• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.407-410
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• 1995

Many researches on measurement technology has been made and developed by various methods. Considering the measurement environment with cutting fluid, coolant and the like, contact type measurement methods are mostly used. But contact measurement method has measuring force and so the sensing head becomes worn. By these reasons, we considered sensors not influenced by the former fluid and so can acquire accrate measured values using error compensation due to temperature and vibration. For this purpose, eddy current sensors and Extended kalman Filter Algorithm for processing measured data has been used. In this paper, we present new technology that can be used for measuring workpiece with previous bad environment using direct method and comparison measurement method. We used cylindrical workpieces which were produced by grinding machine for the target.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.994-1000
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• 2004

대형시험장비가 설치되는 실험실의 계획에서 장비의 진동은 간과할 수 없는 고려사항이다. 따라서 시험장비를 지지하는 구조물과 기초의 설계시 시험장비의 운행 중 발생하는 공진을 피할 수 있는 구조적 체계의 진동특성에 대한 적절한 평가가 요구된다. 본 논문은 동적특성을 얻기 위해 바닥구조물의 FE 모델링에 관하여 기술하였다. 또한 진동저감을 위한 시험장비기초의 설계를 위해 tuning, 진동기준. 방진시스템을 검토하였다. 시험장비의 진동을 줄이는 최선의 방법은 low tuning 이였으며 이의 구현을 위해 방진스프링과 함께 단단한 콘크리트 블록위에 시험장비를 설치하였다. 총체적인 방진시스템의 구조적 진동특성은 이동성, 힘, 속도 스펙트라를 이용해 표현되었다. 전달과 지점이동 FRF의 비를 시뮬레이션을 통해 비교함으로서 바닥 슬래브의 진동전달 정도가 관찰되었다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.23-35
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• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.119-128
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• 2006

A turnout system which permits trains to pass from one track to another is a combination of the switch, the crossing, lead rails which are necessary to connect the switch and the crossing, two guard rails and a switch machine for operating the switch. A turnout is the sole moving part among the railway components and has complex configuration, so the safety has always been raised an issue. In Korea, it is planned to adopt the high speed tilting train, which operates at the maximum speed of 200km/h, at conventional lines by the year of 2010. However, for the application of the tilting train to conventional lines, it is prerequisite to establish a stable turnout system allowing the tilting train to pass through it without reducing speed. Therefore, the improved turnout system for the speed-up of conventional lines has been developed and the prototype of the turnout system has been constructed. In this study, simulation of noise and vibration around the improved turnout system was performed in order to predict the generation level of noise and vibration due to passing of the tilting train through the turnout system.

• Korean Journal of Agricultural Science
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• v.8 no.1
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• pp.90-96
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• 1981

To design more efficient agricultural machinery, the accurately measuring system among many other factors is essential. A light-beam oscillographic recorder is generally used in measuring dynamic strain but it is not compatible with the extremely high speed measuring system such as 1,000 m/s, also is susceptable to damage due to vibration while using the system in field. The recorder used light sensitive paper for strip chart recording. The reading and analysis of data from the strip charts is very cumbersome, errorneous and time consuming. A microcomputer was interfaced with A/D converter, microcomputer program was developed for measuring, system calibration was done and the strain generated from a cantilever beam vibrator was measured. The results are summarized as follows. 1. Microcomputer program was developed to perform strain measuring of agricultural machine elements and could be controled freely the measuring intervals, no. of channels and no. of data. The maximum measuring speed was $62{\mu}s$. 2. Calibration the system was performed with triangle wave generated from a function generator and checked by an oscilloscope. The sampled data were processed using HP 3000 minicomputer of Chungnam National University computer center the graphical results were triangle same as input wave and so the system have been out of phase distorsion and amplitude distorsion. 3. The strain generated from a cantilever beam vibrator which has free vibration period of 0.019 second were measured by the system controlled to have l.0 ms of time interval and its computer output showing vibration curve which is well filted to theoretical value. 4. Using microcomputer on measuring the strain of agricultural machine elements could not only save analyzing time and recording papers but also get excellent adaptation to field experiment, especially in measurement requiring high speed and good precision.

• Wind and Structures
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• v.29 no.6
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• pp.431-440
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• 2019

The aim of this study was to explore the influence of structure coupling effect on structural damping of blade based on the blade vibration characteristic. For this purpose, the scaled blade model of NREL 5 MW offshore wind turbine was processed and employed in the wind tunnel test to validate the reliability of theoretical and numerical models. The attenuation curves of maximum displacement and the varying curves of equivalent damping coefficient of the blade under the rated condition were respectively compared and analyzed by constructing single blade model and whole machine model. The attenuation law of blade dynamic response was obtained and the structure coupling effect was proved to exert a significant influence on the equivalent damping coefficient. The results indicate that the attenuation trend of the maximum displacement response curve of the single blade varies more obviously with the increase of elastic modulus as compared to that under the structure coupling effect. In contrast to the single blade model, the varying curve of equivalent damping coefficient with the period is relatively steep for the whole machine model. The findings are of great significance to guide the structure design and material selection for wind turbine blades.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.161-167
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• 2020

In the process of cutting large aircraft parts, the tool may be abnormally worn or damaged due to various factors such as mechanical vibration, disturbances such as chips, and physical properties of the workpiece, which may result in deterioration of the surface quality of the workpiece. Because workpieces used for large aircrafts parts are expensive and require strict processing quality, a maintenance plan is required to minimize the deterioration of the workpiece quality that can be caused by unexpected abnormalities of the tool and take maintenance measures at an earlier stage that does not adversely affect the machining. In this paper, we propose a method to indirectly monitor the tool condition that can affect the machining quality of large aircraft parts through real-time monitoring of the current signal applied to the spindle motor during machining by comparing whether the monitored current shows an abnormal pattern during actual machining by using this as a reference pattern. First, 30 types of tools are used for machining large aircraft parts, and three tools with relatively frequent breakages among these tools were selected as monitoring targets by reflecting the opinions of processing experts in the field. Second, when creating the CNC machining program, the M code, which is a CNC auxiliary function, is inserted at the starting and ending positions of the tool to be monitored using the editing tool, so that monitoring start and end times can be notified. Third, the monitoring program was run with the M code signal notified from the CNC controller by using the DAQ (Data Acquisition) device, and the machine learning algorithms for detecting abnormality of the current signal received in real time could be used to determine whether there was an abnormality. Fourth, through the implementation of the prototype system, the feasibility of the method proposed in this paper was shown and verified through an actual example.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of Biosystems Engineering
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• v.36 no.6
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• pp.434-443
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• 2011

A large scale seeding system was stable in terms of techniques but a convenient seeding system of small size was unsettled. This study was performed to develop a semi-automatic seeder for small and medium sized scale farm. To investigate optimum needle diameter and vacuum pressure was used vacuum suction needle seeder. Although the needle diameter according to the kinds of seed was different, the needle diameter for salvia and lettuce seed was suitable for 0.34 mm needle nozzle and 0.4 mm taper nozzle. The prototype consisted a seeding frame attached with needle nozzle, seed hopper, vibrating device, seeding part, vacuum ejector, seed tube etc.. As the result with the experiments, the seeding rate of the seeder was 92% and more at 0.34 mm diameter needle nozzle and 0.4 mm taper nozzle. Eccentric weight for seed hopper vibration was suitable that weight is 11 g and eccentric distance is 0.5 mm. Vibration acceleration of upward direction was 0.363 m/$s^2$. Working capacity of the seeder was possible 160 trays per hour. It was possible for sowing small seeds but it was required to make compact and simple model.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.