Health Monitoring of Landing Gear Retraction/Extension System Based on Optimized Fuzzy C-Means Algorithm

被引：5

作者：

Chen, Jie ^{[1
]}

Chen, Senyao ^{[1
]}

Liu, Zhenbao ^{[1
]}

Luo, Caikun ^{[2
]}

Jing, Zhengdong ^{[1
]}

Xu, Qingshan ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Civil Aviat, Xian 710072, Peoples R China

[2] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Peoples R China

来源：

IEEE ACCESS | 2020年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Gears; Actuators; Aircraft; Monitoring; Hydraulic systems; Clustering algorithms; Lubricating oils; Landing gear retraction; extension system; fuzzy c-means; MDS; health monitoring; MODEL;

D O I：

10.1109/ACCESS.2020.3042888

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The landing gear retraction/extension(R/E) system has a critical impact on the safety of aircraft's take-off and landing, and its health status is important to decision-making of the system's prognostics and health management (PHM). With flight parameter data, a method to monitor the health of aircraft landing gear R/E system is proposed based on the improved fuzzy c-means algorithm (FCM). The landing gear health status are classified by the FCM cluster, and the granularity principle and density function are utilized to optimize the number of FCM algorithm clusters and the initial clustering center to better classification. At the same time, an optimized multi-dimensional scaling algorithm (MDS) is used to obtain low-dimensional features which facilitate cluster analysis. And the algorithm comparison and case analysis results show that the proposed method has a great health monitoring effect.

引用

页码：219611 / 219621

页数：11

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