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Automatic taxonomy and modal analysis for vibration diagnosis

机译:自动分类和振动诊断模态分析

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The authors give a case study concentrating on the task of providing automatic aids to both diagnosis and prognosis by recognition of machine condition in the routinely monitored vibration signatures of turbine generator rotors. The target population of rotors is the two-pole, 660 MW turbine generator rotors designed and manufactured by the GEC Alsthom group. The signatures provided by GEC Alsthom are multi-sensor run-up and run-down signatures taken using tachometer pulse and tracking filter techniques. They consist of a number of phasor trajectories, amplitude and phase of transverse displacement at about 300 speed steps. The authors describe the automatic modal analysis of the signatures using the Kennedy-Pancu method and then discuss cluster-based reasoning. The problems encountered with real signatures and the results of simulated signatures are discussed.
机译:作者举例说明通过在涡轮发电机转子的常规监测振动特征中识别机器条件,专注于提供自动辅助为诊断和预后提供诊断和预后的任务。转子的目标群是由GEC Alsthom组设计和制造的双极,660 MW涡轮发电机转子。 GEC Alsthom提供的签名是使用转速计脉冲和跟踪滤波器技术进行的多传感器升降和倒闭签名。它们由大约300个速度步骤组成的许多量相轨迹,横向位移的幅度和阶段。作者描述了使用肯尼迪-PANCU方法的签名的自动模态分析,然后讨论基于集群的推理。讨论了实际签名的问题和模拟签名结果。

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