Operational Modal Analysis of Damage Gear
M. Aarif Amirza1, M. Azhan Anuar2, A.A.Mat Isa3, Zamri A.R4
1Mohammad Aarif Amirza*, INTEKMA Engineering and Services Sdn. Bhd, Menara Mitraland , Kota Damansara, Selangor Malaysia.
2Muhamad Azhan Anuar, Faculty of Mechanical Engineering, University Technology MARA, UiTM Shah Alam, Selangor, Malaysia.
3Ahmad Azlan Mat Isa, Faculty of Mechanical Engineering, University Technology MARA, UiTM Shah Alam, Selangor, Malaysia.
4Zamri Abdul Rahman, Faculty of Mechanical Engineering, University Technology MARA, UiTM Shah Alam, Selangor, Malaysia,
Manuscript received on December 13, 2019. | Revised Manuscript received on December 20, 2019. | Manuscript published on January 10, 2020. | PP: 2778-2783 | Volume-9 Issue-3, January 2020. | Retrieval Number: C9210019320/2020©BEIESP | DOI: 10.35940/ijitee.C9210.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: As natural frequencies and mode shapes are often a key to understanding dynamic characteristics of structural elements, modal analysis provides a viable means to determine these properties. This paper investigates the dynamic characteristics of a healthy and unhealthy condition of a commercially used helical gear using the Frequency Domain Decomposition (FDD) identification algorithm in Operational Modal Analysis (OMA). For the unhealthy condition, a refined range of percentage of defects are introduced to the helical gear starting from one (1) tooth being defected (1/60 teeth) to six (6) teeth being defected (6/60 teeth). The specimen is tested under a free-free boundary condition for its simplicity and direct investigation purpose. Comparison of the results of these varying conditions of the structure will be shown to justify the validity of the method used. Acceptable modal data are obtained by considering and accentuating on the technical aspects in processing the experimental data which are critical aspects to be addressed. The natural frequencies and mode shapes are obtained through automatic and manual peak-picking process from Singular Value Decomposition (SVD) plot using Frequency Domain Decomposition (FDD) technique and the results are validated using the established Modal Assurance Criterion (MAC) indicator. The results indicate that OMA using FDD algorithm is a good method in identifying the dynamic characteristics and hence, is effective in detection of defects in this rotating element.
Keywords: Defected Helical Gear, Frequency Domain Decomposition (FDD), Modal Assurance Criterion (MAC), Operational Modal Analysis (OMA), Singular Value Decomposition (SVD).
Scope of the Article: Measurement & Performance Analysis