• Title/Summary/Keyword: AE Monitoring system

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Characterization of AFM machining mode and Acoustic Emission monitoring (AFM 가공 모드 분석 및 AE 모니터링)

  • Ahn, Byoung-Woon;Lee, Seoung-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.25 no.10
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    • pp.41-47
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    • 2008
  • This study aims to obtain machining characteristics during AFM (Atomic force Microscope) machining of silicon wafers and to monitor the machining states using acoustic emission. As in micro scale machining, two distinct regimes of deformation, i. e. ploughing regime and cutting regime were observed. First, the transition between the two regimes are investigated by analyzing the "pile-up" during machining. As far as in process monitoring is concerned, in the ploughing repime, no chips have been formed and related AE RMS values are relatively low, In the mean time, in the cutting regime, the RMS values are significantly higher than the ploughing regime, with apparent chip formation. From the results, we found out that the proposed scheme can be used for the monitoring of nanomachining, especially for the characterization of nanocutting mode transition.

Fault Detection of the Machine Tool Gearbox using Acoustic Emission Methodof (음향 방출법에 의한 공작기계 기어상자의 결함 검출)

  • Kim, Jong-Hyeon;Kim, Won-Il
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.4
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    • pp.154-159
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    • 2012
  • Condition monitoring(CM) is a method based on Non-destructive test(NDT). Therefore, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days also. Because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. A machine tool consist of many parts such as the bearings, gears, process tools, shaft, hydro-system, and so on. Condition of Every part is connected with product quality finally. To increase the quality of products, condition monitoring of the components of machine tool is done completely. Therefore, in this paper, acoustic emission method is used to detect a machine fault seeded in a gearbox. The AE signals is saved, and power spectrums and feature values, peak value, mean value, RMS, skewness, kurtosis and shape factor, were determined through Matlab.

Low Speed Rolling Bearing Fault Detection Using AE Signal Analyzed By Envelop Analysis Added DWT (웨이블릿변환이 접목된 포락처리를 이용한 저속 회전하는 구름요소베어링 결함 진단)

  • Kim, Byeong-Su;Kim, Won-Cheol;Gu, Dong-Sik;Kim, Jae-Gu;Choi, Byeong-Keun
    • Journal of Advanced Marine Engineering and Technology
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    • v.33 no.5
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    • pp.672-678
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    • 2009
  • Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.

A Study on CNC Machine Tool Wear using AE Sensor (AE 센서를 이용한 CNC 공작기계의 절삭공구 마모에 관한 연구)

  • 정수일;정재수;김광태
    • Proceedings of the Safety Management and Science Conference
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    • 2000.05a
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    • pp.241-248
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    • 2000
  • Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automation system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

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A Study on CNC Machine Tool Wear using AE Sensor (AE 센서를 이용한 CNC 공작기계의 절삭공구 마모에 관한 연구)

  • 정재수;김광태;정수일
    • Journal of the Korea Safety Management & Science
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    • v.2 no.3
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    • pp.185-195
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    • 2000
  • Increased complexity of products and their manufacturing processing demans higher quality control and monitoring than ever before. Therefore, flexible automatization or flexible manufacturing systems (FMS) offer numerous advantages over alternative manufacturing methods. In this state, a in-process monitoring is one of the important flexible automatino system. And as use of NC and CNC machine tool has been increasing, cutting work has automating and it is necessary to develop the automatic production system combined a couple of machine tool. Thus, in this paper to search examination it can measure the tool wear and the tool life and can be more practical research subject.

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The Damage Evaluation and Acoustic Emission Characteristics of the Unidirectional Ply CFRP Composite Materials in a Drilling Procedure (드릴작업중 발생되는 일방향 적층 CFRP 복합재료의 손상평가 및 AE특성)

  • Youn, Y.S.;Kwon, O.H.
    • Journal of Power System Engineering
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    • v.3 no.2
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    • pp.42-50
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    • 1999
  • In recent years, composite materials like CFRP are increasingly used in various fields of engineering because of their unique properties which offer a high strength/density and high modulus/density. When CFRP structures are manufactured in drilling processes which are frequently practiced in an Industry, they bring on the delaminations sometimes. So, acoustic emission(AE) techniques were used for a condition monitoring of the drilling process in CFRP. In this study, the AE from CFRP estimated the delamination which reduces the strength and load carrying capacity under the drilling process and the initial delamination were well caught and measured by a video camera. From the results, it was found the relationships between failure mechanism of CFRP delamination and AE characteristics as like amplitude and count.

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In-Process Detection of Flank Wear Width by AE Signals When Machining of ADI (ADI 절삭시 AE신호에 의한 플랭크 마멸폭의 인프로세스 검출)

  • 전태옥
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.8 no.6
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    • pp.71-77
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    • 1999
  • Monitoring of Cutting tool wear is a critical issue in automated machining system and has been extensively studied for many years. An austempered ductile iron(ADI) exhibits the excellent mechanical properties and the wear resistance. ADI has generally the poor machinability due to the characteristic. This paper presents the in-process detection of flank wear of cutting tools using the acoustic emission sensor and the digital oscilloscope. The amplitude level of AE signal(AErms) is mainly affected by cutting speed and it is proportional to cutting speed. There have been the relationship of direct proportion between the amplitude level of AE signals and the flank wear width of cutting tool. The flank wear with corresponding to the tool life is successfully detected with the monitor-ing system used in this study.

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Monitoring of Laser Fusion Cutting Using Acoustic Emission (AE센서를 이용한 레이저 용융 절단 모니터링)

  • 이성환;민헌식;안선응
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.11 no.3
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    • pp.39-44
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    • 2002
  • As laser cutting process is widely used in industry, an automated on-line process control system has become very important. In this paper, development of a laser cutting monitoring system, which is regarded as the fundamental step toward automation of the process, is presented. Acoustic emission and an artificial neural network were used for the monitoring system. With given process Parameters including laser power and scanning speed the system can predict the suitability of laser beam for the cutting or a stainless steel (STS304) plate.

Real Sea Experiment of Fishing Gear Automatical Identification Monitoring System (어구 자동식별 모니터링 시스템의 실해역 시험)

  • Kim, Seong-Yuel;Lee, Doo-Cheon;Kim, Hyun-Ae;Yim, Choon-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.686-688
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    • 2021
  • The performance assessment in real sea is very important to increase the reliability of the fishing gear automatically identification monitoring system. The concept of real sea experiment for fishing gear automatically identification monitoring system is introduced and results of communication performance of RoLa and LTE Cat.M1 modules are reported through this research.

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Development of process monitoring system in ELID grinding (ELID 연삭에서 가공 상태 감시 시스템 개발)

  • 서영호;김화영;안중환
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.05a
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    • pp.599-602
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    • 2000
  • A new dressing technique with utilizes electrolytic phenomenon for realizing effective mirror surface grindings with metal bonded super-abrasive wheels is called “Electrolytic In-process Dressing Grinding”. This technique enabled metal bonded micro-grain wheels, such as micro-grain cast iron fiber bonded wheels, to be used for mirror surface finish processes effectively. But this technique requires a lot of knowledge and experience to perform. And the condition of dressing is variable according to the time. Therefore adaptation of Monitoring and Control technique is needed.

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