Abstract
Induction motors are mainly used for variable load applications and it is vital to have a condition monitoring system with capabilities to diagnose motor faults in variable load conditions. The environment noise varies has non-linear relation with motor load and it challenges the decision making capability of the condition monitoring system. This paper addresses the issue of reliable decision making on the existence of bearing faults in variable load conditions. Two type of threshold schemes have been proposed to reliably diagnose bearing faults in Park vector modulus spectrum. The performance of the developed threshold based condition monitoring system has been analyzed theoretically and experimentally.
Highlights
The preventive maintenance has gained significant importance in modern production facilities since last decade and it has received a deep focus from the researchers
It is shown that Park vector modulus spectrum analysis (PVMSA) method has much more capability as compared to the previously used instantaneous power analysis (IPA) and motor current signature analysis (MCSA) to detect various motor faults
(2) The decision making in the presence of has environmental noise in has been a challenge in time condition monitoring systems and to tackle this challenge we have developed the threshold real time condition monitoring systems and to tackle this challenge we have developed the threshold eme which can tackle the instantaneous noise for various operating points of theoperating motor. points of the motor
Summary
The preventive maintenance has gained significant importance in modern production facilities since last decade and it has received a deep focus from the researchers. An adaptive threshold design based on the percentage of the fundamental current was reported in [38] These threshold schemes tend to diagnose only severe fault signatures and are limited to specific load condition. It is shown that Park vector modulus spectrum analysis (PVMSA) method has much more capability as compared to the previously used IPA and MCSA to detect various motor faults. Thepaper contributions this paper are (1) toa design and develop a PVMSA based reliable condition nitoring system for the diagnosis of the size faultofbearing outer faults (fault size race less faults (fault size less monitoring system forsmall the diagnosis the small sizerace fault bearing outer n 1 mm) (2) The decision making in the presence of environmental noise been a challenge than 1 mm).
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