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Internal crack detection has been a subject of focus in structural health monitoring. By focusing on crack detection in structural datasets, it is demonstrated that deep learning (DL) methods can effectively analyze seismic wave fields…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Fatahlla Moreh , Yusuf Hasan , Bilal Zahid Hussain , Mohammad Ammar , Sven Tomforde

The characterization of nanostructured surfaces with sensitivity in the sub-nm range is of high importance for the development of current and next generation integrated electronic circuits. Modern transistor architectures for e.g. FinFETs…

Guided wave testing is a popular approach for monitoring the structural integrity of infrastructures. We focus on the primary task of damage detection, where signal processing techniques are commonly employed. The detection performance is…

Signal Processing · Electrical Eng. & Systems 2022-02-02 Ishan D. Khurjekar , Joel B. Harley

We introduce the dynamics mode decomposition for monitoring wide-area power grid networks from sparse measurement data. The mathematical framework fuses data from multiple sensors based on multivariate statistics, providing accurate full…

Pattern Formation and Solitons · Physics 2019-06-11 J. Jorge Ramos , J. Nathan Kutz

This paper proposes a damage detection method based on the train-induced responses of high-speed railway box girder. Under the coupling effects of bending and torsion, the traditional damage detection method based on the Euler beam theory…

Signal Processing · Electrical Eng. & Systems 2023-03-24 Xin Wang , Yi Zhuo , Shunlong Li

Bearings are critical components in industrial machinery, yet their vulnerability to faults often leads to costly breakdowns. Conventional fault detection methods depend on continuous, high-frequency vibration sensing, digitising, and…

Computational Engineering, Finance, and Science · Computer Science 2025-03-11 P. Peralta-Braz , M. M. Alamdari , C. T. Chou , M. Hassan , E. Atroshchenko

Pre-trained model assessment for transfer learning aims to identify the optimal candidate for the downstream tasks from a model hub, without the need of time-consuming fine-tuning. Existing advanced works mainly focus on analyzing the…

Machine Learning · Computer Science 2025-03-07 Tengxue Zhang , Yang Shu , Xinyang Chen , Yifei Long , Chenjuan Guo , Bin Yang

An outage detection framework for power distribution networks is proposed. Given the tree structure of the distribution system, a method is developed combining the use of real-time power flow measurements on edges of the tree with load…

Systems and Control · Computer Science 2016-11-18 Raffi Sevlian , Yue Zhao , Andrea Goldsmith , Ram Rajagopal , H. Vincent Poor

Distribution grids include medium and low voltage lines that are involved in the delivery of electricity from substation to end-users/loads. A distribution grid is operated in a radial/tree-like structure, determined by switching on or off…

Optimization and Control · Mathematics 2016-08-18 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order data sets where standard two-way analysis techniques often fail to discover the hidden correlations between variables in multi-way…

Machine Learning · Computer Science 2020-03-12 Ali Anaissi , Seid Miad Zandavi

We consider a multi-object detection problem over a sensor network (SNET) with limited range sensors. This problem complements the widely considered decentralized detection problem where all sensors observe the same object. While the…

Information Theory · Computer Science 2016-11-17 Erhan B. Ermis , Venkatesh Saligrama

We describe techniques for the robust detection of community structure in some classes of time-dependent networks. Specifically, we consider the use of statistical null models for facilitating the principled identification of structural…

Data Analysis, Statistics and Probability · Physics 2013-04-16 Danielle S. Bassett , Mason A. Porter , Nicholas F. Wymbs , Scott T. Grafton , Jean M. Carlson , Peter J. Mucha

The damage detection problem in mechanical systems, using vibration measurements, is commonly called Structural Health Monitoring (SHM). Many tools are able to detect damages by changes in the vibration pattern, mainly, when damages induce…

Computational Engineering, Finance, and Science · Computer Science 2024-09-25 Luis Gustavo Giacon Villani , Samuel da Silva , Americo Cunha

This work proposes an agnostic inference strategy for material diagnostics, conceived within the context of laser-based non-destructive evaluation methods, which extract information about structural anomalies from the analysis of acoustic…

Computer Vision and Pattern Recognition · Computer Science 2014-05-13 Stefano Gonella , Jarvis D. Haupt

The Finite Elements with Switch Detection (FESD) method is a highly accurate direct transcription method for optimal control of several classes of nonsmooth dynamical systems. This paper extends the FESD method to Projected Dynamical…

Optimization and Control · Mathematics 2024-04-09 Anton Pozharskiy , Armin Nurkanović , Moritz Diehl

Structural health monitoring (SHM) is essential for ensuring the safety and longevity of infrastructure, but complex image environments, noisy labels, and reliance on manual damage assessments often hinder its effectiveness. This study…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Isaac Osei Agyemang , Isaac Adjei-Mensah , Daniel Acheampong , Gordon Owusu Boateng , Adu Asare Baffour

Composites with high strength and high fracture resistance are desirable for structural and protective applications. Most composites, however, suffer from poor damage tolerance and are prone to unpredictable fractures. Understanding the…

Materials Science · Physics 2024-04-23 Tommaso Magrini , Chelsea Fox , Adeline Wihardja , Athena Kolli , Chiara Daraio

Surface anomaly detection is a vital component in manufacturing inspection. Current discriminative methods follow a two-stage architecture composed of a reconstructive network followed by a discriminative network that relies on the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Matic Fučka , Vitjan Zavrtanik , Danijel Skočaj

Electrical impedance tomography (EIT) enables non-invasive, spatially continuous reconstruction of internal conductivity distributions, providing full field sensing beyond conventional point measurements. Here, we report the first in situ…

Emerging Technologies · Computer Science 2026-02-18 Akash Deep , Andrea Samore , Alistair McEwan , Andrew McBride , Shanmugam Kumar

In a typical multi-standard military communication receiver, fast and reliable spectrum sensing unit is required to extract the information of multiple channels (frequency bands) present in a wideband input signal. In this paper, an energy…

Information Theory · Computer Science 2016-08-16 S. J. Darak , A. P. Vinod , E. M-K. Lai