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Reliability analysis of grain dryer based on Weibull distribution
Published:2022-09-22 author:WEN Chang-jun , CHEN Zhe, XU Yun-fei,et al. Browse: 150 Check PDF documents
Reliability analysis of grain dryer based on Weibull distribution

WEN Chang-jun 1,2, CHEN Zhe 1,2, XU Yun-fei 1,2, 
SHAO Ming-ying 1,2, ZUO Xue-qian 1,2
(1.School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China; 
2.Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Wuhan 430068, China)

Abstract:  In order to improve the service life of the grain dryer and reduce the number of maintenance failures, its service life was analyzed and studied by using reliability analysis theory. Firstly, the maintenance data of a certain type of grain dryer was analyzed and sorted, and the Weibull probability plot(WPP)diagram was fitted according to the failure interval time obtained from the maintenance record. Based on the graphical method, it can be preliminarily determined to accept the two-parameter Weibull distribution. Then, the superiority of point estimation was used to judge Criterion, the estimated value obtained by solving the likelihood function with particle swarm algorithm was used as the parameter of the Weibull distribution model. Finally, the K-S(Kolmogorov-Smirnov) test method was used to test the Weibull distribution model, and on the basis, the interval time between failures of the grain dryer was obtained, with probability density function, probability distribution function, and reliability function. The results show that the failure interval of the grain dryer obeys the two-parameter Weibull distribution, and the average failure interval of the dryer is calculated to be 249.8 h, and when the reliability is 0.9, the preventive maintenance period is 137.6 h. The method has high accuracy and ease of use, and is of great significance for enterprises to make reasonable maintenance decisions.
Key words:  grain dryer; mechanical service life; reliability estimation; Weibull distribution model; Weibull probability plot(WPP); reliability function ; K-S(Kolmogorov-Smirnov) test

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