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  • Open Access

    ARTICLE

    A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

    Shuai Chen1, Yinwei Ma2, Zhongshu Wang2, Zongmei Xu3, Song Zhang1, Jianle Li1, Hao Xu1, Zhanjun Wu1,*

    Structural Durability & Health Monitoring, Vol.18, No.2, pp. 125-141, 2024, DOI:10.32604/sdhm.2024.042594

    Abstract The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life. To this end, distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages, such as lightweight and ease of embedding. However, identifying the precise location of damage from the optical fiber signals remains a critical challenge. In this paper, a novel approach which namely Modified Sliding Window Principal Component Analysis (MSWPCA) was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors. The proposed method is able to extract signal… More > Graphic Abstract

    A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

  • Open Access

    ARTICLE

    Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

    Qing Ai1,2, Hao Tian2,3,*, Hui Wang1,*, Qing Lang1, Xingchun Huang1, Xinghong Jiang4, Qiang Jing5

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1797-1827, 2024, DOI:10.32604/cmes.2023.045251

    Abstract Structural Health Monitoring (SHM) systems have become a crucial tool for the operational management of long tunnels. For immersed tunnels exposed to both traffic loads and the effects of the marine environment, efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge. This study proposed a model-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel. Firstly, a dynamic predictive model-based anomaly detection method is proposed, which utilizes a rolling time window for modeling to achieve dynamic prediction. Leveraging the assumption… More >

  • Open Access

    ARTICLE

    A Multi-Objective Genetic Algorithm Based Load Balancing Strategy for Health Monitoring Systems in Fog-Cloud

    Hayder Makki Shakir, Jaber Karimpour*, Jafar Razmara

    Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545

    Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource accessibility, and security. In this… More >

  • Open Access

    REVIEW

    Emerging Trends in Damage Tolerance Assessment: A Review of Smart Materials and Self-Repairable Structures

    Ali Akbar Firoozi1,*, Ali Asghar Firoozi2

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573

    Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification… More >

  • Open Access

    REVIEW

    Study of Intelligent Approaches to Identify Impact of Environmental Temperature on Ultrasonic GWs Based SHM: A Review

    Saqlain Abbas1,2,*, Zulkarnain Abbas3, Xiaotong Tu4, Yanping Zhu2

    Journal on Artificial Intelligence, Vol.5, pp. 43-56, 2023, DOI:10.32604/jai.2023.040948

    Abstract Structural health monitoring (SHM) is considered an effective approach to analyze the efficient working of several mechanical components. For this purpose, ultrasonic guided waves can cover long-distance and assess large infrastructures in just a single test using a small number of transducers. However, the working of the SHM mechanism can be affected by some sources of variations (i.e., environmental). To improve the final results of ultrasonic guided wave inspections, it is necessary to highlight and attenuate these environmental variations. The loading parameters, temperature and humidity have been recognized as the core environmental sources of variations that affect the SHM sensing… More >

  • Open Access

    ARTICLE

    An Overview of Seismic Risk Management for Italian Architectural Heritage

    Lucio Nobile*

    Structural Durability & Health Monitoring, Vol.17, No.5, pp. 353-368, 2023, DOI:10.32604/sdhm.2023.028247

    Abstract The frequent occurrence of seismic events in Italy poses a strategic problem that involves either the culture of preservation of historical heritage or the civil protection action aimed to reduce the risk to people and goods (buildings, bridges, dams, slopes, etc.). Most of the Italian architectural heritage is vulnerable to earthquakes, identifying the vulnerability as the inherent predisposition of the masonry building to suffer damage and collapse during an earthquake. In fact, the structural concept prevailing in these ancient masonry buildings is aimed at ensuring prevalent resistance to vertical gravity loads. Rarely do these ancient masonry structures offer relevant resistance… More >

  • Open Access

    ARTICLE

    Development of Features for Early Detection of Defects and Assessment of Bridge Decks

    Ahmed Silik1,2,7, Xiaodong Wang3, Chenyue Mei3, Xiaolei Jin3, Xudong Zhou4, Wei Zhou4, Congning Chen4, Weixing Hong1,2, Jiawei Li1,2, Mingjie Mao1,2, Yuhan Liu1,2, Mohammad Noori5,6,*, Wael A. Altabey8,*

    Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617

    Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet… More > Graphic Abstract

    Development of Features for Early Detection of Defects and Assessment of Bridge Decks

  • Open Access

    ARTICLE

    A Health Monitoring System Using IoT-Based Android Mobile Application

    Madallah Alruwaili1,*, Muhammad Hameed Siddiqi1, Kamran Farid2, Mohammad Azad1, Saad Alanazi1, Asfandyar Khan2, Abdullah Khan2

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2293-2311, 2023, DOI:10.32604/csse.2023.040312

    Abstract Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate, ECG, nasal/oral airflow, temperature, light sensor, and fall detection sensor. Different researchers have done different work in the field of health monitoring with sensor networks. Different researchers used built-in apps, such as some used a small number of parameters, while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate, and outdated tools for study development. While no efficient, cheap, and updated work is proposed in the field of sensor-based health monitoring systems. Therefore, this study developed… More >

  • Open Access

    ARTICLE

    Health Monitoring of Dry Clutch System Using Deep Learning Approach

    Ganjikunta Chakrapani, V. Sugumaran*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1513-1530, 2023, DOI:10.32604/iasc.2023.034597

    Abstract Clutch is one of the most significant components in automobiles. To improve passenger safety, reliability and economy of automobiles, advanced supervision and fault diagnostics are required. Condition Monitoring is one of the key divisions that can be used to track the reliability of clutch and allied components. The state of the clutch elements can be monitored with the help of vibration signals which contain valuable information required for classification. Specific drawbacks of traditional fault diagnosis techniques like high reliability on human intelligence and the requirement of professional expertise, have made researchers look for intelligent fault diagnosis techniques. In this article,… More >

  • Open Access

    ARTICLE

    Two-Way Approach for Improved Real-Time Transmission in Fog-IoT-Based Health Monitoring System for Critical Patients

    Abeera Ilyas1,*, Saeed Mahfooz1, Zahid Mehmood2,3, Gauhar Ali4, Muhammad ElAffendi4

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3815-3829, 2023, DOI:10.32604/csse.2023.036316

    Abstract Health monitoring systems are now required, particularly for essential patients, following the COVID-19 pandemic, which was followed by its variants and other epidemics of a similar nature. Effective procedures and strategies are required, though, to react promptly to the enormous volume of real-time data offered by monitoring equipment. Although fog-based designs for IoT health systems typically result in enhanced services, they also give rise to issues that need to be resolved. In this paper, we propose a two-way strategy to reduce network latency and use while increasing real-time data transmission of device gateways used for sensors by making educated judgments… More >

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