No abstract

Human hearing is very sensitive to sound, so a subjective index of sound quality is required. Each situation of sound evaluation is composed of Sound Quality (SQ) metrics. When substituting the level of one frequency band, we could not see the tendency of substitution at the whole frequency band during SQ evaluation. In this study, the Design of Experiments (DOE) is used to analyze noise from an automotive Heating, Ventilating, and Air Conditioning (HVAC) system. The frequency domain is divided into 12 equal parts, and each level of the domain is given an increase or decrease due to the change in frequency band based on the "loud" and "sharp" sound of the SQ analyzed. By using DOE, the number of tests is effectively reduced by the number of experiments, and the main result is a solution at each band. SQ in terms of the "loud" and "sharp" sound at each band, the change in band (increase or decrease in sound pressure) or no change in band will have the most effect on the identifiable characteristics of SQ. This will enable us to select the objective frequency band. Through the results obtained, the physical level changes in arbitrary frequency domain sensitivity can be determined.

Recently, there has been a growing consumer interest in the amount of noise produced by household electrical appliances. The designer of the product must determine the source of the noise, in order to eliminate the source. In the case of a household electric appliance such as the washing machine, the consumer's complaint was about the noise that is generated during the dehydrating condition. However, in the case of the washing machine, it is difficult to identify the noise source when the washing machine uses the dehydrating condition. Several noise sources combine making it difficult to determine the key factor that contributes to the noise output. Multi-Dimensional Spectral Analysis (MDSA) is a method that can remove the correlation between different noise sources, and it expresses the key contributing factor as a unique output. This study utilized MDSA to analyze the contribution of each noise source in the output during the dehydrating condition.

Although Fourier-based methods have been standard methods for frequency analysis, they are not well suited for the analysis of nonlinear or non-stationary systems due to their time-varying natures. Thus, in this paper, a wavelet packetbased technique, which calculates time-varying coherence functions for input/output relationships, is developed. The developed method uses the Coiflet wavelet that has been widely used in signal processing. It is applied to obtain the time-varying coherence function, and to detect the impulse signal from the impulse-embedded signal such as an automobile sound/vibration signal with an external impact caused by a collision or passing over rough terrain. Some characteristics of non-stationary behavior such as the wavelet packet coefficients, maximum phase plane (MPP) analysis and fault detection are also demonstrated. The method gives promising results of non-stationary input-output systems, and so may be used as an effective tool for condition monitoring or fault detection area.

This paper proposes an optimal design scheme to reduce the noise of the intake system by using support vector regression techniques. For this, as a measuring tool for the performance of the intake system, the performance prediction software was used. Then, the length and radius of each component of the current intake system were selected as input variables and the L 18 table of orthogonal arrays was adapted as a space-filling design. The simulation of parameter design utilized an orthogonal array design, 1 7 18 (2 3 ) L ×. In order to evaluate the above design and levels, the experiments satisfying the condition were done. With these simulated data, we can estimate parameters in support vector regression by solving a nonlinear problem and finding an optimal level for the intake system by using support vector regression.This optimal design scheme gives noticeable results and is a preferable way to analyze the intake system. Therefore, an optimal design for the intake system is proposed by reducing the noise of its system.