Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis
Abstract
:1. Introduction
- The proposed novel diagnostic technology/feature, which employs the power in a frequency range around the fundamental harmonic and the higher harmonics of the supply frequency;
- It was shown for the first time in worldwide terms, that the energy consumption of a motor changes with the reduction of the gearbox oil level;
- The proposed novel diagnostic technology/feature, which employed spectral magnitudes of the fundamental harmonic of the supply frequency, normalized by the average value of the spectral magnitudes of higher harmonics of the supply frequency in the spectrum of the current signal;
- It was shown for the first time in worldwide terms, that motor current non-linearity level increases with the reduction of gearbox oil levels;
- Novel experimental validations of the proposed two diagnostic technologies were presented via comprehensive experimental trials;
- Novel experimental comparisons of the diagnosis effectiveness of the proposed two diagnostic technologies were presented.
- develop and investigate for the first time in worldwide terms two motor current-based diagnosis technologies for a lack of oil lubrication diagnosis in gearboxes, connected to induction motors;
- perform an experimental validation of the proposed technologies in diagnosing a lack of oil lubrication in gearboxes via comprehensive experimental trials;
- perform a comparison between the proposed diagnostic technologies;
- develop a strategy for diagnosing the lack of oil lubrication in gearboxes based on the obtained results.
2. Novel Diagnostic Technologies for a Lack of Gearbox Oil Lubrication
- The instantaneous frequency (IF) of the supply grid is estimated from the current signals, based on the Hilbert transform phase demodulation approach, Ref. [31];
- The feature is estimated based on the magnitudes of the supply frequency harmonics.
3. Setup for Experimental Technology Validation
4. Diagnosis Effectiveness of the Technologies and Technology Effectiveness Comparison
4.1. Diagnosis Effectiveness of Technology 1
4.2. Diagnosis Effectiveness of Technology 2
- decreasing magnitude of the fundamental supply frequency harmonic;
- increasing magnitudes of the higher supply frequency harmonics;
- increasing motor current level of non-linearity (i.e., less values of Feature 2).
4.3. Diagnosis Efectiveness Comparision between Technologies 1 and 2
5. Conclusions
- For the first time in worldwide terms, a method for performing the diagnosis of a lack of oil lubrication in gearboxes coupled to induction motors, via motor current signature analysis (MCSA) was proposed;
- Two new diagnostic technologies for a lack of oil lubrication in gearboxes, based on MCSA, were proposed, investigated and experimentally validated;
- Comprehensive experimental trials were performed for validation of the proposed two technologies. Three-phase motor current data of an AC induction motor driving a conveyor belt system (for baggage handling at airports) via a gearbox were recorded, respectively, for the standard oil level in the gearbox and for conditions in which specific amounts of oil are removed from the gearbox;
- It was proposed that the gearbox oil level has an influence on the energy consumed by a motor. Thus, the power in a frequency bandwidth around harmonics of the supply frequency was proposed as diagnostic feature (Feature 1) for technology 1.
- The experimental estimates of the probability density functions of Feature 1 values for the standard oil level and for the removed oil cases are evaluated and compared and the total probabilities of correct diagnosis (TPOCD) and the Fisher criteria (FC), based on these estimates, were also evaluated and compared. The study was carried out separately for the three phases of motor current signals and for the case of averaging Feature 1 over the three phases. The results showed that:
- the power level of the first harmonic of the supply frequency is the most beneficial diagnostic feature as a higher TPOCD and the FC are obtained for this harmonic compared to the third harmonic of the supply frequency;
- the power of the supply frequency harmonics changes as type of gear friction varies in the gearbox. When lower levels of oils are removed, there is still enough oil to lubricate gears via a liquid friction between gear teeth; as a result, a lower power is required to circulate oil inside a gearbox and, therefore, Feature 1 value decreases. When the solid–solid friction between gear teeth occurs as a result of removing more oil, a motor energy consumption starts increasing and Feature 1 value starts increasing as well;
- technology 1 was shown to be sensitive/effective to the following oil removals: 120 mL (i.e., relative oil reduction is 8%) and 260 mL (i.e., relative oil reduction is 16%);
- while using datasets corresponding to different days of experimental trials and different conveyor loads with a standard oil level, Feature 1 was shown to be affected by current fluctuations of the grid system and conveyor load variations.
- it was shown that technology 1 could provide essentially different TPOCDs of a lack of gearbox oil lubrication for different current phases; therefore, it is recommended to employ three phases for diagnosis by technology 1;
- Feature 1, averaged over the three phases, was proposed as a useful diagnostic feature, since it provides effective results even if one of the phases does not provide a sufficient level of diagnosis effectiveness.
- It was proposed, for the first time in worldwide terms, that te non-linearity of the motor current changes due to a reduction of oil levels in gearboxes. Therefore, technology 2 was proposed, based on diagnostic Feature 2, for the diagnosis of a lack of gearbox oil lubrication. Feature 2 employs spectral magnitude of the fundamental harmonic of the supply frequency, normalized by the average value of the spectral magnitudes of higher harmonics of the supply frequency in the spectrum of the current signal and characterizes non-linearity of the motor current.
- The experimental estimates of the probability density functions of Feature 2 values for the standard oil level and for the removed oil cases were evaluated and compared and the TPOCDs and the FCs, based on these estimates, were also evaluated and compared. The study was carried out separately for the three phases of motor current signals and for the case of averaging Feature 2 over the three phases. The results showed that:
- non-linearity of the motor current increases with increase of an amount of the removed oil;
- technology 2 was shown to be sensitive/effective to the following oil removals: 260 mL (i.e., relative oil reduction is 16%), 280 mL (i.e., relative oil reduction is 18%) and 490 mL (i.e., relative oil reduction is 31%).
- while using datasets corresponding to different days of experimental trials and to different conveyor loads with standard oil levels, Feature 2 was shown to be almost unaffected by current fluctuations of the grid system and conveyor load variations.
- it was shown that technology 2 could provide essentially different TPOCDs of a lack of gearbox oil lubrication for different current phases; therefore, it is recommended to employ three phases for diagnosis by technology 2.
- Feature 2, averaged over the three phases, was proposed as a useful diagnostic feature, since it provided effective results even if one of the phases does not provide a sufficient level of diagnosis effectiveness.
- It was shown that the increase in non-linearity of the motor current signals due to increase of oil removal results from both increase the magnitudes of the higher harmonics of the supply frequency and decrease of the magnitude of the fundamental harmonic of the supply frequency due to increase of oil removal.
- Novel comparisons are made between the two proposed technologies. The following statements were concluded:
- diagnostic Feature 1 of technology 1 is more affected by current fluctuations in a grid system and by variation of gearbox operating load compared to Feature 2 of technology 2, because Feature 1 is unnormalized. Therefore, technology 1 is recommended for use in conditions of no- to low-current fluctuations of a grid system and of no- to low-variations of a gearbox load to ensure a reliable diagnosis and to avoid false alarms;
- diagnostic Feature 2 is less affected by current fluctuations in a grid system and by variation of gearbox operating load compared to Feature 1, because Feature 2 is normalized. Therefore, technology 2 is recommended to use in conditions of medium to high current fluctuations of a grid system and of medium to high variations of a gearbox load to ensure a reliable diagnosis and to avoid false alarms;
- technology 1 has shown its ability for diagnosing a lack of gear oil lubrication with more sensitivity to training data, compared to technology 2.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
Appendix A
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Farhat, M.H.; Gelman, L.; Conaghan, G.; Kluis, W.; Ball, A. Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis. Sensors 2022, 22, 9507. https://doi.org/10.3390/s22239507
Farhat MH, Gelman L, Conaghan G, Kluis W, Ball A. Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis. Sensors. 2022; 22(23):9507. https://doi.org/10.3390/s22239507
Chicago/Turabian StyleFarhat, Mohamed Habib, Len Gelman, Gerard Conaghan, Winston Kluis, and Andrew Ball. 2022. "Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis" Sensors 22, no. 23: 9507. https://doi.org/10.3390/s22239507
APA StyleFarhat, M. H., Gelman, L., Conaghan, G., Kluis, W., & Ball, A. (2022). Novel Diagnosis Technologies for a Lack of Oil Lubrication in Gearmotor Systems, Based on Motor Current Signature Analysis. Sensors, 22(23), 9507. https://doi.org/10.3390/s22239507