Application of Artificial Neural Network for Identification of Bearing Stiffness Characteristics in Rotor Dynamics Analysis

Pavlenko, Ivan; Simonovskiy, V.; Ivanov, Vitalii; Zajac, Jozef; Piteľ, Ján

doi:10.1007/978-3-319-93587-4_34

Cited by 39 publications

(7 citation statements)

References 13 publications

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“…It should be additionally noted that the proposed approach has significant prospects for further development under the conditions of its comprehensive implementation with the systems of computational intelligence, particularly to identify the parameters of the above-mentioned mathematical models and the related regression dependencies with the use of artificial neural networks, as was previously realized within the research works [31][32][33][34]. Moreover, in further research, special attention should be paid to demonstrate benefits of the proposed designs of the air distribution device in terms of the air diffusion performance index, using the approach presented in the research [35].…”

Section: Discussionmentioning

confidence: 91%

Solving the Coupled Aerodynamic and Thermal Problem for Modeling the Air Distribution Devices with Perforated Plates

et al. 2019

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The article is focused on the comprehensive analysis of the aerodynamics of air distribution devices with the combined heat and mass exchange, with the aim to improve the following hydro- and thermodynamic parameters of ventilation systems: flow rate, air velocity, hydraulic losses, and temperature. The inadequacy of the previously obtained characteristics has confirmed the need for more rational designs of air distribution systems. Consequently, the use of perforated plates was proposed to increase hydraulic losses for reducing the average velocity and ensuring a uniform distribution of the velocity field on the outlet of the device. The effectiveness of one of the five possible designs usage is confirmed by the results of numerical simulation. The coefficient of hydraulic losses decreased by 2.5–3.0 times, as well as the uniformity of the outlet velocity field for the air flow being provided. Based on the three-factor factorial experiment, the linear mathematical model was obtained for determining the dependence of the average velocity on the flow rate, plate’s area, and diameter of holes. This model was significantly improved using the multiparameter quasi-linear regression analysis. As a result, the nonlinear mathematical models were obtained, allowing the analytical determination of the hydraulic losses and average velocity of the air flow. Additionally, the dependencies for determining the relative error of measuring the average velocity were obtained.

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Section: Discussionmentioning

confidence: 91%

Solving the Coupled Aerodynamic and Thermal Problem for Modeling the Air Distribution Devices with Perforated Plates

et al. 2019

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“…The main advantage of the deep learning approach with CNN is the simplification of image data extraction, which was previously done by standard image processing algorithms (thresholding, contouring, segmentation) [20]. The standard artificial neural network differs from convolutional networks mainly by the structure of the hidden layers of neurons and a significantly higher number of neurons per layer [21]. Detectors such as Look Once (YOLO) [22], Faster-Recurrent Convolutional Neural Networks (RCNN) [23], Single-Shot Detectors (SSD) [24] use deep convolutional neural networks to detect and classify objects and are dedicated especially for mobile devices such as smartphones or tablets.…”

Section: Neural Algorithmic Approachmentioning

confidence: 99%

Novel Approach for Augmented Reality using Convolutional Neural Networks

Oufqir¹,

Abderrahmani²,

Satori³

2022

ijasca

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In this paper, we will exploit the potential of convolutional neural networks (CNN) in augmented reality. Our work combines existing approaches and produces a new method for aligning a virtual object in the real world and in real time. Our method consists in detecting 2D objects of one or more classes present in the real world with CNN algorithms, then using the output of the network to calculate the position of the camera with the PnP algorithm in order to augment the detected object with additional information. The lightness of the MobileNet convolutional neural network combined with the speed of the Single Shot multibox Detector (SSD) framework allows to analyze the acquired images in real time and to use devices with limited resources and performance. We use a trained model that detects 20 different classes, the network receives as input an image sequence acquired in real time. The output of the network provides the set of detected classes as well as the coordinates of the corners of the surrounded rectangle on the object of this class. The coplanar coordinates of this rectangle are used to calculate the camera position and to align a 3D virtual object in the middle of the bounding box surrounding the detected object. The results obtained in the experimental part show the importance and the robustness of the method. Keywords: augmented reality; camera pose estimation; convolution neural network; MobileNet-SSD

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“…In research papers [4][5][6][7], examples of the introduction of neural network technology in computer calculation in solving problems of increasing vibration reliability are described for various rotary machines. Methods of nonlinear identification of stiffness characteristics of bearing supports were also developed in the works [8,9,10].…”

Section: Literature Reviewmentioning

confidence: 99%

Ensuring the Vibration Reliability of Rotors Connected by Spline Joints

Verbovyi

Neamțu

Sieryk

et al. 2019

JES

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This article is devoted to the development of refined numerical mathematical models of rotor dynamics of high-performance turbomachines having a spline connection. These models consider the dependence of the critical frequencies of the shaft on the angular stiffness of the spline connection, as well as the procedure of virtual balancing. As a result of the complex application of this approach, the methods of calculation of vibration characteristics taking into ac-count variable values of angular rigidity of splined connection are offered. In addition, the method of evaluating the system of initial imbalances with the corresponding displacements of the rotor axis in the correction and calculation sections has also been improved. The proposed approaches, based on the integrated application of CAE software and computational intelligent systems, allow for modal and harmonic analysis and implement virtual balancing with a significant reduction in preparation and machine time without loss of relative accuracy. In addition, the developed mathematical model of free and forced vibrations of rotor systems have been implemented in the program code operational files “Critical Frequencies of the Rotor” and “Forced Oscillations of the Rotor” of the computer algebra system MathCAD that allows improving the dynamic balancing procedure for evaluating primary imbalances. The high accuracy of the proposed approach is confirmed by checking the dynamic deviations of the rotor axis by the system of residual imbalances in accordance with the standards of vibration stability. Keywords: turbomachine, spline connection, angular stiffness, virtual balancing, modal analysis, harmonic analysis.

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Application of Artificial Neural Network for Identification of Bearing Stiffness Characteristics in Rotor Dynamics Analysis

Cited by 39 publications

References 13 publications

Solving the Coupled Aerodynamic and Thermal Problem for Modeling the Air Distribution Devices with Perforated Plates

Solving the Coupled Aerodynamic and Thermal Problem for Modeling the Air Distribution Devices with Perforated Plates

Novel Approach for Augmented Reality using Convolutional Neural Networks

Ensuring the Vibration Reliability of Rotors Connected by Spline Joints

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