Analysis of fault signatures for the diagnosis of induction motors fed by voltage source inverters using ANOVA and additive models

A comprehensive evaluation of intelligent classifiers for fault identification in three-phase induction motors

“…Furthermore, statistical methods are also studied as an alternative to intelligent systems as can be observed in the work of [25] where this tools were tested to diagnose rotor broken bars faults in three phase induction motors (0.75 and 1.1 kW) by means of features extracted from the stator current by the power spectral density (PSD) using the FFT. For the experiments, the motors were driven by frequency inverters under different load torque conditions.…”

Intelligent fault diagnosis of synchronous generators

“…Solomonoff et al used the NAP to identify and remove the nuisance attributes in the support vector machine (SVM) expansion space to improve the speaker recognition system performance (Solomonoff, Campbell, & Boardman, 2005). NAP is also used in face recognition systems to remove the illumination artifacts from face images ( From this literature review, we can correlate the factors affecting the speaker recognition systems with the study reported in (Duque-perez et al, 2015) for the machine fault diagnosis applications, where the same fault condition generates different fault signatures depending upon the factors such as type of power supply, motor, and loads. In this work, we experiment with NAP to diagnose the faults in a system-independent manner.…”

“…This study also reveals that the same fault condition generates different fault signatures depending upon the type of power supply, motor, and load conditions. Additive models were used to identify and eliminate the influence of these factors in the fault signatures for developing the universal fault diagnosis system (Duque-perez et al, 2015).…”

State of the Art and Trends in the Monitoring, Detection and Diagnosis of Failures in Electric Induction Motors

“…According to Duque-Pérez et al [41], to design a method that is valid for any power source and frequency of operation, it is necessary to consider and identify the influence of the different operating conditions. For this, [41] proposes an experimental study, a statistical analysis based on an additive model that allows for recognition of the effect the power supply has on the field harmonics, the same ones that will be affected by any failure in the motor. This method can detect the broken bars of a motor when it is fed in five different ways, directly to the power supply network and through four converters of various brands and models.…”