• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.4
• /
• pp.347-354
• /
• 2009

Frequency analysis is one of the most useful way to analyze response signal for the purpose of grasping the dynamic characteristics of system through Fourier transformation. Although it is very effective way for frequency analysis, it is hard to analyze out a specific sound or vibration component which is correlated with others. In this thesis, source contribution analysis tool for NI-PXI equipment is developed with LabVIEW using coherences of MISO(multiple-input single-output) model. For the purpose of examining propriety of developed tool, simulation is performed with several correlated signals that have different frequency range. After checking the OCF(ordinary coherence function) and PCF(partial coherence function) of the each signal for concerned frequency domain, an experiment is conducted on an evaporator that cause the principal noise of a refrigerator. This developed tool will be expected to build up more convenient and serviceable measurement system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2013.10a
• /
• pp.525-530
• /
• 2013

With the increasing the importance of emotional quality of vehicle, the sound quality of systems with electric motor components has become increasingly important. Electric motors are used for windows, seats, sun roof, mirrors, steering columns, windshield wiper, climate control blowers, etc. In this paper, a study was conducted to identify sound quality factors that contribute to customer's satisfaction and preference of the window lift system. Jury test for subjective evaluation was carried out and sound quality index was developed. Averaged sound pressure level and sharpness were significant factors when glass moves down. Also, maximum loudness at stop section and averaged loudness were significant factor when glass moves up. Noise source identification was carried out for the reduced the loudness and sharpness during glass transferred section and impulsive noise at stop section, Using the source identification result, several improvement points were applied. And finally, the degree of sound quality improvement was judged using sound quality index.

• ETRI Journal
• /
• v.43 no.6
• /
• pp.991-1003
• /
• 2021

Automatic modulation classification is essential in radar emitter identification. We propose a cascade classifier by combining a support vector machine (SVM) and convolutional neural network (CNN), considering that noise might be taken as radar signals. First, the SVM distinguishes noise signals by the main ridge slice feature of signals. Second, the complex envelope features of the predicted radar signals are extracted and placed into a designed CNN, where a modulation classification task is performed. Simulation results show that the SVM-CNN can effectively distinguish radar signals from noise. The overall probability of successful recognition (PSR) of modulation is 98.52% at 20 dB and 82.27% at -2 dB with low computation costs. Furthermore, we found that the accuracy of intermediate frequency estimation significantly affects the PSR. This study shows the possibility of training a classifier using complex envelope features. What the proposed CNN has learned can be interpreted as an equivalent matched filter consisting of a series of small filters that can provide different responses determined by envelope features.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2006.05a
• /
• pp.1334-1337
• /
• 2006

System identification is the field of modeling dynamic systems from experimental data. As a modeling technique, we can mention finite element method (FEM). In addition, we are able to measure modal data as the experimental data. The system can be generally categorized into a gray box and black box. In the gray box, we know mathematical model of a system, but we don't know structural parameters exactly, so we need to estimate structural parameters. In the black box, we don't know a system completely, so we need to identify system from nothing. To date, various system identification methods have been developed. Among them, we introduce system realization theory which uses Hankel matrix and Eigensystem Realization Algorithm (ERA) that enable us to identify modal parameters from noisy measurement data. Although we obtain noise-free data, however, we are likely to face difficulties in identifying a structure with hidden modes. Hidden modes can be occurred when the input or output position comes to a nodal point. If we change a system using a mode decoupling controller, the hidden modes can be revealed. Because we know the perturbation quantities in a closed loop system with the controller, we can realize an original system by subtracting perturbation quantities from the closed loop system. In this paper, we propose a novel method to identify a structure with hidden modes using the mode decoupling controller and the associated example is given for illustration.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.36 no.4
• /
• pp.233-242
• /
• 2023

The unscented Kalman filter (UKF), which is widely used to estimate the states of nonlinear dynamic systems, can be improved to realize robust system identification by using multiple sigma-point sets. When using Kalman filter methods for system identification, artificial noises must be appropriately selected to achieve optimal estimation performance. Additionally, an appropriate scaling factor for the sigma-points must be selected to capture the nonlinearity of the state-space model. This study entailed the use of Bouc-Wen hysteresis model to examine the nonlinear behavior of a single-degree-of-freedom oscillator. On the basis of the effects of the selected artificial noises and scaling factor, a new UKF method using multiple sigma-point sets was devised for improved robustness of the estimation over various signal-to-noise-ratio values. The results demonstrate that the proposed method can accurately track nonlinear system states even when the measurement noise levels are high, while being robust to the selection of artificial noise levels.

• Journal of KSNVE
• /
• v.21 no.4
• /
• pp.30-32
• /
• 2011

• The Magazine of the IEIE
• /
• v.28 no.11
• /
• pp.80-80
• /
• 2001

• Journal of Power System Engineering
• /
• v.7 no.3
• /
• pp.23-28
• /
• 2003

In heavy nuclear power plant, high energy through main steam line is provided to turbine that generate the electric power. Since plant had generated power, high noise has been occurred. Noise make equipments and work environment worse. For finding out the location and the cause of making noise, noise was measured along main steam line at open/close test of Main Steam Isolation Valve (MSIV hereafter). As the result, it was identified that the vortex shedding in the cavity of MSIV is main noise source. The profile change of MSIV seat ring was proposed as the method of noise reduction. After filletting MSIV seat ring, the noise level reduced $10{\sim}20dB$ compared before the change of profile.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.387-392
• /
• 2003

This study is put a focus on the identification of sound characteristics according to the interior configuration of sound absorption material and air gap. Noise barrier is general consists of front perforated panel, air layer, sound absorption material, air gap and back plate. Noise barrier is required to the NRC value of 0.7. The absorbing performance of the noise barrier relies on the opening ratio of the perforated panel and the efficiency of the absorbing material. This study has observed the effect of opening ratio and hole size, the increase of sound absorbing performance by the configurations of sound absorption material and air gap. New designed noise barrier is achieved the acoustical performance of 0.87 the measurement in a reveration room.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.125-131
• /
• 2000

The turbo chiller uses centrifugal compressor, which operates at about 14500 rpm. Due to the high rpm of the impeller, the noise of chiller makes one of the serious problems. The possibility of the sound reduction by using absorbing material is studied in this paper. The generated sound propagates through the duct and then radiates to the outer field. So, the use of sound absorption material inside the duct is one of the effective methods. To study the effect of location of the material, we use Boundary Element Method to analyze the sound field inside the duct system. Numerical study shows the highest sound pressure region is near the elbow of curved duct. From the analysis, it is also shown that the elbow duct is the main radiator of noise and sound absorption treatment of this duct results noise reduction of the highest noise level at BPF and high frequency region.