The residual strength prediction and assessment of panels with MSD is very important to aged airplane. This paper presented the loadsharing parallel system reliability model to assess residual strength of this kind of structure. The model treated the structure as a load-sharing parallel system with different type components since different ligaments have different area. The probability distribution of the residual strength of system was derived by Monte Carlo simulation method. The model was verified by test results and most relative errors to test results for this model are about 10 percent.
Taking into account the uncertainty in material property and component quality, a complex mechanical component such as a gear should be treated as a series system instead of a component when evaluating its reliability, since there exist many sites of equal likelihood to fail. Besides, conventional system reliability model is not applicable to such a system because of the statistical dependence among the failures of the every element (damage site). The present paper presents a model to estimate complex mechanical component reliability by incorporating order statistic of element strength into load-strength interference analysis, which can deal with multiple failure mechanisms, reflect statistical dependence among element failure events and that among different failure modes.
The most applied principles for parameter estimation are maximum likelihood and least square error. This paper presents a new principle with regard to the parameter estimation of the three-parameter Weibull distribution. By transforming the cumulative distribution function, constructed is a mapping from the value of the random variable and its corresponding cumulative distribution probability to the scale parameter. The scale parameter estimated by such a mapping is the random variable value and the corresponding cumulative distribution probability dependent when the shape parameter and/or location parameter applied in the mapping is subject to error. Given a set of random variable values or a set of sample values, a larger error in the shape/location parameter brings about larger differences between the scale parameter values obtained with the individual random variable values or sample values, respectively. Based on such a causal relationship between the discrepancy and the shape/location parameter value applied in the mapping relation, a new parameter estimation method is proposed. For the Weibull distribution parameter estimation according to a set of sample values, the right shape parameter and location parameter are those minimizing the discrepancy between the scale parameter values obtained with the individual sample values, respectively. Case studies demonstrate that the proposed method outperforms the maximum likelihood method and the Weibull plot-based least squares method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.