Detection of Cavitation in Kaplan Water Turbines (original) (raw)
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Feature Extraction for Vibration Analysis of Cavitation in Kaplan Water Turbines
Several intelligent cavitation indicators obtained from vibration measurements have been compared in a Kaplan turbine. The indicators are based on the nonlinear scaling of features: one of the features is rms value and the other is either kurtosis or peak value. Indicators obtained from acceleration x(2) and higher derivatives x(3) and x(4) were tested by comparing the calculated indices with the sound of the recorded acceleration signals and analysing the signals with an oscilloscope in a wide power range. The results were compared in four frequency ranges with the knowledge-based cavitation index and previous studies. The indicators detect the normal operating conditions, which are free of cavitation, and also provide a clear indication of cavitation already at an early stage. The indices obtained from x(4) are the best alternative though also the index obtained from x(3) provides good results throughout the power range. Acceleration provided a good fit with the data but was less sensitive than higher derivatives. Automatic monitoring can be based on steps: detecting normal conditions, cavitation and the type of cavitation. The indicator also provides warnings of possible risk on short periods of cavitation. Uncertainties can be taken into account by extending the feature calculations and classification rules to fuzzy set systems.
Vibration Analysis of Cavitation in Kaplan Water Turbines
Cavitation is harmful to water turbines and may cause operation delays of several weeks. The real-time detection of cavitation risk is increasingly important, and even narrow cavitation-free power ranges can be utilised in load optimisation. Higher derivative signals x (3) and x (4) calculated from acceleration signals are very suitable for detecting impacts. This paper introduces a generalised moment τ σ M p α which is defined by three parameters: the sensitivity of the moment improves when the order p of the moment increases, especially when short sample time τ is used. In this study, sufficently good results were obtained with moments where the order of derivation α =4, p ≈ 4, and τ =3s. These moments detect the normal operating conditions, which are free of cavitation, and also provide a clear indication for cavitation risk at an early stage. Sufficiently long signals are required for producing reliable maximum moments and data for analysing short-term cavitation. On-line cavitation monitoring is feasible with this approach since the analysis does not need high frequency ranges and the sample times are very short. The moment can be analysed first, and it is then possible to obtain the cavitation index if the moment value exceeds the threshold. Data compression is very efficient as the detailed analysis only requires the feature values of the appropriate samples.
Methods for vibro-acoustic diagnostics of turbine cavitation
Journal of Hydraulic Research, 2003
Basic aspects of noise sampling, signal processing and analysis, and data processing, analysis, and interpretation in vibro-acoustic diagnostics of turbine cavitation are investigated in a series of prototype and model experiments. Several weak points of the practice are identified, and improvements and new techniques are developed. These techniques enable extraction of data on cavitation details and early detection of detrimental effects met in turbine exploitation. A brief review of weak points of the practice, developed improvements, and new techniques, as well as examples of application, are presented in the paper. RÉSUMÉ Des aspects de base de l'enregistrement du bruit, des traitements et analyses analogiques et numériques des signaux, avec leur interprétation dans le diagnostic vibro-acoustique de la cavitation de turbine, sont étudiés dans une série d'expériences de prototype et de modèle. Plusieurs points faibles de la pratique sont identifiés, et des améliorations et de nouvelles techniques sont développées. Ces techniques permettent l'extraction de données sur des détails de cavitation et la détection précoce des effets néfastes rencontrés dans l'exploitation de turbine. Un bref examen des points faibles de la pratique, des améliorations développées, et de nouvelles techniques, aussi bien que des exemples d'application, sont présentés dans le papier.
Turbine Cavitation Diagnostics and Monitoring Multidimensional and Simple Techniques
2010
The consequences of cavitation erosion are best assessed directly, during an overhaul. However, in order to find out from which operating points they stem and clarify the role various turbine parts play in cavitation, one must apply vibro-acoustic measurements or monitoring. Based on the example of the large Francis turbines at the Grand Coulee Dam in the USA, the multidimensional vibro-acoustic technique for cavitation diagnostics and monitoring is presented and compared to simple techniques.
The identification of cavitation in Kaplan turbine runner
38TH MEETING OF DEPARTMENTS OF FLUID MECHANICS AND THERMODYNAMICS
The presented paper deals with monitoring of cavitation in a Kaplan turbine. The main goal of the experimental works was to verify the suitability of the chosen method for application in the technical diagnostics of water turbines. The experiment was carried out in three different ways, where a correlation was looked for between the results. The first method was the standard method used in water turbine test workbenches. A decrease in efficacy is a manifestation of cavitation. The efficiency drop is evaluated from the energy parameters and cavitation tests are necessary. Simultaneously with the mentioned standard measurement, the formation and development of cavitation in the turbine impeller was monitored by a visualization method and subsequent video analysis. A pulsed light source (stroboscope) with a parallel digital camera was used for visualization. The devices were synchronized via the Timing Hub. The third method used was based on sensing and analyses the acoustic emission in the ultrasonic band. To sense the signal, an ultrasonic probe was used. The probe was tuned in a way that it was not sensitive to vibrations and noise in the audible range. The signal was analysis only in the area of cavitation formation, which was verified by visualizing cavitation areas in the turbine wheel. The results from the experiments showed very good correlation for all three methods. One of the outputs of the experiments is the possibility to use experimental procedures for early diagnosis of cavitation formation. The indisputable advantage of determining the onset of cavitation by sensing acoustic emissions is that it is ab extra disassembly method and at the same time it is not necessary to measure the entire complex of energy parameters.
Detection of cavitation in hydraulic turbines
Mechanical Systems and Signal Processing, 2006
An experimental investigation has been carried out in order to evaluate the detection of cavitation in actual hydraulic turbines. The methodology is based on the analysis of structural vibrations, acoustic emissions and hydrodynamic pressures measured in the machine. The proposed techniques have been checked in real prototypes suffering from different types of cavitation. In particular, one Kaplan, two Francis and one Pump-Turbine have been investigated in the field. Additionally, one Francis located in a laboratory has also been tested.
Journal of Fluids Engineering, 2007
The goal of the study was to explain the relationship between different acoustic signals and visual appearance of cavitation. Measurements of acoustic emission, vibration, and noise were performed on a Kaplan turbine model, with only two blades, in a cavitating condition. Since a model with only two blades was used, most of the side effects were eliminated, and it was concluded that the cavitation itself is the source of the recorded signal. Results showed an interesting relationship between the extent of the cavitation and the recorded data from sensors. At a decreasing cavitation number, the recorded amplitudes from all measurements first rose, experienced a local maximum, then fell to a local minimum, and finally rose again. The cavitation was also visually observed. It was concluded from the measurements that there are distinct correlations between acoustic emission, vibration, and noise on one side and the topology, extent, and type of cavitation structures on the other side. A physical explanation for the phenomenon was introduced and included in a semi-empirical model that links the visual appearance of cavitation on the blade of the turbine to the generated noise and vibration.
Visualization Monitoring of Cavitation in Water Turbines
2002
Present methods for cavitation detection in water turbines are based on observation of pressure pulsations, acoustic emission and mechanical vibrations on the turbine casing. In the following a new method of cavitation monitoring, which offers real time evaluation of the cavitation topological structures in the turbine flow field, will be presented. In the paper the application of the method on a model of a Kaplan turbine is presented along with the installation of mechanical equipment on a new power station Doblar II on river Soča (Slovenia).
Multidimensional Diagnostics of Turbine Cavitation1
Journal of Fluids Engineering, 2002
A novel technique for vibro-acoustical diagnostics of turbine cavitation is introduced and its use demonstrated on a Francis turbine. The technique enables identification of different cavitation mechanisms functioning in a turbine and delivers detailed turbine cavitation characteristics, for each of the mechanisms or for the total cavitation. The characteristics specify the contribution of every critical turbine part to the cavitation intensity. Typical diagnostic results: (1) enable optimization of turbine operation with respect to cavitation erosion; (2) show how a turbine’s cavitation behavior can be improved; and (3) form the basis for setting up a high-sensitivity, reliable cavitation monitoring system.
Fluids
Korto’s multidimensional method for vibro-acoustical diagnostics and monitoring of turbine cavitation is based on a high number of spatially distributed sensors and the signal and data processing that systematically utilises three data dimensions: spatial, temporal, and operational. The method delivers unbiased data on cavitation intensity and rich diagnostical data on cavitation mechanisms. It is applicable on Kaplan, Francis, bulb, and reversible pump turbines, as well as pumps. In this paper, the theory of the method is introduced, and its application is illustrated on a prototype and three models of a Kaplan turbine. In the considered case, two distinct cavitation mechanisms responsible for the two erosion patches found in an overhaul are vibro-acoustically identified, quantified, and analysed. The cavitation quality of the models is compared. Cavitation as a source of vibration is discussed.