中文摘要：

针对低速重载齿轮潜故障状态下磁记忆信号特征信息难以获取的问题，提出了一种基于固有时间尺度分解法（ITD）的磁记忆信号特征提取方法。首先利用ITD方法将原始磁记忆信号分解为若干固有旋转分量PRC和一个单调趋势项，然后将前四阶PRC分量重新组合重构，剔除磁记忆信号自身的大周期成分和磁场噪声，最后再利用周期平均和局部统计法提取出该齿轮每个齿根的磁信号强度。实验结果表明，该方法非常适用于信号有效成分的精确拾取和判断，能有效实现信号的特征提取，对低速重载齿轮潜故障早期诊断领域具有重要的应用价值。

英文摘要：

Aiming at the problem that it is difficult to acquire the feature information of magnetic memory signal for low speed and heavy load gear under fault state, a new method based on the intrinsic time-scale decomposition （ITD） is proposed to achieve the extraction of magnetic memory signal feature. Firstly, the original magnetic memory signals are decomposed into several proper rotation components （PRC） and a monotonous tendency item with ITD method. Then the first four order PRCs are reconstructed to eliminate the large cycle composition in magnetic memory signal and magnetic noise. Finally, the magnetic signal strength of each gear tooth root is extracted using cycle average and local statistic method. Experiment results show that the proposed method is suitable for accurately picking up and judging the effective compositions of the signal, it can effectively extract signal feature and has important application value in potential fault diiagnosis of low speed and heavy load gear.