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

共 1528 条记录，以下是21-30 订阅

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process monitoring during interaction of laser with AlMg5 and Ti6Al4V alloys using spectroscopy and high-speed imaging for laser manufacturing 13

Process monitoring during interaction of laser with AlMg5 an...

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conference on High-Power Laser Materials processing - Applications, diagnostics, and Systems XIII

作者： Mohanta, Antaryami Al Ameri, Reem Leparoux, Marc Matras, Guillaume Kasmi, Chaouki Technol Innovat Inst Directed Energy Res Ctr Abu Dhabi U Arab Emirates Empa Swiss Fed Labs Mat Sci & Technol Lab Adv Mat Proc Feuerwerkerstr 39 CH-3602 Thun Switzerland

ISBN: (纸本)9781510670174;9781510670167

Laser manufacturing of aluminum and titanium alloys is gaining interest in the automotive, aerospace, and defense industries due to their diverse applications. Laser interaction with these alloys involves heating, melting, and evaporation, with evaporation being critical. Selective vaporization of low-melting-point constituents in multi-element alloys can affect stoichiometry. In-situ monitoring of the ejected plume helps control product quality. Optical emission spectroscopy (OES) characterizes plume constituents and provides information about excited states. Our study used high-speed imaging and OES to monitor the laser interaction process with AlMg5 and Ti6Al4V alloys. OES analysis revealed a higher rate of magnesium evaporation compared to aluminum, a trend that intensified with an increase in laser power and a decrease in speed. High-speed imaging revealed an increase in spatter and laser-plume interaction with increased laser power and decreased speed. In-situ monitoring during single-shot laser interactions was conducted in a controlled manner with and without Ar gas shielding. The detection of oxidation in the absence of shielding gas through OES analysis highlights its potential for process monitoring.

关键词： AlMg5 Optical emission spectroscopy Laser manufacturing Laser welding High-speed imaging

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Proposta de Template para Proteção e controle aplicado a IEDs de uma Subestação de 230 kV 15

Proposta de Template para Proteção e Controle aplicado a I...

引用

15th IEEE International conference on Industry Applications, INDUSCON 2023

作者： Dornelas, Marcos V.R. Coelhos, Aurélio L.M. Cast Group - Logix Itabira Brazil Instituto de Ciências Tecnológicas Unifei Campus de Itabira Itabira Brazil

ISBN: (纸本)9798350314182

In order to be reliable, safe, selective, and high speed, protection systems have evolved quite significantly. Protection relays, now called intelligent electronic devices (IEDs), are the main elements of these systems and currently encompass not only protection functions but also bring advantages to the entire automation process within a substation, such as control and supervision. In this sense, this paper presents a proposal of auto diagnostics and monitoring template applied to IEDs of a 230 kV substation. To achieve this, analysis of the existing protection, control, monitoring and structures for input circuit breakers, feeders and busbar interconnection are inserted. This proposal explores the latest in terms of the features available in benchtop IED. The main results obtained are presented as a future proposal for improvement and standardization of control, diagnostics, monitoring, protection, and communication logic. © 2023 IEEE.

关键词： Capability control IED IHM Relay Signaling Template

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Joint quality assessment by machine learning using characterized surface thermal radiation images of laser welding process 13

Joint quality assessment by machine learning using character...

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conference on High-Power Laser Materials processing - Applications, diagnostics, and Systems XIII

作者： Kikuchi, T. Takabatake, R. Katayama, K. Ikenoue, H. Nakamura, D. Kyushu Univ Grad Sch ISEE 744 MotookaNishi Ku Fukuoka Fukuoka Japan Kyushu Univ Dept TAMARI Engn 744 MotookaNishi Ku Fukuoka Fukuoka 8190395 Japan Kochi Univ Tech 185 MiyanokuchiTosayamada Kami City Kochi 7828502 Japan

ISBN: (纸本)9781510670174;9781510670167

In recent years, laser welding has been widely used as an alternative to arc welding because of its high power and faster welding speed with local heating. In the welding process, particularly for e-mobility applications, the demand for quality control via all-point inspection is increasing. The laser process enables real-time observation of the welding area during processing, making all-point inspection possible. In this study, we investigated the possibility of predicting weld bead width from a set of images acquired using a CMOS camera with a band-pass filter. Machine learning was used for the prediction, and the prediction accuracy was determined using the root mean squared error (RMSE). The laser parameters, such as irradiation power and scan speed, and 13 feature values, such as the area, centroid, and rotation angle of the light emission acquired from the images and were used as training data. The RMSE of 0.16 mm was achieved for a bead width of 0.5-1.5 mm, confirming that the prediction was sufficiently accurate. Furthermore, we conducted an analysis with and without spectroscopic images to verify whether spectroscopic images are effective for the evaluation of laser welding using machine learning.

关键词： Laser welding Machine learning Image processing Radiant luminescence Quality diagnosis

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Possibilities of Using of Online Vehicle diagnostics in the Future 4th

Possibilities of Using of Online Vehicle Diagnostics in the ...

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4th International conference on Vehicle and Automotive Engineering (VAE)

作者： Nagy, Jozsef Lakatos, Istvan AUDI HUNGARIA Zrt Corp Qual Vehicle Technol Funct Geometry Audi Hungaria Ut 1 H-9027 Gyor Hungary Szechenyi Istvan Univ Fac Mech Engn Informat & Elect Engn Dept Rd & Rail Vehicles Egyet Ter 1 H-9026 Gyor Hungary

ISBN: (纸本)9783031152115;9783031152108

In the premium vehicle category, real-time online internet connection has become a standard in recent years. This trend is likely to spread completely in the automotive industry in the coming years. This fact offers a lot of new options in the field of vehicle maintenance (and predictive maintenance). Another possible use case may be remote diagnostics of in-use vehicles on the market, analysis of their online data and thereby an extension of the product development process after SOP. An additional new option may be to automatically collect, evaluate and generate of onboard diagnostics data to report to different authorities. E.g. OBFCM (onboard fuel consumption) or IUMPR j3 (in use monitoring performance ratio) field reports. In vehicle production, during the test drive, it could be possible to read and log of measurement data of the finished vehicle's control units online Another application may be to test vehicles online during the production process e.g. to read of DTC's (diagnostics trouble codes) during technical tests or to monitor of SoC (state of charge) of battery online while moving vehicles within the factory.

关键词： Online OBD Online vehicle analysis Online data logging on customer's vehicles Predictive maintenance Online transferred OBFCM/IUMPR reports Online in-production vehicle analysis

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Analysis of Blood Smear Microscopic Images Using ML: DL 2nd

Analysis of Blood Smear Microscopic Images Using ML: DL

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2nd International conference on Advances in Computing Research-ACR

作者： Mansouri, Hadia Benzarti, Faouzi Univ Tunis El Manar Univ Campus Farhat Hached ElManar Natl Sch Engn Tunis SITI Lab Tunis Tunisia Univ Tunis High Natl Sch Engn Tunis Natl Sch Engn Tunis SITI Lab Tunis Tunisia

ISBN: (纸本)9783031569494;9783031569500

Emerging AI technology intersects with several techniques simulating human cognitive processes that rely on creating algorithms that run in a dynamic computing environment. It is essential to put in place adequate tools of human intelligence. In this context, Machine Learning (ML) is becoming a real revolution that has greatly contributed to the generalization of AI. In principle, ML refers to a set of many methods aimed at automatically creating models from data. It allows computers to learn without being explicitly programmed to do so. Currently, ML occupies a growing interest in various field, such as: autonomous cars, smart cities, automatic checkouts, personal assistants, algorithmic finance, industrial robots, video games, medical diagnostics, scanners, etc. However, Our work focuses on the development of various machine learning techniques in application control especially medical process applications. The main objective is to implement a method for analyzing microscopic images of blood cells to fulfill tasks and facilitate human activity. More fundamentally, we developed a learning model to accelerate the process of diagnosing and detecting diseases with an accuracy rate that could exceed that of humans. Such analysis can be time-consuming and generate incorrect results for large-scale diagnostics. The process contains two essential phases: identification and classification of blood cells for the diagnosis and the prediction of certain abnormalities. First, we use convolution neural network CNN to extract blood image features and ML methods such as KNN, SVM, Bayes, for classification. Therefore, ML can help improve the performance, predictability, and accuracy of diagnostic systems for many diseases.

关键词： AI ML blood cells medical diagnostic process ML techniques blood disease detection

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Development of a Digital Twin for control and diagnostics of the Gas Transport process 5

Development of a Digital Twin for Control and Diagnostics of...

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5th International conference on control in Technical Systems, CTS 2023

作者： Korablev, Juri A. Saint-Petersburg Electrotechnical University 'LETI' Saint-Petersburg Russia

ISBN: (纸本)9798350304664

The 'digital twin' technology fits well into the ideology of building intelligent fault-tolerant control systems. The technology is based on the premise that for each system it is possible to create a representation in the form of two systems -physical and virtual, including all information about the physical system. In this case, a constant 'mirror image' occurs: the virtual system 'displays' the real one, and vice versa. The basis of the digital twin in this report is the SIMULINK model of a technical system, updated by data received from a real object. When modeling based on the SIMULINK model, the tasks of diagnostics and fault tolerance are solved in parallel with the operation of a real object. The results of solving these problems -fault diagnoses and parameters of reconfiguration / restructuring of regulators -are transferred from the virtual environment of the digital twin to the real object. Another important task solved within the framework of the 'digital twin' technology is forecasting. In the context of this work, we are talking about solving the problem of predicting the occurrence of faults. To predict the occurrence of malfunctions and, accordingly, early detection of potential equipment failure, it is necessary to calculate the degradation function of equipment characteristics in real time, determine and correct the residual life. As a result, there is a reserve of time for repair and maintenance work at a minimum cost and without downtime. © 2023 IEEE.

关键词： Fault tolerance

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Detection of control Valve Diagnosis and Pipeline Using Machine Learning 4

Detection of Control Valve Diagnosis and Pipeline Using Mach...

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4th International conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Selvakarthi, D. Hakeem, A. Abdul Akilesh, D. Dharshini, S. Amjath, M. Mohamed Kongu Engineering College Department of Electronics and Instrumentation Engineering Perundurai Tamilnadu Erode638060 India

ISBN: (纸本)9798331529635

Machine learning has the potential for transforming the workplace across various industries. It can streamline repetitive tasks, improve decisionmaking, enhance safety, and increase operational efficiency. Rather than relying on static images from multiple angles to train object detection models, using video footage can simplify the process and reduce the need for large image datasets. Amazon Rekognition, a service from Amazon Web Services (AWS), leverages deep learning algorithms to analyze both images and videos. Its features include facial recognition, object detection and tracking, text recognition, and content moderation. In this project, AWS Rekognition is utilized to assess control valves and detect pipeline leaks. It also distinguishes between different types of control valves, such as normally open, normally closed, and those with positioners. This approach illustrates the effectiveness of video-based learning for object detection and the utility of cloud-based AI services in industrial diagnostics and monitoring. © 2024 IEEE.

关键词： Safety valves

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Application of Air Gap Sensor for Improved Fault Detection and diagnostics Tools for Hydrogenerators Condition Monitoring Systems 4

Application of Air Gap Sensor for Improved Fault Detection a...

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4th IEEE KhPI Week on Advanced Technology, KhPI Week 2023

作者： Zaitsev, Ievgen Levytskyi, Anatolii Bereznychenko, Viktoriia Zakusilo, Sergy Rassovskyi, Vadim Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment Department №12 The Institute of Electrodynamics The NAS of Ukraine Kiev Ukraine Chief Engineer's Department PJSC "Ukrhydroenergo" Vyshgorod Kyiv Ukraine

ISBN: (纸本)9798350395532

In the paper a present results, which are devoted to the system of monitoring the technical condition and the process of detecting defects of the hydrogenerator based on the control of mechanical defects with air gap sensor. A description of the operation of defect identification tools based on the identification of their characteristics is given. Application of the methods is impossible without the construction of appropriate mathematical models that reflect in detail the main physical processes occurring in the power equipment or in its separate structural unit. The structure of the technical condition control system with additional air gap sensors is given. The development of an air gap sensor for the control system is considered. The use of air gap sensors in the structure of the control system for measuring the parameters of mechanical defects, which allows detecting machine defects at an earlier stage of their development. © 2023 IEEE.

关键词： Condition monitoring

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The Development of Software Solutions for Diagnosis Railway control Systems 27

The Development of Software Solutions for Diagnosis Railway ...

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27th International Scientific conference on Transport Means 2023

作者： Nowakowski, W. Ciszewski, T. Kazimierz Pulaski University of Technology and Humanities in Radom Malczewskiego 29 Radom26-600 Poland

ISBN: (纸本)9781713879534

The task of rail transport, which is a branch of land transport, is to move people and loads using rail transport. Due to the fact that rail traffic control systems belong to the group of safety-critical systems they are required to ensure an appropriate level of reliability and availability. In order to accomplish this task, technical diagnostics is used to which allows railway infrastructure managers to maintain used devices in a state of functional operability. The development of railway traffic control systems is associated with the use of modern information and communications technologies in the process of their construction, which allows to expand the diagnostic functions implemented by them. The development of software solutions for railway control systems diagnosis was presented in the paper. © 2023 Kaunas University of Technology. All rights reserved.

关键词： Railroads

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Quality and physical properties revealed: sensors for monitoring and controlling laser processes in combination with sophisticated data models 12

Quality and physical properties revealed: sensors for monito...

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conference on High-Power Laser Materials processing - Applications, diagnostics, and Systems XII

作者： Kogel-Hollacher, Markus Reiser, Jens Moser, Sebastian Mack, Fabian Schwarz, Joachim Precitec GmbH & Co KG Draisstr 1 D-76571 Gaggenau Germany Precitec Inc 28043 Ctr Oaks Ct Wixom MI 48393 USA Precitec GmbH & Co KG Kaiserstr 158 D-76133 Karlsruhe Germany Precitec Vis GmbH & Co KG Rotfarb 4 CH-8413 Neftenbach Switzerland

ISBN: (纸本)9781510659339;9781510659346

There are many distinct commercial sensor systems for monitoring or controlling laser processes. Most of them are based on camera or photodiode technology. Furthermore, the introduction of real in-process measuring systems in laser material processing like OCT has significantly increased the safety of both defect detection and process control [5][6][7][8][9]. The focus of this contribution, however, relates to the use of artificial intelligence algorithms to "See New Things". We will discuss how classified, physical properties can be derived from already reliable process information - "seeing the unseen", so to speak. Instead of defining complex rules for algorithms, the use of Data Science and Machine Learning methods reveals hidden structures in noisy unstructured data and make it possible to find the relationships of the data to the physical measurement. There are several systems available in the market which capture or measure and analyze physical effects of the process zone and their properties during the laser processing, but none of these effects and properties stand for "seam quality" for themselves, which is typically defined by mechanical, geometrical and metallurgical properties of the solidified seam. The process properties like emitted visible and thermal radiation or geometrical values of the melt pool or the penetration depth of the laser forming the keyhole (penetration depth) only provide indications of how the desired quality might be achieved. When welding thousands of seams per shift during serial production for Li-Ion batteries in e-mobiles, very often users would like to stop their fully automatic machines once the laser process is suddenly running out of previously set boundaries. Such an approach allows users to find systematic faults where and when they occur, rather than at the end of the line where quality inspection takes place and the line is still running, producing more and more parts with the same faults. When it comes to the use of a

关键词： Artificial intelligence Machine learning process monitoring process control Sensor technology OCT

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