No abstract

Due to the harsh working environment of the construction machinery, a simple distribution cannot be used to approximate the shape of the rainflow matrix. In this paper, the Weibull-normal (W-n) mixture distribution is used. The lowest Akaike information criterion (AIC) value is employed to determine the components number of the mixture. A parameter estimation method based on the idea of optimization is proposed. The method estimates parameters of the mixture by maximizing the log likelihood function (LLF) using an intelligent optimization algorithm (IOA), genetic algorithm (GA). To verify the performance of the proposed method, one of the already existing methods is applied in the simulation study and the practical case study. The fitting effects of the fitted distributions are compared by calculating the AIC and chi-square (χ2) value. It can be concluded that the proposed method is feasible and effective for parameter estimation of the mixture distribution.

The peak over threshold (POT) model is commonly used in extreme load extrapolation. Due to the important role that the threshold plays in establishing a POT model, a method to select the suitable threshold is designed based on multi-criteria decision-making (MCDM) technology. The mean deviation in probability distribution function, Kolmogorov-Smirnov test, and Chi-Square test are employed as the test criteria. An entropy method is applied to obtain the weight values of these tests. The VIKOR method is adopted to obtain compromise solutions according to the corresponding criteria and weight values. The POT requirement is used to determine a suitable threshold. The effectiveness and feasibility of this method are validated by the load time history measured in experiment and generated by simulation. A comparative analysis between this method and two other common methods is also conducted. The proposed method based on MCDM shows better performance. Keywords: peak over threshold (POT), extreme load extrapolation, threshold, multi-criteria decision-making (MCDM), entropy method, VIKOR Highlights • Multi-criteria decision-making technology is adopted. • Simulation is used to show the good performance of the method. • The result is closer to the true threshold value with more intervals. • The superiority of the MCDM method is shown through comparative analysis.

Load spectrum is the basement of reliability analysis. Selecting a suitable operator for a certain model in a typical experiment field is of benefit to the acquisition of load spectrum. Different operating performances caused by different operators have the characteristics of multiple evaluation indicators. In this paper, a comprehensive evaluation method based on median damage is proposed. The method is applied to evaluate the actual operating performances in the experiment field of the excavator. Comparative results show that the proposed method is feasible, and will be more convenient when more indicators are involved. The proposed method provides a theoretical reference for the compiling of load spectrum acquisition specification, and proposes an additional method for the evaluation of the operating performances.

In order to establish an accurate peak over threshold (POT) model for reasonable load extrapolation, a new threshold selection method based on multiple criteria decision making (MCDM) technology is proposed. The fitting test criterion is taken into consideration in the method. For each candidate threshold, the fitting values of several fitting test criteria are integrated into a comprehensive evaluation value through entropy method and MCDM technology. The threshold corresponding to the minimum comprehensive evaluation value is assumed as the optimal threshold. A random simulation study is carried out to evaluate the performance of the method and to compare them with other literature methods. Genuine load data are applied the proposed method. Both the results shown that the proposed method could be seen as an additional method that complements existing threshold selection methods.