摘要
在电梯钢丝绳断丝检测中,阈值是噪声和断丝信号区分的关键,断丝信号的降噪效果直接受阈值的影响。经典的小波去噪包括软硬阈值两种方法,但硬阈值处理结果会有伪Gibbs震荡现象,软阈值处理结果有固定偏差,在现有阈值去噪基础上,改进软硬阈值函数的方法并结合加入的特征系数来调节小波系数的大小,能较准确地去除信号中的噪声,保留了断丝处的特性,为后续钢丝绳断丝定量识别的准确性提供了条件。
In the elevator wire rope damage inspection, the threshold is the key to distinguish noise and broken wire signals, and the noise reduction effect of the broken wire signal is directly affected by the threshold value. Classical wavelet denoising includes two methods of soft and hard thresholds, but hard threshold processing results have pseudo Gibbs oscillations, soft threshold processing results have fixed deviations. On the basis of existing threshold denoising, soft and hard thresholding methods were improved, and the added characteristic coefficients were added to adjust the size of the wavelet coefficients, a more accurate removal of noise in the signal was achieved. The characteristics of broken wires are retained, and accuracy is provided for the quantitative identification of subsequent wire rope broken wires.
作者
傅其凤
李松
路贵兰
FU Qifeng;LI Song;LU Guilan(School of Mechanical Engineering, Hebei University of Science and Technology,Shijiazhuang Hebei 050018,China)
出处
《机床与液压》
北大核心
2019年第15期194-196,138,共4页
Machine Tool & Hydraulics
关键词
钢丝绳
小波去噪
特征系数
定量识别
Wire rope
Wavelet denoising
Characteristic coefficient
Quantitative identification
