Detection and Diagnosis of Compound Faults in a Reciprocating Compressor based on Motor Current Signatures

Induction motors are the most common driver in the industry and consume
tremendous energy every year. Monitoring the status of a motor and its
downstream equipment and diagnosing faults in time not only avoids great damage
to mechanical systems but also allows the motor to run at optimal efficiency.
This paper studies the use of information from motor current signals to detect and
diagnose faults of a reciprocating compressor (RC) and its upstream three-phase
motor. The motor is applied by the RC with an oscillator torque which induces
additional components in measured current signals. Moreover, the current signatures
contain changes with the torque profiles due to different types of faults.
Based on these analytical studies, experimental studies were carried out for different
common RC faults, such as valve leakage, intercooler leakage, stator asymmetries
and the compounds of them. The envelope analysis of current signals
allows accurate demodulation of the torque profiles and thereby it can be combined
with overall current levels for implementing model based detections and
diagnosis. The results show these simulated faults can be separated under all operating
pressures.