Traditional ferrography only emphasizes on the characteristics of individual big debris. For diagnosing and monitoring the condition of machines, the traditional ferrography encounters trouble. Ferrography based on debris group theory thinks that there is a one-to-one correspondence between group characteristic of debris group and the operating condition. For this reason, the real wear condition will deduced by studying the group characteristic of debris group in the ferrogram. By drawing out the criteria of the studied machine, the failure of the machine components will be predicted. Theoretical analysis and experimental research show that the operating condition predicted by debris group theory are consistent with the practical condition.

通过对某矿井提升机滑动轴承工况的实际监测，考察了磁流体对铁谱仪中非铁磁性颗粒沉积的影响结果表明：磁流体可以使非铁磁性颗粒有效地沉积在铁谱仪的谱片上，使谱片携带更加全面的信息；磁流体对非铁磁性颗粒的"磁化"作用具有选择性磁流体可以用于监测非铁磁性颗粒。

In this paper, a fuzzy synthetic decision-making system which is based on the method of debris group analysis for wear condition monitoring and fault diagnosis in qualitative ferrographic analysis and the background to establish it have been introduced. Especially, the procedure to find out the membership functions of this fuzzy synthetic decision-making system and the method to arrange the importance sequence of severe wear particles have been explained in detail. The reliability of this fuzzy system has been tested by actual practices of wear condition monitoring and fault diagnosis, and the possibility to realize automation in ferrgraphic analysis has also been revealed.