检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

1,376 篇 会议
148 篇 期刊文献
4 册 图书

馆藏范围

1,528 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,016 篇 工学
- 344 篇 控制科学与工程
- 327 篇 计算机科学与技术...
- 288 篇 电气工程
- 229 篇 机械工程
- 206 篇 软件工程
- 156 篇 材料科学与工程（可...
- 116 篇 化学工程与技术
- 108 篇 仪器科学与技术
- 79 篇 电子科学与技术（可...
- 78 篇 动力工程及工程热...
- 58 篇 信息与通信工程
- 57 篇 生物医学工程（可授...
- 52 篇 石油与天然气工程
- 45 篇 力学（可授工学、理...
- 44 篇 光学工程
- 43 篇 安全科学与工程
- 38 篇 冶金工程
- 26 篇 航空宇航科学与技...
- 22 篇 土木工程
- 22 篇 交通运输工程
507 篇 理学
- 327 篇 物理学
- 114 篇 数学
- 89 篇 化学
- 49 篇 统计学（可授理学、...
- 37 篇 系统科学
192 篇 管理学
- 177 篇 管理科学与工程(可...
- 59 篇 工商管理
69 篇 医学
- 47 篇 临床医学
- 37 篇 基础医学(可授医学...
- 27 篇 药学(可授医学、理...
22 篇 经济学
9 篇 法学
6 篇 教育学
2 篇 军事学
1 篇 文学
1 篇 历史学
1 篇 农学
1 篇 艺术学

主题

199 篇 process control
93 篇 diagnostics
83 篇 control systems
60 篇 monitoring
43 篇 plasma diagnosti...
30 篇 fault detection
28 篇 condition monito...
26 篇 reliability
25 篇 automation
23 篇 sensors
22 篇 manufacturing
21 篇 mathematical mod...
20 篇 quality control
18 篇 neural networks
17 篇 combustion
17 篇 automatic contro...
16 篇 maintenance engi...
16 篇 process monitori...
16 篇 costs
15 篇 safety

机构

5 篇 china academy of...
5 篇 korea univ dept ...
5 篇 precitec gmbh & ...
4 篇 department of pr...
4 篇 kuwait oil compa...
4 篇 univ calif berke...
4 篇 department of me...
4 篇 cern geneva
4 篇 state univ chem ...
3 篇 oak ridge natl l...
3 篇 univ manchester ...
3 篇 precitec optron ...
3 篇 south ural state...
3 篇 tver state techn...
3 篇 warsaw univ tech...
3 篇 eindhoven univ t...
3 篇 department of au...
3 篇 primes gmbh max ...
3 篇 school of inform...
3 篇 bauman moscow st...

作者

8 篇 juuso esko
8 篇 lahdelma sulo
6 篇 kwon kwang-ho
5 篇 durocher david b...
5 篇 kogel-hollacher ...
5 篇 jharko elena
4 篇 tillmann w.
4 篇 anon
4 篇 abdulgader m.
4 篇 spanos cj
4 篇 yong qin
4 篇 viharos zsolt já...
4 篇 kim moonkeun
4 篇 david b. duroche...
4 篇 fang hongzheng
4 篇 efremov alexande...
3 篇 peng xiyuan
3 篇 wang jx
3 篇 moyne james
3 篇 srinivasan tan

语言

1,444 篇 英文
71 篇 其他
10 篇 中文
1 篇 德文
1 篇 法文
1 篇 俄文

检索条件"任意字段=Conference on Process Control and Diagnostics"

共 1528 条记录，以下是91-100 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Algorithm Development for Pneumatic Actuator control and diagnostics

Algorithm Development for Pneumatic Actuator Control and Dia...

引用

Computer Science (COMSCI), International Scientific conference on

作者： Antoniy Petrov Albena Taneva Control Systems Department Plovdiv branch Technical University of Sofia Plovdiv Bulgaria

This paper presents the pneumatic control system widely used in manufacturing process. This is a technology that uses the power of compressed air to create mechanical motion. The purpose of this work is to improve existing manufacturing system with simple control of pneumatic actuators. To do this is necessary to extend the simple control with adding functions to collect data for diagnostics. Such data can be used for estimating remaining lifetime of a pneumatic cylinder during preventive maintenance or replacement. Challenge in front the solution is to be compatible with several of automation systems using PLCs and easy for multiplication in laboratory equipment and real manufacturing environment and assembly systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of Intelligent Epidemic Prevention Vehicle control System Based on Single-Chip Microcomputer 4

Design of Intelligent Epidemic Prevention Vehicle Control Sy...

引用

4th IEEE International conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Li, Xiaolin North China Electric Power University School of Control and Computer Engineering Beijing102206 China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Nowadays, the COVID-19 epidemic continues to repeat, and the novel coronaviruses are highly contagious. In order to solve the difficulties of information collection and cargo transportation in the process of epidemic prevention and control, and reduce the work intensity of epidemic prevention personnel. In this paper, a multi-functional intelligent epidemic prevention vehicle control system based on single-chip microcomputer is proposed to realize the goal of replacing manual control with intelligent vehicles. This design uses the stm32 single-chip microcomputer as the control core, for the work demand of the epidemic prevention site. First of all, the design realizes the intelligent vehicle tracking navigation and path planning function to realize the contactless distribution. Secondly, the function of face recognition and intelligent temperature measurement is completed, which can upload information remotely, process images, measure the temperature for diagnostics, and strengthen better interaction with the doctor terminal. At last, by wireless transmission, human-computer interaction is realized. The intelligent epidemic prevention vehicle control system can basically complete the designed function through many simulation experiments. Among them, the path planning algorithm can be completed within 5 s, and the success rate of face recognition is as high as 97 %, which achieves a good simulation effect and has a certain value in the current environment. © 2022 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Learning-Based diagnostics for Fault Detection and Isolation in Linear Stochastic Systems 30

Learning-Based Diagnostics for Fault Detection and Isolation...

引用

30th Mediterranean conference on control and Automation (MED)

作者： Noorani, Erfaun Somarakis, Christoforos Goyal, Raman Feldman, Alexander Rane, Shantanu Palo Alto Res Ctr Palo Alto CA 94304 USA Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA Univ Maryland Inst Syst Res ISR College Pk MD 20742 USA

ISBN: (纸本)9781665406734

AI-enabled mechanisms are deployed to guard controlled systems against sensor anomalies. We explore a two-level architecture design in which a low-level feedback controller of a linear system uses measurements from one or more potentially unreliable sensors. These observations are prone both to sensor noise but unknown additive faults. Our proposed, high-level, guard mechanism consists of a Reinforcement Learning (RL) agent that monitors available vitals of the system. In the event of a fault on the sensor components, the RL agent automatically detects, estimates the fault, localizes and takes action to cancel the fault. In addition, we develop design methodologies for efficient training of the RL agent that take advantage of system dynamics and sensor fusion schemes. We show that the associated training cost functions can be designed so that their optimal policy achieves efficient of arbitrary constant or piece-wise constant sensor faults. To illustrate our theoretical results, we consider a linearized version of a chemical process with multiple sensors, controlled by a Linear Quadratic Gaussian (LQG) Servo-controller with Integral Action. Our simulations show that the RL-agent is successful in localizing the faulty sensors and mitigating the effects of faults in an online fashion.

关键词： Training Linear systems System dynamics Stochastic systems Fault detection Design methodology Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Online Monitoring of Interturn Short Circuit Current in PMSMs 50

Online Monitoring of Interturn Short Circuit Current in PMSM...

引用

50th Annual conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Zezula, Lukas Blaha, Petr CEITEC Department of Control and Instrumentation Brno University of Technology Brno Czech Republic Brno University of Technology Brno Czech Republic

ISBN: (纸本)9781665464543

This paper extends the previously published parameter estimation-based approach to interturn short circuit diagnostics in permanent magnet synchronous motors by realtime monitoring of hidden machine states after fault occurrence. The designed monitoring method relies on an adaptive formulation of the Kalman filter, which assumes interdependence between measurement and process noise variables. A variable forgetting factor not only mitigates the impact of the process model uncertainty but also facilitates the simultaneous operation of the monitoring algorithm and fault indicator estimation. Furthermore, contributions of fault current and healthy machine model to stationary reference frame currents are estimated from an advanced discrete-time motor description reflecting a stator winding arrangement inside a motor’s case. The monitoring algorithm is validated in steady state, torque load transient, and velocity transient laboratory experiments with diverse fault severity values. © 2024 IEEE.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Development of a Machine Learning Model for Production Facility Predictive diagnostics

Development of a Machine Learning Model for Production Facil...

引用

International conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Daniil Vorsin Nikolay Toichkin Department of Informatics and Computer Engineering Murmansk Arctic University Apatity Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

The usage of artificial intelligence in problems related to industry makes it possible to develop optimization, predictive digital models for their operation in real time. The developed model can conduct predictive diagnostics of equipment's, or can be employed as a system that offers recommendations to the user for subsequent optimization of the technological process Considering the growing complexity of technical equipment and their control systems, it becomes highly imperative to develop an intelligent diagnostic structure for safety management in multi-level industrial systems. The article's relevance stems from the implementation of machine learning algorithms in the industry, enabling the analysis of a considerable amount of sensor-derived data. As a result, this facilitates predictive equipment diagnostics, anomaly prediction, intelligent safety management, uninterrupted operations, and reduced maintenance downtime.

关键词： Training Industries Recurrent neural networks Electric breakdown Safety management Predictive models Boosting

来源：评论

学校读者我要写书评

暂无评论

Identification and Characterization of Modulation Scheme in an EV-PMSM control Strategy for Digital Twin Modeling

Identification and Characterization of Modulation Scheme in ...

引用

conference on diagnostics in Electrical Engineering (Diagnostika)

作者： Mahmoud Ibrahim Anton Rassõlkin Toomas Vaimann Ants Kallaste Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia

ISBN: (数字)9798350361490

ISBN: (纸本)9798350361506

Digital twins (DT), virtual replicas of physical systems, play a pivotal role in design, monitoring, and optimization across various industries. However, the accuracy of DT relies heavily on the precision of their underlying virtual models, presenting a challenge when physical system parameters are not fully known. This research addresses this challenge by proposing a comprehensive approach to identify and characterize the modulation scheme employed in the control strategy of an Electric Vehicle Permanent Magnet Synchronous Motor (EV-PMSM). The proposed algorithm utilizes actual stator voltage and current signals obtained from the EV motor drive test bench. The identification process involves three sequential steps: switching frequency calculation, spectrum analysis, and harmonic analysis. The results of this analysis strongly indicate the utilization of Space Vector Modulation (SVM) in the control strategy. Finally, the voltage vector distribution (VVD) was calculated to serve as a cornerstone for the precise modeling of the modulator.

关键词： Support vector machines Analytical models Motor drives Switching frequency Modulation Stators Harmonic analysis Vectors Voltage control Spectral analysis

来源：评论

学校读者我要写书评

暂无评论

Combination of SGDD and Multiple Time Scale CNN for Bearing Fault Diagnosis 6

Combination of SGDD and Multiple Time Scale CNN for Bearing ...

引用

6th IEEE International conference on Sensing, diagnostics, Prognostics, and control, SDPC 2022

作者： Ye, Ying Jin, Bohan Huang, Yixiang Shanghai Research Institute of Building Sciences Co. Ltd. Shanghai Engineering Research Center for Safety Intelligent Control of Building Machinery Shanghai China Shanghai Jiao Tong University School of Mechanical Engineering Shanghai China

ISBN: (数字)9781665469869

ISBN: (纸本)9781665469869

This paper aims at the fault identification of common types of the rolling element bearings (REBs). A method employs a Savitzky-Golay Digital Differentiator (SGDD) and convolutional neural network (CNN) with multiple time scale mechanism is proposed. The SGDD produces the derivative of the estimated smoothed signal, which can present jerk, the derivative of acceleration. And jerk is a better alternative to extract features from, whose limited usage is mainly due to the high price. The jerk signal is input to ID CNN with modified structure, namely the down-sampling of input signal and the convolution layers and pooling layers for signals of different time scales respectively. Their output are then concatenated. The remaining procedures are identical to them of an essential CNN. The method is validated with a dataset of REB. The results indicate that the approach has a higher accuracy and runs more smoothly during training process than other two related methods, thus confirm the role of SGDD and multiple time scale mechanism in REB fault classification. © 2022 IEEE.

关键词： Roller bearings

来源：评论

学校读者我要写书评

暂无评论

A data-driven approach to fault diagnostics for industrial process plants based on feature extraction and inferential statistics

A data-driven approach to fault diagnostics for industrial p...

引用

International conference on control, Automation and Diagnosis (ICCAD)

作者： Simone Smeraldo Axel Busboom Stefan Bendisch Hristo Hriskov Thomas Morgenstern Maria Prandini Department of Engineering and Management Munich University of Applied Sciences Munich Germany Equipment Health Center Linde plc Pullach Germany Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy

Accurate detection and diagnostics of faults in complex industrial plants are important for preventing unplanned downtime, optimizing operations and maintenance decisions, minimizing repair time, and optimizing spare part logistics. It is often infeasible to generate accurate physics-based models of complex equipment; therefore, and due to lower computational complexity, data-driven methods are frequently employed. We propose a novel method for data-driven fault diagnostics and validate it using the Tennessee Eastman process (TEP) benchmark. It is assumed that the time of the onset of the fault is known, such that time-series data from the process both before and after occurrence of the fault can be extracted. For each of the measured time-series, several statistical features are extracted. A statistical significance level is computed for each feature using inferential statistics measures. The matrix of significance levels serves as a “fingerprint” of each fault category and is used as input to a feedforward neural network. We show that the network can be trained to achieve high classification accuracy on data from the TEP benchmark model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Time Series Clustering in High-Noise Conditions in the Data

Time Series Clustering in High-Noise Conditions in the Data

引用

International conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Timur Murtazin Timur Ismagilov Ufa State Petroleum Technological University Ufa Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

Time series clustering algorithm of a change in process parameters based on statistical homogeneity of time series fragment of a single cluster is suggested in the article. The selected clusters characterize stationary modes, which can be considered as basics of the situational modeling tasks, control and diagnostics of the process object state. For time series clustering in high-noise conditions in the measurement data of technological parameters the frequency-time disintegration on the basis of wavelet function and statistical characteristics analysis of approximating coefficients of discrete wavelet disintegration are used. The considered implementation of the suggested clustering algorithm is based on the time series of changes in the process parameter of an actual technological object with a high level of noise in relation to the useful signal. The algorithm allows to form a set of values of process parameters corresponding to the object's steady working mode, which are used in the task of identifying the technological situation.

关键词： Time-frequency analysis Time series analysis Clustering algorithms process control Wavelet analysis Approximation algorithms Time measurement

来源：评论

学校读者我要写书评

暂无评论

Research on the Local Curve Roughness (LCR) Method Based on Pulse Width

Research on the Local Curve Roughness (LCR) Method Based on ...

引用

International conference on Sensing, diagnostics, Prognostics, and control (SDPC)

作者： Jiajun Yao Lin Yue College of Mechanical & Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798350388855

ISBN: (纸本)9798350388862

Bearing fault detection is important for the normal operation of equipment and the personal safety of operators. However, the weak vibration signals triggered by early bearing failures are often submerged in the harmonics of equipment operation, which are difficult to be extracted by conventional frequency domain analysis. The Local Curve Roughness (LCR) method as a pre-processing method can effectively amplify the weak shock signals, so that the frequency domain analysis can extract the characteristics of early bearing failures. The key of the LCR method lies in the selection of the LCR processing window width, and an inappropriate window width will affect the recognition of the impact signal. A Local Curve Roughness based on Pulse Width Selection (LCR-PWS) is proposed on the basis of LCR, and the pulse width of the shock signal is selected as the window width for LCR processing. Subsequently, bearing fault implantation test data are processed and analyzed, and the results prove that the LCR-PWS preprocessed data can detect the characteristic frequency of bearing faults earlier than the unprocessed data.

关键词： Vibrations Frequency-domain analysis Electric shock Fault detection Rolling bearings process control Harmonic analysis Sensors Safety

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共153页 << < 6 7 8 9 10 11 12 13 14 15 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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

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：