• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.1
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• pp.11-18
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• 2010

Tool condition monitoring (TCM) is crucial for improvement of productivity in manufacturing process. However, TCM techniques have not been applied to monitor tool failure in an industrial gear shaving application. Therefore, this work studied a statistical TCM method for monitoring gear shaving tool condition. The method modeled the vibration signal of the shaving process using beta probability distribution in order to extract the effective features for TCM. Modeling includes rectifying for converting a bi-modal distribution into a unimodal distribution, estimating the parameters of beta probability distribution based on method of moments. The performance of features obtained from the proposed method was evaluated and discussed.

• The Journal of the Acoustical Society of Korea
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• v.8 no.1
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• pp.5-12
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• 1989

This paper is concerned with the characteristics on the statistical parameters of vibration signal from bearing with changing its operating conditions as well as the spreading of faults. The rms, Kurtosis, crest factor, probability of exceedance and probability density function have been chose as the statistical parameters. To characterize of each, vibration signals have been recorded from four ball tester at different loads, operation speeds and time. The values of the statistical parameters for each frequency band have been calculated after A/D conversion and digital filtering of the recorded signals. It has been found that unlike rms values the statistical parameters such as Kurtosis etc. are almost unchanging with the change of the operating conditions such as load and speed. This suggests that the statistical parameters may be used for determining the development of faults independent of the operating conditions. In fact, the statistical parameters deviate considerably from their respective normal values when the faults developed under load conditions in the samples, conforming the suggestion.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.1
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• pp.45-52
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• 2003

A number of stress corrosion cracks in turbine rotor disk keyway in power plants have been found and the necessity has been raised to detect and evaluate the cracks prior to the catastrophic failure of turbine disk. By ultrasonic RF signal analysis and using a neural network based on bark-propagation algorithm, we tried to evaluate the location, size and orientation of cracks around keyway. Because RF signals received from each reflector have a number of peaks, they were processed to have a single peak for each reflector. Using the processed RF signals, scan data that contain the information on the position of transducer and the arrival time of reflected waves from each reflector were obtained. The time difference between each reflector and the position of transducer extracted from the scan data were then applied to the back-propagation neural network. As a result, the neural network was found useful to evaluate the location, size and orientation of cracks initiated from keyway.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.964-972
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• 2006

The kidney keeps with close relationship in the internal organs, that the kidney function filtering eliminate the wastes to the urine on the processing to replace the old with the new blood. In case of these problem in the kidney, there is no way to catch out with self-awakening symptom except for serious illness. This problem can solve with keeping the systematic diagnosis method in the kidney trouble shooting. Under the circumstances, the importance of the diagnosis for the kidney disease is growing day after day. In this paper, among the great four diagnosises, using the way of ocular inspection & auscultation, we would like to propose rouble shooting in the way of the kidney. To do this, through the assistance of the input image, extract the value of the color with appropriate output, analysing the color of the face with related to the kidney, using the results we would like to get the accurate symptoms on the kidney's problems. Also, through analysing and comparing with the relationship the kidney and the signal of voice, we would like to realize the proof system of human health. Finally, we'd like to make proof of the usefulness for proposed method from this study.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.33-41
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• 2001

Wire ropes have been widely used in industrial applications, wherever heavy weight should be carried safely or mechanical energy should be transmitted fast. Especially, wire rope failures in operating elevator may lead to extensive property damage and serious injury to nearby personnel. Hence, it is very important to inspect wire rope periodically. Failure defection of wire rope requires fundamental knowledge of wire rope construction, rope behavior, properties of fault, sensing and signal processing method. In this research, the development of a new fault detecting system incorporating Hall-effect sensors to detect flaws such as abrasion, broken wire, corrosion and deformation for aged wire ropes in elevator, is described. For using a detector as a portable instrument, several performances for implementing sensing part with Hall-effect sensor, analog signal processing unit and programs are described. Experiments and field testing results for the implemented detecting system are also given. As a result, it is verified that the detecting system has good efficiency for inspecting faults of aged wire ropes in service.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.1
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• pp.1-6
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• 2021

Recently, unmanned facilities have been introduced and operated in a way that reduces the cost and development of IT technology. Although unmanned facilities have advantages in terms of efficiency and economy, they have disadvantages such as failure of unmanned facilities and malfunctions, causing damage to facilities caused by intruders, and information leakage. In addition, it is necessary to visit the person in charge at all times to inspect the unmanned facilities, resulting in management costs. In this paper, we designed a system that checks the status of unmanned surveillance facilities in real time to check and automatically recover problems such as malfunctions, and to notify managers of situations by text messages in real time. The system to be designed consists of an integrated network video server (NVR) that receives and determines information on the operation status of the main equipment such as video, sound, and lighting, and a real-time text message using an SMS server.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.64-71
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• 2006

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmill is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for condition monitoring is presented. Also, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by the fuzzy C-means algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.3
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• pp.24-31
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• 2004

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• 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 the Korean Society for Aeronautical & Space Sciences
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• v.34 no.3
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• pp.67-73
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• 2006

In this paper, a reconfigurable model following flight control method is proposed based on direct adaptive scheme using parameter estimation. Adaptive control scheme updates the control gains to make the system output follow the reference output even when fault occurs. By adopting the frequency domain parameter estimation method, system changes by the fault can be estimated. Recursive Fourier transformation is used for system identification. Using recursive Fourier transform, the proposed adaptive control algorithm guarantees the system stability and improves the system characteristics. To evaluate the performance of proposed control method, numerical simulations are performed.