A review on data mining approaches for clustering, classifying and optimizing the level of sound and vibration in vehicle cabin

Zulkifli Mohd Nopiah, Ahmad Kadri Junoh

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Level of acoustics and vibration in the vehicle cabin can serve as two explanatory factors for customer's purchase of a particular vehicle. Since the assessment towards both factors is influenced by subjective judgment therefore this study has carried out data mining approach to analyze the sound and vibration data by clustering and classifying the level of annoyance which is commonly experienced in the car cabin. The theory of fuzzy set was adopted to propose noise annoyance fuzzy index where this index will be employed practically in the fields of engineering since its performance to be more precise. Later regression analysis techniques were employed to observe the correlation trends that exist between both factors. In addition, the effect of exposed vibration that originated by rolling tires interaction with road surface has been investigated by predicting the amount generated noise due to this scenario. The main focus in methodology is on trends that statistically occurred for both noise and vibration which been exposed over the engine transmissions [rpm] at both stationary and non-stationary conditions. At the end of studies linear and non-linear optimization model were developed by making the exposed vibration as model input for gaining optimal acoustics level in the cabin. By referring to the results the studies proposes a beneficial algorithm for acoustics researchers where it is very much fundamental in the process of vehicle manufacturing in order to obtain better acoustical comfort in interior cabin.

Original languageEnglish
Pages (from-to)3693-3703
Number of pages11
JournalInformation (Japan)
Volume18
Issue number8
Publication statusPublished - 1 Aug 2015

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Vibrations (mechanical)
Data mining
Acoustics
Acoustic waves
Fuzzy sets
Tires
Regression analysis
Railroad cars
Engines

Keywords

  • Acoustics
  • Clustering and classification
  • Data mining

ASJC Scopus subject areas

  • General

Cite this

A review on data mining approaches for clustering, classifying and optimizing the level of sound and vibration in vehicle cabin. / Mohd Nopiah, Zulkifli; Junoh, Ahmad Kadri.

In: Information (Japan), Vol. 18, No. 8, 01.08.2015, p. 3693-3703.

Research output: Contribution to journalArticle

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