• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.7
• /
• pp.1581-1589
• /
• 1995

The feasibility of using AE for detecting contact and slip between a workpiece and an end effector has been tested. Specifically, the relationship between the contact and slip motion and the characteristics of the AE signal is theoretically and experimentally investigated. The experimental results manifest that the high sensitivity of AE signal to the contact and slip makes it a good alternative as a robot tactile sensor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.18 no.2
• /
• pp.36-43
• /
• 2004

In this paper, the frequency spectra from respective mechanical noise signals detected using ultrasonic wave and AE(Acoustic Emission) sensor were analysed to under spark generation between brush and commutator side with arbitrarily 15$^{\circ}$ rotation for brush from the DC motor in operation. Also, the frequency spectra from respective magnetizing noise signals detected using ultrasonic wave and AE sensor were analysed to under neutral point for brush from the DC motor in normal operation. And the analyses and comparison between the mechanical noise signal and magnetizing noise signal of ultrasonic wave with brush location change from the DC motor in operation. As the experimental results, tile mechanical noise signal of ultrasonic wave under spark generation between brush and commutator side with brush location change from the DC motor in operation were increased about 2.5∼3.0 times than magnetizing noise signal of ultrasonic wave form the DC motor in normal operation. Also, the main frequency band for mechanical noise signals of AE under spark generation between brush and commutator side with brush location change from the DC motor in operation, appeared about 1.3[MHz]∼l.5[MHz] by the fast fourier transform.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.21 no.4
• /
• pp.601-607
• /
• 2012

The magnetic abrasive polishing (MAP), for online monitoring with AE sensor attachment, was performed in this study. To predict the surface roughness after the magnetic abrasive polishing of NAK80, the signal data acquired from the AE sensor were analyzed. A dimensionless coefficient, which consisted of average of AErms and standard deviation of AE signal, was defined as a characteristic of the MAP and a prediction model was obtained using least square method. A neural network, which had multiple input parameters from AE signals and polishing conditions, was applied for predicting the surface roughness. As a result of this study, it was seen that there was very close correlation between the AE signal and the surface roughness in the MAP. And then on-line prediction of the surface roughness after the MAP of the NAK80 was possible by the developed prediction model.

• Smart Structures and Systems
• /
• v.13 no.1
• /
• pp.155-171
• /
• 2014

Various monitoring techniques are now available for structural health monitoring and Acoustic Emission (AE) is one of them. One of the major advantages of the AE technique is its capability to locate active cracks in structural members. AE crack locating approaches are affected by the signal attenuation and dispersion of elastic waves due to inhomogeneity and geometry of reinforced concrete (RC) members. In this paper, a novel technique is described based on signal processing and sensor arrangement to process multisensory AE data generated by the onset and propagation of cracks and is validated with experimental results from an in-situ load test. Considering the sources of uncertainty in the AE crack location process, a methodology is proposed to capture and locate events generated by cracks. In particular, the relationship between AE events and load is analyzed, and the feasibility of using the AE technique to evaluate the cracking behavior of two RC slab strips during loading to failure is studied.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
• /
• v.5B no.1
• /
• pp.78-83
• /
• 2005

Currently in Japan, the use of the small wind turbine is an upward trend. There are already many well established small wind turbine generators in use and their various failures have been reported. The most commonly sighted failure is blade damage. Thus the research purpose was set to develop a simple failure diagnostic system, where an Acoustic Emission (AE) signal was produced from the failure part of a blade which was measured by AE sensor. The failure diagnostic technique was thoroughly examined. Concurrently, the damage part of the blade was imitated, the AE signal was measured, and a FFT(Fast Fourier Transform) analysis was carried out, and was compared with the output characteristic. When one sheet of a blade was damaged 40mm or more, the level was computed at which failure could be diagnosed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.560-564
• /
• 1999

Burr sensing for burr size measurement and deburring process control is one of the essential elements in an automated deburring procedure. This paper presents the implementation of capacitance sensing and acoustic emission (AE) to deburring. The first application is the "on-line" measurement of burrs using a capacitance sensor. A non-contact capacitance gauging sensor is attached to an ultra precision milling machine which was used as a positioning system. The setup is used to measure burr profiles along machined workpiece edges. The proposed scheme is shown to be accurate, easy to setup, and with minor modifications, readily applicable to automatic deburring processes. As the second example, AE signals were sampled and analyzed for the sensor feedback of a precision deburring process - laser deburring -. The results, such as the sensitivity of AE signals to burr shapes and edge detection capability show a clear correlation between physical process parameters and the AE signals. A subsequent control strategy for deburring automation is also briefly discussed.

• Proceedings of the KIEE Conference
• /
• 2003.07c
• /
• pp.1659-1661
• /
• 2003

Recently, diagnostic techniques have been investigated to defect a partial discharge in high voltage electrical equipment. We have studied the characteristics of the acoustic partial discharge originating from the electrical defects in cubicle GIS(C-GIS). An acoustic emission(AE) sensor is used on the enclosure to detect partial discharge source because the sensor is sensitive to stress waves in its frequency range that may not be from a partial discharge source. AE signal is analyzed with phase-magnitude-frequency number(${\Phi}$-V-n) and pulse per second(PPS). Experience result has shown that the omitted acoustic signal has phase dependency and phase shift characteristic according to increase with applied voltage. These result will be helpful to the pattern recognition of the acoustic partial discharge in a C-GIS.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.10 no.1
• /
• pp.84-90
• /
• 1990

By discriminating the wave propagation paths in cylindrical vessels, a technique for AE source location has been proposed. This method is based on the path difference between several propagating directions from a source to a sensor. One sensor can receive multiple waveforms sequentially including a direct arrival and several others propagated through the circumferential direction. An wave front normally propagates in all directions and as many waveforms can reach the sensor until the signal faded out by attenuation. Only the first four arrivals suffice the condition for calculating the source location. The proposed method was examined for an actual cylindrical vessel by the source location experiment using simulated AE sources. The test showed very promising results and the method can be utilized for a simple AE source location without multi-channel instruments.

• Progress in Superconductivity and Cryogenics
• /
• v.12 no.3
• /
• pp.44-48
• /
• 2010

Acoustic emission (AE) signal from an HTS tape has a low signal to noise ratio, due to the large amount of noise caused by the boiling of the liquid cryogen or mechanical vibration from the cryo-cooler. In an attempt to improve the sensitivity of the AE sensor, $Pb(Zr_{0.54}Ti_{0.46})O_3$ + 0.2 wt% $Cr_2O_3$ + 1.0 wt.% $Nb_2O_5$ ceramics sintered at $1200^{\circ}C$ was synthesized. In addition, the resonance ($f_r$) and anti-resonance frequencies ($f_a$) were measured using the specimens with various thicknesses (1.0, 1.5, 2.0, 2.5 and 3.0 mm). According to the test results, large AE signals with high frequencies were obtained from the AE sensor fabricated using a piezoelectric disc with a thinner thickness.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2011.04a
• /
• pp.419-423
• /
• 2011

Unlike other non-destructive inspection method, AE Structural defects that are likely to grow in the operation status can be detected, and the advantage of being due to the continuous monitoring of large structures has been widely used to evaluate the stability. AE sensor used to detect sound wave that occurs between 20kHz to 20MHz. and Sound wave result may vary depending on sensor's sensitivity. In this paper, Tensile test conducted on STS 304 and SS400, and tries to detect the crack signal. In tensile test, specimens were conducted using different sensor sensitivity to the same tensile test condition. The crack signal parameters divided into 4 types of communities by conducting cluster analysis. It was demonstrated that crack signal of two sensor is not different by statistical analysis of null hypotheses. Based on the results, waveform of this tension test is crack signal.