• Journal of the Korean Society for Precision Engineering
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• v.2 no.1
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• pp.62-71
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• 1985

This is a study on the monitoring technique in tool failure and tool life by AE method. The relation between amplitude level of AE signal and flank wear width was studied by experiments. The relation between amplitude level of AE signal and tool life was also studied. As the result, it was observed that amplitude level of AE signal was only affected by cutting velocity. Amplitude level of AE signal was directly proportional to flank wear width and the increasing rate was related to cutting velocity. So, the relation between amplitude level of AE signal and tool life was represented as follow: $CT^n$ = $AE_{rms}$ where, n=0.35 C=9.5*$10^{-2}$

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.11
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• pp.905-910
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• 2008

Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.153-160
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• 2018

Purpose: A traffic signal controller needs to control and coordinate to ensure that traffic and pedestrians move as smoothly as possible. Since a traffic signal controller has a significant impact on the safety of vehicles and pedestrians, it is important to monitor the failure and deterioration of the traffic signal controller. The purpose of this paper is to propose an IoT (Internet of Things)-based monitoring system for a traffic signal controller. Methods: Every traffic signal controller has a nominal system trajectory specified when it is deployed. The proposed IoT-based monitoring system collects the system trajectory information through real-time monitoring. By comparing the nominal system trajectory and the monitored system trajectory, we are able to detect the failure and deterioration of the traffic signal controller. Conclusion: The proposed IoT-based monitoring system can contribute to the safety of vehicles and pedestrians by maximizing the availability of a traffic signal controller.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.422-427
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• 2002

This paper focuses on the formulation and validation of an automatic strategy for the selection of the locations and directions of strain gauges to capture at best the modal response of a blade in a series of modes. These locations and directions are selected to render the strain measurements as robust as possible with respect to random mispositioning of the gauges and gauge failures. The approach relies on the evaluation of the signal-to-noise ratios of the gauge measurements from finite element strain data and includes the effects of gauge size. A genetic algorithm is used to find the strain gauge locations-directions that lead to the largest possible value of the smallest modal strain signal-to-noise ratio, in the absence of gauge failure, or of its expected value when gauge failure is possible. A fan blade is used to exemplify the applicability of the proposed methodology and to demonstrate the effects of the essential parameters of the problem, i.e. the mispositioning level, the probability of gauge failure, and the number of gauges.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.1168-1173
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• 2007

The Seoul Subway is one of the most heavily used Subway System in the world. It provides reliable transportation services, conveys nearly 4 million Passengers across 117 subway stations with a length of 134.9 Km. Over the years the safety for the Subway has been a major concern, trains going off the track, equipment failure, careless operation, Signal failure are increasing day by day. In a Recent Public opinion 40% said the causes to above facts are Vehicle breakdown because of Operators, Old rail defect, Quality of material. 20% of the opinion said the obstacles were because of Operation, crew carelessness, negligence in signal operation. In case of any accident the crew members cannot resolve the issue on site (Aid insufficiency), because of lack of knowledge and carelessness. The main obstacles for Subway are vehicle breakdown, Electric equipment failure, Signal Equipment failure, and Crew carelessness. This paper aims to provide major problems which are needed to be solved as quickly as possible for citizen's safety for a comfortable subway system making a comfortable ride and providing better service gradually.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.8
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• pp.757-766
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• 2004

This paper focuses on the formulation and validation of an automatic strategy to select the optimal location and direction of strain gauges for the measurement of the modal response. These locations and directions are important to render the strain measurements as robust as possible when a random mispositioning of the gauges and gauge failures are expected. The approach relies on the evaluation of the signal-to-noise ratios of the gauge measurements from strain data of finite element. The multi-step optimization strategy including genetic algorithm is used to find the strain gauge locations-directions that maximize the smallest modal strain signal-to-noise ratio in the absence of gauge failure or its expected value when gauge failure is possible. A flat Plate is used to prove the applicability of the proposed methodology and to demonstrate the effects of the essential parameters of the problem such as the mispositioning level, the probability of gauge failure, and the number of gauges.

• Journal of Applied Reliability
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• v.8 no.2
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• pp.101-111
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• 2008

Good diagnostics improves both the safety and system unavailability of digital safety systems. The measure of a diagnostic capability is called the Coverage Factor. Because the Failure Modes, Effects and Diagnostic Analysis (FMEDA) provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a component, the FMEDA can be used as a useful tool to calculate it. Through performing FMEDA on a digital signal processor (DSP) board used in a digital safety system, it is shown that some components of the DSP board can be replaced or improved to satisfy the required diagnostic coverage. That is, the FMEDA can serve as a useful verification tool to design a diagnostic capability for the DSP board.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.737-747
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• 2011

5678SMRT has installed various sensor for operating conditions(field of electric, facilities, signal, communication equipment and track) and environment of Every Function Room for remotely detecting and monitoring. Installed sound sensor for analyzed after remotely heard the noise of every equipment at Every Function Room and temperature sensor for check the temperature condition of Every Function Room. Additional installed voltage sensor in signal equipment room for monitoring RF track-circuit's voltage condition. Installed displacement sensor at The Chungdam bridge's railway for measuring and monitoring track displacement caused by temperature change and Pan/Tilt camera at sub-station and drainage for remotely field monitoring. Installed sensor for each equipment's operating condition and failure at Every Function Room then periodic check of workforce turned to around-the-clock surveillance by sensor therefore improvement of operating equipment. SMRT is lots of prevent a failure by Immediately detect of precondition of equipment failure by analyzed the sensor data. If the occurrence of an failure, become detected Immediately so possibility correct diagnosis and order by remotely field check by installed camera and sound sensor at field.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.12
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• pp.78-85
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• 2002

The wavelet transform is a popular tool fer studying intermittent and localized phenomena in signals. In this study the wavelet transform of cutting force signals was conducted for the detection of a tool failure in turning process. We used the Daubechies wavelet analyzing function to detect a sudden change in cutting signal level. A preliminary stepped workpiece which had intentionally a hard condition was cut by the inserted cermet tool and a tool dynamometer obtained cutting force signals. From the results of the wavelet transform, the obtained signals were divided into approximation terms and detailed terms. At tool failure, the approximation signals were suddenly increased and the detailed signals were extremely oscillated just before tool failure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.7 s.238
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• pp.1028-1034
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• 2005

In this paper, the failure analysis of an optical disk drive is carried out and the limit ranges of the misalignment f3r the higher performance are presented. Since optical disks are removable from optical disk drive, the translational and angular misalignments, which causes read/write errors, always exist. Therefore, the limit ranges of the misalignment should be investigated. For this reason, the failure analysis by the vibration analysis is studied. The influences of the misalignment are tested by the aging test. And the limit ranges of the misalignment are proposed for the reliability of optical disk drives.