摘要
本文建立了EN信号的小波包分解能量谱分析方法 ,结果表明该方法可准确地表征EN信号的高频“指纹”特征 ,对腐蚀体系、腐蚀类型及腐蚀状态有较强的分辨能力。
A new energy spectrum description method of electrochemical noise(EN)signals was described by wavelet packets decomposition. Compared with SPD described by FFT method, the subbands energy feature vector obtained through the new method can improve the discrimination of high frequency 'fingerprint' characteristics of EN signals, this mathematical approach could become an alternative tool to categorize different corrosion systems, different corrosion types and different corrosion intensity.
出处
《电子测量与仪器学报》
CSCD
2003年第4期53-56,共4页
Journal of Electronic Measurement and Instrumentation
关键词
小波包分解
电化学噪音
能量谱
腐蚀
EN信号
Wavelet packets decomposition, electrochemical noise(EN), energy spectrum.
