• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.22 no.4
• /
• pp.349-354
• /
• 2009

To rationally secure and maintain the safety and serviceability of a high-rise building, monitoring of structural responses of members is necessary. As such health monitoring of large-scale building structures has received growing attention by researchers in recent years. However, due to a very large number of members complexity of structural responses of a high-rise building structure, practical difficulties exist in selection of structural members to be sensored for assessment of structural safety of a structure. In this paper, a selection technique for active members for safety monitoring of a high-rise building based on displacement participation factor and strain energy density of a member is investigated.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.29 no.5
• /
• pp.466-472
• /
• 2009

An acoustic leak monitoring system(ALMS) using acoustic emission(AE) technique was applied for leakage detection of nuclear power plant's pipeline which is operated in high temperature and pressure condition. Since this system only monitors the existence of leak using the root mean square(RMS) value of raw signal from AE sensor, the difficulty occurs when the characteristics of leak size and shape need to be evaluated. In this study, dual monitoring system using AE sensor and accelerometer was introduced in order to solve this problem. In addition, artificial neural network(ANN) with Levenberg.Marquardt(LM) training algorithm was also applied due to rapid training rate and gave the reliable classification performance. The input parameters of this ANN were extracted from varying signal received from experimental conditions such as the fluid pressure inside pipe, the shape and size of the leak area. Additional experiments were also carried out and with different objective which is to study the generation and characteristic of lamb and surface wave according to the pipe thickness.

• Structural Monitoring and Maintenance
• /
• v.3 no.4
• /
• pp.395-406
• /
• 2016

Modal parameter identification has received much attention recently for their usefulness in earthquake engineering, damage detection and structural health monitoring. The identification method based on Matrix Pencil technique is adopted in this paper to identify structural modal parameters, such as natural frequencies, damping ratios and modal shapes using impulse vibration responses. This method can also be applied to dynamic responses induced by stationary and white-noise inputs since the auto- and cross-correlation function of the two outputs has the same form as the impulse response dynamic functions. Matrix Pencil method is very robust to noise contained in the measurement data. It has a lower variance of estimates of the parameters of interest than the Polynomial Method, and is also computationally more efficient. The numerical simulation results show that this technique can identify modal parameters accurately even if the noise level is high.

• Journal of Advanced Marine Engineering and Technology
• /
• v.10 no.3
• /
• pp.1-10
• /
• 1986

This paper describes a new, effective method developed at the National Research Council Canada for rolling element bearing incipient failure detection. This method can detect not only outer race damage, previously published, but also inner race damage with a 100% detection rate based on a sample size of 32. The prediction of the exact angular location of the damage spot along the raceway is illustrated and experimental confirmation is presented. For the first time, a statically measurable parameter for inner and outer race damage is introduced as a means of verifying other techniques which do not offer absolute proof, but resort only to "overwhelming evidence". A brief comparison with other methods such as Shock Pulse Method, Kurtosis Analysis and High Frequency Resonance Technique is presented. A computerized automatic monitoring system utilizing the new method is described and experimental results are presented.presented.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.1 s.94
• /
• pp.53-62
• /
• 2005

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Composites Research
• /
• v.18 no.2
• /
• pp.46-51
• /
• 2005

An active inspection system using Lamb waves for structural health monitoring was considered in this paper. In order to understand the characteristics of the Lamb waves propagating in a composite plate, the experiment was performed for a quasi-isotropic composite plate with thickness variation. Lamb waves were generated and received by the thin PZT transducers bonded on the surface. In this test, a simple new technique was tried for characterizing the Lamb waves propagating across the discontinuity due to the thickness variation. The results showed that Lamb waves were more sensitive to the thinner plate with faster group velocity and that the thickness change in composite plate was detectable. Consequently, the potential of applying this technique to structural health monitoring was verified.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.33 no.3
• /
• pp.264-269
• /
• 2013

Since MFC(macro-fiber composite) transducer has been developed, many researchers have tried to apply this transducer on SHM(structural health monitoring), because it is so flexible and durable that it can be easily embedded to various kinds of structures. The objective of this paper is to figure out the benefits and feasibility of applying MFC transducers to guided wave technique. For this, we have experimentally tested the performance of MFC patches as transmitter and sensors for excitation and reception of guided waves on the thin aluminum alloy plate. In order to enhance the signal accuracy, we applied the FIR filter for noise reduction as well as used STFT(short-time Fourier transform) algorithm to image the guided wave characteristics clearly. From the results, the guided wave generated based on MFC showed good agreement with its theoretical dispersion curves. Moreover, the ultrasonic Lamb wave techniques based on MFC patches in pitch-catch manner was tested for detection of surface notch defects of which depths are 10%, 20%, 30% and 40% of the aluminum plate thickness. Results showed that the notch was detectable well when the notch depth was 10% of the thickness or greater.

• Smart Structures and Systems
• /
• v.1 no.4
• /
• pp.339-353
• /
• 2005

This paper presents the results of a feasibility study on an impedance-based damage detection technique using thickness modes of piezoelectric (PZT) patches for steel structures. It is newly proposed to analyze the changes of the impedances of the thickness modes (frequency range > 1 MHz) at the PZT based on its resonant frequency shifts rather than those of the lateral modes (frequency range > 20 kHz) at the PZT based on its root mean square (RMS) deviations, since the former gives more significant variations in the resonant frequency shifts of the signals for identifying localities of small damages under the same measurement condition. In this paper, firstly, a numerical analysis was performed to understand the basics of the NDE technique using the impedance using an idealized 1-D electro-mechanical model consisting of a steel plate and a PZT patch. Then, experimental studies were carried out on two kinds of structural members of steel. Comparisons have been made between the results of crack detections using the thickness and lateral modes of the PZT patches.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.625-632
• /
• 2004

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.20 no.4
• /
• pp.1-8
• /
• 2016

Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.