Gear anomalies often stem from substandard lubrication conditions, which can result in significant gear damage. This invariably impacts the dynamic torque attributes of the gear system, leading to variations in the modulation of the motor current signal. This study presents a technique known as the Carrier Reconstructed Modulation Signal Bispectrum Analysis (CR-MSB), which adeptly mitigates diverse noise interferences to enable precise demodulation. This methodology proves particularly beneficial for variable frequency closed-loop control(CLC) systems used in industrial motors (IMs). Where harmonic interference from electronic components and inherent background noise often lead to a low signal-to-noise ratio (SNR) signal, thereby compromising precise demodulation. The proposed CR-MSB takes into account that the primary current loop measurement errors, strongly associated with the carrier frequency of the current, can aid in curbing measurement noise interference, allowing for a more accurate extraction of inherent modulated sideband magnitudes. To validate the effectiveness of this method, the comprehensive tests were conducted on a two-stage helical gearbox under a range of operating conditions, systematically varying the lubricant volume. The results disclose distinct current sideband characteristics under improper lubrication conditions, thereby confirming that CR-MSB can provide a effective metric for suppressing interferences and assessing gearbox lubricant conditions.
|Title of host publication
|2023 5th International Conference on Industrial Artificial Intelligence, IAI 2023
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 27 Nov 2023
|5th International Conference on Industrial Artificial Intelligence - Shenyang, China
Duration: 21 Aug 2023 → 24 Aug 2023
Conference number: 5
|5th International Conference on Industrial Artificial Intelligence
|21/08/23 → 24/08/23