• Journal of Welding and Joining
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• v.33 no.4
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• pp.7-16
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• 2015

New lasers such as high power, high brightness and short wavelength laser are using diverse industry. Also new technologies are developing actively to solve various issues such as spattering, process monitoring, deep penetration and key-hole stability. ICALEO is the international congress where recent technology for laser material processing and laser system are present. At 2014, it was held at San Diego in USA and more than 260 papers were presented from 28 country. The effect of the laser beam shape such as Gaussian like and top-hat was investigated on acoustic emission signal and pore formation in welding. Inline penetration depth was measured with ICI(Inline Coherent Imaging) technique and the data was verified with real time X-ray image on laser welding. The laser welding performance at low pressure environment was evaluated for the thick plate alloy steel. UV laser was used to weld various metals such as Cu, Aluminum, steel and stainless steel. The effect of the wavelength of the laser on the formation of the wave at the wall of the key-hole front and the absorptivity was investigated.

• 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.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.5
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• pp.433-441
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• 2023

Piezoelectric ceramics play an important role in electrical and electronic devices such as sensors, actuators, and microelectronic devices. However, traditional ceramics are difficult to be used in various process industries due to their high brittleness and low flexibility. Therefore, piezoelectric paint sensors have been designed for application to the curved surfaces of complicated structures. Furthermore, recently, significant attention has been focused on the development of paint sensors that can be used as structure health monitoring sensors for vibration, impact, and acoustic emission. Several studies have successfully demonstrated the possibility that smart paint sensors can take the place of traditional ceramic sensors. In this review, we briefly introduce the concept of the piezoelectric paint sensors and the expected application field as well as their preparation and history.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1570-1575
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• 1991

The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.05a
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• pp.39-43
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• 2002

As the concept of the smart structure, monitoring of acoustic emission (AE) can be applied to inspect the fracture of the entire structure in operating condition using built-in sensors. The objective of this study is to find the characteristics of matrix crack signals in composites due to the different specimen shapes. To detect matrix crack signals, we performed tensile tests by changing the thickness, width and length of the specimen. For the quantitative evaluation, time frequency analysis such as short-time Fourier transform (STFT) was used to characterize the matrix crack signals from PZT sensor. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.703-710
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• 2012

A structural health monitoring technique for locating impact position in a composite plate is presented in this paper. The method employs a single sensor and spatial focusing properties of time reversal(TR) and inverse filtering(IF). We first examine the spatial focusing efficiency of both approaches at the impact position and its surroundings through impact experiments. The imaging results of impact localization show that the impact location can be accurately estimated in any position of the plate. Compared to existing techniques for locating impact or acoustic emission source, the proposed method has the benefits of using a single sensor and not requiring knowledge of anisotropic material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in other ultrasonic testing of plate-like structures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.70-75
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• 1993

Chatter vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life machine life and the productivity of machining process. The In-process monitoring & control of chatter vibration is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer,Accelerometer and AE(Acoustic Emission) sensor for the credible detection of chatter vibration. And a new approach using a neural network to process the features of multi-sensor for the recognition of chatter vibration in turning operation is proposed. With the back propagation training process, the neural network memorize and classify the feature difference of multi-sensor signals.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.169-174
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• 2006

The outstanding mechanical property of optical fiber and the merits of acoustic emission sensing technique are unified for novel sensor system. The generated ultrasonic wave from piezoelectric generator are propagated along the optical fiber and also sensed. The propagated wave can be influence by external pressure on the optical fiber or environmental circumstance. The optical fiber sensor using ultrasonic wave has advantages compare with existing sensor system. In this study, the sensitivity of the optical fiber sensor is experimentally investigated. As the applications of the optical fiber sensor system using piezoelectric ultrasonic waves, the point load on the optical fiber is measured and the monitoring system for the void fraction of two phase flows is developed. The experimental results show the linear relationship between sensed voltage and void fraction.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.38-45
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• 1996

This study was focused on the prediction of the approprite tool life by clarifying the correlation between progressive drill wear and AE signal. on drilling SM45C the following results have been obtained; RMSAE, AE CUM-CNTS had a tendency to increase slowly according to wear size, at 1000rpm, 150mm/min However, these increased suddenly in the range of 0.20~0.22mm wear, about 102 holes and had a tendency to go up and down until the drilling was impossible. The sudden increase of AE signals shows that something is wrong and it is closely connected with drill wear and chipping. It also makes the working surface bad From the above results, AE signals could be used to monitor the drill's condition and to determine the right time to change tools.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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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.