• International Journal of Fluid Machinery and Systems
• /
• v.8 no.4
• /
• pp.264-273
• /
• 2015

This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and two Francis model test turbines all at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that two to three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible.

• Proceedings of the Korean Society For Composite Materials Conference
• /
• 2001.05a
• /
• pp.268-271
• /
• 2001

When compared to other composite materials such as FRP and MMC, hybrid composite material is more attractive one due to the high specific strength and the resistance to fatigue. However, the fracture mechanism of hybrid composite material is extremely complicated because of the bonding structure of metals and FRP. Recently, nondestructive technique has been used to evaluate the fracture mechanism of these composite materials. In this study, AE technique has been used to clarify the fracture mechanism and the degree of damage for Al 7075/CFRP hybrid composite material. It was found that AE event, energy and amplitude among AE parameters were effective to evaluate fracture process of Al 7075/CFRP composite material. In addition, the relationship between the AE signal and the characteristics of failure surface using optical microscope was discussed.

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

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.05a
• /
• pp.241-245
• /
• 2005

This study introduces the wind turbine (W/T) noise evaluation procedure required in the international standard (IEC 61400-11) and monitoring system for the evaluation. Noise emission characteristics of a 750kW W/T generator is investigated. Test and evaluation are performed on J48 W/T model which is under operation in Daekwanryung Wind Test Site. With the noise signal, meteorological data and W/T operational data are monitored in real time by the integrated monitoring system using LabVIEW. From the measured noise data, acoustic power level and tonality of the W/T are estimated under the wind speeds required by the international standard.

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

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

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.12 no.4
• /
• pp.23-28
• /
• 2003

This paper describes the machining characteristics of a developed micro grooving machine. Experiments have been conducted on the various grooving condition such as spindle revolution speed, feed rate and depth of groove. V and U-shaped blade tool and STD11 workpiece was used in this study. To evaluate the developed micro grooving machine, AE signal obtained from each experimental condition was analyzed, and cutting stability was compared with the surface state. As a result this study presented the process to optimize grooving condition and possibility of application of AE technique in groove machining.

• Journal of the Korean Society for Precision Engineering
• /
• v.7 no.4
• /
• pp.130-139
• /
• 1990

It is well known that mechanisms of fracture and crack growth depend upon material characteristics such as fracture toughness, environmental condition, crack geometry and mechanical properties. It seems to be very important to investighate the effects of the above factors on the behavior of structural components which contain flaws for the detailed evaluation of their integrity. In this experimental research, fracture behaviors of SK-5 high carbon steel was investigated by using Acoustic Emission(AE) technique. Fracturing processes of materials were estimated through both the tension test with nominal specimens and the fracture test with compact tension specimens. The critical applied load which corresponds to the crack initiation and propagation is very improtant for the determination of yield strength of fracture toughness. The critical applied load($P_Q$) was determined through AE method and the source of AE signal was estimated by fractography analysis. The experimental results may contribute to the safety analyses and strength evaluation of structures.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2000.11a
• /
• pp.246-250
• /
• 2000

In this paper, Frequency spectra of AE(acoustic emission) signals generated from the magnetizing and the load currents in the actual operating cast-resin power transformer of 500[kVA] under distribution system of22.9[kV] were also analysed to distinguish the AE signals due to void discharges from the magnetic circuit noises in the core of cast-resin power transformer. As the experimental results, we could distinguish the AE signals whether those signals were caused due to the void discharges or due to the magnetic circuit noises by analyzing the frequency spectrum of AE signals. Frequency spectra of AE signals generated from the cast-resin power transformer in operation due to both the magnetizing and the load currents appeared in the range of 40-120[khz].

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.131-137
• /
• 1994

Detection of grinding trouble occuring during the grinding process is classified into two types, i.e, based on the quantitative and qualitative knowledge. But, since the grinding operation is especially related with a large amount of functional parameters, it is actually defficult to cope with the grinding troubles occuring during process. Therefore, grinding trouble-shooting has difficulty in satisfying the requirement from the user. To cope with the grinding troubles occuring during the process, the application of neural network is on effective way. In this study, we identify the four parameters derived from the AE(Acoustic Emission) signals and present the grinding trouble-shooting system utilizing a back-propagation model of the neural network.