摘要
脱介作业是选煤工序中非常重要的一环,为降低脱介筛因长期满载荷运转引发的故障,采用基于小波变换-能量特征提取的算法,实时检测和诊断脱介筛。通过自适应修正阈值和改进阈值函数优化小波阈值去噪算法;对正常工作状态及故障状态的脱介筛声音信号进行小波分解,阈值去噪后提取重构信号的能量特征;分析低频子带部分,求解不同状态下的主次频率能量比,进行脱介筛故障诊断。结果表明:改进小波阈值去噪算法的修正准确率提升约10%;小波分解重构信号的低频子带部分能量高于其他子带,对该子带的分析具有代表性;低频子带故障情况的主次频率能量比远高于正常情况,可以实现脱介筛故障诊断;试验结果相较于传统故障诊断方法,诊断准确率提高约5%。
The medium draining is considered a crucial link in the coal selection process.In order to mitigate faults triggered by prolonged operation of the medium draining screen under full load conditions,an algorithm based on wavelet transform and energy feature extraction was employed for monitoring and diagnosing the medium draining screen in real time.By employing methods such as adaptive threshold correction and improving the threshold function,the wavelet threshold denoising algorithm was optimized.The sound signals of the medium draining screen in normal and faulty operating states underwent wavelet decomposition.After threshold denoising,the energy features of the reconstructed signals were extracted.The low-frequency sub-band section was analyzed,and the energy ratio of primary frequency to secondary frequency under different states was calculated,enabling the diagnosis of faults in the medium draining screen.Results indicate that the algorithm of improved wavelet threshold denoising increases the correction accuracy by approximately 10%.The energy of the low-frequency sub-band part of the wavelet decomposed reconstructed signal is higher than that of other sub-bands,making its analysis representative.The energy ratio of primary frequency to secondary frequency of the low-frequency sub-band in faulty operating states is significantly higher than that in normal operating states,enabling the diagnosis of faults in the medium draining screen.Compared with traditional fault diagnosis methods,the diagnostic accuracy of the proposed method increases by about 5%.
作者
尚书宏
曹亮
鲁伟
SHANG Shuhong;CAO Liang;LU Wei(Zhuneng Group Co.,Ltd.,China Energy Group,Ordos Inner Mongolia 010300,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2023年第S02期233-237,共5页
China Safety Science Journal
关键词
小波变换
特征提取
脱介筛
故障诊断
能量特征
小波阈值去噪
wavelet transform
feature extraction
medium draining screen
fault diagnosis
energy features
wavelet threshold denoising
