An improved electromechanical spectral signature for monitoring gear-based systems driven by an induction machine. (1st December 2018)

• Record Type: Journal Article
• Authors: Touti, Walid; Salah, Mohamed; Bacha, Khmais; Amirat, Yassine; Chaari, Abdelkader; Benbouzid, Mohamed
• Is Part Of: Applied acoustics. Volume 141(2018)
• Page Start: 198
• Page End: 207
• Publication Date: 2018-12-01
• Subjects: Condition monitoring -- Gearbox -- Harmonic analysis -- Induction motor -- MCSA -- Vibration; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2018.07.019
• Languages: English
• ISSNs: 0003-682X

Abstract

Highlights: Gearbox fault effects analysis on vibration, load torque, MCSA, ZSC, and SCSV frequency responses. A new analysis technique based on data preprocessing using discrete cosine and sinus transforms. Original algorithm for detecting input and output frequencies from the vibration data. Abstract: Even under normal operating conditions, Gear-based systems naturally generate four particular frequencies: the input and output mechanical speeds as well as the gear meshing and the hunting tooth frequencies. Thereby, through amplitude monitoring of these components and their harmonics, the gear state can be easily monitored and successfully assessed. Based on this fact, this paper discusses the fitness of the vibration data and the load torque (mechanical signature) to detect these frequencies. Furthermore, when the system is driven by an induction machine these frequencies will affect the stator currents. Thus, the appropriateness of the spectral analyzing techniques based such amounts as alternate for monitoring gear-based systems will also be discussed. Moreover, for improving the sensitivity detection of these particular frequencies an original preprocessing technique is proposed and its effectiveness is evaluated for spectral analysis of mechanical as well as electrical experimental data.