Data preprocessing method of intelligent sensor fault diagnosis system

JIAN Rong-kun; LI Bing-bing; HAN Cheng

doi:10.13873/J.1000-9787(2016)09-0027-03

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Data preprocessing method of intelligent sensor fault diagnosis system

更新时间：2025-09-11

- Data preprocessing method of intelligent sensor fault diagnosis system
- Vol. 35, Issue 9, Pages: 27-29+32(2016)
- 作者机构：
  
  1. 中国电子科技集团公司第四十九研究所
  2. 中国船舶重工集团公司第七O三研究所
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)09-0027-03
  CLC： TP212.6
- Published：2016
- 稿件说明：
移动端阅览
[1]简荣坤,李冰冰,韩诚.智能传感器故障诊断系统数据预处理方法[J].传感器与微系统,2016,35(09):27-29+32.

JIAN Rong-kun, LI Bing-bing, HAN Cheng. Data preprocessing method of intelligent sensor fault diagnosis system[J]. 2016, 35(9): 27-29+32.
[1]简荣坤,李冰冰,韩诚.智能传感器故障诊断系统数据预处理方法[J].传感器与微系统,2016,35(09):27-29+32. DOI： 10.13873/J.1000-9787(2016)09-0027-03.

JIAN Rong-kun, LI Bing-bing, HAN Cheng. Data preprocessing method of intelligent sensor fault diagnosis system[J]. 2016, 35(9): 27-29+32. DOI： 10.13873/J.1000-9787(2016)09-0027-03.

摘要

发动机故障诊断系统中传感器采集到的信号是实际信号和随机噪声的合成

这给故障检测和诊断带来许多不利的影响。将中值滤波和小波分析结合起来使用

中值滤波用于消除数据中的脉冲噪声

小波滤波用于消除数据中的其他平稳随机噪声

仿真结果表明:混合滤波能够有效去除信号中的脉冲噪声与随机噪声

较好地还原了原始信号

将该方法应用于发动机的试车数据

结果表明:该方法具有理想的去除噪声效果。

Abstract

Signal collected by sensor in engine fault diagnosis system is synthesis of actual signal and random noise.This brings many adverse effects to fault detection and diagnosis.It needs to eliminate noise.In view of data characteristics of sensors for engine

a method of data processing based on faults diagnosis system of intelligent sensor is introduced.The method combines median filtering and wavelet analysis.The median filtering is used to eliminate pulse noise and wavelet analysis is used to eliminate random noise.Simulation results show that hybrid filtering can effectively remove pulse noise and random noise

and can restore the original signal.The method is applied to the engine test data

and the results show that the method is effective in removing noise.The method is applied to the test data of the engine

the results show that the method has ideal effect of denoising.

关键词

Keywords

references

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航空发动机传感器故障与部件故障诊断技术 [J]. 李业波,李秋红,黄向华,赵永平. 北京航空航天大学学报 . 2013(09)

基于多传感器融合的卷烟机自诊断系统设计 [J]. 刘庆贵,周冬桥. 传感器与微系统 . 2012(03)

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中值与小波消噪集成的转子振动信号滤波方法研究 [J]. 赵荣珍,李超,张优云. 振动与冲击 . 2005(04)

主元分析方法的故障可检测性研究 [J]. 王海清,宋执环,李平. 仪器仪表学报 . 2002(03)

发动机试验传感器数据证实的软计算方法与系统实现研究 [D]. 唐雅娟. 国防科学技术大学 2007

Sensor fault identification based on time-lagged PCA in dynamic processes [J] . Changkyu Lee,Sang Wook Choi,In-Beum Lee. Chemometrics and Intelligent Laboratory Systems . 2004 (2)

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