Multi-performance degradation reliability assessment method for a cabin door locking mechanism. (October 2022)

• Record Type: Journal Article
• Authors: Xie, Juanzhang; Jiang, Deyin; Han, Yajie; Jiang, Shuhai; Cui, Weimin
• Is Part Of: Advances in mechanical engineering. Volume 14:Number 10(2022)
• Publication Date: 2022-10
• Subjects: Locking mechanism -- degradation -- multi-performance -- Wiener process -- Copula function -- reliability assessment; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/16878132221129742
• Languages: English
• ISSNs: 1687-8132

Abstract

A crucial part of the aircraft, the landing gear cabin door locking mechanism directly affects how well the landing gear retracts and how stealthily the aircraft operates. A reliability evaluation approach under multiple deterioration is provided, with a focus on the features of high reliability, small sample, and multiple performance degradation of the locking mechanism. The locking angle of the lock hook and the locking displacement offset of the lock hook are chosen as the characteristic quantities based on the analysis of the factors influencing the life of the locking mechanism; next, the Wiener process is used to model the degradation process of the selected characteristic quantities in order to obtain the failure probability density function for both; then, the multiple performance degradation reliability evaluation model is established using the Copula function, which can precisely and effectively characterize the coupled competitive relationships of multiple performance degradations. This model characterizes the stochastic correlation between the locking angle and the locking displacement of the lock hook. Following that, the Akaike information criteria (AIC) is used to choose the Copula function. Finally, the locking mechanism's reliability assessment is carried out, as well as the evaluation findings are contrasted with those of the usual technique, which only takes into account a single failure performance characteristic quantity. A series of data analyses led to the conclusion that the approach is more relevant and accurate than that of the conventional method, and that it is not prudent to undervalue its dependability.