### Abstract

This paper presents a peak-valley segmentation procedure for the wavelet-based extraction of acceleration data. A 60-second acceleration signal was measured on a McPherson frontal coil spring of a 2000 cc Proton sedan car, and the data was used for the simulation. The Morlet wavelet-based analysis was used to extract higher amplitude segments in order to produce a shortened signal that has an equivalent behaviour. Using this process, it has been found that the Morlet wavelet was able to summarise the original data up to 49.45% with less than 10% difference with respect to statistical parameters. This clearly indicates that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well. Finally, it has been proven that the Morlet wavelet successfully identified the higher amplitudes in the acceleration data.

Original language | English |
---|---|

Pages | 475-482 |

Number of pages | 8 |

Publication status | Published - 1 Jan 2013 |

Event | 6th International Conference on Chaotic Modeling and Simulation, CHAOS 2013 - Istanbul, Turkey Duration: 11 Jun 2013 → 14 Jun 2013 |

### Conference

Conference | 6th International Conference on Chaotic Modeling and Simulation, CHAOS 2013 |
---|---|

Country | Turkey |

City | Istanbul |

Period | 11/6/13 → 14/6/13 |

### Fingerprint

### Keywords

- Acceleration data
- Modified data
- Morlet wavelet
- Peak-valley extraction

### ASJC Scopus subject areas

- Modelling and Simulation

### Cite this

*Acceleration data extraction associating to the peak-valley segmentation approach using the morlet wavelet transform*. 475-482. Paper presented at 6th International Conference on Chaotic Modeling and Simulation, CHAOS 2013, Istanbul, Turkey.

**Acceleration data extraction associating to the peak-valley segmentation approach using the morlet wavelet transform.** / Abdullah, S.; Putra, T. E.; Schramm, D.; Nuawi, M. Z.

Research output: Contribution to conference › Paper

}

TY - CONF

T1 - Acceleration data extraction associating to the peak-valley segmentation approach using the morlet wavelet transform

AU - Abdullah, S.

AU - Putra, T. E.

AU - Schramm, D.

AU - Nuawi, M. Z.

PY - 2013/1/1

Y1 - 2013/1/1

N2 - This paper presents a peak-valley segmentation procedure for the wavelet-based extraction of acceleration data. A 60-second acceleration signal was measured on a McPherson frontal coil spring of a 2000 cc Proton sedan car, and the data was used for the simulation. The Morlet wavelet-based analysis was used to extract higher amplitude segments in order to produce a shortened signal that has an equivalent behaviour. Using this process, it has been found that the Morlet wavelet was able to summarise the original data up to 49.45% with less than 10% difference with respect to statistical parameters. This clearly indicates that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well. Finally, it has been proven that the Morlet wavelet successfully identified the higher amplitudes in the acceleration data.

AB - This paper presents a peak-valley segmentation procedure for the wavelet-based extraction of acceleration data. A 60-second acceleration signal was measured on a McPherson frontal coil spring of a 2000 cc Proton sedan car, and the data was used for the simulation. The Morlet wavelet-based analysis was used to extract higher amplitude segments in order to produce a shortened signal that has an equivalent behaviour. Using this process, it has been found that the Morlet wavelet was able to summarise the original data up to 49.45% with less than 10% difference with respect to statistical parameters. This clearly indicates that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well. Finally, it has been proven that the Morlet wavelet successfully identified the higher amplitudes in the acceleration data.

KW - Acceleration data

KW - Modified data

KW - Morlet wavelet

KW - Peak-valley extraction

UR - http://www.scopus.com/inward/record.url?scp=85072339260&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85072339260&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85072339260

SP - 475

EP - 482

ER -