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Analysis of Scanning Schemes of Complex-Profile Products with Automated Complex Non-Destructive Quality control of Coating of Complex-Profile Product 7

Analysis of Scanning Schemes of Complex-Profile Products wit...

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7th International Conference on Information, control, and Communication Technologies, ICCT 2023

作者： Gubin, Maksim S. Malyy, Valeriy V. Fedorov, Alexey V. Kinzhagulov, Igor Y. Sergeev, Dmitriy S. Itmo University Faculty of Control Systems and Robotics ST Petersburg Russia The Institute of Science of the Icc Sect ST Petersburg Russia

ISBN: (纸本)9798350340945

In this paper, the existing problems of non-destructive testing of defects in the surface and subsurface coating layers of complex profile products are considered. The main factors influencing the choice of the scanning scheme are determined. For the implementation of non-destructive testing, several scanning schemes were proposed, which were analyzed in order to determine the necessary trajectory and step of movement of the transducer relative to the surface of a complex profile product. As a result, an optimal scanning scheme was selected. © 2023 IEEE.

关键词： Coatings

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Structural simulation of devices based on patent descriptions

International Journal of Systematic Innovation

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International Journal of Systematic Innovation 2023年第5期7卷 1-9页

作者： Bushuev, Alexandr Chepinskiy, Sergey Lin, Weijie Zhang, Botao Wang, Jian Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russian Federation School of Automation Hangzhou Dianzi University Hangzhou China HDU-ITMO Joint Institute Hangzhou Dianzi University Hangzhou China

The problem of the interaction of patent law and TRIZ is considered in this paper. A su-field analysis is applied from TRIZ tools. The European claim of the invention is used to describe the device. The claim is divided into technical features for structural simulation. Binary relationships are introduced between features to build hierarchy levels. As a result, an oriented graph is obtained, the nodes of which are features, and the branches show the subordination of features. The elements are at the top level, and the connections between them are at the middle level. The properties of elements and links are at the lower level. The physical operating principle of the device from the patent description is used for the numerical evaluation of the structure. At the middle level of the hierarchy, features of interaction between elements are replaced by mechanical, thermal, electric, and magnetic fields from the Su-field analysis. Further, the inventive fields are replaced by the dimensions of the physical quantities in which the fields are measured. For example, the dimensions of ampere, volt, watt, and coulomb are used for electric fields, depending on the specific design of the device. The dimensions of physical quantities are given in the Bartini basis with two basic units time T and space L. Two-dimensional diagonal matrices are introduced to describe the weights of graph branches. A weighted and oriented graph mathematically describes the structure of the claim. The purpose of the simulation is to calculate the resource intensity of the claim structure, as well as a numerical comparison of the novelty of the claims with the prototype. The novelty coefficient is determined by the degree of asymmetry of the new solution and the prototype. The symmetric part is the inventive features included in the restrictive part of the claims. The inventive features included in the characteristic part form the asymmetry of the claims. © 2023, International Journal of Systematic Inn

关键词： claims in the invention novelty simulation Su-field analysis

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Adaptive control of an Uncertain Differential Drive Robot 8

Adaptive Control of an Uncertain Differential Drive Robot

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8th International Conference on control Science and systems Engineering, ICCSSE 2022

作者： Chen, Zhiqiang Liao, Duzhesheng Krasnov, Aleksandr Y. Itmo University Faculty of Control Systems and Robotics St. Petersburg Russia

ISBN: (纸本)9781665484138

This paper proposes an adaptive trajectory tracking control scheme for differentially driven robots in the state of unknown kinematic and dynamic model parameters and uncertain external disturbances. The main idea is to design an adaptive controller to reduce the influence of unknown dynamic parameters and unknown parameters of the kinematic model. A kinematic controller is first designed to generate virtual velocities as reference inputs for dynamic control systems. The kinematic controller is then designed so that the actual velocity tracks the virtual velocity asymptotically. The robot can reach the expected speed and let the attitude error converge quickly. This approach enables the robot to quickly follow the desired trajectory. Finally, the effectiveness of the method is proved by MATLAB simulation. © 2022 IEEE.

关键词： Robots

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Application of Machine Learning Methods for Production Data Analysis

Application of Machine Learning Methods for Production Data ...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Igor Volkov Yuri Andreev Faculty of Control Systems and Robotics ITMO University Saint- Petersburg Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Ensuring the quality of CNC-machined parts is a challenging task in modern manufacturing due to frequent shifts in production conditions and the high costs of traditional inspection methods. In this study, we propose a data-driven approach that integrates machine learning (ML) models with statistical acceptance sampling to dynamically optimize quality control processes. Production data from ERP, MES, and IIoT systems were analyzed with Gradient Boosting model. By continuously retraining the model on newly completed batches, the system adapts to evolving conditions, maintaining predictive accuracy. A key innovation of this work is the timely adjustment of sampling parameters (e.g., sample size, acceptance number) according to predicted defect levels. This adaptive strategy conserves inspection resources when defect risks are low and intensifies monitoring when risks are high. The results demonstrate a marked reduction in inspection costs and a robust capacity to detect defects promptly, aligning with industry goals of minimizing scrap and rework. Overall, this study validates the effectiveness of applying machine learning methods to production data analysis, laying a foundation for future enhancements in adaptive, proactive quality control systems.

关键词： Industries Adaptation models Technological innovation Data analysis Costs Process control Production Quality control Inspection Predictive models

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Fault Detection in Electric Drives Based on LSTM Autoencoder Model Machine Learning Approach 25

Fault Detection in Electric Drives Based on LSTM Autoencoder...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Demidova, Galina Privalov, Daniil Semenov, Denis Lukichev, Dmitry Liu, Zhitao Anuchin, Alecksey Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Electric Drives Moscow Power Engineering Institute Moscow Russia

ISBN: (纸本)9798350389234

Fault detection in electric drives is crucial for ensuring operational reliability and minimizing downtime. This paper provides a brief overview of the methods based on machine learning used for fault detection in electric drives. Additional this research presents a machine learning approach that utilizes the Long Short-Term Memory Autoencoder model for fault detection deal with bearing faults. A flowchart illustrating the implementation steps of the Long Short-Term Memory Autoencoder algorithm is included. Additionally, a case study on bearing faults in an electric drive system is presented to demonstrate the advantage of the proposed approach. By training the Long Short-Term Memory Autoencoder on operational data, accurate prediction of bearing faults is achieved, enabling timely maintenance interventions. It is shown that in the 7th epoch of training, the model achieved a notably high accuracy more than 99%. The results highlight the potential of Long Short-Term Memory Autoencoder models as a valuable tool for fault detection in electric drives, thereby improving system reliability and performance. © 2024 IEEE.

关键词： Machine learning

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Assessment of the Reliability of Technologies Introduced Into Production by Accuracy Parameters

Assessment of the Reliability of Technologies Introduced Int...

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13th International Conference on Modern Mechanical Engineering: Science and Education, MMESE 2024

作者： Ermakov, Sergey P. Pompeev, Kirill P. Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia

ISBN: (纸本)9783031820823

The paper discusses the development of a methodology for assessing the reliability of TPs introduced into production to ensure a given accuracy and, based on it, an algorithm for the accuracy assessment of existing TPs. They were tested using the example of factory technological processes, which confirmed the adequacy of the proposed methodology and the operability of the created algorithm, and also made it possible to identify the shortcomings of these technologies and errors made by the technologist, in particular, when developing the technology for manufacturing a prismatic part, for which appropriate recommendations were given. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Accuracy parameters Algorithm Dimensional analysis Methodology TP reliability

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Water Indicator Measurement and Data Processing From Internet of Things Modules

Water Indicator Measurement and Data Processing From Interne...

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2024 International Conference on Electrical Engineering and Photonics, EExPolytech 2024

作者： Altay, Yeldos A. Bazarbay, Lashin Uskenbayeva, Raisa K. Fedorov, Alexey V. Kalpeyeva, Zhuldyz B. Satbayev University Department of Robotics and Technical Means of Automation Almaty Kazakhstan Satbayev University Almaty Kazakhstan Itmo University Faculty of Control Systems and Robotics Saint-Petersburg Russia Satbayev University Institute of Automation and Information Technologies Almaty Kazakhstan

ISBN: (纸本)9798350388879

This article presents the results of the implementation of a measuring system based on an IoT module for remote transmission of aggregate measurement data obtained during analytical monitoring of five water parameters via a wireless communication channel. A model of an experimental setup is presented and discussed, demonstrating the operability and consistency of the model for monitoring physical parameters during aggregate measurements. The obtained results of remote data transmission via a wireless communication channel revealed a statistically significant correlation between spring water parameters and the most influential predictor of acidity, conductivity, turbidity and oxidation-reduction potential is water temperature. The discovered relationship between the measured parameters is mainly associated with the effect of temperature on the processes occurring with an increase and decrease in the temperature of the analyzed water samples. © 2024 IEEE.

关键词： Data transfer

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Signal Processing for Acoustic Emission Signature Analysis and Defect Detection 26

Signal Processing for Acoustic Emission Signature Analysis a...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Altay, Yeldos A. Kuzivanov, Dmitry O. Altay, Dinara A. Fedorov, Alexey V. Satbayev University Department of Robotics and Technical Means of Automation Almaty Kazakhstan ITMO University Faculty of Control Systems and Robotics Saint-Petersburg Russia Military Engineering Institute of Radio Electronics and Communications Department of Natural Sciences Almaty Kazakhstan

ISBN: (纸本)9798350361728

This article presents the results of implementing a digital signal processing method for analyzing the acoustic emission (AE) signature and detecting defects such as cracks and pores. The signal processing method is based on a cascade connection of digital high-pass filters and ensures the selection of informative signals and increases the signal-to-interference ratio. In order to control the formation of defects in the process of selective laser melting, the paper presents the results of experimental testing of the cascade filtration method for detecting defects in the internal structure such as cracks and pores. The signal components recorded during the development of defects during the growth of additive manufacturing products were extracted. AE signatures were analyzed and statistical relationships were assessed. The relationship between the parameters of the AE signal and the values of laser radiation power has been identified, which characterizes the process of defect formation. © 2024 IEEE.

关键词： High pass filters

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Optimization of Cylindrical Blades for Wind Turbine Based on Magnus Effect

Optimization of Cylindrical Blades for Wind Turbine Based on...

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2023 International Conference on Electromechanical and Energy systems, SIELMEN 2023

作者： Lukin, Aleksandr Demidova, Galina Lukichev, Dmitry Poliakov, Nikolai Anuchin, Alecksey ITMO University Faculty of Control Systems and Robotics Saint-Petersburg Russia Moscow Power Engineering Institute Electric Drives Department Moscow Russia

ISBN: (纸本)9798350315240

Wind turbines based on the Magnus effect open new prospects in terms of energy generation for areas with low average wind speeds. The main feature of these turbines is rotating cylinders which are used to create lift instead of blades. Due to this unconventional design, different parameters of the cylinder, such as mass and moment of inertia, can greatly affect the dynamic characteristics of such energy systems. The goal of this paper was to present an approach to structural optimization of a cylinder flange of the experimental Magnus effect-based wind turbine. The proposed approach, presented as an algorithm, allows us to determine input data for the preferred structural optimization software and achieve lightweight, low-inertia parts. control simulation has shown that optimized parts ensure a high enough factor of safety while also significantly reducing the moment of inertia. © 2023 IEEE.

关键词： Finite element method

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Model Predictive control for systems with Limited State Variables

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Russian Electrical Engineering 2023年第2期94卷 77-83页

作者： Bogdanov, A.N. Anuchin, A.S. Demidova, G.L. Department of Electric Drive Moscow Power Engineering Institute Moscow111250 Russia Faculty of Control System and Robotics ITMO University St. Petersburg197101 Russia

Abstract: Model predictive control are actively used in industry in high-power electric drives, in which it is permissible to use expensive programmable logic matrices that provide calculations with a prediction horizon of up to ten epochs and a forecast tree of several million variants. However, the computing power of microcontrollers is not enough to implement such systems in a low-power electric drive. The development of microcontrollers is following the path of increasing not only computing power, but also memory, which makes it possible to implement model predictive control systems in practice using lookup table methods for calculating control actions for all combinations of state variables and control actions. The paper shows the possibility of designing control with prediction for two types of electric drives—a DC electric drive and a switched reluctance electric drive—as objects with a small number of state variables, which allows one to fit the precalculated lookup tables of control actions in the memory of the microcontroller. Studies on mathematical models have shown that model predictive control with a finite control set and a single prediction horizon has disadvantages due to variable switching frequency, and control with a continuous control set implemented by the lookup table method allows one to perform control calculations immediately before the start of the next pulse width modulation period, reducing the algorithm execution time by hundreds of times. © 2023, Allerton Press, Inc.

关键词： Forecasting

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