Intelligent systems approaches to product sound quality evaluations – A review

Pietila, Glenn; Lim, Teik C.

doi:10.1016/j.apacoust.2012.04.012

Cited by 44 publications

(25 citation statements)

References 45 publications

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“…The shock absorber is bad and should not be applied to mass-produced cars 1 The noise has serious S&R that can be perceived by all passengers…”

Section: Jury Evaluationmentioning

confidence: 99%

“…Therefore, much effort is invested in improving car riding comfort and interior sound quality [1]. However, as the main sound and vibration sources have been increasingly well controlled, other types of noise from previously ignored components, such as gear noise [2], heating, ventilation, and air conditioning (HVAC) noise [3], and wiper noise [4], have become prevalent.…”

Section: Introductionmentioning

confidence: 99%

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Identification of vehicle suspension shock absorber squeak and rattle noise based on wavelet packet transforms and a genetic algorithm-support vector machine

Huang

et al. 2016

Applied Acoustics

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Squeak and rattle (S&R) Wavelet packet transform (WPT) Wavelet packet energy (WPE) Wavelet packet sample entropy (WPSE) Genetic algorithm (GA) Support vector machine (SVM) a b s t r a c tThe squeak and rattle (S&R) noise of a vehicle's suspension shock absorber substantially influences the psychological and physiological perception of passengers. In this paper, a state-of-the-art method, specifically, a genetic algorithm-optimized support vector machine (GA-SVM), which can select the most effective feature subsets and optimize the model's free parameters, is proposed to identify this specific noise. A vehicular road test and a shock absorber rig test are conducted to investigate the relationship between these features, and then an approach for quantifying the shock absorber S&R noise is given. Pre-processed signals are decomposed through a wavelet packet transform (WPT), and two criteria, namely, the wavelet packet energy (WPE) and wavelet packet sample entropy (WPSE), are introduced as the feature extraction methods. Then, the two extracted feature sets are compared based on this genetic algorithm. Another advanced method, known as the genetic algorithm-optimized back propagation neural network (GA-BPNN), is introduced for comparison to illustrate the superiority of the newly developed GA-SVM model. The result shows that the WPSE can extract more useful features than the WPE and that the GA-SVM is more effective and efficient than the GA-BPNN. The proposed approach could be retrained and extended to address other fault identification problems.

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“…The shock absorber is bad and should not be applied to mass-produced cars 1 The noise has serious S&R that can be perceived by all passengers…”

Section: Jury Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of vehicle suspension shock absorber squeak and rattle noise based on wavelet packet transforms and a genetic algorithm-support vector machine

Huang

et al. 2016

Applied Acoustics

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“…Sharpness represents the auditory characteristic involving the high-frequency portion of sound [8]. Generally, the higher the sharpness value, the harsher the sound.…”

Section: Sharpnessmentioning

confidence: 99%

“…Many other studies have sought to determine the relationship between automotive S&R and sound quality [3]. Although vehicle interior noise indices have been widely developed [1,8], few investigations have focused on a complete vehicle road test of the sound quality of the suspension shock absorber rattling noise.…”

Section: Introductionmentioning

confidence: 99%

Sound quality evaluation of vehicle suspension shock absorber rattling noise based on the Wigner–Ville distribution

Huang

et al. 2015

Applied Acoustics

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“…A product sound can be generated from physical factors that are transmitted to psychoacoustic factors, which induce psychological reactions in customers and influence their attitudes and behaviors, such as a preference for industrial products (Özcan & Schifferstein, ; Petiot, Kristensen, & Maier, ; Pietila & Lim, ; Västfjäll, Gulbol, Kleiner, & Gärling, ), food‐related behaviors (Elder & Mohr, ; Spence & Shankar, ; Zampini & Spence, ), and brand‐image enhancement (Fastl, ; Flath & Klein, ; Lyon, ). Companies have attempted to develop appropriate sounds to improve the affective reactions of customers, which refers to people's feelings and emotional responses to the sound.…”

Section: Introductionmentioning

confidence: 99%

Exploring the relationship between psychoacoustic and affective variables in a shutter‐press sound

Rhie

Kim

Yun

2019

Hum Ftrs & Erg Mfg Svc

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Whereas smart products have emerged as a new product category, almost no studies have introduced product sounds that give a smart impression. Moreover, technological development has increased the need to shape or design consequential sounds, which have been recognized to depend on the mechanical properties of a product. Therefore, we introduce an approach to design consequential sounds for a camera‐shutter sound. First, we elicit design variables from existing camera‐shutter sounds and conduct an experiment to examine their effects on smartness and satisfaction. Next, the time structure‐related variables of a camera‐shutter sound are modified and evaluated with eight sound descriptors. The results demonstrate the relationship between design variables and affective variables by adopting the concept of psychoacoustic variables. The proposed method might be able to assist in designing a consequential sound to present both smart impressions and other targeted sound impressions depending on the research purpose.

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Intelligent systems approaches to product sound quality evaluations – A review

Cited by 44 publications

References 45 publications

Identification of vehicle suspension shock absorber squeak and rattle noise based on wavelet packet transforms and a genetic algorithm-support vector machine

Identification of vehicle suspension shock absorber squeak and rattle noise based on wavelet packet transforms and a genetic algorithm-support vector machine

Sound quality evaluation of vehicle suspension shock absorber rattling noise based on the Wigner–Ville distribution

Exploring the relationship between psychoacoustic and affective variables in a shutter‐press sound

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