检索结果-南通市图书馆

Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

Plasma Science and Technology 2024年第6期26卷 149-158页

作者：韩伟伟孙对兄张国鼎董光辉崔小娜申金成王浩亮张登红董晨钟苏茂根 Key Laboratory of Atomic and Molecular Physics&Functional Material of Gansu Province College of Physics and Electronic EngineeringNorthwest Normal UniversityLanzhou 730070People’s Republic of China Gansu Digital Herb Testing Center Dingxi 743000People’s Republic of China Gansu International Scientific and Technological Cooperation Base of Laser Plasma Spectroscopy Lanzhou 730070People’s Republic of China

To obtain more stable spectral data for accurate quantitative analysis of multi-element,especially for the large-area in-situ elements detection of soils, we propose a method for a multielement quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy(CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I324.75 nm for filtering the experimental data of multiple sample sets. Pre-and post-data filtering,the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection(LOD)values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post-data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.

关键词： laser-induced breakdown spectroscopy soil data filtering quantitative analysis multielement

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Estimation of Hammerstein nonlinear systems with noises using filtering and recursive approaches for industrial control

引用

Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 260-271页

作者： Mingguang ZHANG Feng LI Yang YU Qingfeng CAO School of Electrical&Information Engineering Jiangsu University of TechnologyChangzhou213001China College of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou225127China

This paper discusses a strategy for estimating Hammerstein nonlinear systems in the presence of measurement noises for industrial control by applying filtering and recursive approaches.The proposed Hammerstein nonlinear systems are made up of a neural fuzzy network(NFN)and a linear state`-space model.The estimation of parameters for Hammerstein systems can be achieved by employing hybrid signals,which consist of step signals and random signals.First,based on the characteristic that step signals do not excite static nonlinear systems,that is,the intermediate variable of the Hammerstein system is a step signal with different amplitudes from the input,the unknown intermediate variables can be replaced by inputs,solving the problem of unmeasurable intermediate variable information.In the presence of step signals,the parameters of the state-space model are estimated using the recursive extended least squares(RELS)algorithm.Moreover,to effectively deal with the interference of measurement noises,a data filtering technique is introduced,and the filtering-based RELS is formulated for estimating the NFN by employing random signals.Finally,according to the structure of the Hammerstein system,the control system is designed by eliminating the nonlinear block so that the generated system is approximately equivalent to a linear system,and it can then be easily controlled by applying a linear controller.The effectiveness and feasibility of the developed identification and control strategy are demonstrated using two industrial simulation cases.

关键词： Hammerstein nonlinear systems Neural fuzzy network data filtering Hybrid signals Industrial control

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Novel Static Security and Stability Control of Power Systems Based on Artificial Emotional Lazy Q-Learning

引用

Energy Engineering 2024年第6期121卷 1713-1737页

作者： Tao Bao Xiyuan Ma Zhuohuan Li Duotong Yang Pengyu Wang Changcheng Zhou Digital Grid Research Institute Southern Power GridGuangzhou510000China

The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases.In order to improve and ensure the stable operation of the novel power system,this study proposes an artificial emotional lazy Q-learning method,which combines artificial emotion,lazy learning,and reinforcement learning for static security and stability analysis of power systems.Moreover,this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able to effectively screen useful data for learning,and improve the static security stability of the new type of power system more effectively than the traditional proportional-integral-differential control and Q-learning methods.

关键词： Artificial sentiment static secure stable analysis Q-learning lazy learning data filtering

来源：

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

Hierarchical maximum likelihood stochastic gradient identification algorithm for feedback nonlinear systems using the data filtering technique

Hierarchical maximum likelihood stochastic gradient identifi...

引用

第37届中国控制会议

作者： Junhong Li Xiao Li Juping Gu Yi Yang School of Electrical Engineering Nantong University

This paper considers the parameter identification of feedback nonlinear systems with colored noise. The difficulty of the identification is that it need to estimate the parameters of the forward path subsystem and the feedback subsystem.According to the data filtering technique and the hierarchical identification principle, a hierarchical maximum likelihood forgetting factor stochastic gradient identification algorithm based on the filtered model is presented for the discussed feedback nonlinear systems. The simulation results show the effective of the proposed algorithm.

关键词： Hierarchical identification data filtering Maximum likelihood Stochastic gradient Parameter identification

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Least squares based iterative estimation for multi-input output-error systems using the data filtering

Least squares based iterative estimation for multi-input out...

引用

第36届中国控制会议

作者： Jiling Ding Huibo Chen Department of Mathematics Jining University School of Electrical Engineering Sanmenxia Polytechnic

ISBN: (纸本)9781538629185

This paper considers the parameter estimation for multi-input output error autoregressive（OEAR） systems. The main contribution of this paper is to propose iterative algorithms for multi-input OEAR systems using the data filtering technique.Firstly, a least squares iterative（LSI） identification algorithm is given for multi-input OEAR systems as a comparison. Secondly,we transform an OEAR system into two identification models and present a data filtering based least squares iterative（F-LSI）identification algorithm. Finally, an illustrative simulation example is provided to test the proposed algorithms, the simulation results indicate that the F-LSI identification algorithm can produce more accurate parameter estimates than the LSI identification algorithm.

关键词： Multivariable system System identification Least squares Iterative algorithm data filtering Multi-input system

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

A combined technique of Kalman filter, artificial neural network and fuzzy logic for gas turbines and signal fault isolation

引用

Chinese Journal of Aeronautics 2021年第2期34卷 124-135页

作者： Simone TOGNI Theoklis NIKOLAIDIS Suresh SAMPATH Department of Power and Propulsion Cranfield UniversityCranfield MK-43United Kingdom

The target of this paper is the performance-based diagnostics of a gas turbine for the automated early detection of components malfunctions. The paper proposes a new combination of multiple methodologies for the performance-based diagnostics of single and multiple failures on a two-spool engine. The aim of this technique is to combine the strength of each methodology and provide a high success rate for single and multiple failures with the presence of measurement malfunctions. A combination of KF(Kalman Filter), ANN(Artificial Neural Network) and FL(Fuzzy Logic) is used in this research in order to improve the success rate, to increase the flexibility and the number of failures detected and to combine the strength of multiple methods to have a more robust solution. The Kalman filter has in his strength the measurement noise treatment, the artificial neural network the simulation and prediction of reference and deteriorated performance profile and the fuzzy logic the categorization flexibility, which is used to quantify and classify the failures. In the area of GT(Gas Turbine) diagnostics, the multiple failures in combination with measurement issues and the utilization of multiple methods for a 2-spool industrial gas turbine engine has not been investigated extensively.This paper reports the key contribution of each component of the methodology and brief the results in the quantification and classification success rate. The methodology is tested for constant deterioration and increasing noise and for random deterioration. For the random deterioration and nominal noise of 0.4%, in particular, the quantification success rate is above 92.0%, while the classification success rate is above 95.1%. Moreover, the speed of the data processing(1.7 s/sample)proves the suitability of this methodology for online diagnostics.

关键词： Artificial neural network data analytics data filtering Diagnostics Fuzzy logic Gas turbine Kalman filter Performance-based diagnostics

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Fog Computing Architecture-Based data Acquisition for WSN Applications

引用

China Communications 2017年第11期14卷 69-81页

作者： Guangwei Zhang Ruifan Li Institute of Network Technology Beijing University of Posts and Telecommunications 100876 China Engineering Research Center of Information Networks Ministry of Education 100876 China School of Computer Science Beijing University of Posts and Telecommunications 100876 China

Efficient and effective data acquisition is of theoretical and practical importance in WSN applications because data measured and collected by WSN is often unreliable, such as those often accompanied by noise and error, missing values or inconsistent data. Motivated by fog computing, which focuses on how to effectively offload computation-intensive tasks from resource-constrained devices, this paper proposes a simple but yet effective data acquisition approach with the ability of filtering abnormal data and meeting the real-time requirement. Our method uses a cooperation mechanism by leveraging on both an architectural and algorithmic approach. Firstly, the sensor node with the limited computing resource only accomplishes detecting and marking the suspicious data using a light weight algorithm. Secondly, the cluster head evaluates suspicious data by referring to the data from the other sensor nodes in the same cluster and discard the abnormal data directly. Thirdly, the sink node fills up the discarded data with an approximate value using nearest neighbor data supplement method. Through the architecture, each node only consumes a few computational resources and distributes the heavily computing load to several nodes. Simulation results show that our data acquisition method is effective considering the real-time outlier filtering and the computing overhead.

关键词： WSN fog computing abnormal data data filtering intrusion tolerance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

data collection model in hybrid network for participatory sensing

引用

International Journal of Modeling, Simulation, and Scientific Computing 2016年第4期7卷 16-22页

作者： Jeongseok Choi Taeyoung Kim Jaekwon Kim Sunghwan Moon Youngshin Han Jongsik Lee Department of Computer Science and Information Engineering Inha University 100 Inha-roNam-guIncheonKorea Department of Computer Engineering Sungkyul University 53 Sungkyuldaehak-roManan-guAnyang-siGyeonggi-doKorea

Advances in mobile technology make most people have their own mobile devices which contain various sensors such as a smartphone.People produce their own personal data or collect surrounding environment data with their mobile devices at every moment.Recently,a broad spectrum of studies on Participatory Sensing,the concept of extracting new knowledge from a mass of data sent by participants,are conducted.data collection method is one of the base technologies for Participatory Sensing,so networking and data filtering techniques for collecting a large number of data are the most interested research area.In this paper,we propose a data collection model in hybrid network for participatory sensing.The proposed model classifies data into two types and decides networking form and data filtering method based on the data type to decrease loads on data center and improve transmission speed.

关键词： data collection model participatory sensing data filtering hybrid network

来源：

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

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：