Variable amplitude loading strains data distribution using probability density function and power spectral density

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.

Original languageEnglish
Title of host publicationKey Engineering Materials
Pages1115-1120
Number of pages6
Volume462-463
DOIs
Publication statusPublished - 2011
Event8th International Conference on Fracture and Strength of Solids 2010, FEOFS2010 - Kuala Lumpur
Duration: 7 Jun 20109 Jun 2010

Publication series

NameKey Engineering Materials
Volume462-463
ISSN (Print)10139826

Other

Other8th International Conference on Fracture and Strength of Solids 2010, FEOFS2010
CityKuala Lumpur
Period7/6/109/6/10

Fingerprint

Power spectral density
Probability density function
Strain gages
Probability distributions
Data acquisition
Suspensions
Railroad cars
Sampling

Keywords

  • Energy
  • Power spectral density
  • Probability distribution function
  • Variable amplitude loadings

ASJC Scopus subject areas

  • Materials Science(all)
  • Mechanics of Materials
  • Mechanical Engineering

Cite this

Variable amplitude loading strains data distribution using probability density function and power spectral density. / Lennie, A.; Mohd Nopiah, Zulkifli; Abdullah, Shahrum; Baharin, M. N.; Nuawi, Mohd. Zaki; Arifin, Azli.

Key Engineering Materials. Vol. 462-463 2011. p. 1115-1120 (Key Engineering Materials; Vol. 462-463).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lennie, A, Mohd Nopiah, Z, Abdullah, S, Baharin, MN, Nuawi, MZ & Arifin, A 2011, Variable amplitude loading strains data distribution using probability density function and power spectral density. in Key Engineering Materials. vol. 462-463, Key Engineering Materials, vol. 462-463, pp. 1115-1120, 8th International Conference on Fracture and Strength of Solids 2010, FEOFS2010, Kuala Lumpur, 7/6/10. https://doi.org/10.4028/www.scientific.net/KEM.462-463.1115
@inproceedings{a05dce4442284901bfc91e5610f96eb0,
title = "Variable amplitude loading strains data distribution using probability density function and power spectral density",
abstract = "This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.",
keywords = "Energy, Power spectral density, Probability distribution function, Variable amplitude loadings",
author = "A. Lennie and {Mohd Nopiah}, Zulkifli and Shahrum Abdullah and Baharin, {M. N.} and Nuawi, {Mohd. Zaki} and Azli Arifin",
year = "2011",
doi = "10.4028/www.scientific.net/KEM.462-463.1115",
language = "English",
isbn = "9780878492107",
volume = "462-463",
series = "Key Engineering Materials",
pages = "1115--1120",
booktitle = "Key Engineering Materials",

}

TY - GEN

T1 - Variable amplitude loading strains data distribution using probability density function and power spectral density

AU - Lennie, A.

AU - Mohd Nopiah, Zulkifli

AU - Abdullah, Shahrum

AU - Baharin, M. N.

AU - Nuawi, Mohd. Zaki

AU - Arifin, Azli

PY - 2011

Y1 - 2011

N2 - This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.

AB - This paper presents a relative study on variable amplitude (VA) strain data distribution using the approach of probability density function (PDF) and power spectral density (PSD). PDF is a technique to identify the probability of the value falling within a particular interval, and a PSD is to measure the power of a signal by converting it from the time domain to the frequency domain. The objective of this study is to observe the applicability of both techniques in detecting the pattern behaviour in terms of energy and probability distribution. For this reason, a set of case study data consist of nonstationary VA pattern with a random behaviour was used. This kind of data was measured by fixing a strain gauge that connected to the strain data acquisition on the lower suspension arm of a mid-sized sedan car. The data was measured for 60 seconds at the sampling rate of 500 Hz, which gave 30,000 discrete points. The distribution of collected data was then calculated and analysed in the form of both PDF and PSD, and they were then compared for further analysis. The findings from this study are expected for determining the pattern behaviour that exists in VA strain signals.

KW - Energy

KW - Power spectral density

KW - Probability distribution function

KW - Variable amplitude loadings

UR - http://www.scopus.com/inward/record.url?scp=79551492148&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79551492148&partnerID=8YFLogxK

U2 - 10.4028/www.scientific.net/KEM.462-463.1115

DO - 10.4028/www.scientific.net/KEM.462-463.1115

M3 - Conference contribution

AN - SCOPUS:79551492148

SN - 9780878492107

VL - 462-463

T3 - Key Engineering Materials

SP - 1115

EP - 1120

BT - Key Engineering Materials

ER -