Article
Nanoscience & Nanotechnology
Xiyuan Zhang, Yu Wang, Xingyao Gao, Yanda Ji, Fengjiao Qian, Jiyu Fan, Haiyan Wang, Lei Qiu, Weiwei Li, Hao Yang
Summary: The study introduced a flexible, lightweight BaTiO3:Sm2O3/SrRuO3/SrTiO3/mica film sensor for high-temperature SHM on aircraft structures with complex curved surfaces, with enhanced properties and stability up to 150 degrees C.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Review
Construction & Building Technology
Gabriel M. F. Ramalho, Antonio M. Lopes, Lucas F. M. da Silva
Summary: Lamb waves have shown promising results in NDT and SHM, particularly in monitoring the health of adhesive joints. The paper covers equipment, testing procedures and techniques, as well as discussions on signal processing and statistical methods. Further research is needed in the area of monitoring weak adhesion using Lamb wave-based SHM methods.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Engineering, Aerospace
Chung-De Chen, Yu-Cheng Chiu, Yao-Hung Huang, Po-Hao Wang, Rong-Der Chien
Summary: This paper presents assessments of structural health monitoring (SHM) for metallic structures through fatigue crack testing and damage index measurements using Lamb waves with various driving frequencies. The study found that using a driving frequency of 450 kHz yielded the best results in crack monitoring, with detectable crack sizes ranging from 4.83 to 5.92 mm based on a threshold damage index of 0.01. The relationship between the damage index and actual crack length, as well as the probability of detection (POD) curves, can be applied to real structures with similar geometries.
JOURNAL OF AEROSPACE ENGINEERING
(2021)
Article
Engineering, Aerospace
Chung-De Chen, Chia-Hung Hsieh, Chi-Yuan Liu, Yao-Hung Huang, Po-Hao Wang, Rong-Der Chien
Summary: This paper investigates the Lamb wave based structural health monitoring for aluminum bolted joints with multiple-site fatigue damages through experiments. Multiple fatigue cracks were observed at different bolt holes during the fatigue testing. The damage index (DI) was compared before and after the initiation of the fatigue cracks, but it was found to be overestimated due to phase shifts. To overcome this, the envelope damage index (EDI) that considers the envelope curves of the signals was introduced and proved to be a better parameter for monitoring the fatigue crack size and location.
JOURNAL OF AEROSPACE ENGINEERING
(2022)
Article
Materials Science, Ceramics
Xiyuan Zhang, Yu Wang, Xinna Shi, Jie Jian, Xuejing Wang, Min Li, Yanda Ji, Fengjiao Qian, Jiyu Fan, Haiyan Wang, Lei Qiu, Weiwei Li, Hao Yang
Summary: Flexible PZT film sensors are proven to be excellent candidates for receiving Lamb wave in Lamb wave-based SHM of aircraft, demonstrating high sensitivity and potential for real-time monitoring of aging aircraft.
CERAMICS INTERNATIONAL
(2021)
Article
Automation & Control Systems
Hung V. Dang, Hoa Tran-Ngoc, Tung V. Nguyen, T. Bui-Tien, Guido De Roeck, Huan X. Nguyen
Summary: This study developed a practical end-to-end framework for smart structural health monitoring, achieving highly accurate damage detection through a hybrid deep learning model and signal processing techniques. Three case studies demonstrated the effectiveness of the proposed approach, suitable for real-time SHM with reduced resource requirements.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Civil
Rahim Gorgin, Ziping Wang
Summary: This study proposes a Lamb wave-based structural damage identification technique that does not require baseline data. By determining wave velocity and separating waves, effective damage identification in the presence of temperature changes is achieved.
SMART STRUCTURES AND SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Max David Champneys, Andre Green, John Morales, Moises Silva, David Mascarenas
Summary: This study demonstrates that data-driven approaches to structural health monitoring are vulnerable to adversarial attacks. A specific adversarial threat model for structural health monitoring is proposed to stimulate discussion on how to make monitoring methods more robust.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2021)
Article
Engineering, Multidisciplinary
Voon-Kean Wong, Menglong Liu, Wei-Peng Goh, Shuting Chen, Zheng Zheng Wong, Fangsen Cui, Kui Yao
Summary: In this study, direct-write piezoelectric ultrasonic transducers were used to monitor fatigue cracks near fastener holes. A novel ring-design with annular array electrodes and pulse-echo, pitch-catch methods were employed for crack detection. These thin film transducers showed high conformability and potential for structural health monitoring.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Engineering, Multidisciplinary
Phong B. Dao, Wieslaw J. Staszewski
Summary: This study aims to address the technical challenges in applying cointegration theory to structural health monitoring (SHM). Through simulation data and a case study, it provides a clear explanation of how cointegration can be used to remove common trends, detect faults and damages, and understand the relationships between cointegrated variables and residuals. The results demonstrate the effectiveness of cointegration in addressing these issues.
Article
Engineering, Mechanical
Xuerong Liu, Yuanming Xu, Ning Li, Weifang Zhang
Summary: This paper investigates the debonding behavior of piezoelectric sensors in the structural health monitoring system and its impact on the reliability of the monitoring network. Both simulation and experimental results show that the debonding length and direction affect the receiving signal of the sensor. The study also reveals that the increase of right debonding length does not necessarily result in a monotonic decrease in signal amplitude, and the signal amplitude of the sensor is greater when the wave propagation direction is parallel to the sensor debonding direction.
INTERNATIONAL JOURNAL OF MECHANICS AND MATERIALS IN DESIGN
(2023)
Article
Engineering, Mechanical
Shifeng Guo, Hao Ding, Yehai Li, Haowen Feng, Xinhong Xiong, Zhongqing Su, Wei Feng
Summary: This study proposes a hierarchical deep convolutional regression framework based on deep learning to solve the impact source localization problem using acoustic emission signals. The framework shows strong capability in processing time-series data and utilizes data augmentation and transfer learning techniques to enhance model reliability and robustness.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Mechanical
Yuan Jiang, Gang Niu
Summary: This paper introduces a novel dispersive signal decomposition method IFETF, which can accurately estimate dispersion curves, separate overlapped components, and improve TF resolution. Through numerical analysis and engineering applications, it is found that IFETF has higher accuracy and efficiency in signal reconstruction and GD estimation compared to traditional methods.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Multidisciplinary
A. Nokhbatolfoghahai, H. M. Navazi, R. M. Groves
Summary: In this paper, the performance of sparse reconstruction and delay-and-sum methods for damage localization was evaluated under various conditions using numerical and experimental methods. The study employed the Taguchi method for experimental design and defined a modified performance index to represent image quality. Results showed that the delay-and-sum method exhibited better robustness under uncontrolled factors, while sparse reconstruction was more reliable for poor baseline subtraction. These findings offer valuable insights for designing reliable structural health monitoring systems.
Article
Computer Science, Information Systems
Ambarish G. Mohapatra, Jaideep Talukdar, Tarini Ch. Mishra, Sameer Anand, Ajay Jaiswal, Ashish Khanna, Deepak Gupta
Summary: Structural Health Monitoring (SHM) of large structures is critical, and Fiber Bragg Grating (FBG) sensor technology can address this issue. This article discusses the fabrication and application of FBG sensors, and proposes a Smart Distributed Sensing (SDS) model based on FBG sensors.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Materials Science, Characterization & Testing
Alexander C. S. Douglass, Daniel Sparkman, Joel B. Harley
JOURNAL OF NONDESTRUCTIVE EVALUATION
(2020)
Article
Engineering, Electrical & Electronic
Ayobami S. Edun, Naveen Kumar Tumkur Jayakumar, Samuel R. Kingston, Cynthia M. Furse, Michael A. Scarpulla, Joel B. Harley
Summary: Spread spectrum time domain reflectometry (SSTDR) has traditionally been used for detecting hard faults in transmission lines, with little research on impedance issues of circuit elements in the middle of the line. This study considers transmission lines with different impedances on each wire and provides accurate analytical expressions for reflection coefficients.
IEEE SENSORS JOURNAL
(2021)
Biographical-Item
Engineering, Electrical & Electronic
Hagit Messer, Arye Nehorai, Jeff Krolik, Jose M. F. Moura, Al Hero, Joseph Tabrikian
IEEE SIGNAL PROCESSING MAGAZINE
(2021)
Article
Engineering, Electrical & Electronic
Athina Petropulu, Jose M. F. Moura, Rabab Kreidieh Ward, Theresa Argiropoulos
Summary: Signal processing (SP) is a powerful technology that has significantly impacted the digital world and brought about major changes in our lives. The growth of digital SP since the mid-1960s, supported by integrated circuits and digital computers, has led to groundbreaking advances in various fields, profoundly influencing society. The IEEE Signal Processing Society (SPS), as the leading professional society, has played a crucial role in advancing the theory and applications of SP through its publications, conferences, and educational activities. It has fostered collaboration and knowledge sharing among researchers, practitioners, and students, empowering the growth of SP.
IEEE SIGNAL PROCESSING MAGAZINE
(2023)
Editorial Material
Engineering, Electrical & Electronic
Geert Leus, Antonio G. Marques, Jose M. F. Moura, Antonio Ortega, David Shuman
IEEE SIGNAL PROCESSING MAGAZINE
(2023)
Article
Engineering, Electrical & Electronic
Stefan Vlaski, Soummya Kar, Ali H. Sayed, Jose M. F. Moura
Summary: This article reviews the significant advances in networked signal and information processing (SIP) that have allowed decision making, inference, optimization, control, and learning to be extended to distributed agent environments. As interacting agents cooperate, new collective behaviors emerge from their local decisions and actions. Furthermore, networked agents have been shown to match the performance of cloud or federated solutions while offering improved privacy, increased resilience, and conserved resources through cooperation and sharing.
IEEE SIGNAL PROCESSING MAGAZINE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Wei Li, Fangzhou Wang, Jose M. F. Moura, R. D. Blanton
Summary: This study proposes a method of modeling global floorplanning as an SDP problem and solves the rank constraint problem by introducing a direction matrix, which improves the quality of the solution. Furthermore, a series of techniques are introduced to enhance the flexibility, accuracy, and efficiency of the algorithm.
2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
John Shi, Jose M. F. Moura
Summary: In both Discrete Signal Processing (DSP) and Graph Signal Processing (GSP), sampling is a crucial step for signal reconstruction. This paper presents a unified GSP sampling theory that bridges the gap between the vertex and spectral domains, similar to DSP sampling. By exploring the steps of DSP sampling in GSP and considering the impact of different sampling choices, the paper provides new insights and intuition on both DSP and GSP sampling. It also highlights the limitations of current spectral sampling methods in the GSP literature.
2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Shreyas Chaudhari, Jose M. F. Moura
Summary: Direction of arrival (DoA) estimation is a well-studied problem with various applications. Traditional algorithms require prior knowledge of the number of transmitters or sufficient measurements, which limits their performance. Recently, a deep learning approach has been proposed, but it still needs prior knowledge or a large number of snapshots. We propose a new deep learning approach that can determine the number and positions of transmitters, outperforming traditional and recent deep learning methods in low-SNR and low-snapshot scenarios.
2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS
(2022)
Article
Engineering, Electrical & Electronic
John Shi, Jose M. F. Moura
Summary: Vertex based and spectral based GSP sampling methods have been studied recently. This paper introduces a unified graph signal sampling theory that starts from the spectral domain and includes dual versions in both the vertex and spectral domains. The theory shows how GSP sampling reduces to DSP sampling when the graph is a directed time cycle graph. Simple examples illustrate the impact of choices available in GSP sampling.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Rajshekhar Das, Yu-Xiong Wang, Jose M. F. Moura
Summary: Few-shot classification aims to classify categories of a novel task by learning from just a few labelled examples, and a new finetuning approach based on contrastive learning can significantly boost few-shot generalization.
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021)
(2021)
Proceedings Paper
Acoustics
Shreyas Chaudhari, Harideep Nair, Jose M. F. Moura, John Paul Shen
Summary: The study introduces a neuromorphic approach for unsupervised time series clustering, emphasizing ultra-low power and continuous online learning for edge devices. Performance evaluation on a subset of UCR Time Series Archive datasets shows that the proposed method outperforms or compares similarly to existing algorithms, while being more amenable for efficient hardware implementation.
2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)
(2021)
Proceedings Paper
Computer Science, Theory & Methods
Alireza Chamanzar, Xujin Liu, Lavender Y. Jiang, Kimon A. Vogt, Jose M. F. Moura, Pulkit Grover
Summary: The study presents a non-invasive deep learning approach for tracking cortical spreading depressions (CSDs) in scalp electroencephalography (EEG) signals. The method, named CSD spatially aware convolutional network or CSD-SpArC, combines convolutional neural network and graph neural network to extract temporal features and spatial structure of EEG signals, achieving high accuracy in tracking CSDs.
2021 10TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)
(2021)
Proceedings Paper
Computer Science, Information Systems
Lavender Y. Jiang, John Shi, Mark Cheung, Oren Wright, Jose M. F. Moura
2020 54TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS
(2020)
Article
Engineering, Electrical & Electronic
Mashad U. Saleh, Joel B. Harley, Naveen K. T. Jayakumar, Samuel Kingston, Evan Benoit, Michael Scarpulla, Cynthia Furse
PROGRESS IN ELECTROMAGNETICS RESEARCH M
(2020)