潤滑油中の摩耗粉のリアルタイム形状解析としゅう動面劣化診断への適用

抄録

In order to predict the failure of rubbing surfaces through monitoring of wear particles in lubricating oil, an on-line particle image processing and analyzing system was developed using an optical microscope, a CCD camera, a stroboscope and image processing equipment. This technique has been used in the sliding wear tests of lead bronze bearing metal against a carbon steel counter face. The shape characteristics of wear particles, which closely correlate with wear modes, are distinguished by the relationship between the aspect ratio and newly defined roundness parameter. The wear particles with large aspect ratio and low roundness is related to promoting local seizure. It is found that the on-line image analysis of wear particles of greater than 40 μm helps in predicting severe failure of rubbing surfaces.