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为了进一步探讨铁谱定量分析中重现性差、精度不高的深层次原因，应用随机过程理论，通过求解随机微分方程，对机器润滑油循环系统中磨粒浓度随机分布的数字特征进行了分析，对传统的磨粒平衡浓度概念进行了修正。认为在运转参数不变及引入白噪声作为随机分量的情况下，机器磨粒浓度由非平稳过程趋于一个宽平稳过程，并进行了实验分析。认为基于磨粒浓度为宽平稳过程，在油样状态监测或铁谱技术中应采取在线取油样方式或较大容积离线取油样方式，以期得到时间平均或空间平均。
In order to further explore the deep-seated reasons of poor reproducibility and low precision in the quantitative analysis of ferrous materials, by applying the stochastic process theory, the numerical characteristics of random distribution of abrasive concentration in the lubricating oil circulation system were analyzed by solving stochastic differential equations. The concept of traditional balance of abrasive particles was revised. It is considered that in the condition of constant operating parameters and the introduction of white noise as a random component, the concentration of abrasive grains in the machine tends to be a wide and steady process from non-stationary process and experimental analysis is carried out. Considering that the abrasive grain concentration is a broad and steady process, an online oil sampling method or a larger volume offline oil sampling method should be adopted in oil state monitoring or ferrography in order to obtain the time average or the space average.