• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.2
• /
• pp.33-40
• /
• 2020

Various studies have been conducted on the structural health monitoring using optical fiber. Optical fibers can be used to measure multiple and distributed strain. Among the optical fiber sensors, FBG sensor has advantages of dynamic response measurement and high precision, but the number of measurement points is limited. Distributed fiber sensors, represented by distributed Brillouin sensors, usually have more than 1000 measurement points, but the low sampling rate makes dynamic measurements impossible. In this study, a hybrid nerve sensor system using only the advantages of the FBG sensor and the distributed Brillouin sensor has been proposed. Laboratory experiments were performed to verify the proposed system, and the accuracy and reproducibility were verified by comparing with commercial sensors. Applying the proposed system, dynamic response ambient measurements are used to evaluate the global state of the structure. When an abnormal condition is detected, the local condition of the structure is evaluated by static response measurement using the distributed measurement system. The proposed system can be used for efficient structural health monitoring.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.7
• /
• pp.667-672
• /
• 2013

This paper presents the development of a condition monitoring system that monitors the operating conditions of a reduction unit, such as the bearing temperature, gearbox vibration, and gear oil deterioration, and notifies the operator of potential problems or abnormal conditions. A series of field tests on high-speed rail and conventional lines was performed to identify the characteristics of temperature rise and vibration levels on the reduction unit during operation. The monitoring system was designed based on the proper sensor selection, measurement method, and signal analysis to optimize the interface with the operating system of high-speed trains. Application of this monitoring system to high-speed trains will play an important role in their proper maintenance and safe operation.

• Smart Structures and Systems
• /
• v.5 no.4
• /
• pp.317-328
• /
• 2009

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be disassembled and removed or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for a wide array of application scenarios. Multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual flight environments, and the prospects for structural health monitoring applications on aircraft and other civil structures.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.3
• /
• pp.11-22
• /
• 2012

In this study, problems of RTK (Real Time Kinematic)-GPS (Global Positioning System) and an accelerometer sensor when applied to structures were experimentally identified through a comparison between results of the displacement measurement using the RTK-GPS, the accelerometer, and LVDT (Linear variable differential transformer). Integrated displacement was calculated by the improved RTK-GPS and accelerometer on the frequency of observation and positioning accuracy. This integrated displacement was also compared with that of LVDT to check the validity of application and feasibility.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.3
• /
• pp.127-135
• /
• 2014

On lot of ships, Ballast Water Treatment Systems(BWTS) are in use, or the newly built ship should be mandatory installation by 2017. It is IMO(International Maritime Organization) regulations. Because the vessel is in long distance, It is managed this system only in the vessel and it may occur considerable cost of maintenance when a problem arises from BWTS. We describe in this paper how to monitor treated ballast water to make sure the ballast water and BWTS on a ship is in proper condition, but before the port entrance. In addition, analysing and forecasting trend signal to prevent failure. Also we can expect reduce the cost of BWTS maintenance. We can monitor the sensor data value's change which collected through satellite from BWTS. And we can observate the ballasting and de-ballasting state of the vessel easily.

• Journal of the Microelectronics and Packaging Society
• /
• v.31 no.2
• /
• pp.45-53
• /
• 2024

The maintenance of semiconductor equipment is crucial for the continuous growth of the semiconductor market. System management is imperative given the anticipated increase in the capacity and complexity of industrial equipment. Ensuring optimal operation of manufacturing processes is essential to maintaining a steady supply of numerous parts. Particularly, monitoring the status of substrate transfer robots, which play a central role in these processes, is crucial. Diagnosing failures of their major components is vital for preventive maintenance. Fault diagnosis methods can be broadly categorized into physics-based and data-driven approaches. This study focuses on data-driven fault diagnosis methods due to the limitations of physics-based approaches. We propose a methodology for data acquisition and preprocessing for robot fault diagnosis. Data is gathered from vibration sensors, and the data preprocessing method is applied to the vibration signals. Subsequently, the dataset is trained using Gradient Tree-based XGBoost machine learning classification algorithms. The effectiveness of the proposed model is validated through performance evaluation metrics, including accuracy, F1 score, and confusion matrix. The XGBoost classifiers achieve an accuracy of approximately 92.76% and an equivalent F1 score. ROC curves indicate exceptional performance in class discrimination, with 100% discrimination for the normal class and 98% discrimination for abnormal classes.

• Structural Monitoring and Maintenance
• /
• v.9 no.1
• /
• pp.59-80
• /
• 2022

In the present study, the objective is to detect the structural damages using the responses obtained from the sensors at the optimal location under uncertainty conditions. Reducing the error rate in damage detection process due to responses' noise is an important goal in this study. In the proposed algorithm for optimal sensor placement, the noise of responses recorded from the sensors is initially reduced using the principal component analysis. Afterward, the optimal sensor placement is obtained by the damage detection equation based sensitivity analysis. The sensors are placed on degrees of freedom corresponding to the minimum error rate in structural damage detection through this procedure. The efficiency of the proposed method is studied on a truss bridge, a space dome, a double-layer grid as well as a three-story experimental frame structure and the results are compared. Moreover, the performance of the suggested method is compared with three other algorithms of Average Driving Point Residue (ADPR), Effective Independence (EI) method, and a mass weighting version of EI. In the examples, young's modulus, density, and cross-sectional areas of the elements are considered as uncertainty parameters. Ultimately, the results have demonstrated that the presented algorithm under uncertainty conditions represents a high accuracy to obtain the optimal sensor placement in the structures.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.13 no.5 s.57
• /
• pp.93-100
• /
• 2009

This study presents reasonable relationships to estimate the deformation based on beam mechanism analysis and TDR(Time Domain Reflectometry) data. To declar the length points of co-axial cable installed in civil structure, Nano material ($BaTiO_3$ powders and silver mixture) is used on co-axial cables. From the laboratory test, nano material could make the correct information about attached cable points on beam, and TDR sensor system and Fourier series (data filter) found out the deformation of beam. Therefore it is concluded that the correct deformed information of beam were acquired by Nano-TDR and Fourier filter, they are much more effective to apply at health monitoring system in civil structure compared to conventional TDR or Fiber Optic Sensor (FOS) systems.

• Journal of Korean Society of Water and Wastewater
• /
• v.35 no.5
• /
• pp.335-349
• /
• 2021

As the frequency of seismic disasters in Korea has increased rapidly since 2016, interest in systematic maintenance and crisis response technologies for structures has been increasing. A data-based leading management system of Lifeline facilities is important for rapid disaster response. In particular, the water supply network, one of the major Lifeline facilities, must be operated by a systematic maintenance and emergency response system for stable water supply. As one of the methods for this, the importance of the structural health monitoring(SHM) technology has emerged as the recent continuous development of sensor and signal processing technology. Among the various types of SHM, because all machines generate vibration, research and application on the efficiency of a vibration-based SHM are expanding. This paper reviews a vibration-based pipeline SHM system for seismic disaster response of water supply pipelines including types of vibration sensors, the current status of vibration signal processing technology and domestic major research on structural pipeline health monitoring, additionally with application plan for existing pipeline operation system.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.14 no.6
• /
• pp.171-178
• /
• 2010

Pipeline structure is one of core underground infrastructure which transports primary sources. Since the almost pipeline structures are placed underground and connected each other complexly, it is difficult to monitor their structural health condition continuously. In order to overcome this limitation of recent monitoring technique, recently, a Ubiquitous Sensor Network (USN) system based on on-line and real-time monitoring system is being developed by the authors' research group. In this study, real-time pipeline health monitoring (PHM) methodology is presented based on electromechanical impedance methods using USN. Two types of damages including loosened bolts and notches are artificially inflicted on the pipeline structures, PZT and MFC sensors that have piezoelectric characteristics are employed to detect these damages. For objective evaluation of pipeline conditions, Damage metric such as Root Mean Square Deviation (RMSD) value was computed from the impedance signals to quantify the level of the damage. Optimal threshold levels for decision making are estimated by generalized extreme value(GEV) based statistical method. Throughout a series of experimental studies, it was reviewed the effectiveness and robustness of proposed PHM system.