Applied Physics

Influence of the fractional-order strain on an infinite material with a spherical cavity under Green-Naghdi hyperbolic two-temperature thermoelasticity theory
Editor's pick
Research Article
Influence of the fractional-order strain on an infinite material with a spherical cavity under Green-Naghdi hyperbolic two-temperature thermoelasticity theory
By Hamdy M. Youssef, Abdulrahman A. Alghamdi
In this work, a novel mathematical model of thermoelastic, homogenous, isotropic, and infinite medium with a spherical cavity has been constructed. Under the hyperbolic two-temperature Green-Naghdi theory of thermoelasticity type-I and type-III with fractional-order strain, the governing equations have been established. The bounding surface of the cavity has been thermally loaded by a ramp-type heat and is connected to a rigid foundation which prevents volumetric strain. Different values of the fractional-order and two-temperature parameters have shown numerical results for the dynamical and conductive temperature increment, strain, displacement, and average of principal stresses, which are graphically applicable to all the functions studied. The fractional-order parameter has significant effects on stress and strain distributions, while it has a limited effect on the dynamical and conductive temperatures increment. The hyperbolic two-temperature parameter has significant effects on all studied functions based on Green-Naghdi models of type-1 and type-II. Moreover, the ramp-time heat parameter has a significant impact on all the studied functions under all the studied models of thermoelasticity.
June 26, 2023
Applied Physics
Most cited
Research Article
A conversion guide: solar irradiance and lux illuminance
By Peter R. Michael, Danvers E. Johnston, Wilfrido Moreno
December 4, 2020
Applied Physics
Most cited
Research Article
A portable breast cancer detection system based on smartphone with infrared camera
By Jian Ma, Pengchao Shang, Chen Lu, Safa Meraghni, Khaled Benaggoune, Juan Zuluaga, Noureddine Zerhouni, Christine Devalland, Zeina Al Masry
September 26, 2019
Biomechanics
Most cited
Research Article
Experimental kinematic analysis of an intermittent motion planetary mechanism with elliptical gears
By Alexander Prikhodko
September 30, 2020
Applied Physics
Most cited
Research Article
Experimental analysis of cutting force during machining difficult to cut materials under dry, mineral oil, and TiO2 nano-lubricant
By I. P. Okokpujie, L. K. Tartibu
December 13, 2021
Applied Physics

Journal of Vibroengineering

Applying deep learning and wavelet transform for predicting the vibration behavior in variable thickness skew composite plates with intermediate elastic support
Research Article
Applying deep learning and wavelet transform for predicting the vibration behavior in variable thickness skew composite plates with intermediate elastic support
In this paper, the vibration behavior features are extracted from the combination between Wavelet Transform (WT), and Finite Strip Transition Matrix (FSTM) of skew composite plates (SCPs), with variable thickness, and intermediate elastic support. Although, the results of this technique and based on the previous work done by the authors, that show the method can reflect the vibration behavior of the composite plates. Due to the method's difficulty in terms of, a lot of calculations with a large number of iterations these results may not be good choices for quick and accurate vibration behavior extracting. Thus, the new deep neural network (NN) is designed to learn and test these results carrying out by extracting vibration behavior features that reflect the important and essential information about the mode shapes in SCP. The results give high indications about the proposed technique of deep learning is a promising method, particularly when the type structures are complicated and the ambient environment is variable.
February 6, 2021
Vibration Engineering Articles
A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
Research Article
A convolutional neural network method based on Adam optimizer with power-exponential learning rate for bearing fault diagnosis
The extraction of early fault features from time-series data is very crucial for convolutional neural networks (CNNs) in bearing fault diagnosis. To address this problem, a CNN framework based on identity mapping and Adam optimizer is presented for learning temporal dependencies and extracting fault features. The introduction of four identity mappings allows the deep layers to directly learn the data from the shallow layers, which alleviates the gradient disappearance problem caused by the increase of network depth. A new Adam optimizer with power-exponential learning rate is proposed to control the iteration direction and step size of CNN method, which solves the problems of local minima, overshoot or oscillation caused by the fixed values of the learning rates during the updating of network parameters. Compared to existed methods, the identification accuracy of the proposed method outperformed that of other methods for bearing fault diagnosis.
June 30, 2022
Applied Mathematics
Fault diagnosis and health management of bearings in rotating equipment based on vibration analysis – a review
Research Article
Fault diagnosis and health management of bearings in rotating equipment based on vibration analysis – a review
There is an ever-increasing need to optimise bearing lifetime and maintenance cost through detecting faults at earlier stages. This can be achieved through improving diagnosis and prognosis of bearing faults to better determine bearing remaining useful life (RUL). Until now there has been limited research into the prognosis of bearing life in rotating machines. Towards the development of improved approaches to prognosis of bearing faults a review of fault diagnosis and health management systems research is presented. Traditional time and frequency domain extraction techniques together with machine learning algorithms, both traditional and deep learning, are considered as novel approaches for the development of new prognosis techniques. Different approaches make use of the advantages of each technique while overcoming the disadvantages towards the development of intelligent systems to determine the RUL of bearings. The review shows that while there are numerous approaches to diagnosis and prognosis, they are suitable for certain cases or are domain specific and cannot be generalised.
November 26, 2021
Applied Mathematics
A review on wind turbines gearbox fault diagnosis methods
Research Article
A review on wind turbines gearbox fault diagnosis methods
As an renewable and clean energy of the world, wind energy has gained more and more attention and its fault diagnosis becomes more and more important. The gearbox, as the kernel component of the wind turbine system, it’s robust conditions have a great influence on the whole wind turbines system. Wind turbine gearbox has complex structure, which is usually composed of solar planetary gearbox and cylindrical gearbox. In the process of operation, various kinds of faults easily occur, resulting in serious losses. Once the wind turbine gearbox is not functioning as smoothly as it could be, it may result in large economic losses for the company and owner. At the same time, the failure rate of wind turbine gearbox has always been high because of complicated mechanic structure and special motion. Therefore, the tasks of reducing the downtime and increasing the productivity of wind turbine gearbox are urgent. This paper reviewed some research results of faults diagnosis on wind turbines gearbox, such as time-frequency analysis method, vibration based methods, nondestructive testing methods, etc. Meanwhile, this paper finds out some key problems and the channel of the resolution of the issue in order to supply some information for the further research of wind turbines gearbox.
January 27, 2021
Applied Mathematics
Journal of Vibroengineering

Comprehensive platform for advancements in the field of vibration engineering

Impact Factor
1.0
CiteScore
1.5
APC
1050 EUR

Best of Theme

You might also like

Design and analysis of driving motor system for hybrid electric vehicle
Most downloaded
Research Article
Design and analysis of driving motor system for hybrid electric vehicle
By Qiping Chen, Jiacheng Wei, Fanhong Zeng, Qiang Xiao, Hui Chen
In order to improve the reliability and stability of hybrid electric vehicle driving motor system, according to the performance parameters of the hybrid electric vehicle, the driving motor system is designed and analyzed for the hybrid electric vehicle. Based on the performance parameters of the hybrid electric vehicle, the power parameters of the permanent magnet synchronous motor (PMSM) are calculated and determined, then the parameters of the stator core, the permanent magnet and the rotor core are designed and calculated, as well as other main characteristic parameters of the driving motor system are calculated. The model of a PMSM is established and simulated by ANSOFT Maxwell according to the obtained motor parameters, and then the steady state and transient state of the driving motor are simulated in different working points, and the electromagnetic and performance curves are combined to determine the overall performance requirements of the driving motor, which can be used to match the hybrid electric vehicle. The simulation results show that the designed PMSM can be used to match the hybrid electric vehicle and meet the performance requirements of the vehicle. The final simulation analysis results are in good agreement with the theoretical calculation results, which indicates that this method can be used to afford a theoretical basis to reduce the cogging torque and optimize the in-wheel motor of electric vehicle in the future.
March 31, 2020
Computer Science
Error correction and uncertainty measurement of short-open-load calibration standards on a new concept of software defined instrumentation for microwave network analysis
Most downloaded
Research Article
Error correction and uncertainty measurement of short-open-load calibration standards on a new concept of software defined instrumentation for microwave network analysis
By M. Nazrin, S. J. Hashim, F. Z. Rokhani, B. M. Ali, Z. Yusoff
Software-Defined Radio (SDR) has appeared as a sufficient framework for the development and testing of the measurement systems such as a signal generator, signal analyzer, and network analysis used in the network analyzer. However, most of researchers or scientists still rely on commercial analyzers were larger benchtop instruments, highly cost investment and minimum software intervention. In this paper, a new concepts measurement revolution called as Software Defined Instrumentation (SDI) on network analysis is presented, which is based on reconfigurable SDR, a low-cost implementation, ability to access RF chain and utilizing open source signal processing framework. As a result, a Vector Network Analyzer (VNA) has been successful implemented by deploying an SDR platform, test sets, and data acquisition from the GNU Radio software in host PC. The known calibration process on SHORT-OPEN-LOAD (SOL) technique is validated to ensure measurement data from this SDI free from systematic error. Two types of SOL calibration standards used for a comparison study to validate the SDI measurement system which is capable of generating the response on the differential of standard quality and accuracy of standards kits. Finally, calibration uncertainty analysis is also presented in this work by utilizing RF open source package without any cost addition.
September 30, 2019
Applied Physics
FE analysis and experimental determination of a shaft deflection under three-point loading
Increasing industrial demand for new products including advanced production technology leads to substantial natural resources consumption. Furthermore, huge environmental pollution and emerging environmental legislation motivate the machine tools industry as one of the major resource consumers on a global scale to develop methods for more sustainable use of the Earth's resources. Machine tools re-engineering concerning design and failure analysis is an approach by which outdated machines are upgraded and restored to like-new machines. To evaluate the mechanical failure of the used machine components and to ensure their reliable future performance, it is essential to make material, design, and surface investigations. In this paper, an experimental approach based on the principle of a three-point bending test is presented to evaluate the shaft elastic behavior under loading. Moreover, finite element analysis and numerical integration method are used to determine the maximum linear deflection and bending stress of the shaft. Subsequently, a comparison between the results is made. In conclusion, it was found that the measured bending deflection and stress were well close to the admissible design values. Therefore, the shaft can be used again in the second life cycle. However, based on previous surface tests conducted, the shaft surface needs re-carburizing and refining treatments to ensure the reliable performance of the surface.
Read more
Adaptive control of a nonlinear suspension with time-delay compensation
This paper addresses the challenge of predictive control of a quarter-car nonlinear suspension and low controller-precision. This is done by designing and implementing an adaptive controller with time-delay compensation. First, a real-time control model is created. Then, time-delay compensation is realized and both frequency-domain and time-domain simulation of the controller performance are conducted. According to the simulation results, the sprung-mass acceleration of the suspension controlled by an adaptive controller with time-delay compensation is superior to that without time-delay compensation. Both the period to settle down and the peak of vibration acceleration are smaller. This means the proposed controller is capable of dealing with problems including variable time delay, nonlinear vibration and predictive control.
Read more