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Life Prediction Method of Equipment System Based on SVR-Wiener

Life Prediction Method of Equipment System Based on SVR-Wien...

引用

2021 IEEE International conference on Sensing, diagnostics, Prognostics, and control, SDPC 2021

作者： Yan, Bingrong Su, Yan Wang, Jinjun Wen, Tan State Key Laboratory of Smart Grid Protection and Control Nanjing China Nari Group Corporation Nanjing China Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Smart Grid Protection and Control Nanjing China Civil Aviation College Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9781665449762

Aiming at tlie cliaracteristics of liigli reliability, long-life equipment or newly developed equipment with a small number of failure degradation data samples, this paper proposes a method for predicting the remaining useful life of equipment systems based on the fusion of support vector regression (SVR) and drift Wiener process. Firstly, the distribution function of the drift Wiener process is transformed;then, a support vector regression machine method is introduced to establish an optimization model to estimate the parameters of the drift Wiener process, and a life prediction algorithm based on SVR and drift Wiener process is researched and established. Finally, a certain highly reliable and long-life cabin environment system is used as an example to carry out life prediction. The application shows that the method proposed in this paper has better prediction than the traditional maximum likelihood estimation method and moment estimation method in a small sample. © 2021 IEEE.

关键词： Forecasting

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Development of an Information System of Digital Twins of Aviation Electrical Equipment as a Software Module of the Local Load control Center 20

Development of an Information System of Digital Twins of Avi...

引用

20th Technical Scientific conference on Aviation Dedicated to the Memory of N.E. Zhukovsky, TSCZh 2023

作者： Starostin, Igor E. Khalyutin, Sergey P. Druzhinin, Alexei A. Gavrilenkov, Stanislav I. Moscow State Technical University of Civil Aviation Moscow Russia

ISBN: (纸本)9798350324075

diagnostics and real-time forecasting of the technical condition of aircraft electrical equipment plays a crucial role in the process of operation. In order to diagnose and predict the technical condition, it is reasonable to apply digital twin technology. The functioning of various components of aviation electrical equipment is determined by physical and chemical processes occurring in these objects. To model and analyze the dynamics of such processes, the authors have developed a method of mathematical prototyping of energy processes - a unified approach to building correct (not contradicting physical laws) models of processes of various nature. The equations derived by the method of mathematical prototyping make models with inputs containing measurable characteristics, and outputs containing controlled characteristics of the object. Such models are the mathematical basis of digital twins of aviation electrical equipment. Building of the mentioned mathematical models demands big computational expenses;hence there is a necessity of development of the programtechnological platform of digital twins, providing construction and storage of digital twins of aviation electrical equipment. The construction of digital twins is performed on the ground and the use of already constructed digital twins is performed on board the aircraft. The development of the concept of such a digital twin platform is the focus of this paper. © 2023 IEEE.

关键词： Construction equipment

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Improving the Winding Angle Measurement for an Effective process control

Improving the Winding Angle Measurement for an Effective Pro...

引用

IEEE Instrumentation and Measurement Technology conference

作者： Giulio D'Emilia Luciano Chiominto Emanuela Natale Antonios Stamopoulos Department of Industrial and Information Engineering and Economics University of L’Aquila L'Aquila Italy

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Two vision systems are developed to inspect the winding angle of a filament wound carbon fiber and epoxy resin composite cylinder. The first used system relay on a high-resolution color camera. The second vision system is based on a commercial polarization and exploits the polarization information to process the image. A component inspection strategy is proposed, and the metrological performances are experimentally and carefully evaluated. Using the polarization camera variability of data concerning the winding angle is reduced to the order of 0.5°, promising for a better process control and diagnostics and reducing the probability of voids and defects, which are related to the correspondence of the winding angle to the nominal one. This way the reliability of the pieces realized with composite material, which is a mandatory requirement for this kind of component, could be improved. It also results that the additional computational load is negligible making the polarization camera inspection suitable for an online use.

关键词： Optical fiber polarization Image color analysis Machine vision Shape measurement Windings process control Inspection

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Intelligent Support Systems for NPP Operators: Dynamic Modeling and Operational diagnostics

Intelligent Support Systems for NPP Operators: Dynamic Model...

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

作者： Elena Jharko Kirill Chernyshov Laboratory of Distributed Information and Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia Laboratory of Identification of Control Systems V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Moscow Russia

The efficiency of human-machine interaction is highly dependent on the quality of information support that the power unit (PU) operators receive from the control system in different operating modes of NPP PU. The paper shows the importance of intelligent support systems (ISS) for NPP operators to ensure the reliable operation of the NPP power unit. The most significant elements of the ISS for operators in terms of the diagnostic system are the block of dynamic modeling, which anticipates the course of technological processes, and the expert system. The paper analyzes the state of the problem of creating dynamic modeling systems, singles out a "three-step" approach to creating the predictive models of a technological process, and shows its shortcomings. Relationships between dynamic modeling and operational diagnostics (OD) are presented. A group of standard diagnostic systems and classes of problems of the solvable problems of ODs are considered. The implementation of the solution to the problem of diagnosing in the intelligent support system of the NPP operator, as well as functional diagrams of operational diagnostics, is presented. The proposed implementation of the tasks of operational diagnostics is used to create intelligent support systems for NPP operators.

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Methods and equipment for analysis and diagnostics of marine engines 8

Methods and equipment for analysis and diagnostics of marine...

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8th International conference on Smart and Sustainable Technologies, SpliTech 2023

作者： Vrvilo, Petar Vidović, Tino Matulić, Nikola Roldo, Liane Radica, Gojmir University of Split Faculty of Marine Studies Split Croatia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia

ISBN: (纸本)9789532901283

Monitoring the operation of the ship's systems, especially the main engine, has always been carried out by the ship's crew, whose reports were often not considered in a timely manner, resulting in engine and equipment failures. Technological development has enabled much more complex and faster monitoring of engine operation, especially with electronically controlled engines. Complex and fast monitoring using new technologies enables the recording of a large number of parameters in real time and their distribution to competent experts who do not necessarily have to stay on board but can be informed and active from the office on land. Analysis of parameters in real time enables an immediate reaction to anomalies, and timely intervention in order to prevent failure, i.e. increase the percentage of airworthiness of the ship during its working life. The paper explains the key components of a modern surveillance system and describes the process of analyzing remotely collected data. © 2023 University of Split, FESB.

关键词： Ships

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Generalized Input-Output Hidden-Markov-Models for Supervising Industrial processes 3

Generalized Input-Output Hidden-Markov-Models for Supervisin...

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3rd International conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Chasparis, Georgios C. Luftensteiner, Sabrina Mayr, Michael Software Competence Ctr Hagenberg GmbH Softwarepk 32a A-4232 Hagenberg Austria

Often in industrial processes, batches of material are processed sequentially and repeatedly through a deterministic sequence of process steps. The possibly large number of sensor measurements collected throughout such industrial processes require supervisory modeling techniques that allow for characterizing the operating conditions (or states) of these process steps. This would allow for inference and predictions over the operating conditions of the current and upcoming process steps (e.g., abnormal behavior, failures, etc.) which may significantly assist the operators of the process. Traditionally, such inference questions in repeated processes can be handled in a rather straightforward manner via Input-Output Hidden Markov Models (IOHMM). However, standard IOHMM are limited to repeated and identical processes, while industrial processes may comprise multiple non-identical process steps and possibly with non-standard interdependencies between process steps. For this reason, in this paper we propose a generalization of standard IOHMM that is more appropriate for modeling industrial processes. Furthermore, we derive the update recursions for training such models and we show analytically that such update recursions guarantee an increase in the likelihood of the observation sequences. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： Input-Output Hidden Markov Models Industrial processes diagnostics Supervisory control Inference

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Anomaly Detection in Centrifugal Pumps Using Model Based Approach 8

Anomaly Detection in Centrifugal Pumps Using Model Based App...

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8th International conference on Advanced Computing and Communication Systems, ICACCS 2022

作者： Kumar, Swetha R Iniyal, U.S. Harshitha, V. Abinaya, M. Janani, J. Jayaprasanth, D. Psg College of Technology Department of Instrumentation and Control Systems Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9781665408165

In today's society, technological breakthroughs have led to the automation of most industries in order to ensure smooth operations and minimize human interaction. The automation has led to challenges in an important sector called Fault detection and diagnosis. Rather than univariate alerts, fault detection and diagnostics focus on abnormal situations, which is crucial for maintaining optimum operating conditions and anticipating chemical process hazards. Model-based and process history-based fault detection and diagnosis are the two types of fault detection and diagnosis, with the second being more commonly referred to as data-based. Model-based methods are often based on a fundamental grasp of the process's physics. Using a model-based approach, this paper tries to estimate and identify the types of problems in centrifugal pumps. The pump dynamics are estimated using a system identification approach in this paper. The outcomes of the model estimations are then summarized. Estimated and real values are compared while creating residues. Studies are carried out to look into the consequences in both faultless and faulty situations. © 2022 IEEE.

关键词： Fault detection

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Simple neuro-fuzzy system with combined learning for pattern recognition under conditions of short training set in medical diagnostics tasks 5

Simple neuro-fuzzy system with combined learning for pattern...

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5th International conference on Informatics and Data-Driven Medicine (IDDM)

作者： Bodyanskiy, Yevgeniy Chala, Olha Izonin, Ivan Popov, Sergiy Our Lady Immaculate Concept Inst Theol Studies Gorodok Khemlnytska Obl Ukraine Kharkiv Natl Univ Radio Elect Dept Artificial Intelligence Kharkiv Ukraine Lviv Polytechn Natl Univ Dept Artificial Intelligence Lvov Ukraine Kharkiv Natl Univ Radio Elect Control Syst Res Lab Kharkiv Ukraine

There is a widespread problem in the medical diagnostic tasks of the training datasets deficit. The medical data is hard to clinically collect and process into the ready-to-use dataset for supervised learning leading to difficulties in achieving computer-aided detection and diagnosis. The traditional approaches can works with big enough training datasets, however, thay cannot show their efficiency under conditions of limited number of samples. We propose a system that combines various learning paradigms and a neuro-fuzzy approach to solve medical classification problems under conditions of a limited number of training observations-images. The distinctive feature of the proposed system is the usage of the "scatter partitioning" of input space, which provides better system performance both in learning and classification. The results of the computer experiment proved the effectiveness of the proposed system in solving image recognition in the medical diagnostic task. The computational experiment showed that the proposed model works better with limited training datasets than the advanced systems, however, the proposed one yields with bigger amount of training observations.

关键词： Neuro-fuzzy system combined learning medical diagnostics short training set overlapping classes

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diagnostics of the STATE and RECOVERY of REAL TIME SYSTEMS PERFORMANCE 6

DIAGNOSTICS of the STATE and RECOVERY of REAL TIME SYSTEMS P...

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6th International conference on Future Networks and Distributed Systems, ICFNDS 2022

作者： Abidov, Abdujabbar Department of Digital Economy and Information Technologies Tashkent State University of Economics Uzbekistan

ISBN: (纸本)9781450399050

The issues of improving the operational reliability of the software of the adaptive switching node operating in a real-time system (r.t.s.) are considered in this paper. Methods for detecting errors, diagnosing the state of health, and methods for restoring the readiness of systems are analyzed. Redundancy is used to ensure the reliable functioning of the software of real-time systems. Of the three types of redundancy: temporal, informational, software;the paper pays great attention to temporal redundancy. Which consists in the presence of a reserve time exceeding the minimum necessary for the execution of the program with the control and restoration of the computational process in case of a possible error. Issues of diagnosing (testing) software products are touched upon and recommendations are made on the use of the considered methods of software reliability for real-time systems. © 2022 ACM.

关键词： Real time systems

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Spinal Vision CNN-Driven Techniques for Accurate Stenosis Detection

Spinal Vision CNN-Driven Techniques for Accurate Stenosis De...

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International conference on ent Computing and control Systems (ICICCS)

作者： Jenish M J. Praveen Chandar Division of Artificial Intelligence and Machine Learning Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

The need for accurate and efficient detection method of spinal stenosis, a condition that involves the narrowing of the spaces in the spine, so as to avoid serious complications. In this project, SPINAL VISION, we present a deep learn based model with Convolutional Neural Nets (CNNs) to improve spinal stenosis detection accuracy. Based on the advanced image preprocessing and image classification techniques, the system achieves high diagnostic precision and sensitivity for reliable identification of stenotic regions within spinal imaging. This proposed methodology is faster and more accurate than traditional diagnostics leading to early intervention and better patient outcomes. Future work will integrate multimodal data and further investigate the interpretability of models for clinical applicability.

关键词： Deep learning Accuracy Sensitivity Spine process control Streaming media Predictive models Convolutional neural networks Reliability Biomedical imaging

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