• Smart Structures and Systems
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• v.11 no.1
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• pp.69-86
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• 2013

An efficient methodology using static test data and changes in natural frequencies is proposed to identify the damages in structural systems. The methodology consists of two main stages. In the first stage, the Damage Signal Match (DSM) technique is employed to quickly identify the most potentially damaged elements so as to reduce the number of the solution space (solution parameters). In the second stage, a particle swarm optimization (PSO) approach is presented to accurately determine the actual damage extents using the first stage results. One numerical case study by using a planar truss and one experimental case study by using a full-scale steel truss structure are used to verify the proposed hybrid method. The identification results show that the proposed methodology can identify the location and severity of damage with a reasonable level of accuracy, even when practical considerations limit the number of measurements to only a few for a complex structure.

• Speech Sciences
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• v.12 no.1
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• pp.135-142
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• 2005

An important aspect of video indexing is the ability to segment video into meaningful segments, i.e., content-based video segmentation. Since the audio signal in the sound track is synchronized with image sequences in the video program, a speech signal in the sound track can be used to segment video into meaningful segments. In this paper, we propose a new approach to content-based video segmentation. This approach uses closed caption to construct a recognition network for speech recognition. Accurate time information for video segmentation is then obtained from the speech recognition process. For the video segmentation experiment for TV news programs, we made 56 video summaries successfully from 57 TV news stories. It demonstrates that the proposed scheme is very promising for content-based video segmentation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.459-464
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• 2001

A reliable tool wear monitoring technique is the one of important aspects for achieving an integrated and self-adjusting manufacturing system. In this paper, a tool wear estimation approach for turning is proposed. This approach uses the model of cutting force, spindle displacement and their relation. A series of experiments were conducted by designing experimental techniques to determine the relationship between flank wear and cutting force coefficient as well as cutting parameters such as cutting speed, depth of cut and feed. The proposed model performance has shown that the spindle displacement model predicts tool wear with high accuracy and spindle displacement signal is possible to replace cutting force signal.

• Smart Structures and Systems
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• v.9 no.1
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• pp.21-33
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• 2012

In this study, a Lamb-wave based damage detection approach is proposed for damage localization in plate. A sensor network consisting of three PZT wafer type actuators/sensors is used to generate and detect Lamb waves. To minimize the complication resulted from the multimode and dispersive characteristics of Lamb waves, the fundamental symmetric Lamb mode, $S_0$ is selectively generated through designing the excitation frequency of the narrowband input signal. A damage localization algorithm based upon the configuration of the PZT sensor network is developed. Time-frequency analysis method is applied to purify the raw signal and extract damage features. Experimental result obtained from aluminum plate verified the proposed damage localization approach.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.363-365
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• 2007

Novel concept of sensor mat and its signal processing method is proposed for patient monitoring in medical application. Proposed sensor mat structure has sensing inner layer which has cross-linked arrangement using plastic optical fiber(POF). Large core diameter of plastic optical fiber behaved as band pass filter by averaging the noise component. caused by unwanted environmental factors. Signal processor followed by sensor output added noise immune performance by filtering out unwanted component. Fail-proof patient breath monitoring scheme was realized by using intelligent decision algorithm. Unlike the conventional approach by using mechanical sensor, which have high sensitivity both to intruder and to environmental noise, our approach provided reliable breath motion detection.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.4
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• pp.20-29
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• 2004

A Tool wear monitoring system is indispensable for better machining productivity with guarantee of machining safety by informing the tool changing time in automated and unmanned CNC machining. Different from monitoring using other signals, the monitoring of spindle current has been used without requiring additional sensors on machine tools. For the reliable tool wear monitoring, current signal only of tool wear should be extracted from other parameters to avoid exhaustive analyses on signals in which all parameters are fused. In this paper, influences of force components of parameters on measured spindle current are investigated and a hybrid approach to cutting force regulation is employed for tool wear signal extraction in the spindle current. Finally, wear levels are verified with experimental results by means of real-time feedrate aspects changed to regulate the force component of tool wear.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.5
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• pp.343-356
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• 1991

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. The development time and cost for implementing a high speed signal processing system can be considerably reduced because algorithm are implemented in software using commercially available digital signal processors. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach not only requires a simple interconnection network but also reduces the number of communications among the processors very much. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors in the system. A systematic scheduling method has been developed by using a processors which can be used efficiently, the methods for solving dependency problems between the processors are investigated. Implementation procedures and results for FIR, recursive (IIR), and adaptive filtering algorithms are illustrated.

• Journal of Welding and Joining
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• v.14 no.4
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• pp.24-32
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• 1996

용접공정 해석을 위한 접근방법중에서 우선적으로 결정해야할 사항으로는 비선형적인 요소와 복잡한 물리현상들을 실제적으로 해석하기위한 측정변수의 선정과 이러한 변수를 사용하여 물리적인 현상을 적절히 표현할 수 있는 알고리즘의 개발 등 을 들 수 있다. 최근까지의 연구결과를 바탕으로 해서 측정변수들의 예를 들면 용접 전류(welding current), 아크전압(arc voltage), 음향신호(acoustic signal), 아크 광(arc light) 그리고 온도(temperature)등이 있다. 용접공정을 분석하기 위한 알고 리즘으로는 확률론적 접근(statistical approach), 다양한 실험치를 이용한 인공지능 적 접근(artificial intelligence approach) 그리고 경험치를 바탕으로 인덱스(index) 을 선정하여 이를 직접 사용하는 방법 및 인공지능과 결합된 형태를 이용하는 방법등 이 있다. 또한 용접공정의 특성을 분석하기 위해서는 크게 금속이행모드(metal transfer mode), 아크의 안정성(arc stability) 그리고 용접품질(weld quality) 등을 판별할 수 있는 알고리즘의 개발이 필수적이라 할 수 있다. 본 논문에서는 용접공정 분석과 관련된 최근까지의 연구동향 및 용접신호의 특성을 좀더 심도있게 분석하기 위해 구축해야 할 필수 요건 등을 소개하고자 하며 이를 사용자가 손쉽게 이용할 수 있는 사용자 인터페이스 프로그램을 개괄적으로 설명하고자 한다.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.197-202
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• 2013

Large gains in speech intelligibility can be obtained using the SNR-based binary mask approach. This approach retains the time-frequency (T-F) units of the mixture signal, where the target signal is stronger than the interference noise (masker) (e.g., SNR > 0 dB), and removes the T-F units, where the interfering noise is dominant. This paper introduces two alternative binary masks based on the distortion constraints to improve the speech intelligibility. The distortion constraints are induced by a gain function for estimating the short-time spectral amplitude. One binary mask is designed to retain the speech underestimated (T-F) units while removing the speech overestimated (T-F)units. The other binary mask is designed to retain the noise overestimated (T-F) units while removing noise underestimated (T-F) units. Listening tests with oracle binary masks were conducted to assess the potential of the two binary masks in improving the intelligibility. The results suggested that the two binary masks based on distortion constraints can provide large gains in intelligibility when applied to noise-corrupted speech.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.889-897
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• 2016

This paper presents an improved approach for compensating rotor position signal displacement in brushless DC (BLDC) motors with misaligned hall-effect sensors. Typically, the hall-effect sensors in BLDC motors are located in each phase and positioned exactly 120 electrical degrees apart. However, limitations in mechanical tolerances make it difficult to place hall-effect sensors at the correct location. In this paper, a position error compensator to counteract the hall-effect sensor positioning error is proposed. The proposed position error compensator uses least squares error analysis to adjust the relative position error and back-EMF information to reduce the absolute offset error. The effectiveness of the proposed approach is verified through several experiments.