基于小波奇异值分析的汽轮机碰磨特征提取
Feature Extraction of Rubbing Fault for Steam Turbines Based on Wavelet Singularity Analysis
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摘要: 针对汽轮机碰磨故障产生的轴系振动的微弱冲击信号,通过小波变换对测量信号进行滤波处理,在特定的尺度上提取碰磨产生的瞬时冲击成分,并对该冲击成分进行希尔伯特解调分析,用瞬时冲击信号的幅值包络反映信号在碰磨故障作用下产生的突变.对幅值包络信号进行小波奇异值检测,从而确定碰磨故障引起的信号突变点位置和持续作用时间.以某核电汽轮机组实际振动监测信号为例进行了分析,结果表明:采用小波奇异值检测方法对碰磨引起的突变信息进行检测,可以明显改善微弱碰磨故障特征的提取效果.Abstract: Aiming at the weak impact signal produced by rubbing fault of steam turbines, the location and duraction of the signal singularity were determined by conducting filtering process to the measured signal through wavelet transformation, extracting the transient impact component on a specific scale, carrying out Hilbert demodulation analysis to the impact component, enveloping the singularity of the reflection singal under the action of rubbing fault with the amplitude of transient impact singal, and conducting wavelet singularity detection to the amplitude-enveloped singal. An analysis was made to a nuclear power turbine unit using actual measurements of vibration signal. Results show that the feature extraction of slight rubbing fault can be effectively improved by detecting its abrupt information using wavelet singularity analysis.
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