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高噪声背景下故障信号自适应检测
引用本文:李蕴奇,王忠策.高噪声背景下故障信号自适应检测[J].吉林大学学报(信息科学版),2010,28(6):637-642.
作者姓名:李蕴奇  王忠策
作者单位:吉林省经济信息中心,长春,130061;吉林农业科技学院,信息工程系,吉林,吉林,132101
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

Fault Signal Adaptive Detection with High Noisy Environment
LI Yun-qi,WANG Zhong-ce.Fault Signal Adaptive Detection with High Noisy Environment[J].Journal of Jilin University:Information Sci Ed,2010,28(6):637-642.
Authors:LI Yun-qi  WANG Zhong-ce
Institution: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
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 characteristic...
Keywords:high noise  adaptive detection  chirp z-transform(CZT)  fast fourier transformation(FFT)algorithm  cepstrum analysis  
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