• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.5
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• pp.118-123
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• 2004

The compressor has one of important roles in refrigeration cycle and it determines refrigeration efficiency and quality This paper aims to monitor rotary compressors for room air conditioners by using Acoustic Emission(AE) technique. The reliability of rotary compressors has been evaluated through visual inspection on them after long term test. This paper describes methods for acquisition and processing AE raw signal to monitor the state of rotary compressor. A detecting method of abnormal compressor in real time is suggested and special-purpose monitoring system which can be applied to automatic manufacturing line is developed using one-chip microprocessor at low cost.

• 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.

• Journal of Applied Reliability
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• v.13 no.2
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• pp.129-140
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• 2013

As a fundamental experimental study for reliability improvement of lithium ion secondary battery, degradation mechanism was investigated by microscopic observation and acoustic emission monitoring. Microstructural observation of the decomposed battery after cycle test revealed mechanical and chemical damages such as interface delamination, microcrack of the electrodes, and solid electrolyte interphase (SEI). Acoustic emission (AE) signal was detected during charge and discharge of lithium ion battery to investigate relationships among cumulative count, discharge capacity, and microdamages. With increasing number of cycle, discharge capacity was decreased and AE cumulative count was observed to increase. Observed damages were attributed to sources of the detected AE signals.

• Journal of Welding and Joining
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• v.12 no.2
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• pp.97-107
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• 1994

Both in-process quality control and high reliability of the weld is one of the major concerns in applying friction welding to the economical and qualified mass-production. No reliable nondestructive monitoring method is available at present to determine the real-time evaluation of automatic production quality control for friction welding of special hydraulic valve spool of 16mm in diameter. This paper, so that, presents the experimental examinations and statistical quantitative analysis of the correlation between the initial cumulative counts of acoustic emission(AE) occurring during plastic deformation periods of the welding and the tensile strength and other properties of the welded joints of $\phi16$ valve spool as well as the various welding variables, as a new approach which attempts finally to develop real-time quality monitoring system for friction welding.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.90-98
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• 2005

A monitoring system is necessary to make the polishing process more reliable in order to ensure the high quality and performance of the final products. Generally, AE (Acoustic Emission) is known to be closely related to the material removal rate (MRR). As the surface becomes rougher, the MRR and AE increase. Therefore, the surface roughness can be indirectly estimated using the AE signal measured during the polishing. In this study, an AE sensor-based monitoring system was fabricated to detect the very small AE signal resulting from the friction between a tool and a workpiece during polishing. The performance of this monitoring system was estimated according to polishing conditions, the relation between the level of the AE RMS and the surface roughness during the polishing was investigated.

• Smart Structures and Systems
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• v.8 no.3
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• pp.321-341
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• 2011

Acoustic emission (AE) monitoring was conducted for mortar specimens under three types of static loading patterns (cubic-splitting, direct-shear and pull-out). Each of the applied loading patterns was expected to produce a particular fracture process. Subsequently, the AEs generated by various fracture or damage processes carried specific information on temporal micro-crack behaviors of concrete for post analysis, which was represented in the form of detected AE signal characteristics. Among various available characteristics of acquired AE signals, frequency content was of great interest. In this study, cement-based piezoelectric sensor (as AE transducer) and home-programmed DEcLIN monitoring system were utilized for AE monitoring on mortar. The cement-based piezoelectric sensor demonstrated enhanced sensitivity and broad frequency domain response range after being embedded into mortar specimens. This broad band characteristic of cement-based piezoelectric sensor in frequency domain response benefited the analysis of frequency content of AE. Various evaluation methods were introduced and employed to clarify the variation characteristics of AE frequency content in each test. It was found that the variation behaviors of AE frequency content exhibited a close relationship with the applied loading processes during the tests.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.165-173
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• 2011

The acoustic emission(AE) technique is a well established method to carry out structural health monitoring(SHM) of large structures. However, the real-time monitoring of the crack growth in the roller coaster support structures is not easy since the vehicle operation produces very large noise as well as crack growth. In this investigation, we present the waveform parameter filtering method to classify acoustic sources in real-time. This method filtrates only the AE hits by the target acoustic source as passing hits in a specific parameter band. According to various acoustic sources, the waveform parameters were measured and analyzed to verify the present filtering method. Also, the AE system employing the waveform parameter filter was manufactured and applied to the roller coaster support structure in an actual amusement park.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.1
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• pp.45-52
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• 2016

Blast furnaces are crucial equipment for steel production. A typical furnace risks unexpected accidents caused by contraction and expansion of the walls under an environment of high temperature and pressure. In this study, an acoustic emission (AE) monitoring system was tested for evaluating the large-scale structural health of a blast furnace. Based on the growth of shell cracks with the emission of high energy levels, severe damage can be detected by monitoring increases in the AE energy parameter. Using this monitoring system, steel mill operators can establish a maintenance period, in which actual shell cracks can be verified by cross-checking the UT. From this study, we expect that AE systems permit early fault detection for structural health monitoring by establishing evaluation criteria based on the severity of shell cracking.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.37-43
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• 2005

Real time monitoring of exit burr formation is critical in manufacturing automation. In this paper, acoustic emission (AE) was used to detect the burr formation during drilling. By using wavelet transform (WT), AE data were compressed without unnecessary details. Then the transformed data were used as selected features (inputs) of a back-propagation artificial neural net (ANN). In order to validate the in process AE monitoring system, both WT-based ANN and cutting condition (cutting speed, feed, drill diameter, etc.) based ANN outputs were compared with experimental data.