高噪声背景下故障信号自适应检测

J4 ›› 2010, Vol. 28 ›› Issue (06): 637-.

高噪声背景下故障信号自适应检测

李蕴奇1,王忠策2

1吉林省经济信息中心,长春 130061;2吉林农业科技学院信息工程系,吉林吉林 |132101

出版日期:2010-11-27 发布日期:2010-12-24
通讯作者: 李蕴奇(1976— ),女,长春人,吉林省经济信息中心工程师，主要从事信号处理、分布式数据库应用研究（Tel）86-13086868202 E-mail:li.unqi@sina.com。
作者简介:李蕴奇(1976— ),女,长春人,吉林省经济信息中心工程师|主要从事信号处理、分布式数据库应用研究（Tel）86-13086868202（E-mail）li.unqi@sina.com。

Fault Signal Adaptive Detection with High Noisy Environment

LI Yun-qi ¹, WANG Zhong-ce^2

1Center of Economic and Information of |Jilin Province,Changchun 130061,China|
2Department of Information Engineering|Jilin Agriculture and Technology College, Jilin 132101, China

Online:2010-11-27 Published:2010-12-24

摘要/Abstract

摘要：

为尽早发现电厂锅炉潜在故障,以研究高噪音背景下故障自适应检测系统为途径,提出了高噪音背景下故障信号检测的算法。传统的倒谱分析是对信号基于FFT(Fast Fourier Transformation)变换,而该算法对其进行改进,基于CZT（Chirp Z\|Transform）变换进行求逆,得到的故障特征曲线更稳定、更可靠。通过实验证明，该计算方法快速有效,故障报出的正确率在99％以上。

关键词: 高噪音, 自适应检测, CZT变换, FFT算法, 倒谱分析

Abstract:

For early detection of boilers potential failure in power plant the high noise background fault self\|adaptive detection system is studied. A higher background noise fault signal detection algorithm is provided. Simulation experiment results, and points out that the efficiency of the method. The traditional cepstrum analysis is applied to signal based on FFT (Fast Fourier Transformation) transform, and the algorithm is based on the improvement CZT (Chirp Z\| inverse Transform) transform, get the failure characteristics of curve more stable, and more reliable. The experimental results show that this method is fast and effective, fault quoted accuracy over 99%.

Key words: high noise, adaptive detection, chirp z-transform(CZT), fast fourier transformation(FFT)algorithm, cepstrum analysis

中图分类号:

TP391.5

李蕴奇,王忠策. 高噪声背景下故障信号自适应检测[J]. J4, 2010, 28(06): 637-.

LI Yun-qi, WANG Zhong-ce. Fault Signal Adaptive Detection with High Noisy Environment[J]. J4, 2010, 28(06): 637-.