• 한국생산제조학회지
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• 제6권2호
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• pp.112-118
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• 1997

Characteristics of AE(Acoustic Emission) signal is related to cutting conditions, tool materials, and tool geometry in metal cutting. Relation between AE signal and tool wear was investigated experimentally. Experiment is carried out by interrupted cutting for SCM420 workpiece with TiN coating tool on HSS material. AE RMS voltage and count per event were increased according to tool wear. The major results are as follows : 1) AE RMS value is nearly constant as cutting speed changes, but is rapidly increase as feed rate increases. 2) AE RMS value and Count per Event increase as tool wear increases. 3) It is more effective to monitor tool wear by Incremental rate of AE RMS value than by Incremental rate of count per event.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.365-368
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• 1995

Rotary Compressor has many AE(Acoustic Emission) sources according to condition of parts because it is operated with combination of various parts. In this study, analysis of AE raw signal generated form Rotary compressor which artificially-made parts inflicted abnormal condition was carried out. AE raw signals were acquired form high-speed A/D board, and many burst type signals were observed. By analyzing burst type signals which is caused form internal AE source,efficient AE parameters for monitoring and diagnosis were presented.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 추계학술대회 논문집
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• pp.344-348
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• 1992

This paper presents a new methodology for on-line tool breakage detection by sensor fusion concept of an acoustic-emission (AE) sensor. A built-in piezoelectric force sensor was used to measure cutting force instead of a tool dynamometer to preserve the machine tool dynamics. he sensor was inserted in the tool turret housing of an NC lathe. FEM analysis was carried out to locate the most sensitive position for the sensor. When a tool is broken, the explicit changes of signals' pattern take place. A burst-type AE signal increases abruptly. Followingly, a cutting force drops significantly. Therefore a burst of AE signal is used as a triggering signal to inspect the following cutting force. Significant drop of cutting force is utilized to detect tool breakage. The algorithm was implemented in a DSP board for in-process tool breakage detection. The proposed monitoring system was capable of a good applicable tool breakage detection.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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• pp.1196-1199
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• 2003

Recently, the development of diagnosis technique with high confidence is important on power equipment, for this reason is use for measurement and analysis of PD with prior appearance of insulation breakdown. In this paper, we presents the analysis of trouble signal to use ${\phi}-Q$ method which display 2D and 3D Equipment of simulation has made independently DS for 170kV GIS of one phase with same on field. The detected signal through the sensor of Induction and Acoustic Emission is classified to use characteristic neural network algorithm and then it is analysis.

• 한국생산제조학회지
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• 제8권3호
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• pp.76-82
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• 1999

This study was carried out to verify finding performance of dental diamond bur and investigate the possibility of AE application in density field. Work pieces were made of acryl and bovine respectively for the experiments in this study. Grinding test was conducted to get the data of grinding resistance and specific finding energy of low different types of diamond bur by using tool dynamometer. AE signal was acquired to verify grinding process in the AE measuring system. AErms value was increased as the grinding velocity and depth were increasing, but it decreased as the feed rate was increasing. The case of the small value of AE signal is due to abnormal grinding in D type diamond bur. By analyzing AErms start and finish time of grinding working, abnormal grinding state can be confined. Abnormal state can be found through the behavior of AE signal in the finding working. As a result, it is expected that forecast of abnormal state is possible using AE equipments under real time process.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.315-318
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• 1997

In terms of productivity, the speed of machining process has been increasing in most of engineering part. But the tapping process does not reach at enough level compared with other machining processes because of its complicate cutting mechanism. In the high speed tapping process, the one of important elements is tool monitoring system to prevent tool breakage. This paper describes tool monitoring system by acoustic emission(AE) in the tapping process. We used 2 types of AE sensors in this test. The one is commercial sensor which is used in other machining monitoring system like polishing and the other is a self-fabricated sensor for this test. In this test we purpose to find out the frequency of AE signal in tapping process and verify the possibility of applying AE sensor in in-process tapping monitoring system. Also grasp of characteristic of tapping process by AE signal is handled.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.987-990
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• 2000

In modern manufacturing industry such as aerospace, vehicle and die/mold industry, the high hardness malarial which is remarkable in aspects of durability is effectively used. The high-speed and precision machining technology has been applied in these fields. In this study, efficient sensors in high-speed machining by observing similar tendency through comparing cutting force with AE signal, gap sensor signal and accelerometer signal are selected, and machinability of high-speed machining is experimentally evaluated. We performed a basic research for sensing system construction to monitor a machine tool and machining condition.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.8-13
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• 2000

Die polishing technology is very critical to determine quality and performance of the final products. Die polishing processes have not been automated because the automation requires a great deal of experience and skill of experts. Thus, to implement a fully automated polishing process, the development of polishing status monitoring system replacing the skill of experts is critical. AE is known to be closely related to material removal rate(MRR). As the surface is rougher, MRR gets larger and AE increased. The surface roughness can be indirectly estimated using the AE signal measured during automatic die polishing process. In this study, The polishing state monitoring system using AEms signal was developed. This system can be not only to monitor the abnormal state but also to estimate a state of surface roughness of polishing surface qualitatively.

• 한국전기전자재료학회논문지
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• 제17권5호
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• pp.567-571
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• 2004

Recently, GIS(Gas Insulated Switchgear) has been recognizing of importance on development of diagnosis technique which is happened problem on confidence for a long time use. Therefore, the measurement and analysis of PD with prior phenomenon of insulation breakdown is used many method of diagnosis for GIS. In this paper, we simulate trouble condition in DS and analysis trouble signal to use electrical and mechanical methods, interpretation of detected signal has analysed with to use ø-q-n pattern and neural network. For this analysis, we have used the induction and AE(acoustic emission) sensors. For the simulation experiment, we make DS for 170 KV GIS and analyze the classification and characteristics of detected signals with the application of neural network algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.715-722
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• 2012

A structural health monitoring (SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal (TR) and inverse filtering (IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.