Improved linear regression method for estimating Weibull parameters

Saghafi, Abolfazl; Mirhabibi, A.R.; Yari, Gholamhossein

doi:10.1016/j.tafmec.2009.09.007

Cited by 25 publications

(16 citation statements)

References 2 publications

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“…Several procedures for the calculation of Weibull parameters are known. The Weibull plot (linear-regression method) is the most common one [27][28][29][30]. The two-parameter continuous probability density function for the examined variable is given by the following equation:…”

Section: Methodsmentioning

confidence: 99%

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2017

T FAMENA

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SummaryThe purpose of this study was to investigate and analyse the fracture toughness of yttria stabilized tetragonal zirconia polycrystal (Y-TZP) dental ceramics by means of the Vickers indentation technique. Fracture toughness was analysed under the following loads: 29.42 N, 49.03 N, 196.13 N, and 294.20 N. Cracks that had developed from the vertices of a Vickers indentation were measured and used for the determination of fracture toughness by using nine different models. It was found that fracture toughness depends on the indentation load, the morphology of indentation cracking, and the applied model of fracture resistance. The set of fracture toughness data was analysed using the two-parameter Weibull statistics. The Weibull modulus and the scale parameter were determined by the linear regression method. It was concluded that the Weibull distribution can describe the fracture toughness of Y-TZP ceramics properly.

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Section: Methodsmentioning

confidence: 99%

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2017

T FAMENA

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“…Many methods can be used to determine the value ofF i . One of the commonly used method is Bernard's median rank estimation method [18] as follows:…”

Section: Weibull Distribution Model Of Device Reliabilitymentioning

confidence: 99%

Fault diagnosis method based on Petri nets considering service feature of information source devices

Cheng

Wang

et al. 2015

Computers & Electrical Engineering

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“…The P f can be calculated by experimentally testing a number (n) of specimens, and then ranking the measured strengths in ascending order [12]. In the literature, P f is often defined by using several estimators [24] and the most established to be used is the following equation [12,15,25]: (9) in which i is the ranking of the failure stress and n is total number of tested specimens.…”

Section: Weibull Statistical Strength Distributionmentioning

confidence: 99%

Strength prediction and reliability of brittle epoxy adhesively bonded dissimilar joint

Afendi

Majid

Daud

et al. 2013

International Journal of Adhesion and Adhesives

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This paper deals with strength and failure prediction as well as reliability issues of adhesive joints of brittle epoxy bonding two dissimilar adherends. Effects of bond thickness and scarf angle upon the strength of such joints are also addressed. Three kinds of adhesive joints, i.e., butt, scarf and shear joints are considered. It is found that the strength prediction of various adhesive joints under consideration can be done by establishing interface corner toughness, H c parameter. For adhesive joints with an interfacial crack, fracture toughness, J c or interfacial toughness, K c can be used as a fracture criterion depends on the fracture type observed. The predicted strengths based on these fracture criteria (i.e. H c , J c and K c) are in good agreement with experimental data obtained. Weibull modulus is a suitable parameter to define the strength reliability of adhesive joints. From experimental data, scarf joint of 45° is identified to be preferable since it satisfies both outstanding load-bearing performance and tolerable reliability. In addition, Weibull statistical method has made possible the strength reliability determination of non-cracked adhesive joints.

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Improved linear regression method for estimating Weibull parameters

Cited by 25 publications

References 2 publications

Untitled

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Fault diagnosis method based on Petri nets considering service feature of information source devices

Strength prediction and reliability of brittle epoxy adhesively bonded dissimilar joint

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