The synthetic application of ferrography and vibration monitoring technique on engine conditions monitoring is discussed , a monitoring model is built using the fuzzy synthetic decision theory , and an application example is presented
12.
The development of morphology characteristics extraction of wear particle is introduced . the advantages and disadvantages of some methods are pointed out . all those are available for further research of identification of ferrography wear particle in theory and practice
13.
However , the issue how to realize the automatization in ferrograph diagnosis has been brought forth owning to manipulative complexity and subjectivity in the judgement for traditional ferrography technology . thus , the automatic recognition technology for wear debris is a focus research topic and many researchers , whether in overseas or domestic , have paid more attention on studying it last decades
14.
As a matter of fact , three types of wear debris can be classified by the present software programmed in this research , that is , normal , spherical and cutting debris can be identified . by analyzing and processing the actual ferrograph of wear debris from a used oil sample , the experimental results show that the effects of automatic recognition are equal to those of manual recognition , and the automatization of ferrographical diagnosis has been realized simply and partly , which will be helpful to improve the intelligence of the digital ferrography system
15.
The paper validates and perfects the traditional wear theory by using the ferrography , at the same time , combining the practice , mechanical embedded minor particles , scoring , plastic distortion , shaping effect and fatigue effect are analyzed and the results show that the vehicle ' s malfunction can be predicted
16.
In this paper , according to the character of the ship power system and device and the factors that affect it ' s capability , such as environment , utilizing the experience of the field expert , and combined with the practice of ship manufacturing and maintenance , the application of various oil monitoring technology , namely oil quality testing , spectrometric oil analysis , ferrography analysis , and particle counting etc , is studied respectively , and the fault recognition pattern is constructed . on the basis of this , according to dempster - shafter evidence theory , the information infusion mode is constructed and the oil monitoring multi - technology system is integrated . at last , colligating the result of the information infusion system and other information of the device , such as primitive data , maintenance records , running condition etc , the oil monitoring system to ship power system & device is realized
