scholarly journals Stretching Method-Based Operational Modal Analysis of An Old Masonry Lighthouse

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3599 ◽  
Author(s):  
Emmanouil Daskalakis ◽  
Christos G. Panagiotopoulos ◽  
Chrysoula Tsogka ◽  
Nikolaos S. Melis ◽  
Ioannis Kalogeras
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Natural Frequencies ◽  
Time Window ◽  
Structural Vibration ◽  
Actual State ◽  
Time Interval ◽  
Actual Measurement ◽  
Damage Scenarios ◽  
Structural Health

We present in this paper a structural health monitoring study of the Egyptian lighthouse of Rethymnon in Crete, Greece. Using structural vibration data collected on a limited number of sensors during a 3-month period, we illustrate the potential of the stretching method for monitoring variations in the natural frequencies of the structure. The stretching method compares two signals, the current that refers to the actual state of the structure, with the reference one that characterizes the structure at a reference healthy condition. For the structure under study, an 8-day time interval is used for the reference quantity while the current quantity is computed using a time window of 24 h. Our results indicate that frequency shifts of 1% can be detected with high accuracy allowing for early damage assessment. We also provide a simple numerical model that is calibrated to match the natural frequencies estimated using the stretching method. The model is used to produce possible damage scenarios that correspond to 1% shift in the first natural frequencies. Although simple in nature, this model seems to deliver a realistic response of the structure. This is shown by comparing the response at the top of the structure to the actual measurement during a small earthquake. This is a preliminary study indicating the potential of the stretching method for structural health monitoring of historical monuments. The results are very promising. Further analysis is necessary requiring the deployment of the instrumentation (possibly with additional instruments) for a longer period of time.

scholarly journals A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

2018 ◽  
Vol 18 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Mehrisadat Makki Alamdari ◽  
Nguyen Lu Dang Khoa ◽  
Yang Wang ◽  
Bijan Samali ◽  
Xinqun Zhu
Keyword(s):  
Data Analysis ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Scale ◽  
Damage Identification ◽  
Tensor Analysis ◽  
Support Vector ◽  
Damage Scenarios ◽  
Structural Health ◽  
Cable Stayed Bridge

A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated; damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold; first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation; second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification; and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities.

scholarly journals Online frequency and amplitude tracking in structural vibrations under environment using APES spectrum postprocessing and Kalman filtering

2021 ◽  
Author(s):  
Xuewen Yu ◽  
Danhui Dan
Keyword(s):  
Structural Health Monitoring ◽  
Kalman Filtering ◽  
Health Monitoring ◽  
Time Window ◽  
Numerical Study ◽  
Amplitude Spectrum ◽  
Real Life ◽  
Structural Vibrations ◽  
Vibration Signals ◽  
Structural Health

Identifying time-varying frequency and amplitude online in real-life structural vibrations is an essential topic of data processing in structural health monitoring. This paper proposes a novel method for this task. We assume that structural vibration signals are stationary in a short time, thus a spectral analysis method called amplitude and phase estimation (APES) is conducted to obtain the amplitude spectrum at corresponding time window, and a postprocessing technique is proposed to extract the modal frequency and amplitude from the spectrum automatically. The extracted frequency and amplitude could be regarded as the average of the instantaneous frequency and instantaneous amplitude during the window. Due to the instability of measured structural vibrations and the uncertainty of spectral shapes under ambient excitation, Kalman ?filtering is introduced by taking the signal that reconstructed from the identi?fied frequencies and amplitudes as the prediction to enhance the reliability and quality (signal-to-noise ratio) of the next measured signals. Numerical study is performed to inspect the performance of the proposed method. It is also employed to analyze the vibration signals of actual structures, i.e., a cable of a cable-stayed bridge, a hanger of an arch bridge and the main girder of a suspension bridge. The results show its potential to track frequency and amplitude in structural vibrations under environmental measurements. The method is supposed to provide fundamental support for further information obtaining and high-level decision making for structural health monitoring systems.

scholarly journals Use of damping identification technique for damage detection

2018 ◽  
Vol 148 ◽  
pp. 14004
Author(s):  
Vikas Arora
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Natural Frequencies ◽  
Monitoring Methods ◽  
Structural Health ◽  
Damping Matrix ◽  
Step Procedure ◽  
Damage Structure ◽  
Identification Technique

Stiffness-based structural health monitoring methods are widely used for detecting the damage in a structure. These stiffness-based structural health monitoring methods uses change in natural frequencies and modeshapes for damage detection. These methods are based on identifying the change in stiffness of the healthy and damage structure to predict the damage in the structure. These stiffness-based methods are not efficient for detecting a small damage in a structure as there is a negligible change in natural frequencies and modeshapes due to a small damage in a structure, however the damping characteristics of the structure are highly sensitive to the damage in a structure. In this paper, new damping-based damage detection procedure has been proposed. In the proposed procedure, the changes in damping matrix of the structure has been used to detect the damage in the structure. The proposed procedure is able (or can) to detect both the location of the damage and the extend of the damage in the structure. The proposed procedure of damping-based damage detection is a 2-step procedure. In the first step, damping matrices of both the healthy and damage structure are identified and in the second step, the identified damping matrices are used for damage detection. Numerical and experimental case studies are presented to demonstrate the effectiveness of the proposed procedure. The results have shown that the proposed damping-based damage detection procedure can be used for detecting damage in a structure with confidence.

scholarly journals Output-only Structural Health Monitoring of a Riveted Steel Railway Bridge utilizing Proper Orthogonal Decomposition, Artificial Neural Network, and Strain Measurements

Proceedings ◽  
2018 ◽  
Vol 4 (1) ◽  
pp. 30
Author(s):  
Ahmed Rageh ◽  
Saeed Eftekhar Azam ◽  
Daniel Linzell
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Operational Conditions ◽  
Damage Scenarios ◽  
Structural Health ◽  
Damage Indices ◽  
Wide Range ◽  
Artificial Neural ◽  
Output Only ◽  
Proper Orthogonal

This study presents a new scheme for autonomous health monitoring of railroad infrastructure using a continuous stream of structural health monitoring data. The study utilized measured strains from an optimized sensor set deployed on a double track, steel, railway, truss bridge located in central Nebraska. The most common failure mode for the superstructure of this structural system is the stringer-to-floor beam connection failure, which was the focus of this study. However, the proposed methodology could be used to assess the condition of a wide range of structural elements and details. The damage feature adopted in this framework was the variations of Proper Orthogonal Modes (POMs) of the measured structural response. To automatically detect the occurrence, location, and intensity of deficiencies from the POMs, Artificial Neural Networks (ANN) were adopted. POM variations, which are traditionally input (load) dependent, were ultimately utilized as damage indicators. To alleviate the variability of POMs due to non-stationarity of the train loads, a preset windowing of measured output was completed in conjunction with automated peak-picking. Furthermore, input variability necessitated implementing ANNs to help decouple POM changes due to load variations from those caused by deficiencies, changes that would render the proposed framework input independent; a significant advancement. Damage “scenarios” were artificially introduced into select output (strain) datasets recorded while monitoring train passes across the selected bridge. This information, in turn, was used to train ANNs using MATLAB’s Neural Net Toolbox. Trained ANNs were tested against monitored loading events and artificial damage scenarios. Applicability of the proposed, output-only framework was investigated via studies of the bridge under operational conditions. To account for the effects of potential deficiencies at the stringer-to-floor beam connections, measured signal amplitudes were artificially decreased at select locations. Finally, to validate the applicability of the proposed method using low-cost measurement devices, the measured signals were corrupted by high levels of white, Gaussian noises featuring spatial correlations. It was concluded that the proposed framework could successfully identify 20 damage indices, which were artificially imposed on measured signals under operational conditions.

scholarly journals EVALUATION OF VIBRATION-BASED GLOBAL STRUCTURAL HEALTH MONITORING METHOD FOR MEDIUM-RISE BUILDINGS

2021 ◽  
Vol 1 ◽  
pp. 55-61
Author(s):  
Liga Gaile ◽  
Ivars Radins
Keyword(s):  
Reinforced Concrete ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Natural Frequencies ◽  
Construction And Demolition Waste ◽  
Structural Safety ◽  
Reinforced Concrete Buildings ◽  
Monitoring Method ◽  
Concrete Buildings ◽  
Structural Health

The automated monitoring of a building’s structural health during its exploitation is a way to extend its design life without compromising structural safety.  In turn, it helps increase the rate of building renovation works compared to demolition works, which reduces future construction and demolition waste levels.This research explores the vibration-based global monitoring method application to structurally stiff medium-rise reinforced concrete buildings by analysing predicted building vibration amplitudes and spectrum under regular city traffic excitation. These predictions are based on the results obtained from finite element calculations of building models with variated structural stiffness and inertial mass of the building.Regular traffic-generated ground frequency spectrum differs from the first natural frequencies of medium-rise reinforced concrete buildings, and the vibration energy is low. Nevertheless, it is found that the structural identification of such building dynamic parameters is still possible, particularly natural frequencies. It was found that the ratio between fundamental frequency for the fixed base model of the building and elastic spring foundation model is the decisive parameter for selecting the building part to be monitored. Structural health monitoring vibration-based methods are also a promising technology for medium-rise mass house buildings when tailored according to some damage sensitive feature.  

scholarly journals Application of Artificial Immune System in Structural Health Monitoring

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jiachen Zhang ◽  
Zhikun Hou
Keyword(s):  
Immune System ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Artificial Immune System ◽  
Structural Parameter ◽  
Artificial Immune ◽  
Damage Scenarios ◽  
Structural Health ◽  
Specific Parameter ◽  
Parameter Values

A large number of methods have been proposed in the area of structural health monitoring (SHM). However, many of them rely on the prior knowledge of structural-parameter-values or the assumption that the structural-parameter-values do not change without damage. This dependence on specific parameter values limits these methods’ applicability. This paper proposes an artificial immune system- (AIS-) based approach for the civil structural health monitoring, which does not require specific parameter values to work. A linear three-floor structure model and a number of single-damage scenarios were used to evaluate the proposed method’s performance. The high success rate showed this approach’s great potential for the SHM tasks. This approach has merits of less dependence on the structural-parameter-values and low demand on the training conditions.

scholarly journals On the Application of Laser Vibrometry to Perform Structural Health Monitoring in Non-Stationary Conditions of a Hydropower Dam

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3811 ◽  
Author(s):  
Mateja Klun ◽  
Dejan Zupan ◽  
Jože Lopatič ◽  
Andrej Kryžanowski
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Rapid Development ◽  
Laser Doppler Vibrometer ◽  
Vibration Monitoring ◽  
Hydropower Plant ◽  
Structural Vibration ◽  
Measurement Technology ◽  
Structural Health ◽  
Stationary Conditions

This paper presents the first application of the Laser Doppler Vibrometer (LDV) in non-stationary conditions within a hydropower plant powerhouse. The aim of this research is to develop a methodology to include non-contact vibration monitoring as part of structural health monitoring of concrete dams. We have performed in-situ structural vibration measurements on the run-of-the-river Brežice dam in Slovenia during the start-up tests and regular operation. In recent decades, the rapid development of laser measurement technology has provided powerful methods for a variety of measuring tasks. Despite these recent developments, the use of lasers for measuring has been limited to sites provided with stationary conditions. This paper explains the elimination of pseudo-vibration and measurement noise inherent in the non-stationary conditions of the site. Upon removal of the noise, fatigue of the different structural elements of the powerhouse could be identified if significant changes over time are observed in the eigenfrequencies. The use of laser technology is to complement the regular monitoring activities on large dams, since observation and analysis of integrity parameters provide indispensable information for decision making and maintaining good structural health of ageing dams.

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