Mechanical Engineering

Research on road damage recognition and classification based on improved VGG-19
Editor's pick
Research Article
Research on road damage recognition and classification based on improved VGG-19
By Jiaqi Wang, Kaihang Wang, Kexin Li
In recent years, methods of road damage detection, recognition and classification have achieved remarkable results, but there are still problems of efficient and accurate damage detection, recognition and classification. In order to solve this problem, this paper proposes a road damage VGG-19 model construction method that can be used for road damage detection. The road damage image is processed by digital image processing technology (DIP), and then combined with the improved VGG-19 network model to study the method of improving the recognition speed and accuracy of VGG-19 road damage model. Based on the performance evaluation index of neural network model, the feasibility of the improved VGG-19 method is verified. The results show that compared with the traditional VGG-19 model, the road damage VGG-19 road damage recognition model proposed in this paper shortens the training time by 79 % and the average test time by 68 %. In the performance evaluation of the neural network model, the comprehensive performance index is improved by 2.4 % compared with the traditional VGG-19 network model. The research is helpful to improve the model performance of VGG-19 road damage identification network model and its fit to road damages.
October 6, 2023
Informatics
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
Optimization of palm methyl ester and its effect on fatty acid compositions and cetane number
By Sharath Satya, Aditya Kolakoti, Naga Raju B., Shyam Sundar R., Ranga Rao
March 31, 2019
Informatics
Most cited
Research Article
Mathematical modeling of forced oscillations of semidefinite vibro-impact system sliding along rough horizontal surface
By Vitaliy Korendiy, Volodymyr Gursky, Oleksandr Kachur, Volodymyr Gurey, Oleksandr Havrylchenko, Oleh Kotsiumbas
December 2, 2021
Informatics
Most cited
Research Article
Performance of PID-Fuzzy control for cab isolation mounts of soil compactors
By Vanliem Nguyen, Renqiang Jiao, Vanquynh Le, Anhtan Hoang
December 31, 2019
Informatics

Journal of Mechanical Engineering, Automation and Control Systems

Crack classification in rotor-bearing system by means of wavelet transform and deep learning methods: an experimental investigation
Research Article
Crack classification in rotor-bearing system by means of wavelet transform and deep learning methods: an experimental investigation
Parallel with significant growth in industry, especially mysteries related to energy engineering, condition monitoring of rotating systems have been experiencing a noticeable increase. One of the prevalent faults in these systems is fatigue crack, so finding reliable procedures in identification of cracks in rotating shafts has become a pressing problem among engineers during recent decades. While a vast majority of cracked rotors can operate for a specific period of time, to prevent catastrophic failures, crack detection and measuring its characteristics (i.e. size and its location) seem to be essential. In the present essay, a hybrid procedure, consisting of Deep Learning and Discrete Wavelet transform (DWT), is applied in detection of a breathing transverse crack and its depth in a rotor-bearing-disk system. DWT with Daubechies 32(db32) as wavelet mother function is applied in signal noise reduction until level 6, also its Relative Wavelet Energy (RWE) and Wavelet entropy (WE) are extracted. A characteristic vector that is a combination of RWE and WE is considered as input to a multi-layer Artificial Neural Network (ANN). In this supervised learning classifier, a multi-layer Perceptron neural network is used; in addition, Rectified Linear Unit (ReLU) function is exerted as activation function in both hidden and output layers. By comparing the results, it can be seen that the applied procedure has strong capacity in identification of crack and its size in the rotor system.
December 11, 2020
Industrial Engineering
Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition
Research Article
Identification of shallow cracks in rotating systems by utilizing convolutional neural networks and persistence spectrum under constant speed condition
The positive benefits of early faults detection in rotating systems have led scientists to develop automated methods. Although unbalancing is the most prevalent defect in rotor systems, this fault normally is accompanied by other defects such as crack. In this article, an effective self-acting procedure is addressed in identifying shallow cracks in rotor systems throughout the steady-state operation. To classify rotor systems suffering cracks with three various depths, firstly, healthy and cracked systems are modeled by employing the finite element method (FEM). In the following, systems' vibration signals are calculated in different situations numerically; for pre-processing stage, the persistence spectrum is implemented. Finally, by using a supervised convolutional neural network (CNN), rotor systems are classified by regarding the crack depths. The result of the testing step revealed that this hybrid method has rational capacity in distinguishing shallow cracks in steady-state operation where many other methods are somehow powerless.
December 15, 2021
Industrial Engineering
Control performance of suspension system of cars with PID control based on 3D dynamic model
Research Article
Control performance of suspension system of cars with PID control based on 3D dynamic model
To evaluate the control performance of the PID controller for the cars, a 3D car dynamic model with 8-DOF which can fully reflect the pitch and roll of the car body is proposed in this study. The PID controller is then researched and applied to control the active suspension system of the cars under the different excitations of the road surface and the various car speeds. The control performance for improving the ride comfort of the driver is evaluated via the root-mean-square (RMS) of acceleration responses of the vertical driver’s seat, pitching and rolling car body angles. The research results show that the PID controller for the car suspension system have an obvious impact on reducing the vibration and controlling the car body shaking in comparison with the passive suspension system.
June 30, 2020
Industrial Engineering
Summary and outlook of 4D track prediction methods
Research Article
Summary and outlook of 4D track prediction methods
Four-dimensional track prediction is the precise control of the time dimension of three-dimensional space at each stage of the flight. Accurate prediction of the aircraft trajectory is a prerequisite for the automation of air traffic control. This article reviews 4D track prediction technology, that is, particle motion-based prediction method, hybrid estimation-based prediction method and machine learning-based prediction method. At the end, combined with aircraft track data, the method of data mining is used to extract the flight profile and describe the applicable scope of each method. The contents of this paper can be used for reference in the research direction of 4D track prediction technology.
June 30, 2020
Industrial Engineering
Journal of Mechanical Engineering, Automation and Control Systems

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