Determining damaging fatigue cycles under influence of random loadings using the root-mean-square level

Research output: Contribution to journalArticle

Abstract

The aim of this paper is to investigate the damaging fatigue cycles criterion using the root-mean-square level under the influence of random loads for coil spring. Fatigue life cycle analysis especially in signal processing involves high computational effort because it deals with large quantity of data from vibratory loads obtained from the coil spring. The captured data of frequent low amplitude cycles generally consist of noise or vibrations which are meaningless and not significant for analysis. Therefore, a criterion using the root-mean-square level is proposed in assessing fatigue life of the captured strain signal from the coil spring. Four strain signals were analysed statistically using global statistics and distribution fitting. Fatigue damage was determined using the Morrow model and control charts were used in the classification of predefined damaging cycles. For evaluating the contribution of these cycles to fatigue damage, cycle elimination process was performed. The results showed a significant reduction of 48%-62% in damage values with damage probability ranging from 0.9362 to 0.9999. Hence, the criterion is useful and has potential to be extended in determining damaging cycles in fatigue analysis in indicating the damaging effects for coil spring.

Original languageEnglish
Pages (from-to)156-167
Number of pages12
JournalJournal of Mechanical Engineering
Volume5
Issue numberSpecialissue3
Publication statusPublished - 15 Feb 2018

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Fatigue of materials
Fatigue damage
Life cycle
Signal processing
Statistics
Control charts

Keywords

  • Damage
  • Fatigue
  • Random
  • Root-mean-square
  • Suspension

ASJC Scopus subject areas

  • Mechanical Engineering

Cite this

@article{185a2a41e2a44dec8c429a8d12d8104e,
title = "Determining damaging fatigue cycles under influence of random loadings using the root-mean-square level",
abstract = "The aim of this paper is to investigate the damaging fatigue cycles criterion using the root-mean-square level under the influence of random loads for coil spring. Fatigue life cycle analysis especially in signal processing involves high computational effort because it deals with large quantity of data from vibratory loads obtained from the coil spring. The captured data of frequent low amplitude cycles generally consist of noise or vibrations which are meaningless and not significant for analysis. Therefore, a criterion using the root-mean-square level is proposed in assessing fatigue life of the captured strain signal from the coil spring. Four strain signals were analysed statistically using global statistics and distribution fitting. Fatigue damage was determined using the Morrow model and control charts were used in the classification of predefined damaging cycles. For evaluating the contribution of these cycles to fatigue damage, cycle elimination process was performed. The results showed a significant reduction of 48{\%}-62{\%} in damage values with damage probability ranging from 0.9362 to 0.9999. Hence, the criterion is useful and has potential to be extended in determining damaging cycles in fatigue analysis in indicating the damaging effects for coil spring.",
keywords = "Damage, Fatigue, Random, Root-mean-square, Suspension",
author = "M. Mahmud and Singh, {S. S.K.} and Shahrum Abdullah and {Mohd Ihsan}, {Ahmad Kamal Ariffin} and {Mohd Nopiah}, Zulkifli",
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AU - Mahmud, M.

AU - Singh, S. S.K.

AU - Abdullah, Shahrum

AU - Mohd Ihsan, Ahmad Kamal Ariffin

AU - Mohd Nopiah, Zulkifli

PY - 2018/2/15

Y1 - 2018/2/15

N2 - The aim of this paper is to investigate the damaging fatigue cycles criterion using the root-mean-square level under the influence of random loads for coil spring. Fatigue life cycle analysis especially in signal processing involves high computational effort because it deals with large quantity of data from vibratory loads obtained from the coil spring. The captured data of frequent low amplitude cycles generally consist of noise or vibrations which are meaningless and not significant for analysis. Therefore, a criterion using the root-mean-square level is proposed in assessing fatigue life of the captured strain signal from the coil spring. Four strain signals were analysed statistically using global statistics and distribution fitting. Fatigue damage was determined using the Morrow model and control charts were used in the classification of predefined damaging cycles. For evaluating the contribution of these cycles to fatigue damage, cycle elimination process was performed. The results showed a significant reduction of 48%-62% in damage values with damage probability ranging from 0.9362 to 0.9999. Hence, the criterion is useful and has potential to be extended in determining damaging cycles in fatigue analysis in indicating the damaging effects for coil spring.

AB - The aim of this paper is to investigate the damaging fatigue cycles criterion using the root-mean-square level under the influence of random loads for coil spring. Fatigue life cycle analysis especially in signal processing involves high computational effort because it deals with large quantity of data from vibratory loads obtained from the coil spring. The captured data of frequent low amplitude cycles generally consist of noise or vibrations which are meaningless and not significant for analysis. Therefore, a criterion using the root-mean-square level is proposed in assessing fatigue life of the captured strain signal from the coil spring. Four strain signals were analysed statistically using global statistics and distribution fitting. Fatigue damage was determined using the Morrow model and control charts were used in the classification of predefined damaging cycles. For evaluating the contribution of these cycles to fatigue damage, cycle elimination process was performed. The results showed a significant reduction of 48%-62% in damage values with damage probability ranging from 0.9362 to 0.9999. Hence, the criterion is useful and has potential to be extended in determining damaging cycles in fatigue analysis in indicating the damaging effects for coil spring.

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KW - Fatigue

KW - Random

KW - Root-mean-square

KW - Suspension

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