声波的多尺度解析与气固流化床故障检测

Multi-scale analysis of acoustic emissions and malfunction diagnosis in gas-solid fluidized bed

Agglomerations could be detected in a fluidized bed by utilizing wavelet analysis, on the basis of the mechanism that AE signals with different frequencies were emitted when the particles with different sizes impacted the wall.The acoustic signals of particles were investigated in an externally heated fluidized bed 100 in diameter and in a pilot-scale industrial fluidized bed 420 in diameter respectively.In those experiments, the number of small particles decreased obviously while the number of large particles increased due to agglomeration.The signals were decomposed by multi-scale wavelet analysis.While the acoustic energy ratio increased from low scale to high scale layer by layer, the main frequency of acoustic signals transferred from high frequency to low frequency.Meanwhile, the d6th, d7th scales, which represented large size particles, increased suddenly,indicating the occurrence of agglomerations.Thus, the agglomerations in fluidized bed could be quickly and exactly detected online by the acoustic emission technique.

Agglomerations could be detected in a fluidized bed by utilizing wavelet analysis, on the basis of the mechanism that AE signals with different frequencies were emitted when the particles with different sizes impacted the wall. The acoustic signals of particles were investigated in an externally heated fluidized bed Ф100 in diameter and in a pilot-scale industrial fluidized bed Ф420 in diameter respectively. In those experiments, the number of small particles decreased obviously while the number of large particles increased due to agglomeration. The signals were decomposed by multi-scale wavelet analysis. While the acoustic energy ratio increased from low scale to high scale layer by layer, the main frequency of acoustic signals transferred from high frequency to low frequency. Meanwhile, the d6th, d7th scales, which represented large size particles, increased suddenly, indicating the occurrence of agglomerations. Thus, the agglomerations in fluidized bed could be quickly and exactly detected online by the acoustic emission technique.