Nonlinear dynamics of new magneto-mechanical oscillator

Zhifeng Hao* (Corresponding Author), Dan Wang, Marian Wiercigroch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This study presents modelling and analysis of a new magneto-mechanical (MM) oscillator (Nonlinear Dyn 99:323-339,2020), which pays a special attention to mechanical and magnetic nonlinearities for large amplitude responses. The oscillator is comprised of a box structure made of two parallel leaf springs with one end fixed and the other clamped with a proof mass, and an electromagnetic actuator. A solenoid and a permanent magnet are the main parts of the actuator, which acts directly on the proof mass providing an accurate and versatile excitation by varying intensity and frequency of the input current. The new model for a beam of large deflection is based up the constitutive relation of nonlinear beam theory. A new design of the electromagnetic actuator with a pair of identical solenoids and a new concept of quasi-constant force (QCF) are proposed, which aim to generate a nearly constant force for a constant input current. The mathematical model of the MM oscillator is systematically
developed and discussed for different types of excitations depending on designs and parameters of the electromagnetic actuator. The undertaken nonlinear dynamics analysis further demonstrates versatility of the electromagnetic actuator to generate a wide spectrum of excitations. The prediction from the modelling were validated with the experimental results from the previous work (Nonlinear Dyn 102:835-861,2020). The study demonstrates that the electromagnetic actuator provides versatile excitation patterns and can be used to study experimentally subtle nonlinear phenomena.
Original languageEnglish
JournalCommunications in Nonlinear Science and Numerical Simulation
Publication statusAccepted/In press - 21 Oct 2021


  • Magneto-mechanical oscillator
  • Constitutive relation
  • Electromagnetic actuation
  • Nonlinear dynamics


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