Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis

Abstract

Due to the wide use of gearmotor systems in industry, many diagnostic techniques have been developed/employed to prevent their failures. An insufficient lubrication of gearboxes of these machines could shorten their life and lead to catastrophic failures and losses, making it important to ensure a required lubrication level. For the first time in worldwide terms, this paper proposed to diagnose a lack of gearbox oil lubrication using motor current signature analysis (MCSA). This study proposed, investigated, and experimentally validated two new technologies to diagnose a lack of lubrication of gear motor systems based on MCSA. Two new diagnostic features were extracted from the current signals of a three-phase induction motor. The effectiveness of the proposed technologies was evaluated for different gear lubrication levels and was compared for three phases of motor current signals and for a case of averaging the proposed diagnostic features over three phases. The results confirmed a high effectiveness of the proposed technologies for diagnosing a lack of oil lubrication in gearmotor systems. Other contributions were as follows: (i) it was shown for the first time in worldwide terms, that the motor current nonlinearity level increases with the reduction of the sgearbox oil level; (ii) novel experimental validations of the proposed two diagnostic technologies via comprehensive experimental trials (iii) novel experimental comparisons of the diagnosis effectiveness of the proposed two diagnostic technologies.

Novel Fault Diagnosis of a Conveyor Belt Mis-Tracking via Motor Current Signature Analysis

“…The main difference between this communication and the recently published paper by the authors in Ref. [ 31 ] is that, although both pieces of research use MCSA to diagnose faults in rotating machines, neither the technologies, nor the application, the results are similar in both studies. In Ref.…”

“…In Ref. [ 31 ], the authors proposed two new diagnostic features in order to detect the lack of lubrication in the geared motor system: feature 1, which measured the power in a frequency bandwidth around the harmonics of the supply frequency, and feature 2, used the spectral magnitude of the fundamental harmonic of the supply frequency normalized by the average value of the spectral magnitudes of the higher harmonics of the supply frequency in the spectrum of the current signal, and characterized the non-linearity of the motor current. However, in this communication, the proposed and compared technologies were based on the bicoherence, the tricoherence, and the CCSM3, and diagnosis was performed for the mis-tracking of the conveyor belt and not for the gearmotor itself.…”

Innovative Conveyor Belt Monitoring via Current Signals

“…Thus, it is proposed in this paper to investigate the effect of belt mis-tracking on the integrated power of the fundamental harmonic of the supply frequency of motor current signals. The diagnostic "power feature" [17], which is the integrated power in a frequency range around the fundamental harmonic of the supply frequency, is proposed to be used for diagnostic technology for belt tracking:…”

Novel Investigation of Higher Order Spectral Technologies for Fault Diagnosis of Motor-Based Rotating Machinery

“…From the definitions of bicoherence and tricoherence, it is clear that the analyzed spectral components must exhibit statistical dependencies in order to obtain non-zero results, which are associated with bearing faults. However, bicoherence and tricoherence could be used in specific cases in which fault-related spectral components follow “the bicoherence and the tricoherence frequency rules” [ 77 , 78 , 79 ]. These higher-order spectra frequency requirements may not be met for all spectral components, which carry valuable information for a fault diagnosis.…”

“…MCSA can be performed remotely, as the IM current can be measured with only access to the power supply line of a motor. IM current signals are frequently used for detecting electrical faults in motors and faults in coupled gearboxes [27]. Early diagnosis of IM bearing faults via MCSA is a difficult task due to the low signal-to-noise ratio (SNR) of IM current spectral components, which contain the information on the bearing conditions [6][7][8][28][29][30][31][32][33][34][35].…”