Building the Fatigue Curve Fuzzy Intervals by the Censored Information and Tomography Images


  • Irina V. Gadolina IMASH RAS, Moscow, Russia
  • Maidanov Igor Sergeevich JSC ONPP Technologiya, Obninsk, Russia



Fatigue curve, censored samples, fuzzy regression, computer tomography, polymer composite materials


Fatigue curves of materials are very important and useful in engineering practice. A problem in the application of fuzzy set theory arises from the availability of qualitative (non-numerical), imprecise, and incomplete information. Such information is often obtained from fatigue test data. We use computed tomography (CT) to study the extent of damage to censored samples. Censored samples are samples that were excluded from testing when they reached base test criteria. A fuzzy regression model was developed taking into account linguistic variables. Linguistic variables determine the status of the samples (censored or damaged). Considering the fuzzy dependent variable in the regression model, the coefficients of the regression equation were also transformed into fuzzy variables. The fuzzy dependent variable is the time before the destruction of the censored sample. After examining the images of the defects, the degree of damage is estimated using expert judgment. The model uses the fuzzy method, from different from the classical statistical interval for a given stress amplitude on the fatigue curve, to estimate the probabilistic service life interval. To illustrate the construction of a fuzzy interval, a fuzzy fatigue curve of a polymer composite with a fuzzy interval is shown.


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Author Biographies

Irina V. Gadolina, IMASH RAS, Moscow, Russia

Irina V. Gadolina is a Senior Research Worker in a Mechanical Engineering Research Institute named after A.A. Bagonravov of the Russian Academy of Science. She graduated from Moscow Higher Technical School named after Bauman with a specialty in “Strength of Materials”. Since then, she has been working on the problem of Metal fatigue. The sphere of her interests includes also the reliability problems and the analysis of random loading processes. Her PhD thesis was concerned with the method of longevity estimation of the machine parts under the impact of random loading. She is a reviewer of various journals and conferences.

Maidanov Igor Sergeevich, JSC ONPP Technologiya, Obninsk, Russia

Maidanov Igor Sergeevich was born on May 1, 1986. Higher education. Graduated from the Moscow State Engineering University “MAMI”, Moscow by profession as an engineer. Specialty: technology of processing plastics and elastomers. Works at JSC “ONPP “Technology” named after A. G. Romashin” in Obninsk as an engineer. Area of scientific interests: Polymer composite materials, processing of semi-finished products, quality control.


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How to Cite

Gadolina, I. V., & Sergeevich, M. I. (2024). Building the Fatigue Curve Fuzzy Intervals by the Censored Information and Tomography Images. Journal of Graphic Era University, 12(01), 89–104.