Experimental Investigation on Centrifugal Compressor Blade Crack Classification Using the Squared Envelope Spectrum

被引:18
作者
Li, Hongkun [1 ]
Zhang, Xuefeng [1 ]
Xu, Fujian [1 ]
机构
[1] Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China
关键词
centrifugal compressor; blade crack; condition classification; squared envelope spectrum; VIBRATION; FAILURE; ROTOR; SIGNALS;
D O I
10.3390/s130912548
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页码:12548 / 12563
页数:16
相关论文
共 15 条
[1]   Cyclic spectral analysis of rolling-element bearing signals: Facts and fictions [J].
Antoni, J. .
JOURNAL OF SOUND AND VIBRATION, 2007, 304 (3-5) :497-529
[2]   Cyclostationarity by examples [J].
Antoni, Jerome .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (04) :987-1036
[3]  
BAUMGARTNER M, 1995, P ISABE 12 INT S AIR, P1
[4]   Testing second order cyclostationarity in the squared envelope spectrum of non-white vibration signals [J].
Borghesani, P. ;
Pennacchi, P. ;
Ricci, R. ;
Chatterton, S. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 40 (01) :38-55
[5]   A new procedure for using envelope analysis for rolling element bearing diagnostics in variable operating conditions [J].
Borghesani, P. ;
Ricci, R. ;
Chatterton, S. ;
Pennacchi, P. .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2013, 38 (01) :23-35
[6]   Failure investigation of a large pump-turbine runner [J].
Egusquiza, Eduard ;
Valero, Carme ;
Huang, Xingxing ;
Jou, Esteve ;
Guardo, Alfredo ;
Rodriguez, Cristian .
ENGINEERING FAILURE ANALYSIS, 2012, 23 :27-34
[7]   Vibration-based condition monitoring of rotating machines using a machine composite spectrum [J].
Elbhbah, Keri ;
Sinha, Jyoti K. .
JOURNAL OF SOUND AND VIBRATION, 2013, 332 (11) :2831-2845
[8]   Acoustic emission monitoring of small wind turbine blades [J].
Joosse, PA ;
Blanch, MJ ;
Dutton, AG ;
Kouroussis, DA ;
Philippidis, TP ;
Vionis, PS .
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME, 2002, 124 (04) :446-454
[9]   A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes [J].
Lei, Yaguo ;
Lin, Jing ;
He, Zhengjia ;
Kong, Detong .
SENSORS, 2012, 12 (02) :2005-2017
[10]   Support vector machine based online composite helicopter rotor blade damage detection system [J].
Pawar, Prashant M. ;
Jung, Sung Nam .
JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES, 2008, 19 (10) :1217-1228