The presence of a crack in a blade can change the natural frequencies of that blade. It has long been a goal to detect blade cracks by assessing the change in a measured vibration frequency of the blade over time. It has been found that prior frequency assessment methods can be less accurate than is desirable to reliably detect the relatively small frequency changes that are typically associated with blade crack sizes of practical interest. This paper describes and discusses advanced techniques that have significantly improved the accuracy of frequency assessment using time-of-arrival measurements.

It is a common practice to perform periodic non-destructive examinations of blades in rotating machines. Even if a crack is not detected during such a periodic stationary non-destructive examination, such a crack could potentially initiate and grow to critical size between such examinations. Online monitoring is therefore desirable.

One potential approach to online monitoring is based on the observation that the presence of a crack in a blade can change the stiffness and therefore the natural frequencies of that blade. Vibration amplitudes of a blade can be measured as a function of time using, for example, tip timing measurements. Such amplitude measurements can be transformed from the time domain into the frequency domain using, for example, FFT techniques. Such techniques have been applied to analyze data for rows of blades, considering each individual blade successively.

Methods have been proposed to use temporal changes in such assessed blade frequencies to detect blade cracks. Such methods have been found not to be robust. For many useful applications, the variations in the frequencies assessed for the same row of uncracked blades at different times and different operating conditions have been found to be of the same order as the changes in frequencies that would result from the presence of a crack of significant size.

This paper describes a method in which potential temporal changes in the frequencies of individual blades are assessed by periodically analyzing complete rows of blades using mistuning analysis techniques that treat the blade rows as complex systems, in contrast to other techniques that consider each blade individually in turn. This method, while computationally complicated and challenging, has been found to be capable of detecting blade root cracks that are much smaller than can be detected using other techniques. Moreover, this method has been demonstrated to detect cracks that are much smaller than the critical size for mechanical separation of the blade from the rotor.

This improved frequency assessment technique has been used to identify more than 30 blades with frequency changes that were considered to be potential indicators of blade cracks. Subsequent inspections verified indications in all of those blades.

In addition to providing operational guidance, the frequency change data were used to infer the time periods during which crack growth had occurred.


Detection of Cracks in Turbomachinery Blades by Online Monitoring

Division / Sponsor:
International Gas Turbine Institute (IGTI)

Paper Proceedings: https://asmedigitalcollection.asme.org/GT/GT2020/volume/84058

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