• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.100-108
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• 1995

The In-process minitoring of the chatter vibration is necessarily required to an automatic manufacturing system. In this study, we constructed a multi-sensing system using tool dynamoneter, accelerometer and AE(Acoustic Emission) sensor for a more credible detection of chatter vibration. And a new approach using a multiple neural network to extract the features of multi-sensor for the recognition chatter vibration is proposed. With the Back-propagation training process, the neural network memorize and classify the features of multi-sensor signals. As a result, it is shown by multiple neural network that the chatter vibration can be monitored accurately, and it can be widely used in practical unmanned system.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.395-399
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• 2007

Renewable energy sources such as wind energy is copiously available without any limitation. Wind turbines are used to tap the potential of wind energy which is available in millions of megawatt. Reliability of wind turbine is critical to extract this maximum amount of energy from the wind. We reviewed different techniques, methodologies, and algorithms developed to monitor the performance of wind turbine as well as for an early fault detection to keep away the wind turbines from catastrophic conditions due to sudden breakdowns. To keep the wind turbine in operation, implementation of Condition Monitoring System (CMS) is paramount, and for this purpose ample knowledge of these types of system is mandatory. So, an attempt has been made in this direction to review maximum approaches related to CMS in this piece of writing.

• Journal of the Korean Society of Safety
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• v.16 no.2
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• pp.22-26
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• 2001

The machining process on be considered as a planned interaction of the workpiece, the tool and the machine tool. In an unmanned situation, the results of this interaction are to be continuously monitored so that any changes in the machining environment on be sensed to corrective actions. In order to design the process monitoring system for unmanned manufacturing, the identification of chip formation is proposed. The system proposes the method of using acoustic emission(AE) signal analysis to identify the chip formation during cutting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1349-1352
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• 2005

This paper is to investigate a defect for thermal barrier coating layers by acoustic emission method in 4-point bending test. The two-layer thermal barrier coating is composed of $150\mu{m}\;CoNiCrAlY\;bond\;coating\;by\;vacuum\;plasma\;spray(VPS)\;process\;and\;250\mu{m}\;ZrO_2-8wt%Y_2O_3$ ceramic coating layer by air plasma spray(APS) process on Inconel-718. The specimen prepared by cyclic thermal test(500, 1000, 2000cycle) at $1050^{\circ}C$ The AE monitoring system is composed of PICO type sensor, a wide band pre-amplifier(40dB), PC and AE DSP(16/32 PAC) board. The AE event, amplitude, Cumulative energy and count of coating specimens is evaluated according to cyclic thermal test.

• Smart Structures and Systems
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• v.16 no.1
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• pp.67-79
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• 2015

Acoustic emission analysis is an effective technique for monitoring the evolution of damage in a structure. An experimental analysis on a set of reinforced concrete beams under flexural loading was carried out. A mixed AE analysis method which used both parameter-based and signal-based techniques was presented to characterize and identify different failure mechanisms of damage, where the signal-based analysis was performed by using the Hilbert-Huang transform. The maximum instantaneous energy of typical damage events and the corresponding frequency characteristics were established, which provided a quantitative assessment of reinforced concrete beam using AE technique. In the bending tests, a "pitch-catch" system was mounted on a steel bar to assess bonding state of the steel bar in concrete. To better understand the AE behavior of bond-slip damage between steel bar and concrete, a special bond-slip test called pullout test was also performed. The results provided the basis of quantitative AE to identify both failure mechanisms and level of damages of civil engineering structures.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.91-98
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• 2010

This study proposes a monitoring system that effectively watches surroundings by cooperating the various sensor information including image information on a sensor network system. The monitoring system proposed in this paper is developed to watch certain intruders to the internal spaces through the interested region for exceptional time by installing cameras, PIR(Pyroelectric Infrared Ray) sensor and body detectors in such interested regions. Moreover the monitering system is implemented based on the SenWeaver plateform which is a integrated development tools for building wireless sensor network system. In the results of the test that was applied to a practically experimental environment by implementing some interfaces for the proposed system, it was considered that it is possible to watch surroundings effectively using the image information obtained from cameras and multiple sensor information acquisited from sensor nodes.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1993.12a
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• pp.77-84
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• 1993

Systems with journal bearings generally operate in large scale and under severe loading conditions such as steam generator turbines and internal combustion engines, in contrast to the machineries using rolling element bearings. Failure of the bearings in these machineries can result in the system breakdown. To avoid the time consuming repair and considerable economic loss, the detection of incipient failure in journal bearings becomes very important. In this experimental approach, acoustic emission monitoring is employed to the detection of incipient failure caused by intervention of foreign particles most probable in the journal bearing systems. It has been known that the intervention of foreign materials, insufficient lubrication and misassembly etc. are principal factors to cause bearing failure and distress. The experiment was conducted under such designed conditions as inserting alumina particles to the lubrication layer in the simulated journal bearing system. The results showed that acoustic emission could be an effective tool to detect the incipient failure in journal bearings.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.952-955
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• 2000

Nowadays, Internet is so popular that we can easily access the remote site to search information and to communicate remote site and users. People who want to make a collaborate working environment can use JAVA, CORBA, and other internet programming tools like a Perl/XML. The mechanist are try to make the environment fur collaboration within design/manufacturing, simulation, remote sensing through TCP/IP And many industries and research institutions are working towards the agile manufacturing. This paper describes an internet-based real-Time remote monitoring system. The system consists of a hardware setup and a software interface. The hardware setup consists of a machine and its data acquisition hardware, while the software interface incorporates the data acquisition software, the server program, and the client program. The server program acts as the main interface between the data acquisition system and the internet technology. The client program is to be distributed to the remote users who want to monitor the machining status. The system has been demonstrated and verified for an industrial High-Speed Machine (HSM) especially measuring cutting force and acoustic emission. To share the signal, we make the WWW server and display its value. The system has been found to be highly efficient, reliable and accurate.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.817-823
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• 2020

In recent, the machining of difficult-to-cut materials such as titanium alloys, stainless steel, Inconel, ceramic, glass, and carbon fiber reinforced plastics (CFRP) used in aerospace, automobile, medical industry is actively researched. Abrasive waterjet is a non-traditional processing method in which ultra-high pressure water and abrasive particles are mixed in a mixing chamber and shoot out jet through a nozzle, and removed by erosion due to collision with a material. In particular, the nozzle of the abrasive waterjet is one of the most important parts that affect the machining quality as with a cutting tool in general machining. It is very important to monitor the condition of the nozzle because the workpiece is uncut or the surface quality deteriorates due to wear, expanding of the bore, damage of the nozzle and clogging of the abrasive, etc. Therefore, in this paper, we propose a monitoring system based on Acoustic Emission(AE) sensor that can detect nozzle condition in real time during AWJ processing.

• Journal of Aerospace System Engineering
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• v.7 no.1
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• pp.8-18
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.