• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.6
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• pp.1-6
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• 2015

Tool condition monitoring plays one of the most important roles in the improvement of both machining quality and productivity. In this regard, various process signals and monitoring methods have been developed. However, most of the existing studies used cutting force or acoustic emission signals, which posed risks of interference with the machining system in dynamics, fixturing, and machining configuration. In this study, a feed motor current signal is used as a process signal representing process and tool states in tool breakage monitoring based on an adaptive autoregressive model and unsupervised neural network. From the experimental results using various cases of tool breakage, it is shown that the developed system can successfully detect tool breakage before two revolutions of the spindle after tool breakage.

• The KIPS Transactions:PartC
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• v.14C no.3 s.113
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• pp.305-312
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• 2007

In this paper, we present a received signal strength (RSS) prediction model to timely Initiate link layer triggers for fast handoff in a wireless LAN system. Noting that the distance between a mobile terminal and an access point is not changed abruptly in a short time interval, an adaptive RSS predictor based on a stationary time series model is proposed. RSS data obtained from ns-2 simulations are used to identity the time series model and verify the predictability of the RSS data. The results suggest that an autoregressive process of order 1 (AR(1)) can be used to represent the measured RSSs in a short time interval and predict at least 1-step ahead RSS with a high confidence level.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3066-3068
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• 2005

Noise can make surrounding environments inferior and deteriorates operation efficiency, and it can bring aural damage as well as give a person psychological stress. Therefore, necessity of study about noise control is increased for better labor conditions and agreeable habitat. In this paper, implementation of active mufflers using a stable IIR adaptive filters is presented. The IIR filter structure is more effective when acoustic feedback exists, but the adaptive IIR filters could be unstable when the filter algorithm is not yet converged. A stabilizing process for adaptive IIR filter is introduced in this paper. Experiments using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.615-623
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• 2016

The paper describes a hysteretic buck converter including a differentiator and an adaptive hysteresis window controller. Differentiating the feedback signal achieves ultra-fast switching of the buck converter. The adaptive hysteresis window control allows a monotonous operation with predictable noise spectrum, and gives way to efficient design for variable supply and output voltages. The measurement results in a $0.13-{\mu}m$ CMOS process indicated that the switching frequency became double times higher, and the voltage ripple was reduced by up to 69%. They also indicated that the normalized switching frequency variation was reduced by 74% with variable $V_{DD}$ and by 63% with variable $V_{OUT}$. The power efficiency was improved by 3.5% depending on loading condition.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.92-100
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• 2018

This paper presents a link adaptation scheme for adaptive full duplex (AFD) systems. The signal modulation levels and communication link patterns are adaptively selected according to the changing channel conditions. The link pattern selection process consists of two successive steps such as a transmit-receive antenna pair selection based on maximum sum rate or minimum maximum symbol error rate, and an adaptive modulation based on maximum minimum norm. In AFD systems, the antennas of both nodes are jointly determined with modulation levels depending on the channel conditions. An adaptive algorithm with relatively low complexity is also proposed to select the link parameters. Simulation results show that the proposed AFD system offers significant bit error rate (BER) performance improvement compared with conventional full duplex systems with perfect or imperfect self-interference cancellation under the same fixed sum rate.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.9
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• pp.27-35
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• 1993

In this paper, a new algorithm for high level security and quality of speech is proposed. The algorithm is based on the rearrangement of the fast fourier transform (FFT) coefficients with pre and post filter process, hamming window and adaptive pseudo spectrum insertion. Then, the pre and post filters are used for the whitening of speech spectrum and the adaptive pseudo spectrum is inserted for the unclassification of silence/speech. Also, the hamming window technique is applied for the robustness to the syncronization error in the telephone line. According to the simulation results, it can be seen that the security of scrambled signal and the quality of descrambled signal have been improved fairly in both subjective and objective performance test and the new FFT scrambler is robust to the synchronization error.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.163-164
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• 2016

이전까지 많은 연구자들은 적응 신호처리(Adaptive Signal Process)를 이용한 잡음 제거 방법을 연구해 왔다. 그러나, 최근 발전하고 있는 멀티콥터는 프로펠러 모터의 RPM(Revolution Per Minute)이 실시간으로 변하기 때문에 적응 신호처리를 이용하여도 깔끔한 결과를 얻어 내기가 어렵다는 한계가 존재한다. 또한, 특정 주파수를 기준으로 형성되는 고조파(Harmonics)는 적응 알고리즘인 (N)LMS 를 이용한 예측에서 오차를 발생시키는 문제를 발생시킨다. 따라서, 본 논문에서는 멀티콥터를 이용한 음향 취득에 대한 소음 저감 방법으로 회전 속도계(Tachometer), 콤 필터(Comb Filter), NLMS 알고리즘(Normalized Least Mean Square Algorithm)을 이용한 방법을 제안한다.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.457-468
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• 2007

This paper proposes an adaptive moving average (A-MA) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI A-MA chart is to adjust sampling intervals as well as to accumulate previous samples selectively in order to increase the sensitivity. The VSI A-MA chart employs a threshold limit to determine whether or not to increase sampling rate as well as to accumulate previous samples. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI A-MA chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The control length L is introduced to prevent small mean shifts from being undetected for a long period. A Markov chain model is employed to investigate the VSI A-MA sampling process. Formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI A-MA chart is proposed. Comparative studies show that the proposed VSI A-MA chart is uniformly superior to the adaptive Cumulative sum (CUSUM) chart and to the Exponentially Weighted Moving Average (EWMA) chart, and is comparable to the variable sampling size (VSS) VSI EWMA chart with respect to the ATS performance.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.442-450
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• 2000

Active noise control is an approach to noise reduction in which a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and a time-adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Opppenheim model assumed that transfer function characteristics from the canceling source to the error sensor is only propagation delay. But this paper proposes a modified Oppenheim model by considering transfer characteristics of acoustic device and noise path. This transfer characteristics is adaptively cancelled by adaptive model. This is proved by computer simulation with artifically generated random noise and sine wave noise. The details of the proposed architecture, and theoretical simulation and experimental results of the noise cancellation system for three dimension enclosure are presented in the paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.55-60
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• 2021

This paper relates with the performance evaluation of QE-MMA (Quantized Error-MMA) adaptive equalization algorithm based on the stepsize and quantizer bit number in order to reduce the intersymbol interference due to nonlinear distortion occurred in the time dispersive channel. The QE-MMA was proposed using the power-of-two arithmetic for the H/W implementation easiness substitutes the multiplication and addition into the shift and addition in the tap coefficient updates process that modifies the SE-MMA which use the high-order statistics of transmitted signal and sign of error signal. But it has different adaptive equalization performance by the step size and quantizer bit number for obtain the sign of error in the generation of error signal in QE-MMA, and it was confirmed by computer simulation. As a simulation, it was confirmed that the convergence speed for reaching steady state depend on stepsize and the residual quantities after steady state depend on the quantizer bit number in the QE-MMA adaptive equalization algorithm performance.