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通过对大型烟气发电机组发生故障时振动信号特点的分析及现场测试,利用无量纲振动信号分析技术,进行故障的长期在线诊断及预测预报技术研究,并提出了采用声发射技术结合振动分析的方法,实现了对烟机机组运行状态的全面在线监测诊断与预测。运用表明,这种混合型的分析方法诊断效果良好,能满足实际需求,为大型烟机组故障的在线诊断与预测提供了一种可行的新方法。
Through the analysis of the characteristics of the vibration signal and the field test in the event of a large-scale flue gas turbine generating unit failure, the long-term on-line diagnosis of fault and its prediction and forecasting technology are studied by using the dimensionless vibration signal analysis technology. The acoustic emission technique combined with vibration analysis Method to achieve a comprehensive on-line monitoring and diagnosis of smoke machine operating status and prediction. The application shows that the hybrid analysis method can diagnose well and meet the actual demand, which provides a feasible new method for the on-line diagnosis and prediction of the large smoke units.