Vibro-Acoustic Analysis of Geared Systems—Predicting and Controlling the Whining Noise

Journal of Vibration and Acoustics

Cornuault

et al. 2017

This paper deals with the vibroacoustic behavior of an electric window-lift gear motor for automotive vehicle which consists of a direct current (DC) motor and a worm gear. After describing the overall vibroacoustic behavior of this system and identifying the various excitation sources involved, this study focuses on the excitation sources associated to the contacts between brushes and commutator. To that end, a specific test bench is designed. It makes use of a modified gear motor for which various specific rotors are driven with an external brushless motor. It allows the discrimination of some excitation sources associated to the contact between brushes and commutator by removing them one after the other. The respective weight of friction, mechanical shocks, electrical current flow, and commutation arcs occurring jointly at the brush/commutator interface are dissociated and evaluated. The friction and the mechanical shocks between brushes and commutator blades increase the vibroacoustic response of the window-lift gear motor. The flowing of electrical current in brushes/commutator contacts tends to moderate the frictional component of excitation sources, while commutation arcs induce their rising, leading to a global additive contribution to the dynamic response.

Section: Noise Friction Between Brushes and Commutator Blades Broadbandmentioning

confidence: 99%

Experimental Analysis of the Vibroacoustic Response of an Electric Window-Lift Gear Motor Generated by the Contact Between Carbon Brushes and Commutator

Diop

Journal of Vibration and Acoustics

Cornuault

et al. 2017

“…The methodology was then extended to the worm gear mesh [17,18]. Prediction of the whining noise induced by these excitations was performed by Rigaud [10] and Carbonelli [19] from solving the parametric equations of motion describing the system dynamic response. Models of the overall dynamic response should also consider potential coupling between the different excitation sources.…”

Section: Introductionmentioning

confidence: 99%

Numerical and experimental analysis of the vibroacoustic behavior of an electric window-lift gear motor

Cornuault

Bazin³

et al. 2018

Arch Appl Mech

Self Cite

This paper focuses on the numerical analysis of the vibroacoustic behavior of an electric window-lift gear motor for automotive vehicle which consists of a DC motor and a worm gear. A dynamic modelling of the gear motor is proposed. The excitation sources correspond to radial electromagnetic forces applied to steel stator, electromagnetic input torque fluctuation, rotor mechanical imbalance, worm gear static transmission error and mesh stiffness fluctuations and gear wheel eccentricity. Parametric equations of motion are solved using an iterative spectral method. It allows the computing of the vibroacoustic response of the system, taking account of the interaction between the mesh stiffness fluctuation and the other excitations. The simulation results are validated from comparison with experimental vibroacoustic measurements performed with a specific test bench. Spectrograms of the dynamic response show components corresponding to the harmonics of the excitation spectra, as well as lateral components arising around the mesh frequency and the input torque fluctuation frequency. This spectral enrichment is generated by the interaction between the mesh stiffness fluctuation and the other excitations. The lateral components contribute little to the overall level of the vibroacoustic response but they may have a significant impact on the quality of noise radiated directly by the gear motor or indirectly by its supporting structure. Finally, the weights of the different excitation sources to the spatial-average mean-square velocity of the radiating surface and the equivalent global dynamic force transmitted to the supporting structure are compared.

“…The mesh stiffness is usually deduced from STE estimation [4,5,18,19]. Welbourn has suggested an average value of 13.9 N.µm −1 per tooth width millimeter for standard spur gears [2].…”

Section: Introductionmentioning

confidence: 99%

“…The excitation sources are characterized by various frequency components, so that the time discretization methods generally fail to solve the system of parametric equations of motion, since a short time step is needed, as well as a simulation during a long time range. Consequently, an alternative method has been proposed [25,48,19]. This iterative spectral method is based on the solving of the linear parametric equations of motion in the spectral domain and leads to reduce the computation time.…”

Section: Introductionmentioning

confidence: 99%

“…This iterative spectral method is based on the solving of the linear parametric equations of motion in the spectral domain and leads to reduce the computation time. It has been used to predict and analyze the dynamic response and whining noise for mono [18,49,48,19] and multi-gear systems [50]. The variability of the dynamic response generated by the micro-level manufacturing errors has also been studied [51,52], as well as the dynamic response induced by an external random excitation with gyroscopic terms [53,54].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiphysics coupling between periodic gear mesh excitation and input/output fluctuating torques: Application to a roots vacuum pump

Garambois

Donnard

Journal of Sound and Vibration

et al. 2017

Self Cite

This paper presents the analysis of multiphysics coupling between periodic gear mesh excitation and upstream/downstream fluctuating loads using an iterative spectral methodology. This one is based on the resolution of the parametric equations of motion in the spectral domain. Its efficiency makes possible to treat both low and high frequency excitations for systems having a large number of degrees-of-freedom. The different excitation sources, the dynamic coupled equations of motion, the spectral methodology and the iterative resolution principle are described. The dynamic responses of a roots vacuum pump for which the spur gear high mesh frequency parametric excitation is coupled with a low fluidic drag torque frequency. The coupling between excitations generates a frequency enrichment of the dynamic response which is reflected on waterfall plots by emergence of numerous sidebands around harmonics of the mesh frequency.