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共 1531 条记录，以下是311-320 订阅

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Intelligent Diagnostic System for Hydraulic Actuator

Intelligent Diagnostic System for Hydraulic Actuator

引用

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

作者： Khaziev, Emil L. Khaziev, Marat L. Kazan Fed Univ Naberezhnye Chelny Inst Naberezhnye Chelny Russia

ISBN: (纸本)9781538681190

The proposed technical solution allows optimizing the process of hydraulic drive control, which leads to increased energy efficiency, as well as diagnosing the state of the hydraulic system of the industrial machine. To ensure the speed of the process of diagnosing the state of the hydraulic drive in addition to the hardware of the system, an analytical software expert system is required. The subsystem allows one not only to speed up the existing diagnostic process, but to perform it faster and more accurately, in addition, it allows you to implement the prediction of diagnostic parameters in real time and planning the optimal timing of maintenance and repair to prevent failure in the process of equipment operation. In addition, the establishment of the causes of failure increases the likelihood of elimination of violations committed during the operation or detection of factory and other defects in the details of the equipment.

关键词： diagnostics intelligent system intelligent sensor hydraulic drive

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Independent Variables to control a Time-Varying Energy Distribution of Charged Species in a Capacitively Coupled Plasma

Independent Variables to Control a Time-Varying Energy Distr...

引用

IEEE International conference on Plasma Science (ICOPS)

作者： Jung Yeol Lee Hae June Lee Pusan National University Busan South Korea

ISBN: (纸本)9781728153087

Currently, most experimental plasma diagnostics have commonly used a physical approach based on the time-invariant energy distribution function, and the effect of time-varying parameters is underestimated. It is helpful to analyze the spatio-temporal evolution of charged particle dynamics using a particle-in-cell Monte Carlo Collision (PIC-MCC) simulation for advanced plasma control. Driving voltage, pressure, gap length, driving frequency, gas mixture, and gas pressure are the external variables to control the plasma kinetics. The control of the electron energy distribution functions in helium or argon discharges is investigated with the variation of these parameters at a specific pressure regime from 50 mTorr to 200 Torr. Additionally, the energy relaxation mechanism is investigated to verify the kinetic approach in this study. It was found that the spatio-temporal energy relaxation process dominantly determines not only the energy distribution but also macroscopic plasma properties including the electric field, velocity, plasma potential, and so on 1 .

关键词： Plasma properties Electric potential Monte Carlo methods Plasma diagnostics Kinetic theory Helium Voltage control

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Identifiability of a Series of Discrete process Cycles Based on Multirate Data

Identifiability of a Series of Discrete Process Cycles Based...

引用

American control conference

作者： Cheol W. Lee University of Michigan-Dearborn Dearborn MI USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

On-line identification of the manufacturing process based on process data is a crucial step for model-based control and diagnostics. A typical discrete manufacturing process generates multirate data streams. Whereas various sensors provide in-process information about the process, many important process outcomes such as product qualities are usually measured via postprocess inspection. This paper proposes a method for studying the identifiability of model parameters of the manufacturing process using both in-process and postprocess data. The identification of the model parameters based on multirate output is formulated using the maximumlikelihood method. The Fisher information matrix for a multirate-sampled discrete manufacturing system is derived to study identifiability of model parameters. A method to calculate the sensitivity matrices in the Fisher information matrix is also proposed. A case study is conducted using a model of metal removal in the cylindrical grinding process to demonstrate the efficacy of the proposed method for assessing the identifiability. It is observed using both sensor signal and postprocess output for identification effectively improves the identifiability.

关键词： Mathematic Identifiability model parameters Manufacturing process information matrix series (mathematics) Fisher information

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Subsystem for On-line diagnostics of Cutting process in Flexible Manufacturing

Subsystem for On-line Diagnostics of Cutting Process in Flex...

引用

2019 International Russian Automation conference, RusAutoCon 2019

作者： Desyatirikova, Elena N. Chernenkaya, Liudmila V. Mager, Vladimir E. Dpt. of Control systems and Information Technologies in Construction Voronezh State Technical University Voronezh Russia High School for Cyber physic systems and Control Peter the Great St.Petersburg Polytechnic University St.Petersburg Russia

ISBN: (纸本)9781728102658

Automation of various types of production assumes high a priori reliability of production equipment, which could be able to assure the product quality in the mode of unmanned production. Despite of the application of high-tech, emergence situations still occur, which is an inevitable consequence of the presence of a class of sudden failures. To prevent serious consequences of emergency situations, the equipment must be fitted up with systems that allow recognizing these situations at an early stage of failure occurrence, and perform an equipment shutdown. Recommendations on the integration into a flexible manufacturing system (FMS) of the adaptive subsystem for diagnostics of machining process in real time based on the measuring of a cutting force are proposed, intended to determine emergency situations and timely shutdown of the executive mechanisms of the processing equipment of FMS. © 2019 IEEE.

关键词： Flexible manufacturing systems

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Preprocessing Algorithms of Fuzzy Medical Data of Patient Examinations 21

Preprocessing Algorithms of Fuzzy Medical Data of Patient Ex...

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21st International conference on Complex Systems - control and Modeling Problems (CSCMP)

作者： Kolodenkova, Anna Novokshenov, Sergey Ketsko, Yuriy Samara State Tech Univ Inst Automat & IT Samara Russia Samara State Med Univ ICU Clin Univ Samara Russia

ISBN: (纸本)9781728167008

This research work proposes a novel algorithms of processing fuzzy data got while medical examinations of patients in the hospital. These algorithms are based on the use of a set of binary masks of a set of examination parameter states, classified by parameter sets for each type of medical examination. The amount of medical examinations for patient in a hospital differs by a more comprehensive set of examinations. And the amount of fuzzy data generated is significantly higher than in outpatient diagnostics. To solve problems associated with getting a clinical diagnosis, predicting the dynamics of a patient's clinical condition and the outcome of a patient's treatment based on medical screenings and examinations the specific algorithms are necessary both at the initial stage and during treatment. These algorithms are coding / decoding, classification and building of structured interconnected models and states of the diagnostic system throughout the entire patient treatment process. A diagnostic system is a set of methods, knowledge and algorithms for solving the problem of decision support in the clinical diagnostics of patients' diseases in a hospital or outpatient clinic. The methods and algorithms presented in the article allow pre-processing fuzzy data of medical examinations of patients in order to optimize and further use fuzzy cognitive models and artificial intelligence methods. Also a method for the classification of medical examination parameters is proposed for applying the proposed algorithms.

关键词： fuzzy data medical examination differential diagnostics processing algorithms fuzzy production rules

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An Object Segmentation Method for Railway Surrounding Environment Based on Three-dimensional Point Cloud

An Object Segmentation Method for Railway Surrounding Enviro...

引用

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

作者： Qixian Li Yong Qin Ping Chen Zhipeng Wang Xianbin Cao State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University School of Traffic and Transportation Beijing Jiaotong University Beijing China State Key Lab of Rail Traffic Control & Safety Beijing Jiaotong University Beijing China School of Electronic and Information Engineering Beihang University Beijing China

ISBN: (数字)9781728170503

ISBN: (纸本)9781728170510

The dramatic changes of railway surrounding environment seriously affect the railway operation safety, however the change detection mostly depends on human visual interpretation. For facilitating the change detection and reducing the human involvement, this paper proposed an automatic segmentation method for modeling railway surrounding environment using point cloud data and mainly focusing on simplifying the processing process and segmentation accuracy. Firstly, a process-based processing method is used, and only a few parameters need to be set to convert the original data to a specific model. Secondly, by analyzing the geometric and spatial features of various objects, a series of algorithms are selected to achieve the accurate segmentation of the target model. Finally, actual data along a section in Beijing-Langfang high-speed railway is used to verify the proposed method, and the results show that the method achieve a high-accuracy of segmentation.

关键词： Visualization Three-dimensional displays Object segmentation Rail transportation Data models Sensors Safety

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Fuzzy Reasoning in control and diagnostics of a Turbine Engine - A Case Study 18th

Fuzzy Reasoning in Control and Diagnostics of a Turbine Engi...

引用

18th International conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Rafajlowicz, Wojciech Domski, Wojciech Jablonski, Andrzej Ratajczak, Adam Tarnawski, Wojciech Zajda, Zbigniew Wroclaw Univ Sci & Technol Fac Elect Wroclaw Poland

ISBN: (纸本)9783030209124;9783030209117

The article presents selected cases of application of fuzzylogic techniques in technological process control. It presents the possibilities of supporting manufacturers of road machines for road drying with innovative solutions in the field of artificial intelligence. It presents an algorithmic approach to determine the quality (welfare) of the device, taking into account important process parameters, processed with the use of fuzzy-logic technique. The methodology for controlling the rotation of the turbine engine in the initial phase of its start-up is presented, using rules based on fuzzy logic. The results of the calculations are presented in a graphical form, friendly to interpretation by users and machine manufacturer. The article discusses the technical aspects of the TORGOS road machine control system, indicating the multifunctionality of the authors' controller and its software.

关键词： Soft computing Fuzzy-logic Industrial application

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Performance evaluation of CFB unit combustion system based on comprehensive economics and entropy weight method

Performance evaluation of CFB unit combustion system based o...

引用

2019 International conference on Sensing, diagnostics, Prognostics, and control, SDPC 2019

作者： Qin, Ce Gao, Mingming Zhang, Hongfu North China Electric Power University State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources School of Control and Computer Engineering Beijing China

ISBN: (纸本)9781728101996

performance evaluation method for the combustion system in the variable load process of circulating fluidized bed (CFB) unit based on the minimum variance control is proposed. Each operating parameter are initially weighted according to the dynamic economic index of the operating parameters, and entropy weight method is used to adjust the weights of operating parameter under different operating conditions. Then, the minimum variance index based on comprehensive economic and entropy weight method is proposed to evaluate the performance of the combustion system of CFB unit, which reduces the polarization effect generated by the single weighting performance evaluation method and improves the objective scientificality of the operating parameter weighting. Finally, a case study on the combustion system of a 300MW CFB unit reveals that the minimum variance index based on the comprehensive economy and entropy weight method can better evaluate the performance of the combustion system in the dynamic process of the unit, compared with the traditional performance evaluation method. It is of great significance to the operational safety and economy of CFB boiler units. © 2019 IEEE.

关键词： Economics

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Fault diagnosis method for fire control system based on empirical wavelet transform and relevance vector machine

Fault diagnosis method for fire control system based on empi...

引用

2019 International conference on Sensing, diagnostics, Prognostics, and control, SDPC 2019

作者： Li, Yingshun Li, Runhao Yi, Xiaojian Beijing Institute of Petrochemical Technology Beijing China China North Vehicle Research Institute Academy of Mathematics and Systems Science Chinese Academy of Sciences !!!School of Mechatronical Engineering Beijing China

ISBN: (数字)9781728101996

ISBN: (纸本)9781728101996

The fire control system is an extremely important part of the tank and directly determines whether the tank can accurately hit the target. In extremely sophisticated fire control system devices, the signals generated by faults are mostly non-stationary, nonlinear, multi-component complex signals. In order to improve the accuracy of fault diagnosis of fire control systems, it is necessary to analyze and process complex signals more accurately. In this paper, a fault diagnosis method for fire control system is proposed. The acquired signal is denoised and extracted by empirical wavelet transform (EWT). The extracted signal is sent to the trained relevance vector machine (RVM) model. To achieve fault diagnosis of the fire control system. © 2019 IEEE.

关键词： Wavelet transforms

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A Combined Support Vector Machine and Support Vector Representation Machine Method for Production control 18

A Combined Support Vector Machine and Support Vector Represe...

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18th European control conference (ECC)

作者： Acernese, Antonio Del Vecchio, Carmen Fenu, Gianfranco Glielmo, Luigi Pellegrino, Felice Andrea Univ Sannio Dept Engn Benevento Italy Univ Trieste Dept Engn & Architecture Trieste Italy

ISBN: (纸本)9783907144008

Machine learning techniques have been widely applied to production processes with the aim of improving product quality, supporting decision-making, or implementing process diagnostics. These techniques proved particularly useful in manufacturing industry where huge variety of heterogeneous data, related to different production processes, can be gathered and recorded but where traditional models fail due to the complexity of the production process. In this study, we describe a novel Machine Learning methodology to associate some product attributes (either defects or desirable qualities) to process parameters. Namely we combine Support Vector Machine (SVM) and the Support Vector Representation Machine (SVRM) to perform instance ranking. The combination of SVM and SVRM guarantees a high flexibility in modeling the decision surfaces (thanks to the kernels) while limiting overfitting (thanks to the principle of margin maximization). Thus, this method is well suited for modeling unknown, possibly complex relationships, that may not be captured by simple handcrafted models. We apply our method to production data of an investment casting industry placed in South Italy. We obtain an instance ranking that may be used to infer proper values of process parameter set-points.

关键词： Support vector machines

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