Vibration Based Blind Identification of Bearing Failures for Autonomous Wireless Sensor Nodes

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Andrea Sanchez Ramirez Richard Loendersloot Tiedo Tinga

Abstract

Despite all the attention received by maintainers, undetected roller bearings failures are still a major source of concern in relation with reliability losses and high maintenance costs. Because of that, bearing condition assessment through vibration monitoring remains an intensive topic of scientific research, focusing on the definition of monitoring strategies that allow early stage damage detection, failure causes identification and remaining life prediction. Next to the developments on signal processing, new opportunities of advanced monitoring platforms are devised as those based on Wireless Sensor Networks (WSNs). The combination of integrated sensing, embedded computing and wireless communication provides interesting elements on the development of a new generation of vibration monitoring systems. The algorithms for bearing assessment remain a crucial point for achieving a balance between efficient monitoring strategies and highly flexible monitoring platforms. Though current trends on signal processing for mechanical vibrations focuses on the development of robust techniques, the constraints of embedded processing in relation to energy and memory consumption hamper their implementation on WSN.
The present paper discusses the problem of bearing condition characterization from the basis of extraction of damage features associated with the specific stage of its deterioration process. This, other than data driven methods, allow to find the best compromise between robustness of the bearing assessment algorithm and the applicability of the algorithm on a WSN. Two cases are presented as validation of this approach: an artificial damage on a lab setup and a train bearing, for which the possibilities for detection, diagnostics and prognostics are discussed. The advantages and constraints of the use of autonomous wireless sensor nodes is discussed as final part of the paper.

How to Cite

Ramirez, A. S., Loendersloot, R., & Tinga, T. (2014). Vibration Based Blind Identification of Bearing Failures for Autonomous Wireless Sensor Nodes. PHM Society European Conference, 2(1). https://doi.org/10.36001/phme.2014.v2i1.1523
Abstract 56 | PDF Downloads 30

##plugins.themes.bootstrap3.article.details##

Keywords

bearing diagnostics, , blind identification

References
Sanchez Ramirez, A; Loendersloot, R., Jauregui, J. M., & Tinga, T. (2013). Design Framework for Vibration Monitoring Systems for Helicopter Rotor Blade Monitoring using Wireless Sensor Networks. In International Workshop on Structural Health Monitoring (pp. 1023 – 1030). September 10-12. Stanford University. California.
Tinga, T. (2013). Principles of Loads and Failure Mechanisms. London: Springer London. doi:10.1007/978-1-4471-4917-0
Lugt, P.M. (2012). Grease Lubrication in Rolling Bearings. New York: John Wiley & Sons. ISBN: 978-1-118-35391-2
Wijnant. Y.H. (1998). Contact Dynamics in the field of Elastohydrodynamic Lubrication. Ph.D. Thesis. University of Twente. The Netherlands.
Liew and Lim (2005). Analysis of time-varying rolling element bearing characteristics. In Journal of Sound and Vibration 283. Pg 1163-1179.
Swartjes, M. (1995) Resonant Ultrasonic Spectroscopy: measurement system for detection of cracks in rolling elements. Master Thesis. University of Twente. The Netherlands
Wensing, J.A. (1998). On the dynamics of ball bearings. Ph.D. Thesis. University of Twente. The Netherlands.
Tandon. N. & Choudhury. A. (1999). A review of vibration and acoustic measurement methods for the detection of defects in rolling elements bearings. Tribology International 32. Pg 469-480.
Alessandro Cisi, Alessandro Zanella, Giuseppe D’Angelo. (2013). Rolling Element Bearing Fault Detection Based on Orthogonal Hilbert-Huang Transform, In Tenth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, CM and MFPT, June 18-20, Poland
Randall, R.B. Vibration- Based Condition Monitoring. Industrial, Aerospace and Automotive Applications. New York: John Wiley & Sons. ISBN: 978-0-470-74785-8
Railways SKF (2012). Bearing designs Cylindrical roller bearings and units. Railway technical handbook, Vol 1, Ch 4, Pg 88- 95.
SKF Engineering Calculator. www.skf.com. Retrieved March 2014.
Section
Technical Papers

Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.