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Cavitation Detection in Hydraulic Turbines

Application to a Machine Condition Monitoring System

The term cavitation is used to describe the phenomenon of liquid-to-gas and gas-to-liquid phase changes that occur when the local fluid dynamic pressures in areas of accelerated flow drop below the vapor pressure of the local fluid. The liquid-to-gas phase change is akin to the boiling of water, except that it occurs at ambient temperatures. The gas-to-liquid phase change produces extremely high local pressures as vapor cavities implode on themselves. Cavitation commonly occurs in hydroelectric turbines, generally appearing around guide vanes, wicket gates, the turbine runner, and in the draft tube. Usually, cavitation within the fluid stream is not damaging to the turbine. However, when implosions occur near solid boundaries within the machine, flow surfaces can be damaged and eroded, figure 1. Damage to the runner has to be routinely repaired to maintain the bucket profiles. If left unrepaired, the erosion damage can lead to drops in efficiency and ultimately major damage to the rest of the machine.

figure

Detection of the cavitation phenomenon is straight forward. Large increases in noise, particularly in moderately high frequency ranges (15- to 100-kHz) are characteristic of cavitation. In addition, vibration levels generally increase. However, in a machine condition monitoring program, the simple ability to detect cavitation is not too beneficial. The real need is to learn when the cavitation is damaging parts of the machine, figure 2.

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The challenge then is to develop techniques for separating the noise and vibration caused by cavitation damage from that caused by non-damaging cavitation and other background noise and vibration sources. A promising approach under development in recent years is based on the observation that when cavitation occurs in a rotating machine, the periodic rotational components will amplitude modulate the wide-band high frequency noise generated by collapsing cavitation bubbles. Modulation may occur due to the periodic rotation of continuous noise sources relative to a fixed sensor, or because of periodicity in the hydrodynamics of the flow (e.g., blades passing through wake zones downstream of wicket gates). This amplitude modulation has spurred development of many techniques for cavitation detection, including one that is now commercially available.

Amplitude modulated based cavitation detection techniques identify cavitation as a hidden periodicity within an isolated band of the high frequency noise floor. Typically the raw signal is bandpass filtered for the desired high frequency band and the discovery of the hidden periodicity is accomplished through demodulation of the bandpassed signal using the principal of envelope detection. Most of the cavitation detection techniques use half- or full-wave rectification spectral analysis or true RMS detection to perform wide-band demodulation on the raw measurement signals. These methods can be accomplished either by hardware or software methods. Generally, the resulting frequencies of interest are the unit's rotational speed and its harmonics, particularly the blade passing frequency of the turbine runner.

In a machine condition monitoring system, a fixed sensor is desirable from a practicality standpoint. Placement of the sensor is very important. Broadband acoustic emission sensors or high frequency accelerometers (amplified analog output proportional to stress wave activity or vibration), mounted on the wicket gate assembly or the turbine guide bearing assembly have successfully detected "damaging" cavitation. Acoustic emission sensors mounted on the shell of the draft tube have produced similar results. Either of these techniques has deficiencies, particularly related to universal application on different machines. Again, the cavitation phenomenon can be detected easily. However determining the severity of the damage that may be occurring on the runner by either of these methods is difficult. Calibrating the system with data about known cavitation zones, duration of exposure, and extent of damage from maintenance data is possible. However, geometric differences between similar machine types and totally different machine types (i.e., Francis vs. Kaplan) significantly affect amplitudes produced by these fixed sensor demodulation techniques and probably would require machine specific calibrations.

One limitation of the half- or full-wave rectification demodulation technique is that it is affected by discrete components (machine noise) that are present and so bandpass filtering has to take place prior to demodulation. Otherwise, these discrete frequencies will generate peaks in the demodulated signal as well, erroneously showing hidden periodicity.

A new technique that overcomes this limitation has been used successfully to identify cavitation in high speed turbo pumps. This technique uses a recently discovered unique coherent phase relationship within the wide-band noise floor of a cavitation-generated signal. The combination of a Phase-Only filter and an Amplitude-Medium filter removes discrete components and allows for detection of hidden periodicity generated by the coherent phase components in the wide-band noise floor and a non-normalized spectral function detects the strength of the cavitation generated wide-band modulated signals. Another noticeable advantage is that no high-pass filtering or high frequency analysis is required since the low frequency noise floor contains the wide-band modulated coherent phase information.

Detection of cavitation damage directly by monitoring acoustic emissions can be accomplished but is still in a testing phase. Material damage or the attack of the surface which may lead to damage is detectable with acoustic emission sensors. The initial attack is characteristic of an out-of-plane (OOP) source on the runner blade. However as the pit grows in size and depth, a larger percentage of the acoustic emissions become in-plane (IP) sources. Most of the energy in the stress waves created by OOP sources occur at frequencies below 100 kHz. This energy is carried by a low frequency flexure wave in the plate. The IP sources generate energy in the stress wave which is carried by high frequency extensional and shear waves. Recent developments in sensor designs have lead to a transducer which is equally sensitive to both OOP an IP sources. This transducer utilizes a "false" aperture, consisting of a piezoelectric crystal that is mass loaded over a small (typically 1/8-inch) area of the center of the crystal. The transmission of acoustic emissions, especially IP sources, should prove no problem over a lubricated bearing due to mode conversion at the boundary. Thus, mounting one of these dual IP-OOP sensors on the turbine guide bearing might prove promising both in detecting the presence of cavitation and the extent of the damage. This technique has proven successful for detection of both IP and OOP sources in thick steel plates, however, the complex geometries characteristic of turbine runners may prove to be too difficult to allow application of this technique. Monitoring the ratio of IP to OOP levels will provide not only the onset of cavitation damage but as the ratio becomes more and more dominated by IP sources, an indication that damage is becoming more severe and may need attention.

New techniques and sensors have made the detection of damaging cavitation in hydro turbines a reality. There still exists some questions regarding the absolute comparisons from unit to unit and among different turbine types. However, we are near a point where a cavitation detection/damage monitor can be including in a machine condition monitoring system. The use of a cavitation detection/damage module can provide both real-time operating information as well as machine condition-based maintenance information.

Contact: Warren Frizell email: kfrizell@usbr.gov.

Last reviewed: 10/25/04