• Structural Monitoring and Maintenance
• /
• v.9 no.2
• /
• pp.107-127
• /
• 2022

Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.

• Structural Engineering and Mechanics
• /
• v.86 no.6
• /
• pp.715-730
• /
• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• International Journal of Automotive Technology
• /
• v.8 no.1
• /
• pp.75-82
• /
• 2007

This paper presents practical work on the reduction of gear whine noise. In order to identify the source of the gear whine noise, transfer paths are searched and analyzed by operational deflection shape analysis and experimental modal analysis. It was found that gear whine noise has an air-borne noise path instead of structure-borne noise path. The main sources of air-borne noise were the two global modes caused by the resonance of an axle system. These modes created a vibro-acoustic noise problem. Vibro-acoustic noise can be reduced by controlling the vibration of the noise source. The vibration of noise source is controlled by the modification of structure to avoid the resonance or to reduce the excitation force. In the study, the excitation force of the axle system is attenuated by changing the tooth profile of the hypoid gear. The modification of the tooth profile yields a reduction of transmission error, which is correlated to the gear whine noise. Finally, whine noise is reduced by 10 dBA.

• Smart Structures and Systems
• /
• v.6 no.4
• /
• pp.373-388
• /
• 2010

The updated finite element model of K$\ddot{o}$m$\ddot{u}$rhan Highway Bridge on the Firat River located on the $51^{st}$ km of Elazi$\breve{g}$-Malatya highway is obtained by using analytical and experimental results. The 2D and 3D finite element model of the bridge is created by using SAP2000 structural analyses software, and the dynamic characteristics of the bridge are determined analytically. The experimental measurements are carried out by Operational Modal Analysis Method under traffic induced vibrations and the dynamic characteristics are obtained experimentally. The vibration data are gathered from the both box girder and the deck of the bridge, separately. Due to the expansion joint in the middle of the bridge, special measurement points are selected when experimental test setups constitute. Measurement duration, frequency span and effective mode number are determined by considering similar studies in literature. The Peak Picking method in the frequency domain is used in the modal identification. At the end of the study, analytical and experimental dynamic characteristic are compared with each other and the finite element model of the bridge is updated by changing some uncertain parameters such as material properties and boundary conditions. Maximum differences between the natural frequencies are reduced from 10% to 2%, and a good agreement is found between natural frequencies and mode shapes after model updating.

• Smart Structures and Systems
• /
• v.17 no.3
• /
• pp.391-411
• /
• 2016

This study investigates the mode identifiability of a multi-span cable-stayed bridge in terms of a benchmark study using stabilization diagrams of a system model identified using stochastic subspace identification (SSI). Cumulative contribution ratios (CCRs) estimated from singular values of system models under different wind conditions were also considered. Observations revealed that wind speed might influence the mode identifiability of a specific mode of a cable-stayed bridge. Moreover the cumulative contribution ratio showed that the time histories monitored during strong winds, such as those of a typhoon, can be modeled with less system order than under weak winds. The blind data Acc 1 and Acc 2 were categorized as data obtained under a typhoon. Blind data Acc 3 and Acc 4 were categorized as data obtained under wind conditions of critical wind speeds around 7.5 m/s. Finally, blind data Acc 5 and Acc 6 were categorized as data measured under weak wind conditions.

• Wind and Structures
• /
• v.15 no.4
• /
• pp.285-299
• /
• 2012

This paper describes the development and calibration of a structural monitoring system installed in a 80 meters high steel wind tower supporting a 2.1 MW turbine Wind Class III IEC2a erected in the central part of Portugal. The several signals are measured at four different levels and include accelerations, strains on the tower wall and inside the connection bolts, inclinations and temperature. In order to correlate measurements with the wind velocity and direction and with the turbine operational parameters the corresponding signals are obtained directly from the turbine own monitoring system and are incorporated in the developed system. Results from the system calibration, the structural identification and the initial period of data acquisition are presented in this paper.

• Smart Structures and Systems
• /
• v.33 no.2
• /
• pp.165-175
• /
• 2024

Rotating beams play a crucial role in representing complex mechanical components that are prevalent in vital sectors like energy and transportation industries. These components are susceptible to the initiation and propagation of cracks, posing a substantial risk to their structural integrity. This study presents a two-stage methodology for detecting the location and estimating the size of an open-edge transverse crack in a rotating Euler-Bernoulli beam with a uniform cross-section. Understanding the dynamic behavior of beams is vital for the effective design and evaluation of their operational performance. In this regard, modal parameters such as natural frequencies and eigenmodes are frequently employed to detect and identify damages in mechanical components. In this instance, the Frobenius method has been employed to determine the first two natural frequencies and corresponding eigenmodes associated with flapwise bending vibration. These calculations have been performed by solving the governing differential equation that describes the motion of the beam. Various parameters have been considered, such as rotational speed, beam slenderness, hub radius, and crack size and location. The effect of the crack has been replaced by a rotational spring whose stiffness represents the increase in local flexibility as a result of the damage presence. In the initial phase of the proposed methodology, a damage index utilizing the slope of the beam's eigenmode has been employed to estimate the location of the crack. After detecting the presence of damage, the size of the crack is determined using a Genetic Algorithm optimization technique. The ultimate goal of the proposed methodology is to enable the development of more suitable and reliable maintenance plans.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.16 no.3
• /
• pp.23-33
• /
• 2012

Dynamic response measurements from natural excitation were carried out for three 18-story office buildings to determine their inherent properties. The beam-column frame system was adopted as a typical structural form, but a core wall was added to resist the lateral force more effectively, resulting in a mixed configuration. To extract modal parameters such as natural frequencies, mode shapes and damping ratios from a series of vibration records at each floor, the most advanced operational system identification methods based on frequency- and time-domain like FDD, pLSCF and SSI were applied. Extracted frequencies and mode shapes from the different identification methods showed a greater consistency for three buildings, however the three lower frequencies extracted were 1.2 to 1.7 times as stiff as those obtained using the initial FE models. Comparing the extracted fundamental periods with those estimated from the code equations and FE analysis, the FE analysis results showed the most flexible behavior, and the most simple equation that considers the building height as the only parameter correlated fairly well with test results. It is recognized that such a discrepancy arises from the fact that the present tests exclude the stiffness decreasing factors like concrete cracking, while the FE models ignore the stiffness increasing factors, such as the contribution of non-structural elements and the actual material properties used.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.561-578
• /
• 2010

This study proposes a multi-level damage localization strategy to achieve an effective damage detection system for civil infrastructure systems based on wireless sensors. The proposed system is designed for use of distributed computation in a wireless sensor network (WSN). Modal identification is achieved using the frequency-domain decomposition (FDD) method and the peak-picking technique. The ASH (angle-between-string-and-horizon) and AS (axial strain) flexibility-based methods are employed for identifying and localizing damage. Fundamentally, the multi-level damage localization strategy does not activate all of the sensor nodes in the network at once. Instead, relatively few sensors are used to perform coarse-grained damage localization; if damage is detected, only those sensors in the potentially damaged regions are incrementally added to the network to perform finer-grained damage localization. In this way, many nodes are able to remain asleep for part or all of the multi-level interrogations, and thus the total energy cost is reduced considerably. In addition, a novel distributed computing strategy is also proposed to reduce the energy consumed in a sensor node, which distributes modal identification and damage detection tasks across a WSN and only allows small amount of useful intermediate results to be transmitted wirelessly. Computations are first performed on each leaf node independently, and the aggregated information is transmitted to one cluster head in each cluster. A second stage of computations are performed on each cluster head, and the identified operational deflection shapes and natural frequencies are transmitted to the base station of the WSN. The damage indicators are extracted at the base station. The proposed strategy yields a WSN-based SHM system which can effectively and automatically identify and localize damage, and is efficient in energy usage. The proposed strategy is validated using two illustrative numerical simulations and experimental validation is performed using a cantilevered beam.

• Smart Structures and Systems
• /
• v.17 no.3
• /
• pp.363-389
• /
• 2016

Deficient modes that cannot be always identified from different sets of measurement data may exist in the application of operational modal analysis such as the stochastic subspace identification techniques in large-scale civil structures. Based on a recent work using the long-term ambient vibration measurements from an instrumented cable-stayed bridge under different wind excitation conditions, a benchmark problem is launched by taking the same bridge as a test bed to further intensify the exploration of mode identifiability. For systematically assessing this benchmark problem, a recently developed SSI algorithm based on an alternative stabilization diagram and a hierarchical sifting process is extended and applied in this research to investigate several sets of known and blind monitoring data. The evaluation of delicately selected cases clearly distinguishes the effect of traffic excitation on the identifiability of the targeted deficient mode from the effect of wind excitation. An additional upper limit for the vertical acceleration amplitude at deck, mainly induced by the passing traffic, is subsequently suggested to supplement the previously determined lower limit for the wind speed. Careful inspection on the shape vector of the deficient mode under different excitation conditions leads to the postulation that this mode is actually induced by the motion of the central tower. The analysis incorporating the tower measurements solidly verifies this postulation by yielding the prevailing components at the tower locations in the extended mode shape vector. Moreover, it is also confirmed that this mode can be stably identified under all the circumstances with the addition of tower measurements. An important lesson learned from this discovery is that the problem of mode identifiability usually comes from the lack of proper measurements at the right locations.