Skip to main content
Log in

Physics-based modeling strategies for diagnostic and prognostic application in aerospace systems

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

This paper presents physics-based models as a key component of prognostic and diagnostic algorithms of health monitoring systems. While traditionally overlooked in condition-based maintenance strategies, these models potentially offer a robust alternative to experimental or other stochastic modeling data. Such a strategy is particularly useful in aerospace applications, presented in this paper in the context of a helicopter transmission model. A lumped parameter, finite element model of a widely used helicopter transmission is presented as well as methods of fault seeding and detection. Fault detection through diagnostic vibration parameters is illustrated through the simulation of a degraded rolling-element bearing supporting the transmission’s input shaft. Detection in the time domain and frequency domain is discussed. The simulation shows such modeling techniques to be useful tools in health monitoring analysis, particularly as sources of information for algorithms to compare with real-time or near real-time sensor data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

B d :

Ball or roller diameter

[C]:

Damping matrix

{F(t)}:

Force and moment vector

[G]:

Gyroscopic matrix

[K]:

Stiffness matrix

[M]:

Mass matrix

N b :

Number of balls of rollers

P d :

Bearing pitch diameter

{q}:

General coordinate vector

RPM:

Operating speed in revolutions per minute

θ :

Contact angle

References

  • Bengtsson, M., Olsson, E., Funk, P., & Jackson, M. (2004). Technical design of condition based maintenance system—A case study using sound analysis and case-based reasoning. In Proceedings of the 8th congress, maintenance and reliability conference, Knoxville, TN.

  • Blankenship, G., & Singh, R. (1992). A comparative study of selected gear mesh interface dynamic models. In Proceedings of the 6th international power transmission and gearing conference, Scottsdale, AZ.

  • Blankenship S., Mello F. (1998) Physics-based models to support test and evaluation. High Performance Computing Workshop, Las Cruces, NM

    Google Scholar 

  • Bechhoefer, R., & Hochmann, D. (2004). Method and apparatus for determining a condition indicator for use in evaluating the health of a component. U.S. Patent 6711523.

  • Box G., Jenkins G. (1976) Time series analysis: Forecasting and control. Holden-Day Publications, San Francisco

    Google Scholar 

  • Choy F., Ruan Y., Tu Y., Zakrajsek J., Oswald F. (1993) Modal simulation of gearbox vibration with experimental correlation. Journal of Propulsion and Power 9: 301–306

    Article  Google Scholar 

  • Choy, F., Ruan, Y., Tu, Y., Zakrajsek, J., & Townsend, D. (1991). Modal analysis of multistage gear systems coupled with gearbox vibrations. NASA TM-103797. AVSCOM TR-90-C-033.

  • Choy, F., Ruan, Y., Tu, Y., Zakrajsek, J., & Townsend, D. (1990). Dynamics of multistage gear transmission with effects of gearbox vibrations. NASA TM-103109. AVSCOM TR-89-C-022.

  • Choy, F., Townsend, D., & Oswald, F. (1988). Dynamic analysis of multimesh-gear helicopter transmissions. NASA TP-2789.

  • Decker, H., & Lewicki, D. (2003). Spiral Bevel crack detection in a helicopter gearbox. In Proceedings of the American helicopter society 59th annual forum, Phoenix, AZ.

  • Dempsey, P., Lewicki, D., & Decker, H. (2004). Transmission bearing damage detection using decision fusion analysis. NASA TM 2004-213382. ARL-TR-3328.

  • Department of Defense. (2007). Condition based maintenance plus (CBM+) for materiel maintenance. DOD Instruction 4151.22. http://www.dtic.mil/whc/directives/pdf/415122p.pdf. Accessed 26 January 2009.

  • Garga, A., Elverson, B., & Lang, D. (1997). Fault classification in helicopter vibration signals. In Proceedings of the American helicopter society 53rd annual forum, Virginia Beach, VA.

  • Johnson D. (1962) Modes and frequencies of shafts coupled by straight spur gears. Journal of Mechanical Engineering Science 4: 241–250

    Article  Google Scholar 

  • Keller, J., & Grabill, P. (2005). Inserted fault vibration monitoring tests for a CH-47D Aft swashplate bearing. In Proceedings of the American helicopter society 61st annual forum, Grapevine, TX.

  • Krantz, T., & Carr, D. (2009). Summary of research to implement CBM for a grease-lubricated bearing from the army’s AH-64 helicopter. Condition based maintenance AHS specialists’ meeting, Huntsville, AL.

  • Lebold, M., McClintic, K., Campbell, R., Byington, C., & Maynard, K. (2000). Review of vibration analysis methods for gearbox diagnostics and prognostics. In Proceedings of the 54th meeting of the society for machinery failure prevention technology, Virginia Beach.

  • Lebold, M., Reichard, K., & Boylan, D. (2003). Utilizing DCOM in an open system architecture framework for machinery monitoring and diagnostics. In Proceedings of the 2003 IEEE aerospace conference, Big Sky, MT.

  • Lewicki, D., & Coy, J. (1987). Vibration characteristics of OH-58A helicopter main rotor system. NASA TP-2705. ARL TR-86-C-42.

  • Lewicki, D., Decker, H., & Shimski, J. (1992). Development of a full-scale transmission testing procedure to evaluate advanced lubricants. NASA TP-3265. AVSCOM TR-91-C-026.

  • Lin J., Parker R. (1999) Analytical characterization of the unique properties of planetary gear free vibration. Journal of Vibration and Acoustics 121: 316–321

    Article  Google Scholar 

  • Mitchell, J. (1998). Five to ten-year vision for CBM. ATP fall meeting—Condition based maintenance workshop, Atlanta, GA.

  • Olsen, E., & Mavris, D. (2006). Aircraft conceptual design and risk analysis using physics-based noise prediction. AIAA Paper 2006-2619. 12th Aeroacoustics conference, Cambridge, MA.

  • Özgüven H., Houser D. (1988) Mathematical models used in gear dynamics. Journal of Sound and Vibration 121: 383–411

    Article  Google Scholar 

  • Parker, R., & Lin, J. (2001). Modeling, modal properties, and mesh stiffness variation instabilities of planetary gears. NASA CR 2001-210939. ARL CR 462.

  • Samuel P., Pines D. (2005) A review of vibration-based techniques for helicopter transmission diagnostics. Journal of Sound and Vibration 282: 475–508

    Article  Google Scholar 

  • Stevens, M., Handschuh, R., & Lewicki, D. (2008). Concepts for variable/multi-speed rotorcraft drive system. In Proceedings of the American helicopter society 64th annual forum, Montreal, Canada.

  • Stringer, D. (2008). Geared rotor dynamic methodologies for advancing prognostic capabilities in rotary-wing transmission systems. Ph.D. diss., Charlottesville, VA: University of Virginia.

  • Stringer, D., Sheth, P., Allaire, P. (2008). Gear modeling methodologies for advancing prognostic capabilities in rotary-wing transmission systems. In Proceedings of the American helicopter society 64th annual forum, Montreal, Canada.

  • Stringer, D., Sheth, P., & Allaire, P. (2009). A new helicopter transmission model for condition-based maintenance technologies using first principles. In Proceedings of the 45th AIAA/ASME/SAE/ASEE joint propulsion conference and exhibit, Denver, Colorado.

  • Tuplin W. (1950) Gear-tooth stresses at high speed. Proceedings of the Institution of Mechanical Engineers 163: 162–167

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to David B. Stringer.

Additional information

Pradip N. Sheth—Deceased.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Stringer, D.B., Sheth, P.N. & Allaire, P.E. Physics-based modeling strategies for diagnostic and prognostic application in aerospace systems. J Intell Manuf 23, 155–162 (2012). https://doi.org/10.1007/s10845-009-0340-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-009-0340-4

Keywords

Navigation