Analysis of wear debris, vibration and temperature of journal bearing has been integrated to increase the accuracy in fault diagnosis of a hydropower plant. Samples of used lubricating oil, vibration data and bearing temperature at different intervals were collected. Wear particles and acceleration caused by vibration were analysed for the fault detections. An abnormal increase in the temperature and vibrational energy was observed after 200 days of continuous operations. In the last sample, an abnormal increase in aspect ratio of the wear particles was also observed. Scratches and wiping mark were found over the surface of bearing block and side thrust pad. This confirmed the fault of machine by the analysis of condition monitoring data. Further rectification was done by the replacement of bearing block.

中文翻译：

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基于磨屑、振动和温度分析的水电站滑动轴承故障诊断案例研究

集成了对滑动轴承磨损碎片、振动和温度的分析，以提高水电站故障诊断的准确性。收集了不同间隔的用过润滑油样品、振动数据和轴承温度。分析了由振动引起的磨损颗粒和加速度以进行故障检测。连续运行 200 天后，观察到温度和振动能量异常增加。在最后一个样品中，还观察到磨损颗粒的纵横比异常增加。在轴承座和侧止推垫表面发现划痕和擦痕。这通过状态监测数据的分析确认了机器的故障。通过更换轴承座进行了进一步的整改。