• Smart Structures and Systems
• /
• 제33권2호
• /
• pp.93-103
• /
• 2024

Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

• Smart Structures and Systems
• /
• 제11권5호
• /
• pp.477-496
• /
• 2013

Due to their cost-effectiveness and ease of installation, wireless smart sensors (WSS) have received considerable recent attention for structural health monitoring of civil infrastructure. Though various wireless smart sensor networks (WSSN) have been successfully implemented for full-scale structural health monitoring (SHM) applications, monitoring of low-level ambient strain still remains a challenging problem for WSS due to A/D converter (ADC) resolution, inherent circuit noise, and the need for automatic operation. In this paper, the design and validation of high-precision strain sensor board for the Imote2 WSS platform and its application to SHM of a cable-stayed bridge are presented. By accurate and automated balancing of the Wheatstone bridge, signal amplification of up to 2507-times can be obtained, while keeping signal mean close to the center of the ADC span, which allows utilization of the full span of the ADC. For better applicability to SHM for real-world structures, temperature compensation and shunt calibration are also implemented. Moreover, the sensor board has been designed to accommodate a friction-type magnet strain sensor, in addition to traditional foil-type strain gages, facilitating fast and easy deployment. The wireless strain sensor board performance is verified through both laboratory-scale tests and deployment on a full-scale cable-stayed bridge.

• Journal of Ocean Engineering and Technology
• /
• 제25권4호
• /
• pp.59-65
• /
• 2011

In structural health monitoring (SHM) using electro-mechanical impedance signatures, it is a critical issue for extremely large structures to extract the best damage diagnosis results, while minimizing unknown environmental effects, including temperature, humidity, and acoustic vibration. If the impedance signatures fluctuate because of these factors, these fluctuations should be eliminated because they might hide the characteristics of the host structural damages. This paper presents a long-term SHM technique under an unknown noisy environment for tidal current power plant structures. The obtained impedance signatures contained significant variations during the measurements, especially in the audio frequency range. To eliminate these variations, a continuous principal component analysis was applied, and the results were compared with the conventional approach using the RMSD (Root Mean Square Deviation) and CC (Cross-correlation Coefficient) damage indices. Finally, it was found that this approach could be effectively used for long-term SHM in noisy environments.

• Structural Monitoring and Maintenance
• /
• 제3권1호
• /
• pp.91-114
• /
• 2016

In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

• Structural Monitoring and Maintenance
• /
• 제3권1호
• /
• pp.1-32
• /
• 2016

This paper describes the backgrounds, motivations and recent history of structural health monitoring (SHM) developments to various types of engineering structures. Extensive applications of SHM technologies in bridges, high-rise buildings, sport avenues, offshore platforms, underground structures, dams, etc. in mainland China are summarily categorized and listed in tables. Sensors used in implementations, their deployment, damage identification strategies if applicable, preliminary monitoring achievements and experience are presented in the lists. Finally, existing problems and promising research efforts in civil SHM are discussed, highlighting challenges and future trends.

• Smart Structures and Systems
• /
• 제4권4호
• /
• pp.449-464
• /
• 2008

An array based, outward monitoring, ultrasonic guided wave based SHM technique using a single transmitter and multiple receivers (STMR), with a small footprint is discussed here. The previous implementation of such SHM arrays used a phase-reconstruction algorithm (that is similar to the beam-steering algorithm) for the imaging of reflectors. These algorithms were found to have a limitation during the imaging of defects/reflectors that are present in the "near-field" of the array. Here, the "near-field" is defined to be approximately 3-4 times the diameter of the compact array. This limitation is caused by approximations in the beam-steering reconstruction algorithm. In this paper, a migration-based reconstruction algorithm, with dispersion correction in the frequency domain, is discussed. Simulation and experimental studies are used to demonstrate that this algorithm improves the reconstruction in the "near-field" without decreasing the ability to reconstruct defects in the "far-field" in both isotropic and anisotropic plates.

• Journal of Power Electronics
• /
• 제17권5호
• /
• pp.1186-1194
• /
• 2017

This paper proposes an improved low frequency Selective Harmonic Mitigation-PWM (SHM-PWM) technique. The proposed method mitigates the low order harmonics of the output voltage up to the $50^{th}$ harmonic well and satisfies the grid codes EN 50160 and CIGRE-WG 36-05. Using a modified criterion for the switching angles, the range of the modulation index for non-linear SHM equations is improved, without increasing the switching frequency of the CHB converter. Due to the low switching frequency of the CHB converter, mitigating the harmonics of the converter up to the $50^{th}$ order and finding a wider modulation index range, the size and cost of the passive filters can be significantly reduced with the proposed technique. Therefore, the proposed technique is more efficient than the conventional SHM-PWM. To verify the effectiveness of the proposed method, a 7-level Cascaded H-bridge (CHB) converter is utilized for the study. Simulation and experimental results confirm the validity of the above claims.

• Smart Structures and Systems
• /
• 제5권4호
• /
• pp.357-367
• /
• 2009

Structural Health Monitoring (SHM), particularly remote monitoring, is an emerging field with great potential to help infrastructure owners obtain more and up-to-date knowledge of their structures. The methodology could provide supplemental information to guide the frequency and extent of visual inspections, and the possible need for maintenance. The instrumentation for a SHM system needs to be developed with longevity and the objectives for the system in mind. Sensors need to be selected for reliability and durability, sited where they provide the maximum information for the objectives, and where they can be accessed and replaced should the need arise over the monitoring period. With the rapid changes now occurring with sensors and software, flexibility needs to be in place to allow the system to be upgraded over time. Damage detection needs to be considered in terms of the type of damage that needs to be detected, informing maintenance requirements, and how detection can be achieved. Current vibration analysis techniques appear not yet to have achieved the necessary sensitivity for that purpose. Societal factors will influence the design of a SHM system in terms of the sophistication of the instrumentation and methodology employed.

• Smart Structures and Systems
• /
• 제6권3호
• /
• pp.335-347
• /
• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

• Smart Structures and Systems
• /
• 제5권4호
• /
• pp.457-468
• /
• 2009

A novel approach for integrating active sensing data interrogation algorithms for structural health monitoring (SHM) applications is presented. These algorithms cover Lamb wave propagation, impedance methods, and sensor diagnostics. Contrary to most active-sensing SHM techniques, which utilize only a single signal processing method for damage identification, a suite of signal processing algorithms are employed and grouped into one package to improve the damage detection capability. A MATLAB-based user interface, referred to as HOPS, was created, which allows the analyst to configure the data acquisition system and display the results from each damage identification algorithm for side-by-side comparison. By grouping a suite of algorithms into one package, this study contributes to and enhances the visibility and interpretation of the active-sensing methods related to damage identification. This paper will discuss the detailed descriptions of the damage identification techniques employed in this software and outline future issues to realize the full potential of this software.