Research of transfer path analysis based on contribution factor of sound quality

Shang, Zhihao; Hu, Feng; Fa-lin, Zeng; Wei, Liangben; Xu, Qiufu; Wang, Jiasheng

doi:10.1016/j.apacoust.2020.107693

Cited by 9 publications

(5 citation statements)

References 11 publications

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“…In the formula, matrix [P] represents response matrix; matrix [H] represents path transfer function matrix; matrix [F] represents excitation force matrix [14]. This calculation requires the transfer functions of reference points near the excitation point.…”

Section: Structure-borne Noise Transfer Function Measurementsmentioning

confidence: 99%

“…Transfer path analysis (TPA) and transfer path synthesis (TPS) techniques have been widely used in the automotive noise, vibration, and harshness (NVH) industry [9][10][11][12][13][14]. TPA technology has been a mainstay of ICEVs and has been more recently considered for EVs.…”

Section: Introductionmentioning

confidence: 99%

“…The low-frequency vibrations of steering wheels have been reduced by a systematic analysis based on classical TPA [13]. TPA can accurately and effectively determine the composition of the structural vibration transfer path and its impact on the interior noise [14].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis

et al. 2021

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The interior sound quality (SQ) of pure electric vehicles (PEVs) has become an important consideration for users purchasing vehicles. At present, it is insufficient to take the sound pressure level as the interior acoustics design index of PEVs. Transfer path analysis (TPA) and transfer path synthesis (TPS) that take the SQ of interior noise as the improvement target remains in the preliminary exploration stage. In this paper, objective psychoacoustic parameters of SQ were taken as evaluation indexes of interior PEV noise. A virtual interior SQ synthesis model was designed on the basis of TPA and TPS, which combines experimentation and simulation. The SQ synthesis model demonstrates each noise component contribution in a PEV by new SQ separation technology. First, the interior noise transfer path and noise source of the PEV were determined in a synthesis analysis method of the interior PEV noise. Second, on the basis of the composition mechanism of interior noise and the basic principle of TPA, the excitation signal and transfer function of each interior noise path in the PEV were tested. On the basis of TPS, the interior SQ synthesis model of PEV was then established. Finally, the accuracy of the prediction model was verified in simulation and experimental comparison studies on the psychoacoustic objective parameters of SQ. The SQ objective parameter value of each transfer path was quantified by using contribution analysis. The results are expected to improve the comfort of the interior acoustic environment and enhance the competitiveness of vehicle products. They also provide an effective reference and new ideas for the development of interior SQ in PEVs.

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Section: Structure-borne Noise Transfer Function Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis

et al. 2021

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“…The evaluation of sound quality includes two parts: objective evaluation and subjective evaluation of sound samples. The loudness, sharpness, and clarity of sound all have an impact on sound comfort, so scholars have put forward many objective evaluation parameters of sound quality by considering acoustic physical parameters such as sound pressure, frequency, and other characteristics of human auditory perception such as characteristic frequency band and auditory masking effect [4,5]. Common objective evaluation parameters of sound quality include loudness, roughness, sharpness, etc.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Adaptive PSO-ELM Algorithm Applied to Vehicle Sound Quality Prediction

Wang,

Yang,

et al. 2023

Applied Sciences

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When dealing with specific tasks, the hidden layer output matrix of an extreme learning machine (ELM) may change, largely due to the random assigned weight matrix of the input layer and the threshold matrix of the hidden layer, which sequentially leads to the corresponding change to output weights. The unstable fluctuations of the output weights increase the structural risk and the empirical risk of ELM. This paper proposed a fuzzy adaptive particle swarm optimization (PSO) algorithm to solve this problem, which could nonlinearly control the inertia factor during the iteration by fuzzy control. Based on the fuzzy adaptive PSO-ELM algorithm, a sound quality prediction model was developed. The prediction results of this model were compared with the other three sound quality prediction models. The results showed that the fuzzy adaptive PSO-ELM model was more precise. In addition, in comparison with two other adaptive inertia factor algorithms, the fuzzy adaptive PSO-ELM model was the fastest model to reach goal accuracy.

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“…The transfer matrix method (or modified transfer matrix method) in conjunction with experimental technique have been developed for analyzing and controlling the vibration and noise transmission of engineering structure, such as the study of the effect of structure-borne or air-borne paths induced interfering noise of a vehicle cab (e.g. braking noise [13] ,road noise [8,14,15] , acceleration noise [16] , sound quality [17] ). With the two time-domain TPA models, Liu [2] found that the models can predict the transient vibration in the door slamming event and the contribution of each transfer path was obtained.…”

Section: Introductionmentioning

confidence: 99%

Analysis and control of vehicle steering wheel vibration based on acceleration transfer path analysis method

Ye,

Wang,

Liu

et al. 2023

Preprint

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This paper is aimed to analyze and control the structure vibration of a vehicle steering wheel by using the acceleration transfer path analysis (TPA) method and vibration sensitivity method. A steering wheel vibration test is conducted to obtain the critical engine speed and corresponding to the frequency. The acceleration-acceleration transfer function from mounts body side to steering wheel is deducted and tested, in conjunction with the actual acceleration spectrums of mounts body side, the acceleration spectrum of steering wheel is synthesized and the accuracy of the synthetic results is evaluated high. Then the vibration transmitted by each path is investigated and the main vibration participation paths are picked out from numerous paths. The interaction mechanisms between the path transfer vibration, path vibration participation and the total vibration are further obtained. The critical parameters (mounting stiffnesses and vibration sensitivity) of the main vibration participation paths are matched, modified and the vibration control effect is experimental verified. The results indicate that, by pertinently matching the stiffness parameters of the mounts and reducing vibration sensitivity of structure, the dynamic force transmitted by the paths are decreased, the vibration transfer functions from mounts body side to steering wheel are decreased, and then the actual steering wheel vibration is controlled.

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Research of transfer path analysis based on contribution factor of sound quality

Cited by 9 publications

References 11 publications

Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis

Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis

Fuzzy Adaptive PSO-ELM Algorithm Applied to Vehicle Sound Quality Prediction

Analysis and control of vehicle steering wheel vibration based on acceleration transfer path analysis method

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