数据集进行数字增加。其次,使用GELU替换MobileViT中MV2模块中常规ReLU6,从而作为该模块的激活函数,有效解决神经元死亡的问题,提升模型的收敛速度。最后,划分训练集和测试集,使用余弦退火算法自动更新学习率,以迁移学习加速训练过程,实现岩石薄片图像中针对岩性的自动识别。实验结果表明,改进后的MobileViT对岩性识别的准确率达82.9%,模型的参数仅为7.66M,通过实例验证该算法具有较好的鲁棒性。

关键词：岩石薄片岩性识别 MobileViT 余弦退火轻量化