2020
DOI: 10.1155/2020/1294609
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Numerical Noise Transfer Analysis of a Flexible Supported Gearbox Based on Impedance Model and Noise Transfer Function

Abstract: To investigate the gearbox radiation noise properties under various rotational speeds, a noise prediction method based on impedance model and noise transfer function (NTF) is proposed. One only needs to extract the NTF of the housing once rapid gearbox noise prediction under different working conditions is realized. Taking a flexible supported gearbox as a research object, the external excitation of the housing (the bearing excitation load and isolator excitation load) is calculated through a gear-housing-foun… Show more

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Cited by 3 publications
(1 citation statement)
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“…The effects of different excitation components and noise transfer functions on the noise were analyzed using the gear-box-foundation coupled impedance model and vibro-acoustic coupled boundary element model. Their results showed that high-speed bearings were the main source of radiated noise [13]. Tengjiao et al used numerical simulation to calculate the vibration response of a dynamic finite element model consisting of a gear-rotor-bearing-case coupling, and then used the vibration displacement results of the gearbox surface nodes as acoustic boundary conditions to establish an acoustic boundary model of the gearbox.…”
Section: Introductionmentioning
confidence: 99%
“…The effects of different excitation components and noise transfer functions on the noise were analyzed using the gear-box-foundation coupled impedance model and vibro-acoustic coupled boundary element model. Their results showed that high-speed bearings were the main source of radiated noise [13]. Tengjiao et al used numerical simulation to calculate the vibration response of a dynamic finite element model consisting of a gear-rotor-bearing-case coupling, and then used the vibration displacement results of the gearbox surface nodes as acoustic boundary conditions to establish an acoustic boundary model of the gearbox.…”
Section: Introductionmentioning
confidence: 99%