Centrifugal compressors are a key piece of equipment for modern production. Among the components of the centrifugal compressor, the impeller is a pivotal part as it is used to transform kinetic energy into pressure energy. Blade crack condition monitoring and classification has been broadly investigated in the industrial and academic area. In this research, a pressure pulsation (PP) sensor arranged in close vicinity to the crack area and the corresponding casing vibration signals are used to monitor blade crack information. As these signals cannot directly demonstrate the blade crack, the method employed in this research is based on the extraction of weak signal characteristics that are induced by blade cracking. A method for blade crack classification based on the signals monitored by using a squared envelope spectrum (SES) is presented. Experimental investigations on blade crack classification are carried out to verify the effectiveness of this method. The results show that it is an effective tool for blade crack classification in centrifugal compressors.
References
[1]
Baumgartner, M.; Kameier, F.; Hourmouziadis, J. Non-Engine Order Blade Vibration in a High Pressure Compressor. Proceedings of Twelfth International Symposium on Airbreathing Engines, Melbourne, Australia, 10–15 September 1995; pp. 1–13.
[2]
Lei, Y.G.; Lin, J.; He, Z.J.; Kong, D.T. A method based on multi-sensor data fusion for fault detection of planetary gearboxes. Sensors 2012, 12, 2005–2017.
[3]
Roy, N.; Ganguli, R. Helicopter rotor blade frequency evolution with damage growth and signal processing. J. Sound Vib. 2005, 283, 821–851.
[4]
Elbhbah, K.; Sinha, J.K. Vibration-based condition monitoring of rotating machines using a machine composite spectrum. J. Sound Vib. 2013, 332, 2831–2845.
[5]
Saravanan, K.; Sekhar, A.S. Crack detection in a rotor by operational deflection shape and kurtosis using laser vibrometer measurements. J. Vib. Control 2013, 19, 1227–1239.
[6]
Rao, A.R.; Dutta, B.K. Vibration analysis for detecting failure of compressor blade. Eng. Fail. Anal. 2012, 25, 211–218.
[7]
Witek, L. Experimental crack propagation and failure analysis of the first stage compressor blade subjected to vibration. Eng. Fail. Anal. 2009, 16, 2163–2170.
[8]
Egusquiza, E.; Valero, C.; Huang, X.X.; Jou, E.; Guardo, A.; Rodriguez, C. Failure investigation of a large pump-turbine runner. Eng. Fail. Anal. 2012, 23, 27–34.
[9]
Joosse, P.A.; Blanch, M.J.; Dutton, A.G.; Kouroussis, D.A.; Philippidis, T.P.; Vionis, P.S. Acoustic emission monitoring of small wind turbine blades. J. Sol. Energy Eng. 2002, 124, 446–454.
[10]
Pawar, P.M.; Jung, S.N. Support vector machine based online composite helicopter rotor blade damage detection system. J. Intell. Mater. Syst. Struct. 2008, 19, 1217–1228.
[11]
Rao, A.R. A Method for Non-Intrusive On-Line Detection of Turbine Blade Condition. WO2008093349 A1, 7 August 2008.
[12]
Antoni, J. Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions. J. Sound Vib. 2007, 304, 497–529.
[13]
Borghesani, P.; Ricci, R.; Chatterton, S.; Pennacchi, P. A new procedure for using envelope analysis for rolling element bearing diagnostics in variable operating conditions. Mech. Syst. Signal Process. 2013, 38, 23–35.
[14]
Antoni, J. Cyclostationarity by examples. Mech. Syst. Signal Process. 2009, 23, 987–1036.
[15]
Borghesani, P.; Pennacchi, P.; Ricci, R.; Chatterton, S. Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals. Mech. Syst. Signal Process. 2013, 40, 38–55.
