• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1993년도 춘계학술대회 논문집
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• pp.97-101
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• 1993

In this work, the imaginary part of the inner modulation transfer function of the cutting dynamics is introduced for tool wear monitoring. Time-series method is utilized to construct the generalthree dimensional cutting dynamics whose imaginary part of the inner modulation transfer funcition shows the proportionality to tool wear at the natural frequency of the machine tool dynamics. This modelis reduced to single-input single- output model without altering the proporitonality characteristics to tool wear and implemented to the dual computer system in which one computer performs measurement while the other calculates the imaginary part of the inner modulation transfer function of th cutting dynamics by the batchleast square method. The values of the imaginary part at the natural frequencyof the machine tool structure in the cutting direction are compared to the one calculated during machining with a brand new tool to decide the current stants of the tool. The experiments shows the relevance of the proposed concept.

• 한국정밀공학회지
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• 제14권11호
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.

• 유공압시스템학회논문집
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• 제1권2호
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• pp.1-7
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• 2004

In-process diagnosis is essential to achieve predictive maintenance in industrial plants. An in- process diagnosis method was proposed for hydraulic servo systems, which was based upon leakage flow measurement. Leakage due to servovalve wear was analysed and modeled mathematically far computer simulation work. The key idea of diagnosis algorithm is that when monitoring signals, such as servovalve input and load displacement are in steady states, the return-line flow of hydraulic servo systems can be regarded as null-leakage of servovalve. Virtual experiments were performed to ensure effectiveness of the proposed diagnosis method.

• 유공압시스템학회논문집
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• 제6권2호
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• pp.22-30
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• 2009

An in-process method of diagnosing the spool wear of hydraulic servovalves was explored. The diagnostic method discussed in this paper is for force-control hydraulic servo systems. The key principle used is that pressure sensitivity of a servovalve drops as the valve spool wears out so that it is possible to determine the spool condition by monitoring pressure sensitivity. A diagnostic algorithm was developed and evaluated through numerical simulation and experiments. Two major steps of diagnosis are the evaluation of null bias of the servovalve and the approximation of pressure sensitivity, both of which could be successfully done during normal operation of a servo system. The difference between a new servovalve and a worn valve could be clearly detected in-process, and the diagnostic test was found to be repeatable.

• Tribology and Lubricants
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• 제13권2호
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• pp.82-88
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• 1997

This paper describes an empirical equation which can be used to predict the engine condition of supersonic aircraft. The equation, which is derived from the trend analysis of JOAP data, represents the concentration of Fe particles in the engine oil. The result of the trend analysis shows that the concentration of Fe particles is a function of running time of engine oil. Meanwhile the slope of Fe concentration is a function of running time of engine. Threfore, the empirical equation was derived as $w=a(t_e).t_o+b$. However, the equation could not enough to diagnose the damaged part of engine quantitatively. To make up for the weak points of the equation, qualitative analysis was carried out. For that purpose wear debris were collected from the abnormal engine and analyzed by EDS to detect the damaged parts of engine.

• 한국정밀공학회지
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• 제8권1호
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• pp.74-83
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• 1991

A study on the Correlation of Orthogonal Cutting Parameter (Cutting speed, Depth of cut, Feed Rate) and Acoustic Emission Signal. It is well known that acoustic emission (AE) is the emission of elastic wave resulting from the deformation and fracture of materials. This study estabished correlation of orthogonal cutting parameter and AE signal, and researched into in-process monitoring of tool wear and failure. The results are as follow; 1. AE RMS was under the influence of cutting speed but hardly influenced by depth of cut and feed rate. 2. AE RMS was under the influence of flank wear. 3. AE count rate increased by increased cutting speed. 4. AE RMS value was rapidly increased in 130 m flank wear.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1996년도 제24회 추계학술대회
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• pp.176-182
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• 1996

This paper describes an empherical equation which is to predict the engine condition of the supersonic aircraft. The equation, which is a function of running time of engine and engine oil, is derived from the trend analysis of JOAP data. Qualitative analysis is carried out to make up for the weak points in the current JOAP system. Also wear debris collected from the abnormal engine is analyzed by EDS to detect the damaged parts of engine.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.95.5-95
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• 2002

Tool condition monitoring is recognized important in CNC machining processes since the excessive wear or breakage of tool has to be noticed immediately in an automated manufacturing system to keep the quality and productivity. In this research, as an economic way of detecting the status of tool change, the wavelet transform has been applied to the measurement of spindle motor current. The energy of a specific level shows the difference between a normal tool and worn one. By setting a limit on the change of energy, it is possible to notify the time to inspect the tool.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.204-209
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• 1999

The dressing time monitoring in cylindrical grinding is very important with respect to machining efficiency. Therefore, the purpose of this paper is to determine the wheel life by monitoring behavior of grinding power for Wa, 19A and GC. For this purpose, we investigated indirectly the attritious wear of grain edge, the loading of grinding wheel and the breakage of grain through the grinding power and the surface roughness under various grinding conditions. From obtained the results, the relationship between the wheel life and the average sectional chip area is examined to guide for the determination of dressing time.

• 한국생산제조학회지
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• 제7권3호
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• pp.14-21
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• 1998

The in-process detection of the state of cutting tool is one of the most important technical problem in Intelligent Machining System. This paper presents a method of detecting the state of cutting tool in turning process, by using Artificial Neural Network. In order to sense the state of cutting tool. the sensor fusion of an acoustic emission sensor and a force sensor is applied in this paper. It is shown that AErms and three directional dynamic mean cutting forces are sensitive to the tool wear. Therefore the six pattern features that is, the four sensory signal features and two cutting conditions are selected for the monitoring system with Artificial Neural Network. The proposed monitoring system shows a good recogniton rate for the different cutting conditions.