Hybrid de-noising approach for fiber optic gyroscopes combining improved empirical mode decomposition and forward linear prediction algorithms

2016 ◽  
Vol 87 (3) ◽  
pp. 033305 ◽  
Author(s):  
Chong Shen ◽  
Huiliang Cao ◽  
Jie Li ◽  
Jun Tang ◽  
Xiaoming Zhang ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Linear Prediction ◽  
Fiber Optic ◽  
Prediction Algorithms ◽  
Mode Decomposition

A New Method for Discharge State Prediction of Micro-EDM Using Empirical Mode Decomposition

2009 ◽  
Vol 132 (1) ◽  
Author(s):  
Zhenyuan Jia ◽  
Lingxuan Zhang ◽  
Fuji Wang ◽  
Wei Liu
Keyword(s):  
Empirical Mode Decomposition ◽  
Linear Prediction ◽  
Electrical Discharge Machining ◽  
Model Identification ◽  
Prediction Method ◽  
Ar Model ◽  
Micro Edm ◽  
Multisensor Data Fusion ◽  
State Prediction ◽  
Mode Decomposition

The property of high frequency in micro-EDM (electrical discharge machining) causes the discharge states to vary much faster than in conventional EDM, and discharge states of micro-EDM have the characteristics of nonstationarity, nonlinearity, and internal coupling, all of this makes it very difficult to carry out stable control. Thus empirical mode decomposition is adopted to conduct the prediction of the discharge states obtained through multisensor data fusion and fuzzy logic in micro-EDM. Combined with the autoregressive (AR) model identification and linear prediction, the mathematical model for EDM discharge state prediction using empirical mode decomposition is established and the corresponding prediction method is presented. Experiments demonstrate that the new prediction method with short identification data is highly accurate and operates quickly. Even using short model identification data, the accuracy of empirical mode decomposition prediction can stably reach a correlation of 74%, which satisfies statistical expectations. Additionally, the new process can also effectively eliminate the lag of conventional prediction methods to improve the efficiency of micro-EDM, and it provides a good basis to enhance the stability of the control system.

Ensemble Empirical Mode Decomposition Based Event Classification Method for the Fiber-Optic Intrusion Monitoring System

2015 ◽  
Vol 35 (10) ◽  
pp. 1006002 ◽  
Author(s):  
蒋立辉 Jiang Lihui ◽  
盖井艳 Gai Jingyan ◽  
王维波 Wang Weibo ◽  
熊兴隆 Xiong Xinglong ◽  
梁生 Liang Sheng ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Monitoring System ◽  
Fiber Optic ◽  
Ensemble Empirical Mode Decomposition ◽  
Classification Method ◽  
Event Classification ◽  
Mode Decomposition
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