汽轮机转子是汽轮机故障预测及诊断问题的一个重要方面。
The rotor is the main component during turbine fault forecasting and diagnosing.
根据汽轮机故障的分形特征，采用分形盒维数方法进行了不同故障试验数据的分形盒维数研究计算。
Using box counting dimension method the different type of turbine fault with fractal characteristic is numerically researched.
针对当前专家系统知识获取瓶颈的难题，提出了基于粗糙集数据挖掘的汽轮机故障预报及诊断方法。
A novel approach for fault forecast and diagnosis of steam turbine based on rough set data mining theory is brought forward, aiming at overcoming shortages of some current knowledge attaining methods.
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