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Method of shaft crack detection based on squared gain of vibration amplitude

机译：基于振动幅度的平方增益的轴裂纹检测方法

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Rotating machines are exposed to different faults such as shaft cracks, bearing failures, rotor misalignment, stator to rotor rub, etc. Therefore, turbo-generators, aircraft engines, compressors, pumps, and many other rotating machines should be constantly diagnosed to warn about the probable appearance of a possible rotor failure. Unfortunately, despite the ongoing work on various rotor fault detection methods, there are still very few techniques that can be considered as reliable and applicable in practical problems. The difficulty lies in the fact that usually the fault introduces very subtle local changes in the overall structure of the rotor. The symptoms of these changes must be isolated and extracted from a wide spectrum of vibration data obtained from sensors measuring the vibrations of the machine. The measured data are usually disturbed with some noise or other disturbances, and that is why the detection of a possible rotor fault is even more difficult. The paper presents a new rotor fault detection method. The method is based on a new diagnostic model of rotor signals and external disturbances. The model utilizes auto-correlation functions of measured rotor's vibrations. By proper processing of the measured vibration data, the influence of environmental disturbances is completely compensated and reliable indications of the possible rotor fault are obtained. The method has been tested numerically using the finite element model of the rotor and then verified experimentally at the shaft crack detection test rig. The results are presented in a readable graphical form and confirm high sensitivity and reliability of the method.
机译：旋转机器暴露于诸如轴裂缝，轴承故障，转子未对准，定子的不同故障，转子摩擦等。因此，涡轮发电机，飞机发动机，压缩机，泵和许多其他旋转机器应不断被诊断为警告可能的转子故障的可能外观。遗憾的是，尽管在各种转子故障检测方法上进行了持续的工作，但仍有很少的技术可以被认为是可靠的并且适用于实际问题。难度在于，通常故障引入了转子整体结构的非常微妙的局部变化。这些变化的症状必须从从测量机器振动的传感器获得的传感器获得的宽频谱数据中分离和提取。测量的数据通常受到一些噪声或其他干扰的干扰，这就是为什么检测可能的转子故障更加困难。本文提出了一种新的转子故障检测方法。该方法基于转子信号和外部干扰的新诊断模型。该模型利用测量转子振动的自动相关函数。通过正确处理测量的振动数据，获得了环境干扰的影响得到了完全补偿，并且获得了可能的转子故障的可靠指示。该方法已经使用转子的有限元模型在数值上进行测试，然后在轴裂纹检测试验台上通过实验验证。结果以可读的图形形式呈现并确认该方法的高灵敏度和可靠性。

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