Abstract
In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72–0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.
Original language | English |
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Pages (from-to) | 18-30 |
Number of pages | 13 |
Journal | International Journal of Reliability and Safety |
Volume | 13 |
Issue number | 1-2 |
DOIs | |
Publication status | Published - 1 Jan 2019 |
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Keywords
- Fatigue lives
- Metal magnetic memory signals
- Probabilistic
- Weibull distribution
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
Cite this
The probabilistic analysis of fatigue crack effect based on magnetic flux leakage. / Ahmad, M. I.M.; Arifin, Azli; Abdullah, Shahrum; Jusoh, W. Z.W.; Singh, S. S.K.
In: International Journal of Reliability and Safety, Vol. 13, No. 1-2, 01.01.2019, p. 18-30.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The probabilistic analysis of fatigue crack effect based on magnetic flux leakage
AU - Ahmad, M. I.M.
AU - Arifin, Azli
AU - Abdullah, Shahrum
AU - Jusoh, W. Z.W.
AU - Singh, S. S.K.
PY - 2019/1/1
Y1 - 2019/1/1
N2 - In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72–0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.
AB - In this paper, probabilistic analysis on the fatigue crack effect was investigated by applying the Metal Magnetic Memory (MMM) method, based on Self-Magnetic Leakage Field (SMLF) signals on the surface of metal components. The precision of MMM signals is essential in identifying the validity of the proposed method. The tension-tension fatigue test was conducted using the testing frequency of 10 Hz with 4 kN loaded, and the MMM signals were captured using the MMM instrument. As a result, a linear relationship was observed between the magnetic flux leakage and cyclic loading parameter, presenting the R-squared value at 0.72–0.97. The 2P-Weibull distribution function was used as a probabilistic approach to identify the precision of the data analysis from the predicted, and experimental fatigue lives, thereby showing that all points are placed within the range of a factor of 2. Additionally, the characteristics of PDF, CDF, failure rate and failure probability data analysis were plotted and described. Therefore, a 2P-Weibull probability distribution approach is determined to be an appropriate method to determine the accuracy of data analysis for MMM signals in a fatigue test for metal components.
KW - Fatigue lives
KW - Metal magnetic memory signals
KW - Probabilistic
KW - Weibull distribution
UR - http://www.scopus.com/inward/record.url?scp=85058789169&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85058789169&partnerID=8YFLogxK
U2 - 10.1504/IJRS.2019.097011
DO - 10.1504/IJRS.2019.097011
M3 - Article
AN - SCOPUS:85058789169
VL - 13
SP - 18
EP - 30
JO - International Journal of Reliability and Safety
JF - International Journal of Reliability and Safety
SN - 1479-389X
IS - 1-2
ER -