• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.5
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• pp.509-515
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• 2009

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the optimal design for noise reduction of the engine cooling fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1307-1312
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• 2007

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1175-1176
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• 2008

This paper deals with the study on the development of Audio SMPS with reduced noise. The noise defined here is in the range between 20 - 20 kHz frequency that a human can listen. We proposed a design method for Audio SMPS, which reduce noise and raise audio performances. This was achieved by new electronic elements, grounding, pattern, and shielding methods.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.83-87
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• 2008

EPS(Electric Power Steering) system, which has replaced the hydraulic steering system(HPS or HPAS) in many passenger cars recently, have many merits such as low energy consumption, easy mounting, light weight and improvement of environmental pollution. However, EPS system has the problem of motor noise when motor is rotated, which can make a driver feel uncomfortable. There are many techniques to solve those problems, but they are not clear. It is necessary to evaluate the mechanical noise in steering systems, because an EPS has vibration sources such as at the motor gear reducer, manual gears and intermediate joints. In this paper, reduction technique of EPS motor noise is introduced.

• Journal of Engineering Education Research
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• v.27 no.4
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• pp.21-27
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• 2024

This study introduces a series of processes aimed at understanding the noise characteristics generated by jet engines and devising measures to mitigate them through interdisciplinary capstone design projects. During the project execution, educational methods were applied to foster 4Cs (creativity, communication, collaboration, critical thinking) competencies. Project objectives were set through team discussions, and individual team members were assigned primary roles to act as subgroup leaders. As a result, the project was executed as follows: combustion tests were conducted using an SR-30 turbojet engine to generate noise, and the locations and characteristics of the noise sources were identified using beamforming techniques and frequency analysis applied to a 30-microphone array. Additionally, chevron nozzles were designed and fabricated to confirm their noise reduction performance.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.923-936
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• 2014

Images can be contaminated with different types of noise, for different reasons. The neighborhood averaging and smoothing by image averaging are the classical image processing techniques for noise removal. The classical spatial filtering refers to the aggregate of pixels composing an image and operating directly on these pixels. To reduce or remove effectively noise in image sequences, it usually needs to use noise reduction filter based on space or time domain such as method of spatial or temporal filter. However, the method of spatial filter can generally cause that signals of objects as the target are also blurred. In this paper, we propose temporal filter using the piece-wise quadratic function model and enhancement algorithm of image quality for the performance improvement of target detection and tracking by heterogeneous noise reduction. Image tracking simulation that utilizes real IIR(Imaging Infra-Red) images is employed to evaluate the performance of the proposed image processing algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.154-160
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• 2004

In this paper, implementation of active noise curtains using multiple channel adaptive filters is presented. The same numbers of single channel LMS algorithms as control loudspeakers is used instead of a multi-channel LMS algorithm to reduce the computational burden of adaptive filter algorithms. In general, a multi-channel LMS algorithm is usually used in active noise control system. but this algorithm has much more computational complexity. The single channel control techniques have less amount of DSP calculation, compared to multiple channel control techniques. A stabilizing procedure for adaptive IIR filters is also proposed to improve the stability of recursive LMS algorithms. Both experimental results of two control techniques using TMS320VC33 digital signal processor show the similar noise reduction, but the single channel control techniques are more efficient in practical active noise curtain applications

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.737-742
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• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.119-138
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• 2024

Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

• JSTS:Journal of Semiconductor Technology and Science
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• v.9 no.4
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• pp.216-224
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• 2009

The endless scaling down of the semiconductor process made the impact of the power network noise on the performance of the state-of-the-art chip a serious design problem. This paper compares the performances of two popular circuit reduction approaches used to improve the efficiency of power network noise analysis: moment matching-based model order reduction (MOR) and node elimination-based MOR. As the benchmarks, we chose PRIMA and R2Power as the matching-based MOR and the node elimination-based MOR. Experimental results indicate that the accuracy, efficiency, and memory requirement of both methods very strongly depend on the structure of the given circuit, i.e., numbers of the nodes and sources, and the number of moments to preserve for PRIMA. PRIMA has higher accuracy in general, while the error of R2Power is also in the acceptable range. On the other hand, PRIMA has the higher efficiency than R2Power, only when the numbers of nodes and sources are small enough. Otherwise, R2Power clearly outperforms PRIMA in efficiency. In the memory requirement, the memory size of PRIMA increases very quickly as the numbers of nodes, sources, and preserved moments increase.