The Need to Evaluate Reliability Based Fatigue Data Analysis

  • Authors

    • N. N. M. Nasir
    • S. Abdullah
    • S. S. K. Singh
    • S. M. Haris
    • S. S. M. Zainal
    https://doi.org/10.14419/ijet.v7i3.36.29357
  • cumulative damage, decomposition, expert systems, fatigue life, reliability

  • Abstract

    This study focuses on an expert system for calculating the variable loading amplitude to predict the fatigue life and reliability analysis of Gumbel distribution. The expert system can provide an effortless way to perform all analyses in one time. This system can also be used to analyse reliability on other distributions, including normal, lognormal, Weibull and Gumbel distribution. The poor ability to analyse an interface with many utility software packages is thus addressed. Strain data signals are calculated using empirical -mode decomposition algorithm. The decomposed signals are sifted into a number of intrinsic mode functions (IMFs) until the signals stop and only shortened signals remain. The total cumulative damage and fatigue-life prediction for decomposed signals are further analysed. The expert system also calculates the statistical parameters. The decomposed signals are then examined based on the reliability model, which can produce the probability density, cumulative distribution and reliability functions. The highest frequency signal is the first intrinsic mode function (IMF 1), with 2.84  10-5 total damage and 3.52  104    cycles for fatigue life of the Coffin-Manson strain-life model. Overall, the developed expert system can enable integrated analysis and produce reliable analysis performance.

     

  • References

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  • How to Cite

    N. M. Nasir, N., Abdullah, S., S. K. Singh, S., M. Haris, S., & S. M. Zainal, S. (2018). The Need to Evaluate Reliability Based Fatigue Data Analysis. International Journal of Engineering & Technology, 7(3.36), 1491-1495. https://doi.org/10.14419/ijet.v7i3.36.29357

    Received date: 2019-05-26

    Accepted date: 2019-05-26