Special Issue "Computational Methods in Vibration Problems and Wave Mechanics"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Physics".

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 10185

Special Issue Editor

Prof. Dr. Tomasz Figlus
E-Mail Website1 Website2
Guest Editor
Faculty of Transport and Aviation Engineering, Silesian University of Technology, 8 Krasinskiego Street, 40-019 Katowice, Poland
Interests: signal processing; condition monitoring; vibration; noise; transport means
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Special Issue Information

Dear Colleagues,

The development of computational methods makes it possible to conduct advanced analyses related to the generation and transmission of vibration, and the use of vibration in the assessment of technical condition. The search for sources of vibration and analysis of its transmission requires the application of various computational methods, including both computer simulations and multi-sensor test bench measurements. Vibration signals are also a valuable source of information on the technical condition. Early detection of faults increases reliability and prevents unforeseen failures. The developed calculation methods facilitate quickly finding symptoms of wear and damage of components, and enable the determination of measures of changes in the technical condition.

For this Special Issue, I invite the submission of original papers and reviews of scientific papers presenting innovative solutions in the field of computational methods dedicated to the generation and transmission of vibrations, as well as the application of vibration in the assessment of technical conditions. I encourage you to present new computational methods encompassing simulation tests and the analysis of signals recorded during bench tests. This Special Issue is dedicated to the presentation of calculation methods using advanced signal processing in the time and frequency domains, and the use of artificial intelligence methods in the research. Should you have any queries, please contact me by e-mail.

Dr. Tomasz Figlus
Guest Editor

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Keywords

  • Computational methods
  • Vibration
  • Signal processing
  • Condition monitoring
  • Transport means

Published Papers (10 papers)

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Research

Article
Stress Wave Propagation through Rock Joints Filled with Viscoelastic Medium Considering Different Water Contents
Appl. Sci. 2020, 10(14), 4797; https://doi.org/10.3390/app10144797 - 13 Jul 2020
Cited by 4 | Viewed by 726
Abstract
A rock mass often contains joints filled with a viscoelastic medium of which seismic response is significant to geophysical exploration and seismic engineering design. Using the propagator matrix method, an analytical model was established to characterize the seismic response of viscoelastic filled joints. [...] Read more.
A rock mass often contains joints filled with a viscoelastic medium of which seismic response is significant to geophysical exploration and seismic engineering design. Using the propagator matrix method, an analytical model was established to characterize the seismic response of viscoelastic filled joints. Stress wave propagation through a single joint highly depended on the water content and thickness of the filling as well as the frequency and incident angle of the incident wave. The increase in the water content enhanced the viscosity (depicted by quality factor) of the filled joint, which could promote equivalent joint stiffness and energy dissipation with double effects on stress wave propagation. There existed multiple reflections when the stress wave propagated through a set of filled joints. The dimensionless joint spacing was the main controlling factor in the seismic response of the multiple filled joints. As it increased, the transmission coefficient first increased, then it decreased instead, and at last it basically kept invariant. The effect of multiple reflections was weakened by increasing the water content, which further influenced the variation of the transmission coefficient. The water content of the joint filling should be paid more attention in practical applications. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Structural Damage Detection Based on Real-Time Vibration Signal and Convolutional Neural Network
Appl. Sci. 2020, 10(14), 4720; https://doi.org/10.3390/app10144720 - 09 Jul 2020
Cited by 7 | Viewed by 1475
Abstract
The traditional methods of structural health monitoring (SHM) have obvious disadvantages such as being time-consuming, laborious and non-synchronizing, and so on. This paper presents a novel and efficient approach to detect structural damages from real-time vibration signals via a convolutional neural network (CNN). [...] Read more.
The traditional methods of structural health monitoring (SHM) have obvious disadvantages such as being time-consuming, laborious and non-synchronizing, and so on. This paper presents a novel and efficient approach to detect structural damages from real-time vibration signals via a convolutional neural network (CNN). As vibration signals (acceleration) reflect the structural response to the changes of the structural state, hence, a CNN, as a classifier, can map vibration signals to the structural state and detect structural damages. As it is difficult to obtain enough damage samples in practical engineering, finite element analysis (FEA) provides an alternative solution to this problem. In this paper, training samples for the CNN are obtained using FEA of a steel frame, and the effectiveness of the proposed detection method is evaluated by inputting the experimental data into the CNN. The results indicate that, the detection accuracy of the CNN trained using FEA data reaches 94% for damages introduced in the numerical model and 90% for damages in the real steel frame. It is demonstrated that the CNN has an ideal detection effect for both single damage and multiple damages. The combination of FEA and experimental data provides enough training and testing samples for the CNN, which improves the practicability of the CNN-based detection method in engineering practice. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Structural Damage Features Extracted by Convolutional Neural Networks from Mode Shapes
Appl. Sci. 2020, 10(12), 4247; https://doi.org/10.3390/app10124247 - 20 Jun 2020
Cited by 8 | Viewed by 982
Abstract
This paper aims to locate damaged rods in a three-dimensional (3D) steel truss and reveals some internal working mechanisms of the convolutional neural network (CNN), which is based on the first-order modal parameters and CNN. The CNN training samples (including a large number [...] Read more.
This paper aims to locate damaged rods in a three-dimensional (3D) steel truss and reveals some internal working mechanisms of the convolutional neural network (CNN), which is based on the first-order modal parameters and CNN. The CNN training samples (including a large number of damage scenarios) are created by ABAQUS and PYTHON scripts. The mode shapes and mode curvature differences are taken as the inputs of the CNN training samples, respectively, and the damage locating accuracy of the CNN is investigated. Finally, the features extracted from each convolutional layer of the CNN are checked to reveal some internal working mechanisms of the CNN and explain the specific meanings of some features. The results show that the CNN-based damage detection method using mode shapes as the inputs has a higher locating accuracy for all damage degrees, while the method using mode curvature differences as the inputs has a lower accuracy for the targets with a low damage degree; however, with the increase of the target damage degree, it gradually achieves the same good locating accuracy as mode shapes. The features extracted from each convolutional layer show that the CNN can obtain the difference between the sample to be classified and the average of training samples in shallow layers, and then amplify the difference in the subsequent convolutional layer, which is similar to a power function, finally it produces a distinguishable peak signal at the damage location. Then a damage locating method is derived from the feature extraction of the CNN. All of these results indicate that the CNN using first-order modal parameters not only has a powerful damage location ability, but also opens up a new way to extract damage features from the measurement data. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Diffraction of Transient Cylindrical Waves by a Rigid Oscillating Strip
Appl. Sci. 2020, 10(10), 3568; https://doi.org/10.3390/app10103568 - 21 May 2020
Viewed by 802
Abstract
This investigation portrays the transient cylindrical wave diffraction by an oscillating strip. Mathematical analysis of the problem is carried out with the help of an integral transforms and the Wiener–Hopf technique. Using far zone approximation, the scattered field is evaluated by the method [...] Read more.
This investigation portrays the transient cylindrical wave diffraction by an oscillating strip. Mathematical analysis of the problem is carried out with the help of an integral transforms and the Wiener–Hopf technique. Using far zone approximation, the scattered field is evaluated by the method of steepest descent. This study takes into consideration the transient cylindrical source and an oscillating strip such that both the source and a scatterer have different oscillating frequencies ω 1 and ω 0 , respectively. The situation under consideration is well supported by graphical results showing the effects of emerging parameters. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Study on Passenger Comfort Based on Human–Bus–Road Coupled Vibration
Appl. Sci. 2020, 10(9), 3254; https://doi.org/10.3390/app10093254 - 07 May 2020
Cited by 2 | Viewed by 1151
Abstract
Nowadays, the comfort of drivers and passengers is drawing more and more attention. The interaction between vehicles and the asphalt road can cause coupled vibration and reduce the comfort of passengers. Therefore, the research on human–vehicle–road coupled vibration and the comfort of passengers [...] Read more.
Nowadays, the comfort of drivers and passengers is drawing more and more attention. The interaction between vehicles and the asphalt road can cause coupled vibration and reduce the comfort of passengers. Therefore, the research on human–vehicle–road coupled vibration and the comfort of passengers is of great importance. In this paper, the three-dimensional human–bus–road coupled vibration system is established, including the bus model, the parallel biomechanical human model with 2 degrees-of-freedom (DOF), and road surface roughness condition. The proposed coupled model was then used to study the dynamic response of the system and the comfort evaluation of the human body. In the comfort evaluation, the annoyance rate based method was proposed to consider the randomness of passenger vibration, the difference of the psychosensory vibration, and the fuzziness of evaluation indicators. Compared to the fuzzy evaluation based on the ISO 2631 standard, the proposed annoyance rate based method gives a quantitative evaluation of human comfort. Not only the degree of comfort can be evaluated, but the percentage of people feeling uncomfortable can also be obtained. Finally, parametric studies were conducted to investigate the effects of road surface roughness, interlayer bonding condition, bus weight, bus speed, and sitting position. It is found that the road surface roughness has the most significant effect on human comfort. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Study on Pressure Characteristics and Its Evolution Law at the Ellipsoidal End Cover Pole of Cylindrical Explosion Containment Vessels
Appl. Sci. 2020, 10(9), 3060; https://doi.org/10.3390/app10093060 - 28 Apr 2020
Viewed by 669
Abstract
To explore the postposition of the maximum pressure at the pole of the ellipsoidal end cover of cylindrical explosion containment vessels and to reveal the mechanism of the load evolution, the experimental method was used to measure the pressure curve at the pole [...] Read more.
To explore the postposition of the maximum pressure at the pole of the ellipsoidal end cover of cylindrical explosion containment vessels and to reveal the mechanism of the load evolution, the experimental method was used to measure the pressure curve at the pole under different charges, and the numerical simulation method was used to analyze the evolution law of the explosion flow field within the end cover. The results show that the end cover pole was subjected to three types of pressure: the primary explosion wave, the secondary shock wave and the convergence wave. In addition, the pressure peaks increased in sequence. The evolution of the flow field in the end cover was affected by the amount of charge and the aspect ratio of the vessel. When the scaled distance due to a small charge increased, or when the aspect ratio of the vessel was reduced, the time interval between the convergence wave and the secondary shock wave at the end cover pole decreased gradually. When the scaled distance increased to 4.05 m·kg−1/3, the convergence wave at the pole superimposed on the secondary shock wave. As the aspect ratio of the vessel ranged from 1.75 to 2.50, the time interval between the two peaks was about 150 μs. However, if the aspect ratio was less than 1.40, the convergence wave and the secondary shock wave were fused through complex interaction. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Coupled Numerical Model of Vibration-Based Harvester
Appl. Sci. 2020, 10(8), 2725; https://doi.org/10.3390/app10082725 - 15 Apr 2020
Viewed by 759
Abstract
Herein, the authors publish the complex design of a numerical coupled model of a vibration-based harvester that transforms mechanical vibrations into electric energy. A numerical model is based on usage of the finite element method, connecting analysis of the damped mechanical oscillation, electromagnetic [...] Read more.
Herein, the authors publish the complex design of a numerical coupled model of a vibration-based harvester that transforms mechanical vibrations into electric energy. A numerical model is based on usage of the finite element method, connecting analysis of the damped mechanical oscillation, electromagnetic field and electrical circuit. The model was demonstrated on the design of a microgenerator (MG), and then experimentally tested. The numerical model allows us to execute optimization of the design with many degrees of freedom. The transformation of the wave spreading in the form of mechanical vibrations was solved in the area of resonance of the electromechanical system. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Graphical abstract

Article
Selection of the Informative Frequency Band in a Bearing Fault Diagnosis in the Presence of Non-Gaussian Noise—Comparison of Recently Developed Methods
Appl. Sci. 2020, 10(8), 2657; https://doi.org/10.3390/app10082657 - 12 Apr 2020
Cited by 27 | Viewed by 1643
Abstract
The vibration signals acquired on machines usually have complex spectral structure. As the signal of interest (SOI) is weak (especially at an early stage of damage) and covers some frequency range (around structural resonance), it requires its extraction from a raw observation. Until [...] Read more.
The vibration signals acquired on machines usually have complex spectral structure. As the signal of interest (SOI) is weak (especially at an early stage of damage) and covers some frequency range (around structural resonance), it requires its extraction from a raw observation. Until now, most of the techniques assumed the presence of Gaussian noise. Unfortunately, there are cases when the non-informative part of the signal (considered as the noise) is non-Gaussian due to the random disturbances or nature of the process executed by the machine. Thus, the problem can be formulated as the extraction of the SOI from the non-Gaussian noise. Recently this problem has been recognized by several authors and some new ideas have been developed. In this paper, we would like to compare these techniques for benchmark signals (Gaussian noise, cyclic impulsive signals, non-cyclic impulsive signals with random amplitudes and locations of impulses and a mixture of all of them). Our analysis will cover spectral kurtosis, kurtogram, stability index (Alpha selector), conditional variance-based selector, spectral Gini index, spectral smoothness index and infogram. Finally, a discussion on the efficiency of each method is provided. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
An Exact Method for Calculating the Eigenvector Sensitivities
Appl. Sci. 2020, 10(7), 2577; https://doi.org/10.3390/app10072577 - 09 Apr 2020
Cited by 4 | Viewed by 668
Abstract
Eigenvector sensitivities are often used in many engineering problems such as structural vibration control, optimization design, model updating and damage identification. So far, modal superposition method and Nelson’s method are the two main methods for exactly calculating eigenvector sensitivities. However, modal superposition method [...] Read more.
Eigenvector sensitivities are often used in many engineering problems such as structural vibration control, optimization design, model updating and damage identification. So far, modal superposition method and Nelson’s method are the two main methods for exactly calculating eigenvector sensitivities. However, modal superposition method has a great limitation in applications because it needs all the eigenvectors in its calculation. Although Nelson’s method does not need to use all the eigenvectors, there is no unified sensitivity calculation formula for each eigenvector. In this paper, a new exact method for calculating the eigenvector sensitivity is proposed. The explicit expressions for the first-order and second-order sensitivities of eigenvectors are derived, and strict proof is given. The developed eigenvector sensitivity formulas are simple and convenient in programming. The proposed method is as powerful as Nelson’s method, but much more easy to use. Two numerical examples are used to demonstrate the proposed method and the results show that the developed eigenvector sensitivity formulas are exact and reliable. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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Article
Study on the Transmission and Evolution Characteristics of Vibration Wave from Vibratory Roller to Filling Materials Based on the Field Test
Appl. Sci. 2020, 10(6), 2008; https://doi.org/10.3390/app10062008 - 15 Mar 2020
Cited by 2 | Viewed by 888
Abstract
Compaction quality of railroad subgrade relates directly to the stability and safety of train operation, and the core problem of the Intelligent Compaction of railroads is the transmission and evolution characteristics of vibration wave. Aiming at the shortages in exploring the transmission and [...] Read more.
Compaction quality of railroad subgrade relates directly to the stability and safety of train operation, and the core problem of the Intelligent Compaction of railroads is the transmission and evolution characteristics of vibration wave. Aiming at the shortages in exploring the transmission and evolution characteristics of the vibration signal, the typical subgrade compaction project of Jingxiong Intercity Railway Gu’an Station was selected to carry out the field prototypes tests, and the dynamic response from the vibratory roller to filling materials was monitored in the whole compaction process, and some efficient field tests data will be obtained. Based on this, the transmission and evolution characteristics of the vibration wave from the vibratory roller to filling materials in the compaction process are studied from the time domain, frequency domain, jointed time–frequency domain and energy domain by using one new signal analysis technology—Hilbert–Huang Transform. Some conclusions are shown as follows: first, the vibration acceleration peak gradually decreases with the increase of buried depth, and when the buried depth reaches 1.8 m, the vibration acceleration peak is closed to zero. At the same time, when the vibration wave propagates from the wheel to the surface of filling, the attenuation rate of acceleration gradually increases with the increase of rolling compaction times, while the attenuation rate of other layers in different buried depths gradually decreases. Second, the vibration wave contains fundamental wave and multiple harmonics, and the dominant frequency of the fundamental wave is nearly 21 Hz. With the increase of buried depth, the amplitude of fundamental, primary, secondary, until fifth harmonics decreases exponentially and the concrete functional relationship among different amplitudes of harmonics can be summarized as y = Ae−BX. Third, the vibration energy focuses on the fundamental wave and primary wave, which can increase with the increase of rolling compaction times, and when the rolling compaction time reaches five, their energy reaches maximum. However, when the filling reaches a dense situation, the energy of the primary wave gradually decreases. Therefore, the maximum rolling compaction time is five in the practical engineering applications, which will be helpful for optimizing the compaction quality control models and providing some support for the development of the Intelligent Compaction theory of railway subgrade. Full article
(This article belongs to the Special Issue Computational Methods in Vibration Problems and Wave Mechanics)
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