基于一种灰色聚类滤波算法的飞机远程故障诊断虚警辨识方法

 在航线排故过程中，常会出现飞机远程实时故障报文信息的“飞机通信与寻址系统(ACARS)虚警”现象，使排故效率降低。对此，本文将灰色聚类和滤波理论结合提出了一种新的辨识算法——灰色聚类滤波算法，将常增益滤波引入灰色聚类算法，在灰色聚类算法中使用ACARS报文故障的当前数据分类故障、判断虚警的基础上，增加报文故障的历史数据，用滤波方法将历史的和当前的数据结合起来，提高辨识虚警的准确性。本算法应用于航空公司的波音777机队，能够有效辨识飞机实时故障报文信息中的虚警。

A Gray Clustering Filtering Algorithm for Identifying False Alert in Aircraft Long-distance Fault Diagnosis

In the course of the line maintenance,"aircraft communication and addressing system(ACARS) false alert" in the fault report downloaded by the aircraft with ACARS often occurs which reduces the maintenance efficiency.To solve the problem,a gray clustering filtering algorithm is set up which is based on gray cluster and filter theory.The algorithm mainly adds a constant coefficient filter to the gray clustering algorithm.First the gray clustering algorithm uses current fault data in the fault report to diagnose false alert, and then the constant coefficient filter combines the result and past fault data to further identify the false alert.This improved the veracity of identification.The algorithm has already been applied in the airlines,which identified effectively the ACARS false alert in the fault report of aircraft Beoing 777.