Skip to main content
SpringerLink
Log in

Mathematic Modeling and Chaotic Identification for Practice Construction in Vibratory Compacting

  • Original Paper
  • Published:
Journal of Vibration Engineering & Technologies Aims and scope Submit manuscript

Abstract

Background

Vibratory compactor that depends on the principle of vibration is important in earthwork and pavement building. The compactor is an important technical equipment in transportation and energy development. However, in the practical application of vibratory engineering, shortage of traditional construction design and the effects of nonlinear chaos vibration on human health are ignored.

Objective

Our objective was to explore a simple non-smooth collision model that could effectively represent the dynamic properties of practical system during compaction to eliminate the nonlinear chaotic responses of mechanical structure and to reduce irregular vibration that is harmful to the physical and mental health of operators.

Methods

An advisable construction method for pavement material compaction based on chaotic identification is proposed. A simple non-smooth dynamic model that supposes generalized restoring force was established for a compacting system by introducing dimensionless variables. The dynamic responses of an excitation system were analyzed by time domain, phase diagram, Poincare section, power spectrum, and bifurcation diagram methods. Moreover, the advisable construction method based on chaotic identification was applied to field tests on asphalt construction by using a YZC12 vibratory roller compactor on the Beijing–Fuzhou highway.

Results

Research showed that the dynamic characteristics of excitation system were experienced from a single cycle, single periodic bifurcation, a double cycle, and double periodic bifurcation until chaos evolution because of different model parameters that represented all types of working conditions. Results also showed that for the earlier stage of compacted material, dimensionless angular frequency might be reasonably selected within the range of 1.69 to 2.21 under large exciting forces. For the later stage of compacted material, dimensionless angular frequency might be selected within the range of 1.75 to 2.13 under large exciting forces or within the range from 1.64 to 2.25 under small exciting forces. Such a situation could weaken the nonlinear characteristics of a dynamic system to avoid chaotic vibration. Test results showed that the higher density compacting construction, the smaller exciting force with higher vibration frequency were suitable for eliminating the nonlinear chaos of a dynamic system.

Conclusions

Such dynamic nonlinearity elimination could improve the driver’s comfort and extend the service life of vibratory machinery equipment. The results obtained using the non-smooth model and the construction method based on chaotic identification were appropriate for engineering applications.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Wersall C, Larsson S (2013) Small-scale testing of frequency-dependent compaction of sand using a vertically vibrating plate. Geotech Test J 36(3):394–403

    Article  Google Scholar 

  2. Mooney MA, Gorman PB, Gonzalez JN (2005) Vibration-based health monitoring of earth structures. Structural Health Monit 4(2):137–152

    Article  Google Scholar 

  3. Monica LA, Rosalia PT, Dolores MA et al (2013) Comparative analysis of exposure limit values of vibrating hand-held tools. Int J Ind Ergon 43(3):218–224

    Article  Google Scholar 

  4. Yoo TS, Selig ET (1979) Dynamics of vibratory-roller compaction. J Geotechn Eng Division 105(10):1211–1231

    Google Scholar 

  5. Rinehart RV, Berger JR, Mooney MA (2009) Comparison of stress states and paths vibratory roller-measured soil stiffness and resilient modulus testing. J Transp Res Board 2116:8–15

    Article  Google Scholar 

  6. Lu S, Chung DDL (2014) Viscoelastic behavior of silica particle compacts under dynamic compression. J Mater Civ Eng 26(3):551–553

    Article  Google Scholar 

  7. Pietzsch D, Poppy W (1992) Simulation of soil compaction with vibratory rollers. J Terrramech 29(6):585–597

    Article  Google Scholar 

  8. Grabe J (1993) Continuous inverse calculation of soil stiffness from the dynamic behaviour of a driving vibratory roller. Arch Appl Mech 63(1):472–478

    Google Scholar 

  9. Beainy F, Commuri S, Zaman M et al (2013) Viscoelastic-plastic model of asphalt-roller interaction. Int J Geomech 13(5):581–594

    Article  Google Scholar 

  10. Cao YW, Huang XJ, Ma LY (2011) Finite element analysis to vibratory drum-soil model of vibratory roller. Appl Mech Mater 94–96:2005–2008

    Article  Google Scholar 

  11. Liu DH, Sun J, Zhong DH (2012) Compaction quality control of earth-rock dam construction using real-time field operation data. J Constr Eng Manage 138(9):1085–1094

    Article  Google Scholar 

  12. Xu Q, Chang GK (2013) Evaluation of intelligent compaction for asphalt materials. Autom Constr 30:104–112

    Article  Google Scholar 

  13. Wu JL, Luo Z, Zhang N et al (2015) A new uncertain analysis method and its application in vehicle dynamics. Mech Syst Signal Process 50:659–675

    Article  Google Scholar 

  14. Luo HY, Wang YF (2015) Dynamics of a continuum rotor with two nonlinear models of bearing and transverse electromagnetic excitations. J Vib Eng Technol 3(1):49–64

    Google Scholar 

  15. Harvey PS, Wiebe R, Gavin HP (2013) On the chaotic response of a nonlinear rolling isolation system. Physica D 256–257(8):36–42

    Article  MathSciNet  MATH  Google Scholar 

  16. Anderegg R, Kaufmann K (2004) Intelligent compaction with vibratory rollers: feedback control systems in automatic compaction and compaction control. J Transp Res Board 1868(1):124–134

    Article  Google Scholar 

  17. Susante PJ, Mooney MA (2008) Capturing nonlinear vibratory roller compactor behavior through lumped parameter modeling. J Eng Mech 134(8):684–693

    Article  Google Scholar 

  18. Shen PH, Lin SW (2008) Mathematic modelling and characteristic analysis for dynamic system with asymmetrical hysteresis in vibratory compaction. Meccanica 43(5):505–515

    Article  MathSciNet  MATH  Google Scholar 

  19. Ata AA, Hamid RR, Said HT et al (2012) Loading frequency effect on stiffness, damping and cyclic strength of modeled rockfill materials. Soil Dyn Earthq Eng 33(1):1–18

    Article  Google Scholar 

  20. White DJ, Thompson MJ (2008) Relationships between in situ and roller-integrated compaction measurements for granular soils. J Geotech Geoenviron Eng 134(12):1763–1770

    Article  Google Scholar 

  21. Han QK, Wen BC (1998) Analysis of a forced vibration system with asymmetrical hysteresis. J Vib Eng 11(3):291–297

    Google Scholar 

  22. Krishnamurthy BK, Tsernh HP, Schmitt RL et al (1998) Autopave: towards an automated paving system for asphalt pavement compaction operations. Autom Constr 8(2):165–180

    Article  Google Scholar 

  23. Horan RD, Chang GK, Xu Q et al (2012) Improving quality control of hot-mix asphalt paving with intelligent compaction technology. J Transp Res Board 2268(1):82–91

    Article  Google Scholar 

  24. Minaev OP (2011) Development of vibratory method for soil compaction during construction. Soil Mech Found Eng 48(5):190–195

    Article  Google Scholar 

Download references

Acknowledgements

This work has been financially supported by the National Natural Science Foundation of China with Grants no. 51175086, The Fostering foundation for Excellent Youth of Fujian College with Grant no. JA11299, the Scientific and Technological Program of Fujian Provincial Communications Department with Grant no. 201120, and the Natural Science Foundation of Fujian Province with Grant no. 2015J01186. The work has been supported by the Training Program of Fujian Excellent Talents in University (FETU). The writers thank Professor Huang and Dr. Guan for their assistance with data gathering and for their insights in discussing results.

Author information

Authors and Affiliations

  1. Fujian Chuanzheng Communications College, Fuzhou, 350007, People’s Republic of China

    Peihui Shen

  2. College of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350002, People’s Republic of China

    Shuwen Lin

Authors
  1. Peihui Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shuwen Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peihui Shen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, P., Lin, S. Mathematic Modeling and Chaotic Identification for Practice Construction in Vibratory Compacting. J. Vib. Eng. Technol. 6, 1–13 (2018). https://doi.org/10.1007/s42417-018-0008-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42417-018-0008-5

Keywords

Search

Navigation