English
Related papers

Related papers: A Novel Method of Bolt Detection Based on Variatio…

200 papers

This work continues the parametric investigation on the sampling nuances of the Dynamic Mode Decomposition (DMD) under the Koopman analysis. Through turbulent wakes, the investigation corroborated the generality of the universal convergence…

Epilepsy affects about 1% of the population every year, and is characterized by abnormal and sudden hyper-synchronous excitation of the neurons in the brain. The electroencephalogram(EEG) is the most widely used method to record brain…

Signal Processing · Electrical Eng. & Systems 2020-03-31 Akshith Ullal , Ram Bilas Pachori

Bolts are the most numerous fasteners in transmission lines and are prone to losing their split pins. How to realize the automatic pin-missing defect detection for bolts in transmission lines so as to achieve timely and efficient trouble…

Image and Video Processing · Electrical Eng. & Systems 2020-01-20 Zhenbing Zhao , Hongyu Qi , Yincheng Qi , Ke Zhang , Yongjie Zhai , Wenqing Zhao

Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow analysis, and reduced-order modeling. In situations where a system is time varying, one would like to update the system's description online as time…

Optimization and Control · Mathematics 2017-07-11 Hao Zhang , Clarence W. Rowley , Eric A. Deem , Louis N. Cattafesta

In this study, viscoelastic properties of polymeric composites were investigated through a non-destructive test (NDT) method based on longitudinal free vibration. First, three different polyester composites reinforced separately with…

Materials Science · Physics 2015-11-17 Mohammad Mehdi Jalili , Amir Soheil Pirayeshfar , Seyyed Yahya Mousavi

A recently developed Projection-based Digital Image Correlation (P-DVC) method is here extended to 4D (space and time) displacement field measurement and mechanical identification based on a single radiograph per loading step instead of…

Computational Physics · Physics 2019-05-23 Clément Jailin , Ante Buljac , Amine Bouterf , François Hild , Stéphane Roux

In this paper we provide new methodology for inference of the geometric features of a multivariate density in deconvolution. Our approach is based on multiscale tests to detect significant directional derivatives of the unknown density at…

Methodology · Statistics 2016-11-21 Konstantin Eckle , Nicolai Bissantz , Holger Dette

To improve the performance in identifying the faults under strong noise for rotating machinery, this paper presents a dynamic feature reconstruction signal graph method, which plays the key role of the proposed end-to-end fault diagnosis…

Signal Processing · Electrical Eng. & Systems 2023-10-02 Wenbin He , Jianxu Mao , Yaonan Wang , Zhe Li , Qiu Fang , Haotian Wu

The motor control board has various defects such as inconsistent color differences, incorrect plug-in positions, solder short circuits, and more. These defects directly affect the performance and stability of the motor control board,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-26 Jingde Huang , Zhangyu Huang , Chenyu Li , Jiantong Liu

In many experimental contexts, it is necessary to statistically remove the impact of instrumental effects in order to physically interpret measurements. This task has been extensively studied in particle physics, where the deconvolution…

High Energy Physics - Phenomenology · Physics 2024-12-17 Huanbiao Zhu , Krish Desai , Mikael Kuusela , Vinicius Mikuni , Benjamin Nachman , Larry Wasserman

External influences such as traffic and environmental factors induce vibrations in structures, leading to material degradation over time. These vibrations result in cracks due to the material's lack of plasticity compromising structural…

Machine Learning · Computer Science 2024-07-02 Melanie Schaller , Daniel Schlör , Andreas Hotho

The DMD (Dynamic Mode Decomposition) method has attracted widespread attention as a representative modal-decomposition method and can build a predictive model. However, the DMD may give predicted results that deviate from physical reality…

Computational Physics · Physics 2023-11-29 Yuhui Yin , Chenhui Kou , Shengkun Jia , Lu Lu , Xigang Yuan , Yiqing Luo

The increasing penetration of renewable energy sources, characterised by low inertia and intermittent disturbances, presents substantial challenges to power system stability. As critical indicators of system stability, frequency dynamics…

Systems and Control · Electrical Eng. & Systems 2025-02-19 Xiao Li , Xinyi Wen , Benjamin Schäfer

Data-driven decompositions of Particle Image Velocimetry (PIV) measurements are widely used for a variety of purposes, including the detection of coherent features (e.g., vortical structures), filtering operations (e.g., outlier removal or…

Fluid Dynamics · Physics 2020-08-26 Miguel A Mendez , David Hess , Bo B Watz , Jean-Marie Buchlin

Modal analysis is the process of estimating a system's modal parameters such as its natural frequencies and mode shapes. One application of modal analysis is in structural health monitoring (SHM), where a network of sensors may be used to…

Information Theory · Computer Science 2018-03-14 Shuang Li , Dehui Yang , Gongguo Tang , Michael B. Wakin

Balanced data is required for deep neural networks (DNNs) when learning to perform power system stability assessment. However, power system measurement data contains relatively few events from where power system dynamics can be learnt. To…

Signal Processing · Electrical Eng. & Systems 2024-06-14 Tetiana Bogodorova , Denis Osipov , Luigi Vanfretti

X-ray image plays an important role in manufacturing industry for quality assurance, because it can reflect the internal condition of weld region. However, the shape and scale of different defect types vary greatly, which makes it…

Computer Vision and Pattern Recognition · Computer Science 2021-11-19 Moyun Liu , Youping Chen , Lei He , Yang Zhang , Jingming Xie

Matter-wave interferometry is a highly sensitive tool to measure small perturbations in a quantum system. This property allows the creation of precision sensors for dephasing mechanisms such as mechanical vibrations. They are a challenge…

Scientific research and engineering practice often require the modeling and decomposition of nonlinear systems. The Dynamic Mode Decomposition (DMD) is a novel Koopman-based technique that effectively dissects high-dimensional nonlinear…

Varying coefficient model is often used in statistical modeling since it is more flexible than the parametric model. However, model detection and variable selection of varying coefficient model are poorly understood in mode regression.…

Methodology · Statistics 2020-09-23 Xuejun Ma , Yue Du , Jingli Wang
‹ Prev 1 4 5 6 7 8 10 Next ›