Acoustic emission (AE) signals were recorded during tribological tests on 52100 steel specimens, sliding under boundary lubrication conditions in the presence of different chemical additives (an anti-wear, two friction modifiers, an extreme pressure additive and a dispersant). Various parameters of the AE signal were analyzed and compared with the coefficient of friction (CoF), electrical contact resistance (ECR), surface roughness and wear volume. The measured friction, ECR, surface roughness and wear varied between tests as expected due to the action of whichever additive was present. Within each test, the variation over time of certain AE frequencies correlated strongly with the variation in friction and while other frequency components correlated with the ECR signal. AE and friction, surface roughness and wear parameters were also averaged over each test, and the results plotted against each other while varying the lubricant additive. This showed that the average of certain AE frequencies correlated well with the average friction, certain AE frequencies correlated with the surface roughness and while other average frequency components correlated with the wear volume per test. Together this demonstrates that the AE signal is rich in tribological information and is sensitive to asperity interactions and surface film composition. It is therefore a powerful tool to monitor tribological behavior and lubricant condition.

在对 52100 个钢试样进行摩擦学测试期间，记录了声发射 （AE） 信号，这些试样在不同化学添加剂（一种抗磨剂、两种摩擦改进剂、一种极压添加剂和一种分散剂）存在下在边界润滑条件下滑动。分析了声发射信号的各种参数，并与摩擦系数 （CoF） 、接触电阻 （ECR） 、表面粗糙度和磨损体积进行了比较。由于存在任何添加剂的作用，测得的摩擦、ECR、表面粗糙度和磨损在测试之间会如预期的那样发生变化。在每次测试中，某些 AE 频率随时间的变化与摩擦的变化密切相关，而其他频率分量与 ECR 信号相关。还对每次测试的 AE 和摩擦、表面粗糙度和磨损参数进行了平均，并在改变润滑油添加剂的同时将结果相互绘制。这表明，某些 AE 频率的平均值与平均摩擦力密切相关，某些 AE 频率与表面粗糙度相关，而其他平均频率分量与每次测试的磨损量相关。总之，这表明 AE 信号具有丰富的摩擦学信息，并且对凹凸相互作用和表面膜成分敏感。因此，它是监测摩擦学行为和润滑剂状况的强大工具。