• Smart Structures and Systems
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• 제11권4호
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• pp.349-364
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• 2013

Recently, researchers in the field of structural health monitoring (SHM) have been rigorously striving to replace the conventional NDE techniques with the smart material based SHM techniques, employing smart materials such as piezoelectric materials. For instance, the electromechanical impedance (EMI) technique employing piezo-impedance (lead zirconate titanate, PZT) transducer is known for its sensitivity in detecting local damage. For practical applications, various external factors such as fluctuations of temperature and loading, affecting the effectiveness of the EMI technique ought to be understood and compensated. This paper aims at investigating the damage monitoring capability of EMI technique in the presence of axial stress with fixed boundary condition. A compensation technique using effective frequency shift (EFS) by cross-correlation analysis was incorporated to compensate the effect of loading and boundary stiffening. Experimental tests were conducted by inducing damages on lab-sized aluminium beams in the presence of tensile and compressive forces. Two types of damages, crack propagation and bolts loosening were simulated. With EFS for compensation, both cross-correlation coefficient (CC) index and reduction in peak frequency were found to be efficient in characterizing damages in the presence of varying axial loading.

• 한국가시화정보학회:학술대회논문집
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• 한국가시화정보학회 2006년도 추계학술대회 논문집
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• pp.96-101
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• 2006

3-D visualization using confocal laser scanning microscopy (CLSM) in a chaotic micromixer was performed as a reproduction experiment and the feasibility of 3-0 imaging technique in the microscale was confirmed. For diagonal micromixer (DM) and two types of staggered herringbone micromixers (SHM) designed by Whitesides et al., to verify the evolution of mixing, cross sectional images are reconstructed at the end of every cycle. In a DM, clockwise rotational flow motion generated by diagonal ridges placed on the floor of micromixer is observed and this motion makes the fluid commingle. On the contrary, there are two rotational flow structures in the SHM and the centers of rotation exchange their position each other every half cycle because of the V shape of ridges varying their orientation every half cycle. Local rotational flow and local extensional flow generated by the complicate ridge pattern make the flow be chaotic and accelerate the mixing of fluid. The dominant parameter that influences on the mixing characteristic of SHM is not the length of micromixer but the number of ridges under the same flow configurations.

• Smart Structures and Systems
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• 제23권3호
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• pp.295-306
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• 2019

Shanghai Tower is a 632-meter super high-rise building located in an area with wind and active earthquake. A sophisticated structural health monitoring (SHM) system consisting of more than 400 sensors has been built to carry out a long-term monitoring for its operational safety. In this paper, a reduced-order model including 31 elements was generated from a full model of this super tall building. An iterative regularized matrix method was proposed to tune the system parameters, making the dynamic characteristic of the reduced-order model be consistent with those in the full model. The updating reduced-order model can be regarded as a benchmark model for further analysis. A long-term monitoring for structural dynamic characteristics of Shanghai Tower under different construction stages was also investigated. The identified results, including natural frequency and damping ratio, were discussed. Based on the data collected from the SHM system, the dynamic characteristics of the whole structure was investigated. Compared with the result of the finite element model, a good agreement can be observed. The result provides a valuable reference for examining the evolution of future dynamic characteristics of this super tall building.

• Smart Structures and Systems
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• 제24권3호
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• pp.319-332
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• 2019

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.

• Structural Monitoring and Maintenance
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• 제8권4호
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Smart Structures and Systems
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• 제33권3호
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• 한국산학기술학회논문지
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• 제22권5호
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• pp.81-88
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• 2021

최근 지진 빈도 증가로 구조물 건전도 모니터링 (SHM: Structural Health Monitoring, 이하 SHM) 시스템에 대한 관심이 증가하고 있다. Smart concrete는 전기-역학적 거동을 바탕으로 구조물 상태를 분석할 수 있는 기술이다. 하지만 콘크리트 구조물은 지진 시 정적 변형률 또는 하중 속도 보다 10배 이상 빠른 하중 속도가 작용하나 기존 연구 대부분은 정적 하중 속도에서의 감지 능력을 주로 조사하고 있다. 본 연구는 지진과 같이 높은 하중 속도에서 자가 응력감지 능력을 평가하기 위해 만능재료시험기 (UTM: Universal Testing Machine, 이하 UTM)를 사용하여 3가지 하중 재하 속도 (1, 4, 8 mm/min) 하에서 Smart Ultra High Performance Concrete (S-UHPC)의 전기-역학적 거동을 측정하였다. S-UHPC의 최대 압축 하중에서 Stress sensitive Coefficient (SC)는 1 mm/min 하중 속도 기준 -0.140%/MPa로 측정되었으나, 하중 속도가 각각 4, 8 mm/min으로 증가함에 따라 42.8 %, 72.7% 감소하였다. 전도성 재료의 변형 감소, 미세균열 증가로 인하여 S-UHPC의 감지능력이 하중속도 증가에 따라 감소하였지만, 그럼에도 불구하고 높은 하중 속도 하에서도 우수한 감지 성능을 보여 구조물 지진 하중 감지를 위한 SHM 시스템에 활용 가능함을 확인하였다.

• 한국염색가공학회:학술대회논문집
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• 한국염색가공학회 2008년도 제38차 학술발표대회
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• pp.135-137
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• 2008

PVA films with 1,2,3,4-Butanetetracarboxylic acid(BTCA) and sodium hypophosphite monohydrate(SHM) were crosslinked via thermal curing. Different parameters affecting on the crosslinking were investigated including BTCA and SHM concentration, curing temperature and time. The cured films was extracted with boiling water and gel fraction was calculated from weight change of the PVA films. Moisture regain of the gelled films was also measured. While the gel fraction of PVA films increased with increasing curing temperature and time, moisture regain decreased. Water resistance of the crosslinked PVA films improved by the BTCA crosslinking treatment.

• Smart Structures and Systems
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• 제11권5호
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• pp.511-531
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• 2013

Recent advances in low-cost remote monitoring systems have made it possible and practical to perform structural health monitoring (SHM) on a large scale. However, it is difficult for a single remote monitoring system to cover a wide range of SHM applications due to the amount of specialization required. For the remote monitoring system to be flexible, sustainable, and robust, this article introduces a new cost-effective, advanced remote monitoring and inspection system named DuraMote that can serve as a next generation supervisory control and data acquisition (SCADA) system for civil infrastructure systems. To evaluate the performance of DuraMote, we conduct experiments at two representative counterpart sites: a bridge and water pipelines. The objectives of this article are to improve upon the existing SCADA by integrating the remote monitoring system (i.e., DuraMote), to describe a prototype SCADA for civil engineering structures, and to validate its effectiveness with long-term field deployment results.

• Smart Structures and Systems
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• 제20권1호
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• pp.35-42
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• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.