Gearbox Fault Features Extraction Using Vibration Measurements and Novel Adaptive Filtering Scheme. (24th July 2012)

• Record Type: Journal Article
• Authors: Ibrahim, Ghalib R.; Albarbar, A.
• Other Names: Ikuta Akira Academic Editor.
• Is Part Of: Advances in acoustics and vibration. Volume 2012(2012)
• Publication Date: 2012-07-24
• Subjects: Sound -- Periodicals; Vibration -- Periodicals; Sound; Vibration; Periodicals; 620.2
• DOI: 10.1155/2012/283535
• Languages: English
• ISSNs: 1687-6261

Abstract

Abstract : Vibration signals measured from a gearbox are complex multicomponent signals, generated by tooth meshing, gear shaft rotation, gearbox resonance vibration signatures, and a substantial amount of noise. This paper presents a novel scheme for extracting gearbox fault features using adaptive filtering techniques for enhancing condition features, meshing frequency sidebands. A modified least mean square (LMS) algorithm is examined and validated using only one accelerometer, instead of using two accelerometers in traditional arrangement, as the main signal and a desired signal is artificially generated from the measured shaft speed and gear meshing frequencies. The proposed scheme is applied to a signal simulated from gearbox frequencies with a numerous values of step size. Findings confirm that 10 −5 step size invariably produces more accurate results and there has been a substantial improvement in signal clarity (better signal-to-noise ratio), which makes meshing frequency sidebands more discernible. The developed scheme is validated via a number of experiments carried out using two-stage helical gearbox for a healthy pair of gears and a pair suffering from a tooth breakage with severity fault 1 (25% tooth removal) and fault 2 (50% tooth removal) under loads (0%, and 80% of the total load). The experimental results show remarkable improvements and enhance gear condition features. This paper illustrates that the new approach offers a more effective way to detect early faults.