中文摘要：

提出一种自适应小波阈值去噪方法,该方法综合软、硬阈值函数的优点,构建了改进的阈值函数,赋予融合系数μ非定值表达式,使其具有较好的适应性。针对采煤机振动信号采集过程中的背景噪声较大的问题,采取分段阈值的方式,阈值根据信号分解层数的不同来确定。Matlab仿真实验表明,与软、硬阈值去噪法相比,改进的阈值去噪法去噪能力更强,而且能更好地保留原始信号的特征,对原始信号的重构更为准确。运用该方法对采煤机摇臂所采集的振动信号进行去噪处理,有效地去除了高频噪声信号,保留了齿轮啮合频率所在的低频频段,提高了信号的信噪比。

英文摘要：

This paper presents a kind of adaptive wavelet threshold denoising method.A new threshod function is built by combining the advantages of soft and hard threshold functions in the method,which gives confluent quotiety a non-constant expression,and has better adaptability.Besides,aiming at the big background noise in the process of coal mining machine vibration signal acquisition,the authors take the form of segmental threshold,which can be determinded according to the different number of signal decomposition layers.The results of the Matlab simulation show that the denoising method has stronger denoising ability.Compared with the soft and hard threshold denoising method,the new method has better ability to remain the characterisitics of original signal,and is more accurate in original signal refactoring.By denoising the vibration signal collected from the coal mining machine with this method,high frequency noise signal is eliminated and low frequency band is remained where meshing frequency of gear is located,then higher SNR is obtained.