• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.3
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• pp.8-16
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• 2003

Monitoring of the drill wear :md hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work-piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process and provide a relatively easy way to monitor a machining process for industrial application. for this advantage, AE signal is used to estimate the abnormal fate. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so of but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality. As the results of this experiment AE RMS signal and measurements by vision system are shorn the similar tendency as abnormal state of drilling.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1038-1042
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• 2002

Monitoring of the drill wear and hole quality change is conducted during the drilling process. Cutting force measured by tool dynamometer is a evident feature estimating abnormal state of drilling. One major difficulty in using tool dynamometer is that the work piece must be mounted on the dynamometer, and thus the machining process is disturbed and discontinuous. Acoustic transducer do not disturb the normal machining process, and provide a relatively easy way to monitor a machining process for industrial application. For this advantage, AE signal is used to estimate the abnormal state. In this study vision system is used to detect flank wear tendency and hole quality, there are many formal factors in hole quality decision circularity, cylindricity, straightness, and so on, but these are difficult to measure in on-line monitoring. The movement of hole center and increasement of hole diameter is presented to determine hole quality As the results of this experiment, AE RMS signal and measurements by vision system are shown the similar tendency as abnormal state of drilling. And detection of the abnormal states using BPNs was achieved 96.4% reliability.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.142-147
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• 1998

Developing robot hands with multi-degree-of-freedom is one of the topics that researchers have recently begun to improve the limitation by adding flexibility and dexterity. In this study, an articulated servo-pneumatic robot hand system with direct-drive joints has been developed whose main feature is the minimization of the dimension. The servo-pneumatic system is advantageous to fabricate a dexterous robot hand system due to the high torque-to-weight and torque-to-volume ratio. This enables the design of a finger joint with an integrated rotary vane type actuator which produces high output torque without reduction gears, being very robust. In order to control the servo-pneumatic finger joints, a miniature proportional valve that can be attached to the robot hand is required. In this paper, a flapper nozzle type 4/3-way proportional directional valve has been designed and tested. The experimental results show that the developed valve can control a finger joint satisfactorily without much vibratory joint movements and acoustic noises.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.853-858
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• 2006

TMHMM(Tied Mixture Hidden Markov Model) is an important approach to reduce the number of free parameters in speech recognition. However, this model suffers from a degradation in recognition accuracy due to its GPDF (Gaussian Probability Density Function) clustering error. This paper proposes a clustering algorithm, called HCNN(Homogeneous Centroid Neural network), to cluster acoustic feature vectors in TMHMM. Moreover, the HCNN uses the heterogeneous distance measure to allocate more code vectors in the heterogeneous areas where probability densities of different states overlap each other. When applied to Korean digit isolated word recognition, the HCNN reduces the error rate by 9.39% over CNN clustering, and 14.63% over the traditional K-means clustering.

• Smart Structures and Systems
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• v.1 no.1
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• pp.63-82
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• 2005

This paper introduces a technology for robust and low maintenance cost sensor network capable to detect accelerations below a micro-g in a wide frequency bandwidth (above 1,000 Hz). Sensor networks with such performance are critical for navigation, seismology, acoustic sensing, and for the health monitoring of civil structures. The approach is based on the fabrication of an array of high sensitivity accelerometers, each utilizing Fabry-Perot cavity with wavelength-dependent reflectivity to allow embedded optical detection and serialization. The unique feature of the approach is that no local power source is required for each individual sensor. Instead one global light source is used, providing an input optical signal which propagates through an optical fiber network from sensor-to-sensor. The information from each sensor is embedded onto the transmitted light as an intrinsic wavelength division multiplexed signal. This optical "rainbow" of data is then assessed providing real-time sensing information from each sensor node in the network. This paper introduces the Fabry-Perot based accelerometer and examines its critical features, including the effects of imperfections and resolution estimates. It then presents serialization techniques for the creation of systems of arrayed sensors and examines the effects of serialization on sensor response. Finally, a fabrication process is proposed to create test structures for the critical components of the device, which are dynamically characterized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2569-2574
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• 2012

HMS(Hull Mount Sonar) equipment mounted on PCC(Patrol Combat Corvette) is suitably designed for active mode, and the specific character of sensor or system is not appropriate for the frequency range to detect a torpedo. In this article, in order to implement the function of detecting torpedoes with HMS of existing PCC, I will analyze the feature of input signals each PCCs and design a circuit to compensate reversely for the input signal in certain frequency. And also, I will suggest the most adequate torpedo defense system suitable for the special operating environment and the characteristic of naval vessels, implementing functions such as AGC of input signal and fixing the frequency range of different input signals per different warships.

• Proceedings of the Acoustical Society of Korea Conference
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• 1997.06a
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• pp.27-34
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• 1997

In this study , we tried to test the classification performance of a neural netow and thereby to examine its applicability to the signals distorted by a shallow water einvironment . We conducted an acoustic experiment iin a shallow sea near Pohang, Korea in which water depth is about 60m. The signals, on which the network has been tested, is ilinear frequency modulated ones centered on one of the frequencies, 200, 400, 600 and 800 Hz, each being swept up or down with bandwidth 100Hz. we considered two transforms, STFT(short-time Fourier transform) and PWVD (pseudo Wigner-Ville distribution), form which power spectra were derived. The training signals were simulated using an acoutic model based on the Fourier synthesis scheme. When the network has been trained on the measured signals of center frequency 600Hz,it gave a little better results than that trained onthe simulated . With the center frequencies varied, the overall performance reached over 90% except one case of center frequency 800Hz. With the feature extraction techniques(STFT and PWVD) varied,the network showed performance comparable to each other . In conclusion , the signals which have been simulated with water depth were successully applied to training a neural network, and the trained network performed well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• Speech Sciences
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• v.14 no.4
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• pp.99-114
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• 2007

This study attempted to acoustically analyze the diphthongs of native Jeju speakers in their 70s, 50s, and 20s to observe their diphthong inventories 96 subjects participated in the recording using a set of picture cards. Results show that Jeju dialect speakers in their 70s distinguish /we/ and $/w{\varepsilon}/$, /yo/ and /yc/, but have difficulty pronouncing /ye/, $/y{\varepsilon}/$, and /iy/ correctly. It is interesting to find that the diphthong inventory of Jeju dialect speakers in their 50s are in transitional stage. They share the diphthong inventories of those people in their 70's containing /we/ and $/w{\varepsilon}/$, and /yo/ and /yc/, but they do not produce them as clearly as the latter age group. The former age group also share the common feature with those people in their 20's because both age groups show the same pronunciation of /iy/. The youngest group seldom pronounce /we/ and $/w{\varepsilon}/$, /yo/ and /yc/ correctly unlike native Jeju speakers in their 70s, but they can easily pronounce the diphthong /iy/ like standard Korean speakers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2137-2142
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• 2012

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target classification technique has been considered as a difficult technique. And it has a difficult in collecting actual underwater data. In this paper, we implemented the simulator to synthesize the active target signal, to extract feature and to classify the target in the underwater environment. In target signal synthesis, highlight and three-dimensional model are used and multi-aspect based hidden markov model is used for target classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2505-2511
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• 2013

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target classification technique has been considered as a difficult technique. And it has difficulties in collecting actual underwater data. In this paper, we synthesized active target echoes based on ray tracing algorithm using target model having 3-dimensional highlight distribution. Then, Fractional Fourier transform was applied to synthesized target echoes to extract feature vector. Recognition experiment was performed using neural network classifier.