Abstract

Online image visual ferrography (OLVF) is an acquisition method for oil debris information, which is affected significantly by the aggregation and overlap of wear debris and air bubbles in practice. In this work, a debris deposition video from OLVF is recorded as raw data. A relationship between wear debris concentration and debris deposition rate in a deposition process of OLVF is derived. Based on this, a deposition rate-based index of debris concentration (IDC) from OLVF video is proposed. A matching algorithm is developed to calculate the IDC. Moreover, a full-life accelerated gear wear test is performed, in which in total 1505 bubble-debris videos are obtained by OLVF. The verification results show that the approach not only can overcome the interference of air bubbles but also can avoid the error of saturation nonlinearity caused by agglomeration and overlap of wear debris, and that the proposed IDC performs better than the previously used index of particle coverage area (IPCA).

摘要

在线图像视觉铁谱（OLVF）是一种获取油屑信息的方法，在实践中受磨屑和气泡的聚集和重叠影响很大。在这项工作中，来自 OLVF 的碎片沉积视频被记录为原始数据。推导出了OLVF沉积过程中磨屑浓度与碎屑沉积速率之间的关系。在此基础上，提出了一种基于沉积速率的 OLVF 视频碎片浓度指数 (IDC)。开发了一种匹配算法来计算IDC。此外，还进行了全寿命加速齿轮磨损测试，其中通过OLVF获得了总共1505个气泡碎片视频。