• Journal of KSNVE
• /
• v.9 no.2
• /
• pp.265-272
• /
• 1999

A LMS algorithms has been widely used for an adaptive filter algorithm in active noise control systems. But this algorithm has poor convergence and it is very difficult to select optimal convergence parameters in this algorithm. In this paper, a fuzzy LMS algorithm where the convergence parameters are computed using a fuzzy logic controller was proposed. A proposed algorithm was applied to active noise control system in HVAC(central Heating Ventilation and Air Conditioning) ducts. The experimental ducts and experimental apparatus were designed and manufactured for experiments, and the modelling of the experimental ducts was also performed for computer simulations. Computer simulations and experiments were performed to show the effectiveness of a proposed algorithm.

• Journal of Sensor Science and Technology
• /
• v.32 no.6
• /
• pp.475-480
• /
• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.17 no.10
• /
• pp.983-992
• /
• 2007

It was proposed to identify Thiele Small Parameters for loudspeaker attached to closed-box using known dynamic mass of moving parts. Also, enhanced PSPICE circuit model for closed-box loudspeaker system was proposed to more accurately simulate real closed-box loudspeaker system. Frequency dependent parameters were used to model voice coil inductor. Acoustic pressure response curves and electrical impedance curves were simulated and investigated by PSPICE circuit model according to compensation filter's parameters. Finally, proposed method is expected to be utilized for identification of pseudo Thiele Small parameters of microspeaker.

• Journal of Korea Multimedia Society
• /
• v.16 no.12
• /
• pp.1368-1375
• /
• 2013

In this paper, we presents a spatially adaptive noise detection and removal algorithm. Under the assumption that an observed image and the additive noise have Gaussian distribution, the noise parameters are estimated with local statistics, and the parameters are used to define the constraints on the noise detection process, where the first order Markov Random Field (MRF) is used. In addition, an adaptive low-pass filter having a variable window sizes defined by the constraints on noise detection is used to control the degree of smoothness of the reconstructed image. Experimental results demonstrate the capability of the proposed algorithm.

• Journal of Mechanical Science and Technology
• /
• v.19 no.spc1
• /
• pp.336-342
• /
• 2005

The DC motor of a vehicle may cause noise and vibration due to high-speed revolution, which can make a driver feel uncomfortable. There have been various studies attempting to solve these problems, mostly focusing on the causes of noise and vibration and a means of preventing them. The CAE methodology is more efficient than a real test for the purpose of looking for various design parameters to reduce the noise and vibration of the DC motor. In this study, a design process for reducing brush noise is presented with the use of a computer model, which is made by using a multi-body dynamics program (DADS). The design parameters to reduce the brush noise and vibration were proposed using a computer model. They were used to reduce the noise and vibration of the DC motor and verified by the test results of the fan DC motor in the vehicle. This method may be applicable to various DC motors.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.875-880
• /
• 2004

The DC Motor of a vehicle may cause noise and vibration due to high-speed revolution, which can make a driver feel uncomfortable. There have been various studies that attempted to solve these problems, mostly focusing on the causes of noise and vibration and the means of preventing them. The CAE methodology is more efficient than a real test for the purpose of looking for various design parameters to reduce the noise and vibration of the DC motor. In this study, a design process for reducing brush noise is presented with the use of a computer model, which is made by using a multi-body dynamics program (DADS). The design parameters to reduce the brush noise and vibration were proposed using a computer model. They were used to reduce the noise and vibration of a DC motor and verified by the test results of a fan DC motor in a vehicle. This method may be applicable to various DC motors.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.11
• /
• pp.1633-1640
• /
• 2013

In this paper, noise parameters for high frequency modeling of dual-gate FET are extracted and analyzed. To extract thermal noise parameter of dual gate, noise characteristics are measured by changing input impedance of noise source using Tuner, and the influence of pad parasitic elements are subtracted using open and short dummy structure. Measured results indicated that the dual-gate FET is improved the noise figure by 0.2dB compared with conventional cascode structure FET at 5GHz, and it confirmed that the noise figure has dropped due to reduction of capacitances between the drain and source, gate and drain by simulation and analysis of small-signal parameters.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.1964-1966
• /
• 2001

Active Noise control(ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. This research presents ANFIS (Adaptive Network Fuzzy Inference System) controller for adaptively noise cancelling in a duct. ANC system generates secondary control sound pressure with same amplitude and with opposite phase as noise to be eliminated. ANFIS controller is trained to optimize its parameters for adaptively cancelling noise. That is ANFIS train its parameters by gradient descent and LSE method so called hybrid method. This paper present ANFIS in active noise control which provides an improvement convergence speed and limitation of linearity condition. It can model nonlinear functions of arbitrary complexity and ANFIS can construct an input-ouput mapping based on both human knowledge in the form of Takagi and Sugeno's fuzzy if-then rules and stipulated input-output data pairs. This paper also shows that the proposed ANFIS active noise control system successfully cancelled noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.05a
• /
• pp.843-848
• /
• 2001

Railroad noise is one of the main causes of environmental impact. Whenever a new railroad line is planned or a housing project near an existing railroad is proposed, an estimate of the relevant noise levels is usually required. For this, it is necessary to quantify those parameters that affect the railroad noise. This paper deals with an estimation of railroad noise using soundproof tunnel in a high-rise apartment building

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.11a
• /
• pp.139-144
• /
• 2001

Railroad noise is one of the main causes of environmental impact. Whenever a new railroad line is planned or a housing project near an existing railroad is proposed, an estimate of the relevant noise levels is usually required. For this, it is necessary to quantify those parameters that affect the railroad noise. This paper deals with an estimation of railroad noise by the barrier and deck plate of the bridge.