Monitoring the Status of the Pride Gear Box Using the Beta-Kurtosis of Its Vibrating Signals

Alireza Dadkhah Laleh, Mirmohammad Ettefagh, Reza Hasanezhad Qadim


Today, with the growth of industry and the increasing development of industrial machinery, the maintenance of these machines and the evaluation of their operation during the work is of particular importance. In this paper, we have tried to find out all the vibration signals associated with it in the case of a healthy and defective gearbox, and to examine the results by familiarizing them with the methods of receiving and analyzing the transmission of the Pride transmission. Using a laboratory gearbox belonging to this vehicle, all of its vibrational signals should be considered. For this purpose, using the vibration sensor, the data is extracted in different operating modes of the machine. After collecting data of each mode, using the MATLAB program and using the Beta-Kurtosis method, one of the statistical methods suitable for diagnosis of the gears will be extracted and examined by the vibration patterns of the transmission of the pride vehicle.


Gearbox, Vibrating rotary machines, Preventive maintenance, Troubleshooting, Beta-Kurtosis

Full Text:



. Andrew D. Dimarogon and Sam Haddad. (1992), "Vibration for Engineers.", Machinary Vibration: Monitoring and Diagnosis 14,675-706.

. Anonymous (1988), Vibration Technology 1, IRD Mechanalysis Inc.

. Lin, J. & Zuo, M.J. (2003). Gearbox fault diagnosis using an adaptive wavelet filter. Mechanical systems and signal processing, 17 (6), 1259-1269.

. Wuxing, L., Peter, W. T., Guicai, Z. & Tielin, S. (2004). Classification of gear faults using cumulants and the radial base function network. Mechanical systems and signal processing, 18 (2), 381-389.

. Joentgen, A., Mikenina, L., Weber, R., Zeugner, A., & Zimmermann, H. J. (1999). Automatic fault detection in gearboxes by dynamic fuzzy data analysis. Fuzzy Sets and Systems, 105 (1), 123-132.

. Zhang, B., Sconyers, C., Byington, C., Patrick, R., Orchard, M. E., & Vachtsevanos, G. (2011). A probabilistic fault detection approach: application to bearing fault detection. IEEE Transactions on Industrial Electronics, 58 (5).

. Skrike, V., Bogdevičius, M., & Junevičius, R. (2016). Diagnostic features for the condition monitoring of a hypoid gear utilizing the wavelet transform. Applied Acoustics, 106, 51-62.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Revista Publicando.

Licencia de Creative Commons


This Content is available under licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional.