为了分析发电机组振动信号在能量和波形方面的细小变化，从而反映发电机组的早期故障趋势，提出了基于数学形态谱的故障特征量。
Fault features based on pattern spectrum were presented for analyzing tiny changes of energy and waveform of generator sets vibration and reflecting the trend of early faults.
为了提取机车滚动轴承早期损伤类故障特征，本文提出了一种双重小波平均谱方法，并通过诊断实例验证了方法的有效性。
To extract early fatigue feature of engine bearings, the paper presents an average spectrum method with double-wavelet and the diagnosis examples are used to show the validity of the method.
可以将三阶谱的峰值作为判断气阀是否漏气的一个诊断特征量，同时也为诊断内燃机气阀的早期漏气故障提供了依据。
The peak value varies in different fault conditions and it can be used as a characteristic for diagnosing leakage fault of exhaust valve, the fault in initial stages can also be diagnosed.
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