• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.718-723
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• 2008

Bearing is one of the important mechanical elements used in various industrial equipments. Most of failures occurred during the equipment operation result from bearing defects and breakages. Therefore, monitoring of bearings is essential in preventing equipment breakdowns and reducing unexpected loss. The purpose of this paper is to present an online monitoring method to predict bearing states using vibration signals. Bearing vibrations, which are collected as a form of profile signal, are first analyzed by a discrete wavelet transform. Next, some statistical features are obtained from the resultant wavelet coefficients. In order to select significant ones among them, analysis of variance (ANOVA) is employed in this paper. Statistical features screened in this way are used as input variables to support vector machine (SVM). An hierarchical SVM tree is proposed for dealing with multi-class problems. The result of numerical experiments shows that the proposed SVM tree has a competent performance for classifying bearing fault states.

• Structural Engineering and Mechanics
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• v.54 no.1
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• pp.105-119
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• 2015

Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.

• Smart Structures and Systems
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• v.21 no.5
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• pp.705-713
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• 2018

High-speed rail (HSR) has been in operation and development in many countries worldwide. The explosive growth of HSR has posed great challenges for operation safety and ride comfort. Among various technological demands on high-speed trains, vibration is an inevitable problem caused by rail/wheel imperfections, vehicle dynamics, and aerodynamic instability. Ride comfort is a key factor in evaluating the operational performance of high-speed trains. In this study, online monitoring data have been acquired from an in-service high-speed train for condition assessment. The measured dynamic response signals at the floor level of a train cabin are processed by the Sperling operator, in which the ride comfort index sequence is used to identify the train's operation condition. In addition, a novel technique that incorporates salient features of Bayesian inference and time series analysis is proposed for outlier detection and change detection. The Bayesian forecasting approach enables the prediction of conditional probabilities. By integrating the Bayesian forecasting approach with time series analysis, one-step forecasting probability density functions (PDFs) can be obtained before proceeding to the next observation. The change detection is conducted by comparing the current model and the alternative model (whose mean value is shifted by a prescribed offset) to determine which one can well fit the actual observation. When the comparison results indicate that the alternative model performs better, then a potential change is detected. If the current observation is a potential outlier or change, Bayes factor and cumulative Bayes factor are derived for further identification. A significant change, if identified, implies that there is a great alteration in the train operation performance due to defects. In this study, two illustrative cases are provided to demonstrate the performance of the proposed method for condition assessment of high-speed trains.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.78-83
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• 2014

Recently, a rapid growth of wind power system as a leading renewable energy source has compelled a number of companies to develop intelligent monitoring and diagnostic system. Such systems can detect early mechanical faults, which prevents from costly repairs. Generally, fault diagnostic system for wind turbines is based on vibration and process signal analysis. In this work, different type of mechanical faults such as mass unbalance and shaft misalignment which can always happen in wind turbine system is considered. The proposed intelligent fault diagnostic algorithm utilizes artificial neural network and Wavelet transform. In order to verify the feasibility of the proposed algorithm, mechanical fault generation experimental system manufactured by Gaon corporation is utilized.

• Smart Structures and Systems
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• v.17 no.6
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• pp.859-880
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• 2016

This study aims to establish an effective methodology for the detection of instant damages occurred in cable-stayed bridges with the measurements of cable vibration and structural temperatures. A transfer coefficient for the daily temperature variation and another for the long-term temperature variation are firstly determined to eliminate the environmental temperature effects from the cable force variation. Several thresholds corresponding to different levels of exceedance probability are then obtained to decide four upper criteria and four lower criteria for damage detection. With these criteria, the monitoring data for three stay cables of Ai-Lan Bridge are analyzed and compared to verify the proposed damage detection methodology. The simulated results to consider various damage scenarios unambiguously indicate that the damages with cable force changes larger than ${\pm}1%$ can be confidently detected. As for the required time to detect damage, it is found that the cases with ${\pm}2%$ of cable force change can be discovered in no more than 6 hours and those with ${\pm}1.5%$ of cable force change can be identified in at most 9 hours. This methodology is also investigated for more lightly monitored cases where only the air temperature measurement is available. Under such circumstances, the damages with cable force changes larger than ${\pm}1.5%$ can be detected within 12 hours. Even though not exhaustively reflecting the environmental temperature effects on the cable force variation, both the effective temperature and the air temperature can be considered as valid indices to eliminate these effects at high and low monitoring costs.

• Earthquakes and Structures
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• v.13 no.4
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• pp.377-386
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• 2017

Earthquake-induced pounding damages to building structures were repeatedly observed in many previous major earthquakes. Extensive researches have been carried out in this field. Previous studies mainly focused on the regular shaped buildings and each building was normally simplified as a single-degree-of-freedom (SDOF) system or a multi-degree-of-freedom (MDOF) system by assuming the masses of the building lumped at the floor levels. The researches on the pounding responses between irregular asymmetric buildings are rare. For the asymmetric buildings subjected to earthquake loading, torsional vibration modes of the structures are excited, which in turn may significantly change the structural responses. Moreover, contact element was normally used to consider the pounding phenomenon in previous studies, which may result in inaccurate estimations of the structural responses since this method is based on the point-to-point pounding assumption with the predetermined pounding locations. In reality, poundings may take place between any locations. In other words, the pounding locations cannot be predefined. To more realistically consider the arbitrary poundings between asymmetric structures, detailed three-dimensional (3D) finite element models (FEM) and arbitrary pounding algorithm are necessary. This paper carries out numerical simulations on the pounding responses between a symmetric rectangular-shaped building and an asymmetric L-shaped building by using the explicit finite element code LS-DYNA. The detailed 3D FEMs are developed and arbitrary 3D pounding locations between these two buildings under bi-directional earthquake ground motions are investigated. Special attention is paid to the relative locations of two adjacent buildings. The influences of the left-and-right, fore-and-aft relative locations and separation gap between the two buildings on the pounding responses are systematically investigated.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.58-67
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• 2019

The low-voltage connection box used as a low-voltage transmission line of KEPCO is intended to branch or connect to an underground line. In comparison with the utility considering the aesthetics of the distance, and safety measures are needed. In this paper, temperature and humidity, $CO_2$, water level, acceleration, and vibration sensor are installed inside the underground low voltage handhole, and the sensor data is transmitted to the ground using the Zigbee module. Antenna (Bolted Antenna) for communication with the ground was proposed and the data reception through it was confirmed. In the LF mode and the HEX mode, the transmitted data was confirmed to be a perfect reception success rate. In the case of the bolted antenna, the difference between the ground state and the underwater state was observed as a result of the experiment in the environmental environment. However, It was judged that reception sensitivity was sufficient for communication. The received data could be confirmed through PC based GUI.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.195-208
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• 2023

The nodular diaphragm wall (NDW) is a novel type of foundation with favorable engineering characteristics, which has already been utilized in high-rise buildings and high-speed railways. Compared to traditional diaphragm walls, the NDW offers significantly improved vertical bearing capacity due to the presence of nodular parts while reducing construction time and excavation work. Despite its potential, research on the vertical bearing characteristics of NDW requires further study, and the investigation and visualization of its displacement pattern and failure mode are scant. Meanwhile, the measurement of the force component acting on the nodular parts remains challenging. In this paper, the vertical bearing characteristics of NDW are studied in detail through the indoor model test, and the displacement and failure mode of the foundation is analyzed using particle image velocimetry (PIV) technology. The principles and methods for monitoring the force acting on the nodular parts are described in detail. The research results show that the nodular part plays an essential role in the bearing capacity of the NDW, and its maximum load-bearing ratio can reach 30.92%. The existence of the bottom nodular part contributes more to the bearing capacity of the foundation compared to the middle nodular part, and the use of both middle and bottom nodular parts increases the bearing capacity of the foundation by about 9~12% compared to a single nodular part of the NDW. The increase in the number of nodular parts cannot produce a simple superposition effect on the resistance born by the nodular parts since the nodular parts have an insignificant influence on the exertion and distribution of the skin friction of NDW. The existence of the nodular part changes the displacement field of the soil around NDW and increases the displacement influence range of the foundation to a certain extent. For NDWs with three different nodal arrangements, the failure modes of the foundations appear to be local shear failures. Overall, this study provides valuable insights into the performance and behavior of NDWs, which will aid in their effective utilization and further research in the field.

• Smart Structures and Systems
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• v.21 no.6
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• pp.741-749
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• 2018

Structural health monitoring (SHM) systems are necessary to achieve smart predictive maintenance and repair planning as well as they lead to a safe operation of mechanical structures. In the context of vibration-based SHM the measured structural responses are employed to draw conclusions about the structural integrity. This usually leads to a mathematically illposed inverse problem which needs regularization. The restriction of the solution set of this inverse problem by using prior information about the damage properties is advisable to obtain meaningful solutions. Compared to the undamaged state typically only a few local stiffness changes occur while the other areas remain unchanged. This change can be described by a sparse damage parameter vector. Such a sparse vector can be identified by employing $L_1$-regularization techniques. This paper presents a novel framework for damage parameter identification by combining sparse solution techniques with an Extended Kalman Filter. In order to ensure sparsity of the damage parameter vector the measurement equation is expanded by an additional nonlinear $L_1$-minimizing observation. This fictive measurement equation accomplishes stability of the Extended Kalman Filter and leads to a sparse estimation. For verification, a proof-of-concept example on a quadratic aluminum plate is presented.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.134-138
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• 2011

Fault detection for dynamic loading conditions of rotational machineries was considered from the contactless, non-destructive infrared thermographic method, rather than the traditional diagnosis method. In this paper, by applying a rotating deep-grooved ball bearing, passive thermographic experiment was performed as an alternative way proceeding the traditional fault monitoring. In addition, the thermographic experiments were compared with the vibration spectrum analysis to evaluate the efficiency of the proposed method. Based on the results, it was concluded the temperature characteristics of the ball bearing under dynamic loading conditions were analyzed thoroughly.