Diagnosis of Bearing Outer Race Faults Using a Low-Cost Non-Contact Method with Advanced Wavelet Transforms

Abstract

This study analyses the vibration of Squirrel Cage Induction Motor (SCIM) with bearing faults using highfrequency signal (Handheld UWB radar) and Software Phase Locked Loop algorithm (SPLL). The contact or non-contact methods perform condition monitoring of the SCIM. The proposed method is a non-contact technique to perform condition monitoring of the SCIM. The contact methods execute via vibration, instantaneous frequency, rotor speed and flux signals analysis; whereas non-contact methods accomplish via acoustic, current and stray flux measurement. The existing techniques suffer from the influence of adjoining electrical machines; require human expertise to mount sensors and analysing the signals. In this paper, a new, non-contact method proposed for bearing fault identification in the SCIM. The proposed method uses a high-frequency signal projected on the motor and the reflected signal captured. The signal obtained is analysed with an advanced signal processing algorithm like Rational Dilation Wavelet Transform (RDWT) to identify the faults in the SCIM. The signal energy at the fault frequency level increases from 4.72 % to 5.82 % with the increase in the number of the faults. The signal energy variation indicates the severity of the faults. From the experimental results, the bearing fault of the motor identified in the beginning stage of the fault.

Recall Network: A Simple Brain-Inspired Algorithm for Classification

“…Generally, 10 runs of 10-fold cross validation must be used to average the above results [ 25 ] with the exception of run time, which uses the total time.…”

“…(1) Accuracy (ACC): number of correctly predicted items divided by the total of the item to predict. Generally, 10 runs of 10-fold cross validation must be used to average the above results [25] with the exception of run time, which uses the total time.…”

Non-Invasive Inspections: A Review on Methods and Tools

“…In that study, the reflected signal increased from 2.19/100 to 4.72/100 for the rotor bar and bearing in the no-fault condition. However, in the fault condition, the energy increased from 2.7/100 to 14.6/100 [48][49][50]. Radar features can be used to detect multi-machine faults simultaneously.…”

“…There are limitations associated with all of the reviewed tools and methods but it is possible to select the best option if the machine operational requirements and maintenance needs are considered. It has been noted that sensors based on radar principles are highly effective for monitoring assets in remote locations or from a distance [36] but further research is required to explore the full potential of sensors in the context of NII machine health diagnostics [37][38][39][40][41][42][43][44][45][46][47][48][49][50].…”