• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.796-801
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• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.5
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• pp.795-799
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• 2013

This paper describes a novel hybrid surface polishing process combining non-traditional electrochemical polishing (ECP) with external artificial ultrasonic vibration. The purpose of this study is to develop an easier method for improving stainless steel surfaces. To this end, vibration electrochemical polishing (VECP), a novel ultrasonic manufacturing process, for enhancing electrochemical reaction and surface quality compared with that achieved using conventional ECP is suggested. In addition, for finding the optimized experimental conditions, the two methods are compared under various current densities. Localized roughness of the work material is measured with atomic force microscopy (AFM) and scanning electron microscopy (SEM) for obtaining detailed surface information.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.787-797
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• 2015

In this paper, a cochlea-inspired artificial filter bank(CAFB) was developed in order to efficiently acquire dynamic response of structure, and it was also evaluated via dynamic response experiments. To sort out signals containing significant modal information from all the dynamic responses of structure, it was made to adopt a band-pass filter optimizing algorithm(BOA) and a peak-picking algorithm (PPA). Optimally designed on the basis of El-centro and Kobe earthquake signals, it was then embedded into the wireless multi-measurement system(WiMMS). In order to evaluate the performance of the developed CAFB, a vibration test was conducted using the El-centro and Kobe earthquake signals, and structural responses of a two-span bridge were obtained and analyzed simultaneously by both a wired measurement system and a CAFB-based WiMMS. The test results showed that the compressed dynamic responses acquired by the CAFB-based WiMMS matched with those of the wired system, and they included significant modal information of the two-span bridge. Therefore this study showed that the developed CAFB could be used as a new, economic, and efficient measurement device for wireless sensor networks(WSNs) based real time structural health monitoring because it could reconstruct the whole dynamic response using the compressed dynamic response with significant modal information.

• Steel and Composite Structures
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• v.46 no.3
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• pp.319-334
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• 2023

Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 15⁰, 30⁰, 45⁰, and 60⁰ folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.

• Smart Structures and Systems
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• v.6 no.4
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• pp.389-403
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• 2010

By using image recognition technology, this paper presents a new fault diagnosis method for rotating machinery with artificial immune algorithm. This method focuses on the vibration state parameter image. The main contribution of this paper is as follows: firstly, 3-D spectrum is created with raw vibrating signals. Secondly, feature information in the state parameter image of rotating machinery is extracted by using Wavelet Packet transformation. Finally, artificial immune algorithm is adopted to diagnose rotating machinery fault. On the modeling of 600MW turbine experimental bench, rotor's normal rate, fault of unbalance, misalignment and bearing pedestal looseness are being examined. It's demonstrated from the diagnosis example of rotating machinery that the proposed method can improve the accuracy rate and diagnosis system robust quality effectively.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.22-31
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• 2005

The purpose of this study is to design a flexural structure that has a function of pan and tilt for an artificial eyeball. The artificial eyeball system has a function of image stabilization, which compensate panning and tilting vibration of the body on which the artificial eyeball is attached. The target closed loop control bandwidth is 50Hz, so the mechanical resonance frequency is required to be more than the control bandwidth, which is a tough design problem because of a big mass of camera and actuator. In this study, the design process including the selection of the principal parameters by numerical analysis with ANSYS will be described, as well as the design results and frequency response.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5C
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• pp.185-192
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• 2012

The objective of this study is to present and verify a method for evaluating the fundamental period of a rockfill dam using artificially generated vibration from a blasting event. In this study, the artificial blasting vibration tests were carried out at the site adjacent to the existing Seongdeok Dam for the first time in Korea. The artificial vibrations were induced by 4 different types of blasting with the various depths of blasting boreholes and the various explosive charge weight. During the tests, the accelerations time histories were recorded at the crest of the dam. In this acceleration history, only free vibration decay part following the main vibration event was extracted and it was analyzed by frequency domain analysis using Fast Fourier Transform (FFT). From the results of FFT, the fundamental period of the target dam was evaluated. It is found that the effect of different blasting types on the fundamental period of the target dam is negligible and the fundamental period of the target dam can be consistently obtained by blasting vibration tests. Furthermore, it is found that the period of the target dam calculated by the method using blasting vibration test is similar to that obtained by the method of previous researchers using the real earthquake records. Therefore, in case that the earthquake record is not available, the fundamental period of a rockfill dam can be reasonably evaluated if blasting vibration test is allowed at the site adjacent to the dam.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.10a
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• pp.291-292
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• 2010

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.393-393
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• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.950-955
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• 2002

ISO 140-11 specifies a method for measuring the acoustic properties of floor coverings from the view-point of reducing impact sound transmission. This test method is limited to the specification of procedures for the physical measurement of sound originating from an artificial impact source under laboratory conditions. In this study, ISO 140-11 was reviewed to applicable to domestic floor coverings installed on lightweight floors.