• Journal of Digital Convergence
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• v.11 no.7
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• pp.135-140
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• 2013

Noise estimation and detection algorithm to adapt quickly to changing noise environment using the LMS Filter. However, the LMS Filter for noise estimation for a certain period of time and need time to adapt. If the signal changes occur, have the disadvantage of being more adaptive time-consuming. Therefore, noise removal method is proposed to a frame basis AELMS Filter to compensate. In this paper, we split the input signal on a frame basis in noisy environments. Remove the LMS Filter by configuring noise predictions using the mean and variance. Noise, even if the environment changes fast adaptation time to remove the noise. Remove noise and environmental noise and speech input signal is mixed to maintain the unique characteristics of the voice is a way to reduce the damage of voice information. Noise removal method using a frame basis AELMS Filter To evaluate the performance of the noise removal. Experimental results, the attenuation obtained by removing the noise of the changing environment was improved by an average of 6.8dB.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.4
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• pp.393-405
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• 2018

Objective: This study examines the types of hazardous factors in the working environment and the time-trend for their exposure levels over 10 years (2007 to 2016). Study Design and Method: The types of hazardous factors and exposure levels were drawn from the 19 measurement reports on the working environment over 10 years at a shock absorber manufacturing facility. Risk assessment of the types of factors and time-trend of exposure levels were evaluated using the factors and exposure levels. Results: A total of 34 hazardous factors were evaluated. The types were noise, 15 organic compounds, seven kinds of acid sand alkalis, eight kinds of heavy metals, and three other compounds. Special management materials used were nickel, hexavalent chrome, and sulfuric acid. Human carcinogens (1A) used were trichloroethylene, nickel, and sulfuric acid. There were six types of substances belonging to the IARC's 2B (body carcinogens) classification or higher, including, methyl isobutyl ketone, ethyl benzene, and trichloroethylene. No detection was found for 627 out of the 2065 total measurements in 19 exposure survey reports, representing 30.4%. Organic solvents, acid and alkali products, and heavy metals showed continuous low exposure concentrations. Noise, welding fumes, and the evaluation of mixed solvents show a gradual decrease in geometric mean and maximum over the time-trend of 10 years. Conclusions: In the case of a shock absorber manufacturing facility, the hazardous factors of noise and the evaluation of mixed solvents still indicate high concentrations exceeding the exposure limits and necessitate reduction studies. These two factors and welding fumes showed a continuous decrease in their ten-year tendency. Organic compounds, acids/alkalis, and heavy metals were managed smoothly in a work environment of continuous low concentrations.

• ETRI Journal
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• v.32 no.2
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• pp.265-272
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• 2010

To supply a power distribution network with stable power in a high-speed mixed mode system, simultaneous switching noise caused at the multilayer PCB and package structures needs to be sufficiently suppressed. The uni-planar compact electromagnetic bandgap (UC-EBG) structure is well known as a promising solution to suppress the power noise and isolate noise-sensitive analog/RF circuits from a noisy digital circuit. However, a typical UC-EBG structure has several severe problems, such as a limitation in the stop band's lower cutoff frequency and signal quality degradation. To make up for the defects of a conventional EBG structure, a partially located EBG structure with decoupling capacitors is proposed in this paper as a means of both suppressing the power noise propagation and minimizing the effects of the perforated reference plane on the signal quality. The proposed structure is validated and investigated through simulation and measurement in both frequency and time domains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.10
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• pp.797-810
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• 1990

The error rate equations of digitally modulated signals transmitted through the Gaussian noise and tone multiple interference channel have been derived. Using the derived equations of error probabilities in the environments of Gaussian noise tone interferer and Gaussian noise multiple interferer, the error rate performances of various digitally modulated signals have been evaluated, and compared in graphs as a function of average carrier to tone interferer power ratio(CIR), average carrier to multiple interferer power ratio(CIT) and the average carrer-to-Gaussian noise powr ratio(CIR). In this paper, the modulation schemes such as amplitude shift keying (ASK), phase shift keying(PSK), frequency shift keying(FSK), minimum shift keying(MSK), quadrature amplitud modulation(QAM) and amplitude phase shift keying(APK) have been selected for the study of performance comparison. The results of comparison show us that, in low bits/sec/Hz, PSK is superior to the other schemes, but in high bits/sec/Hz, mixed multi ary type is better than single multi ary type. And in strong noise evironment, the multiple interferer has much influence than tone interferer, however, in low noise environment. the mojor error factor is tone interferer. But tone interference effect nearly disappears over specified CIR level about 20[dB]. And the modulation schemes using amplitude are heavily influenced by multiple interference.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.695-706
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• 2014

Partial discharge (PD) measurements have emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. But the major problem behind them the PD signal is severely polluted by several noises like White noise, Random noise, Discrete Spectral Interferences (DSI) and the challenge lies with removing these noise from the onsite PD data effectively which leads to preserving the signal for feature extraction. Accordingly the paper is mainly classified into two parts. In first part the PD signal is artificially simulated and mixed with white noise. In second part the PD is measured then it is subjected to the proposed denoising techniques namely Translation Invariant Wavelet Transform (TIWT). The proposed TIWT method remains the edge of the original signal efficiently. Additionally TIWT based denoising is used to suppress Pseudo Gibbs phenomenon. In this paper an attempt has been made to review the methodology of denoising the PD signals and shows that the proposed denoising method results are better when compared to other wavelet-based approaches like Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), by evaluating five different parameters like, Signal to noise ratio, Cross-correlation coefficient, Pulse amplitude distortion, Mean square error, Reduction in noise level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.434-436
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• 2022

For 4th industrial revolution and the development of various communication media, unmanned and automation are rapidly progressing in various fields. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. Accordingly, the importance of preprocessing in a system operating based on an image is increasing, and an algorithm for effectively removing noise from an image is attracting attention. In this paper, we propose a filtering algorithm using noise judgment and a segmentation mask in a complex noise environment. The proposed algorithm calculates the final output by switching the segmentation mask suitable for filtering by performing noise judgment on the pixel values of the input image. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared and evaluated with the existing filter algorithm.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.313-319
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• 2023

In this paper, a time series machine learning model, Long Short Term Memory (LSTM), is applied into the bubble flow noise data and the underwater projectile launch noise data to predict missing values of time-series underwater noise data. The former is mixed with bubble noise, flow noise, and fluid-induced interaction noise measured in a pipe and can be classified into three types. The latter is the noise generated when an underwater projectile is ejected from a launch tube and has a characteristic of instantaenous noise. For such types of noise, a data-driven model can be more useful than an analytical model. We constructed an LSTM model with given data and evaluated the model's performance based on the number of hidden units, the number of input sequences, and the decimation factor of signal. It is shown that the optimal LSTM model works well for new data of the same type.

• International Journal of Fluid Machinery and Systems
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• v.5 no.1
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• pp.18-29
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• 2012

This paper deals with the CFD analysis of cavitating flow in the mixed-flow pump with the specific speed of 1.64 which suffers from a high level of noise and vibrations close to the optimal flow coefficient. The ANSYS CFX package has been used to solve URANS equations together with the Rayleigh-Plesset model and the SST-SAS turbulence model has been employed to capture highly unsteady phenomena inside the pump. The CFD analysis has provided a good picture of the cavitation structures inside the pump and their dynamics for a wide range of flow coefficients and NPSH values. Cavitation instabilities were detected at 70% of the optimal flow coefficient close to the NPSH3 value (NPSH3 is the net positive suction head required for the 3% drop of the total head of the pump).

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.129-132
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• 1999

This paper deals with the optimal filtering problem constrained to input noise signal corrupting the measurement output for linear discrete-time systems. The transfer matrix H$_2$and/or H$_{\infty}$ norms are used as criteria in an estimation error sense. In this paper, the mixed $H_2/H_{\infty}$ filtering Problem in lineal discrete-time systems is solved using the LMI approach, yielding a compromise between the H$_2$and H$_{\infty}$ filter designs. This filter design problems we formulated in a convex optimization framework using linear matrix inequalities. A numerical example is presented.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.209-216
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• 2009

A development in method of evaluating the measurement precisions using approximate F tests and variance components from expected mean square (EMS) is investigated. The research proposes three-factor mixed measurement models with the fixed and random factors. Unrestricted and unconstrained design work was rarely studied, while restricted and constrained designs have been significantly discussed. The unrestricted and unconstrained designs assume to be an independence of interaction. The proposed evaluation method about the measurement precisions can be extended to four-factor random measurement model or mixed measurement model. The study also presents the three evaluation indexes of precisions such as R&RTR (Reproducibility & Repeatability-To-Total Precision Ratio), PTR (Precision-To-Tolerance Ratio), and SNR (Signal-To-Noise Ratio). Numerical examples are proposed to evaluate the approximate F tests with Satterthwaite degrees of freedom and three indexes using the measurement precisions from EMS.