Fault Diagnosis of Centrifugal Pumps Using Motor Electrical Signals

Centrifugal pumps are some of the most widely used pumps in the industry (Bachus & Custodio, 2003) and many of them are driven by induction motors. Failure to either the induction motor or the centrifugal pump would result in an unscheduled shutdown leading to loss of production and subsequently loss of revenue. A lot of effort has been invested in detecting and diagnosing incipient faults in induction motors and centrifugal pumps through the analysis of vibration data, obtained using accelerometers installed in various locations on the motor-pump system. Fault detection schemes based on the analysis of process data, such as pressures, flow rates and temperatures have also been developed. In some cases, speed is used as an indicator for the degradation of the pump performance. All of the above mentioned schemes require sensors to be installed on the system that leads to an increase in overall system cost. Additional sensors need cabling, which also contributes towards increasing the system cost. These sensors have lower reliability, and hence fail more often than the system being monitored, thereby reducing the overall robustness of the system. In some cases it may be difficult to access the pump to install sensors. One such example is the case of submersible pumps wherein it is difficult to install or maintain sensors once the pump is underwater. To avoid the above-mentioned problems, the use of mechanical and/or process sensors has to be avoided to the extent possible.

[1]  Alexander G. Parlos,et al.  SENSORLESS DETECTION OF IMPELLER CRACKS IN MOTOR DRIVEN CENTRIFUGAL PUMPS , 2008 .

[2]  D. Casada Detection of pump degradation , 1995 .

[3]  Thomas G. Habetler,et al.  An amplitude modulation detector for fault diagnosis in rolling element bearings , 2002, IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02.

[4]  Larry Bachus,et al.  Know and understand centrifugal pumps , 2003 .

[5]  J. E. McInroy,et al.  Using power measurements to diagnose degradations in motor drivepower systems: a case study of oilfield pump jacks , 2001 .

[6]  Antal A. Sarkady,et al.  Motor Current Signal Analysis for Diagnosis of Fault Conditions in Shipboard Equipment , 1995 .

[7]  Vincent Cocquempot,et al.  Model based fault detection in a centrifugal pump application , 2006, IEEE Transactions on Control Systems Technology.

[8]  D. A. Casada,et al.  The use of the motor as a transducer to monitor system conditions , 1996 .

[9]  Fredrik Carlsson,et al.  Diagnosis of Submersible Centrifugal Pumps: A Motor Current and Power Signature Approaches , 2010 .

[10]  P.J. Unsworth,et al.  Fuzzy logic system to detect pump faults from motor current spectra , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[11]  Paul C. Krause,et al.  Analysis of electric machinery , 1987 .

[12]  Jie Chen,et al.  Robustness in quantitative model-based fault diagnosis , 1992 .

[13]  C. J. Dister On-line health assessment of integrated pumps , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[14]  Alexander G. Parlos,et al.  Sensorless Detection and Isolation of Faults in Motor-Pump Systems , 2008 .

[15]  Mohamed Benbouzid,et al.  A review of induction motors signature analysis as a medium for faults detection , 1998, IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200).

[16]  Ron J. Patton,et al.  Model-based fault diagnosis of a two-pump system , 1998 .

[17]  Alexander G. Parlos,et al.  Signal-based versus model-based fault diagnosis-a trade-off in complexity and performance , 2003, 4th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2003. SDEMPED 2003..

[18]  Alexander G. Parlos,et al.  Sensorless Detection of Cavitation in Centrifugal Pumps , 2006 .

[19]  Donald A. Casada Monitoring Pump and Compressor Performance Using Motor Data , 1996 .

[20]  S. A. McInerny,et al.  Basic vibration signal processing for bearing fault detection , 2003, IEEE Trans. Educ..