基于改进BP算法的惯性仪器故障诊断

Fault Diagnosis of Inertial Apparatus Based on Improved BP Algorithm

为了挖掘隐藏在惯性仪器测试数据背后的信息知识,运用数据挖掘技术,以Clementine12.0为平台建立模型并实现对惯性仪器故障诊断的过程。提出一种基于两阶段聚类并做改进的BP算法,与传统BP算法相比,提高了预测精度和普适能力。

In order to tap the information and knowledge hidden behind the inertial apparatus test data,applying data mining technology and taking Clementine12.0 as platform to establish model and realize the fault diagnosis of inertial instruments.Proposing BP algorithm based on two-stage clustering and its improving,compared with traditional BP algorithm,the prediction accuracy and universal capacity have been improved.