• Journal of the Korea institute for structural maintenance and inspection
• /
• v.18 no.6
• /
• pp.147-154
• /
• 2014

The cable damages of the bridge structures induce very important impact on the structural safety, which implies the close monitoring of the cable damage is required to secure sustained safety of the bridges. Most usual available maintenance techniques are based on the monitoring the change of the natural frequency of the structures by damages. However, existing method are based on vibration method to calculate lateral vibration and system identification can calculate the axial stiffness using sensitivity equation by trial error method. But the frequency study by the longitudinal movement need because of the sag effect in system identification. This study proposes a new method to investigate the damage magnitudes and status. The method improves the accuracies in the magnitudes and status of damages by adopting the natural frequency of longitudinal movement. The study results have been validated by comparing them with the approximate solution of FEM. Thus, the relationship of cable damage and frequency appear with relation that the severe damage has the little frequency. If we know the real frequency we can estimate the cable damage severity using this relationship. This method can be possible the efficient management of the cable damage.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.14 no.1
• /
• pp.43-53
• /
• 1990

The manufacturing errors such as pitch error and run-out error in planetary gear system bring about the irregular displacement of the center of each gear, which cause the torqe variation, vibration and noise. In this study, the relation between manufacturing errors and error motions of the center of gear was analyzed, and it can be applied to identyfy the errors of gears by investigating the measured locus of the center of each gear. Also, another identification method of power spectrum estimation using FFT algorithm was introduced, which analyze the frequency of the measured error motions. The results show that the error of each gear had a corresponding unique frequency, therefore, this method proved to be more effective.

• Journal of KSNVE
• /
• v.8 no.6
• /
• pp.1181-1192
• /
• 1998

This paper describes the performance of a full-authority neural network-based fault tolerant system within a flight control system. This fault tolerant flight control system integrates sensor and actuator failure detection, identification, and accommodation (SFDIA and AFDIA), The first task is achieved by incorporating a main neural network (MNN) and a set of n decentralized neural networks (DNNs) to create a system for achieving fault tolerant capabilities for a system with n sensors assumed to be without physical redundancy The second scheme implements the same main neural network integrated with three neural network controllers (NNCs). The function of NNCs is to regain equilibrium and to compensate for the pitching, rolling. and yawing moments induced by the failure. Particular emphasis is placed in this study toward achieving an efficient integration between SFDIA and AFDIA without degradation of performance in terms of false alarm rates and incorrect failure identification. The results of the simulation with different actuator and sensor failures are presented and discussed.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.1
• /
• pp.106-113
• /
• 2008

The starter motor noise is usually well identified by the customers since it is operated while the engine is quiet, and leaves distinct impressions of the vehicle. In this study the design of experiments(DOE) was applied to the identification of the noise sources of direct drive starter motor since this process usually requires lengthy analysis and elaborate experiments. In the first stage of the test, five controllable factors(alignment and dynamic unbalance of armature, tightening torques of T/bolt and center bracket bolt, and alignment of the center bracket-yoke-rear bracket), excluding static unbalance, are sorted out of all possible factors. Test results showed that the dynamic unbalance and misalignment of armature are the major factors. However, the error level of the first test was relatively high, indicating that there might be some missing major factors. In the second stage test the results showed that both static and dynamic unbalances are the dominant factors contributing to more than 80% of the overall noise, while the misalignment contributes around 12%. Error of the second test was about 4% that could be considered satisfactory. The noise level of the optimal product was predicted to be reduced by 19dBA, and verification test showed the average noise reduction of 16.8dBA with the standard deviation of 3.2dBA, and proved the usefulness of the whole DOE process.

• Computational Structural Engineering
• /
• v.10 no.3
• /
• pp.157-165
• /
• 1997

This research aims to develop an algorithm of optimal transducer placement for health monitoring of large structural system. The structural vibration response-based health monitoring is considered one of the best for the system which requires a long-term, continuous monitoring. In its experimental modal testing, however, it is difficult to decide on the measurement locations and their number, especially for complex structures, which have a major influence on the quality of the results. In order to minimize the number of sensing operations and optimize the transducer location while maximizing the accuracy of results, this paper discusses about an optimum transducer placement criterion suitable for the identification of structural damage for continuous health monitoring. As a criterion algorithm, it proposes the Kinetic Energy Optimization Technique (EOT), and then addresses the numerical issues which are subsequently applicable to actual experiment where a bridge model is used. By using the experimental data, it compares the EOT with the EIM(Effective Indefence Method) which is generally used to optimize the transducer placement for the damage identification and control purposes. The comparison conclusively shows that the EOT algorithm proposed in this paper is preferable when a structure is to be instrumented with fewer sensors for monitoring purpose.

• Journal of the Korean Society for Precision Engineering
• /
• v.22 no.8 s.173
• /
• pp.143-150
• /
• 2005

To verify applicability of multi-dimensional spectral analysis (MDSA) fur noise source identification two different approaches which are frequency response and coherent function have been investigated. The coherence function approach appears able to separate the correlated system when the noise sources were coherent. In this study, we identify contribution of structure-borne-noise of vehicle HVAC system using MDSA method. Firstly, to identify the applicability of MDSA method, 4-inputs of vehicle HVAC system were the signals measured by accelerometers attached on the selected noise sources which were composed of blower, evaporator, heater and duct. While 1-output which was driver's position sound was the SPL signals measured by a remote microphone, when the blower motor was operating. We identify efficiency of systems modeled with four Inputs/single output through ordinary coherence function (OCF) and partial coherence function (PCF). As a result of experiment, the blower accounted for $62-88\%$ of the overall level of sound energy density. Also, according to the analysis of acoustic signal and vibration signals measurement, an investigation of the noise source identification in the vehicle HVAC is presented. With the sound intensity method, the major sources of the vehicle HVAC radiation are verified. Also the method of improving the noise reduction is proposed by attaching damping patch access to blower motor and noise reduction is verified.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.34 no.1
• /
• pp.38-43
• /
• 2014

An experimental method based on flexural wave propagation is proposed for identification of structural damage in rail fastening systems. The vibration of a rail clamped and supported by viscoelastic pads is significantly influenced by dynamic support properties. Formation of a defect in the rail fastening system induces changes in the flexural wave propagation characteristics owning to the discontinuity in the structural properties. In this study, frequency-dependent support stiffness was measured to monitor this change by a transfer function method. The sensitivity of wave propagation on the defect was measured from the potential energy stored in a continuously supported rail. Further, the damage index was defined as a correlation coefficient between the change in the support stiffness and the sensitivity. The defect location was identified from the calculated damage index.

• Smart Structures and Systems
• /
• v.6 no.9
• /
• pp.1057-1077
• /
• 2010

An early detection of structural damages is critical for the decision making of repair and replacement maintenance in order to guarantee a specified structural reliability. Consequently, the structural damage detection, based on vibration data measured from the structural health monitoring (SHM) system, has received considerable attention recently. The traditional time-domain analysis techniques, such as the least square estimation (LSE) method and the extended Kalman filter (EKF) approach, require that all the external excitations (inputs) be available, which may not be the case for some SHM systems. Recently, these two approaches have been extended to cover the general case where some of the external excitations (inputs) are not measured, referred to as the adaptive LSE with unknown inputs (ALSE-UI) and the adaptive EKF with unknown inputs (AEKF-UI). Also, new analysis methods, referred to as the adaptive sequential non-linear least-square estimation with unknown inputs and unknown outputs (ASNLSE-UI-UO) and the adaptive quadratic sum-squares error with unknown inputs (AQSSE-UI), have been proposed for the damage tracking of structures when some of the acceleration responses are not measured and the external excitations are not available. In this paper, these newly proposed analysis methods will be compared in terms of accuracy, convergence and efficiency, for damage identification of structures based on experimental data obtained through a series of laboratory tests using a scaled 3-story building model with white noise excitations. The capability of the ALSE-UI, AEKF-UI, ASNLSE-UI-UO and AQSSE-UI approaches in tracking the structural damages will be demonstrated and compared.

• Smart Structures and Systems
• /
• v.6 no.7
• /
• pp.835-849
• /
• 2010

This study investigated propagation characteristics of piezo-activated guided waves in an aluminium rectangular-section tube for the purpose of damage identification. Changes in propagating velocity and amplitude of the first wave packet in acquired signals were observed in the frequency range from 50 to 250 kHz. The difference in guided wave propagation between rectangular- and circular-section tubes was examined using finite element simulation, demonstrating a great challenge in interpretation of guided wave signals in rectangular-section tubes. An active sensor network, consisting of nine PZT elements bonded on different surfaces of the tube, was configured to collect the wave signals scattered from through-thickness holes of different diameters. It was found that guided waves were capable of propagating across the sharp tube curvatures while retaining sensitivity to damage, even that not located on the surfaces where actuators/sensors were attached. Signal correlation between the intact and damaged structures was evaluated with the assistance of a concept of digital damage fingerprints (DDFs). The probability of the presence of damage on the unfolded tube surface was thus obtained, by which means the position of damage was identified with good accuracy.

• Earthquakes and Structures
• /
• v.12 no.4
• /
• pp.425-436
• /
• 2017

Vibration control using a tuned mass damper (TMD) is an effective technique that has been verified using analytical methods and experiments. It has been applied in mechanical, automotive, and structural applications. However, the damping of a TMD cannot be adjusted in real time. An excessive mass damper stroke may be introduced when the mass damper is subjected to a seismic excitation whose frequency content is within its operation range. The semi-active tuned mass damper (SATMD) has been proposed to solve this problem. The parameters of an SATMD can be adjusted in real time based on the measured structural responses and an appropriate control law. In this study, a stiffness-controllable TMD, called a leverage-type stiffness-controllable mass damper (LSCMD), is proposed and fabricated to verify its feasibility. The LSCMD contains a simple leverage mechanism and its stiffness can be altered by adjusting the pivot position. To determine the pivot position of the LSCMD in real time, a discrete-time direct output-feedback active control law that considers delay time is implemented. Moreover, an identification test for the transfer function of the pivot driving and control systems is proposed. The identification results demonstrate the target displacement can be achieved by the pivot displacement in 0-2 Hz range and the control delay time is about 0.1 s. A shaking-table test has been conducted to verify the theory and feasibility of the LSCMD. The comparisons of experimental and theoretical results of the LSCMD system show good consistency. It is shown that dynamic behavior of the LSCMD can be simulated correctly by the theoretical model and that the stiffness can be properly adjusted by the pivot position. Comparisons of experimental results of the LSCMD and passive TMD show the LSCMD with less demand on the mass damper stroke than that for the passive TMD.