Skip to main content
Erschienen in: Neural Computing and Applications 1/2019

18.04.2017 | Original Article

Failure prognostics of heavy vehicle hydro-pneumatic spring based on novel degradation feature and support vector regression

verfasst von: Cheng Yang, Ping Song, Xiongjun Liu

Erschienen in: Neural Computing and Applications | Ausgabe 1/2019

Einloggen

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The hydro-pneumatic spring, as an important element of the suspension system for heavy vehicles, has attracted the attention of researchers for a long time because it plays such an important role in the steering stability, driving comfort, and driving safety of these vehicles. In this paper, we aim to solve the maintenance problems caused by gas leakage and oil leakage faults in hydro-pneumatic springs. The causes of hydro-pneumatic spring faults and their modes are investigated first. Then, we propose a novel time domain fault feature, called degraded pressure under the same displacement, and a novel feature extraction method based on linear interpolation and redefined time intervals. This feature extraction method is then combined with a data-driven prognostic method that is based on support vector regression to predict the failure trends. When compared with traditional prognostic methods for suspension systems based on vibration signals and vehicle dynamics models, the proposed method can evaluate the real-time spring condition without use of additional sensors or an accurate dynamic model. Therefore, the computational cost of the proposed method is very low and is also suitable for use in vehicles that are equipped with low-cost microprocessors. In addition, hydro-pneumatic spring performance degradation experiments and simulations based on AMEsim software are designed. The experimental data, real vehicle historical data, and simulation data are used to verify the feasibility of the proposed method.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Vichare NM, Pecht MG (2006) Prognostics and health management of electronics [J]. IEEE Transactions on Components & Packaging Technologies 29(1):222–229CrossRef Vichare NM, Pecht MG (2006) Prognostics and health management of electronics [J]. IEEE Transactions on Components & Packaging Technologies 29(1):222–229CrossRef
2.
Zurück zum Zitat Lee J, Wu F, Zhao W et al (2014) Prognostics and health management design for rotary machinery systems—reviews, methodology and applications [J]. Mechanical Systems & Signal Processing 42(1–2):314–334CrossRef Lee J, Wu F, Zhao W et al (2014) Prognostics and health management design for rotary machinery systems—reviews, methodology and applications [J]. Mechanical Systems & Signal Processing 42(1–2):314–334CrossRef
3.
Zurück zum Zitat Tsui KL, Chen N, Zhou Q et al (2015) Prognostics and health management: a review on data driven approaches [J]. Math Probl Eng 2015(6):1–17CrossRef Tsui KL, Chen N, Zhou Q et al (2015) Prognostics and health management: a review on data driven approaches [J]. Math Probl Eng 2015(6):1–17CrossRef
4.
Zurück zum Zitat David Ludovici, Michael Bray, Vish Wickramanayake (2013) Health and usage monitoring proof of concept study using army land vehicles [C]. 15th Australian International Aerospace Congress David Ludovici, Michael Bray, Vish Wickramanayake (2013) Health and usage monitoring proof of concept study using army land vehicles [C]. 15th Australian International Aerospace Congress
5.
Zurück zum Zitat Sankavaram C, Kodali A, Pattipati K (2013) An integrated health management process for automotive cyber-physical systems[C]. IEEE ICNC 2013 International Workshop on Cyber-Physical Systems :82–86 Sankavaram C, Kodali A, Pattipati K (2013) An integrated health management process for automotive cyber-physical systems[C]. IEEE ICNC 2013 International Workshop on Cyber-Physical Systems :82–86
6.
Zurück zum Zitat Ompusunggu A, Papy JM, Vandenplas S (2016) Kalman-filtering-based prognostics for automatic transmission clutches [J]. IEEE/ASME Transactions on Mechatronics 21(1):419–430 Ompusunggu A, Papy JM, Vandenplas S (2016) Kalman-filtering-based prognostics for automatic transmission clutches [J]. IEEE/ASME Transactions on Mechatronics 21(1):419–430
7.
Zurück zum Zitat Ompusunggu A P, Vandenplas S, Sas P et al. (2012) Health Assessment and Prognostics of Automotive Clutches[C]// European Conference of the Prognostics and Health Management Society Ompusunggu A P, Vandenplas S, Sas P et al. (2012) Health Assessment and Prognostics of Automotive Clutches[C]// European Conference of the Prognostics and Health Management Society
8.
Zurück zum Zitat Yu M, Wang D (2014) Model-based health monitoring for a vehicle steering system with multiple faults of unknown types [J]. IEEE Trans Ind Electron 61(61):3574–3586 Yu M, Wang D (2014) Model-based health monitoring for a vehicle steering system with multiple faults of unknown types [J]. IEEE Trans Ind Electron 61(61):3574–3586
9.
Zurück zum Zitat Banks J, Brought M, Estep J et al. (2011) Health and usage monitoring for military ground vehicle power generating devices[C]. IEEE Aerospace Conference. IEEE Computer Society :1–17 Banks J, Brought M, Estep J et al. (2011) Health and usage monitoring for military ground vehicle power generating devices[C]. IEEE Aerospace Conference. IEEE Computer Society :1–17
10.
Zurück zum Zitat Hamed M, Tesfa B, Gu F et al. (2014) A study of the suspension system for the diagnosis of dynamic characteristics[C]. Automation and Computing (ICAC), 2014 20th International Conference on, Cranfield 152–157 Hamed M, Tesfa B, Gu F et al. (2014) A study of the suspension system for the diagnosis of dynamic characteristics[C]. Automation and Computing (ICAC), 2014 20th International Conference on, Cranfield 152–157
11.
Zurück zum Zitat Solomon U, Padmanabhan C (2011) Hydro-gas suspension system for a tracked vehicle: modeling and analysis[J]. J Terrramech 48(2):125–137CrossRef Solomon U, Padmanabhan C (2011) Hydro-gas suspension system for a tracked vehicle: modeling and analysis[J]. J Terrramech 48(2):125–137CrossRef
12.
Zurück zum Zitat Bartnicki A, Muszyński T, Rubiec A (2015) Hydropneumatic suspension efficiency in terms of Teleoperated UGV research[J]. Solid State Phenom 237(1):195–200CrossRef Bartnicki A, Muszyński T, Rubiec A (2015) Hydropneumatic suspension efficiency in terms of Teleoperated UGV research[J]. Solid State Phenom 237(1):195–200CrossRef
13.
Zurück zum Zitat Ferreira C, Ventura P, Morais R et al (2009) Sensing methodologies to determine automotive damper condition under vehicle normal operation[J]. Sensors & Actuators A Physical 156(1):237–244CrossRef Ferreira C, Ventura P, Morais R et al (2009) Sensing methodologies to determine automotive damper condition under vehicle normal operation[J]. Sensors & Actuators A Physical 156(1):237–244CrossRef
14.
Zurück zum Zitat Hernandezalcantara D, Moralesmenendez R, Amezquitabrooks L (2015) Fault Detection for Automotive Shock Absorber[C]// Journal of Physics: Conference Series :012037 Hernandezalcantara D, Moralesmenendez R, Amezquitabrooks L (2015) Fault Detection for Automotive Shock Absorber[C]// Journal of Physics: Conference Series :012037
15.
Zurück zum Zitat Luo J, Pattipati KR, Qiao L et al (2008) Model-based prognostic techniques applied to a suspension system [J]. IEEE Trans Syst Man Cybern Syst Hum 38(5):1156–1168CrossRef Luo J, Pattipati KR, Qiao L et al (2008) Model-based prognostic techniques applied to a suspension system [J]. IEEE Trans Syst Man Cybern Syst Hum 38(5):1156–1168CrossRef
16.
Zurück zum Zitat Wei X, Jia L, Liu H (2013) A comparative study on fault detection methods of rail vehicle suspension systems based on acceleration measurements [J]. Vehicle System Dynamics International Journal of Vehicle Mechanics & Mobility 51(5):700–720CrossRef Wei X, Jia L, Liu H (2013) A comparative study on fault detection methods of rail vehicle suspension systems based on acceleration measurements [J]. Vehicle System Dynamics International Journal of Vehicle Mechanics & Mobility 51(5):700–720CrossRef
17.
Zurück zum Zitat Zhao F, Guan JF, Gu L et al. (2016) Experimental study on wheeled vehicle hydro-pneumatic suspension fault detection [J]. Journal of Beijing Institute of Technology (2) Zhao F, Guan JF, Gu L et al. (2016) Experimental study on wheeled vehicle hydro-pneumatic suspension fault detection [J]. Journal of Beijing Institute of Technology (2)
18.
Zurück zum Zitat Jaoude AA (2014) Analytic and linear prognostic model for a vehicle suspension system subject to fatigue [J]. Systems Science & Control Engineering 3(1):81–98CrossRef Jaoude AA (2014) Analytic and linear prognostic model for a vehicle suspension system subject to fatigue [J]. Systems Science & Control Engineering 3(1):81–98CrossRef
19.
Zurück zum Zitat Guo J, Jiao N, Jiang L et al. (2014) Hydro-pneumatic suspension gasbag reliability improvement based on FMEA and FTA[C]. International Conference on Reliability, Maintainability and Safety. IEEE 592–594 Guo J, Jiao N, Jiang L et al. (2014) Hydro-pneumatic suspension gasbag reliability improvement based on FMEA and FTA[C]. International Conference on Reliability, Maintainability and Safety. IEEE 592–594
20.
Zurück zum Zitat Drucker H, Burges CJC, Kaufman L et al (1996) Support vector regression machines. [J]. Adv Neural Inf Proces Syst 28(7):779–784 Drucker H, Burges CJC, Kaufman L et al (1996) Support vector regression machines. [J]. Adv Neural Inf Proces Syst 28(7):779–784
21.
Zurück zum Zitat Loutas TH, Roulias D, Georgoulas G (2013) Remaining useful life estimation in rolling bearings utilizing data-driven probabilistic E-support vectors regression[J]. IEEE Trans Reliab 62(4):821–832CrossRef Loutas TH, Roulias D, Georgoulas G (2013) Remaining useful life estimation in rolling bearings utilizing data-driven probabilistic E-support vectors regression[J]. IEEE Trans Reliab 62(4):821–832CrossRef
22.
Zurück zum Zitat Wang S, Zhao L, Su X et al. (2014) Prognostics of lithium-ion batteries based on flexible support vector regression[C]. Prognostics and System Health Management Conference. IEEE 317–322. Wang S, Zhao L, Su X et al. (2014) Prognostics of lithium-ion batteries based on flexible support vector regression[C]. Prognostics and System Health Management Conference. IEEE 317–322.
23.
Zurück zum Zitat Benkedjouh T, Medjaher K, Zerhouni N et al (2015) Health assessment and life prediction of cutting tools based on support vector regression [J]. J Intell Manuf 26(2):213–223CrossRef Benkedjouh T, Medjaher K, Zerhouni N et al (2015) Health assessment and life prediction of cutting tools based on support vector regression [J]. J Intell Manuf 26(2):213–223CrossRef
24.
Zurück zum Zitat Chen S, Xin P, Tao L (2014) A method for predicting life of electronic components based on generic algorithm and support vector machine (SVM) [J]. Journal of Northwestern Polytechnical University 32(4):637–641 Chen S, Xin P, Tao L (2014) A method for predicting life of electronic components based on generic algorithm and support vector machine (SVM) [J]. Journal of Northwestern Polytechnical University 32(4):637–641
25.
Zurück zum Zitat Lyu W-L, Chang C-C (2016) An image compression method based on block truncation coding and linear regression [J]. Journal of Information Hiding and Multimedia Signal Processing 7(1):198–215 Lyu W-L, Chang C-C (2016) An image compression method based on block truncation coding and linear regression [J]. Journal of Information Hiding and Multimedia Signal Processing 7(1):198–215
26.
Zurück zum Zitat Lee J, Wu F, Zhao W et al (2014) Prognostics and health management design for rotary machinery systems—reviews, methodology and applications [J]. Mech Syst Signal Process 42:314–334CrossRef Lee J, Wu F, Zhao W et al (2014) Prognostics and health management design for rotary machinery systems—reviews, methodology and applications [J]. Mech Syst Signal Process 42:314–334CrossRef
27.
Zurück zum Zitat Duan WY, Huang LM, Han Y et al (2015) A hybrid AR-EMD-SVR model for the short-term prediction of nonlinear and non-stationary ship motion [J]. Journal of Zhejiang University: Science A 16(7):562–576CrossRef Duan WY, Huang LM, Han Y et al (2015) A hybrid AR-EMD-SVR model for the short-term prediction of nonlinear and non-stationary ship motion [J]. Journal of Zhejiang University: Science A 16(7):562–576CrossRef
28.
Zurück zum Zitat Wang JE, Qiao JZ (2013) Parameter selection of SVR based on improved K-fold cross validation[J]. Applied Mechanics & Materials 462-463:182–186CrossRef Wang JE, Qiao JZ (2013) Parameter selection of SVR based on improved K-fold cross validation[J]. Applied Mechanics & Materials 462-463:182–186CrossRef
Metadaten
Titel
Failure prognostics of heavy vehicle hydro-pneumatic spring based on novel degradation feature and support vector regression
verfasst von
Cheng Yang
Ping Song
Xiongjun Liu
Publikationsdatum
18.04.2017
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 1/2019
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-017-2986-8

Weitere Artikel der Ausgabe 1/2019

Neural Computing and Applications 1/2019 Zur Ausgabe