RETRACTED ARTICLE: Research on the virtual reality of vibration characteristics in vehicle cabin based on neural networks

Peng, Jinshuan; Xu, Lei; Shao, Yiming

doi:10.1007/s00521-016-2829-z

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…Zhang et al [20] conducted modal experiments, The obtained body-in-white first-order modal frequencies, roof local modal frequencies and first-order torsional modal frequencies are 18.97 Hz, 29.04 Hz, and 39.42 Hz, respectively. Peng et al [28] calculated that the first-order modal frequency of the body-in-white and the local modal frequency of the roof were 19.62 Hz and 40.1 Hz, respectively. Chen et al [41] obtained the first-order bending modal frequency of the body-in-white and the local modal frequency of the front door are 49.67 Hz and 55.34 Hz, respectively.…”

Section: Modal Analysismentioning

confidence: 99%

“…Zhang et al [27] demonstrated the feasibility for the neural network to optimize noise in a vehicle through the error of the neural network prediction and boundary element calculation values. Peng et al [28] used a BP neural network model to predict the acoustic response characteristics of commercial cabs. Qian et al [29] proposed a GA-BP-based electric vehicle sound quality prediction model, which offers many advantages in accuracy and generalizability.…”

Section: Introductionmentioning

confidence: 99%

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Vehicle Interior Noise Prediction Based on Elman Neural Network

Zhou

Liu

et al. 2021

Applied Sciences

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Vehicle interior noise is an important factor affecting ride comfort. To reduce the noise inside the vehicle at the vehicle body design stage, a finite element model of the vehicle body must be established. While taking the first-order global modal of the body-in-white, the maximum sound pressure level of the target point in the vehicle, the body mass, and the side impact conditions into account, the thickness of the body panel as determined via sensitivity analysis is treated as the input variable, and the sample is determined by following the Hamersley experimental design. Specifically, the Elman neural network predicts the noise value in the vehicle, and a vehicle body structure optimization method that comprehensively considers NVH performance and side impact safety is established. The prediction errors of the Elman neural network algorithm were within 3%, which meets the prediction accuracy requirements. To achieve satisfactory restraint performance, the maximum sound pressure level of the target point in the vehicle is reduced by 5.92 dB, and the maximum intrusions of the two points on the B-pillar inner panel are reduced by 31.1 mm and 33.71 mm, respectively. The side impact performance is improved while the noise inside the vehicle is reduced. This study provides a reference method for multidisciplinary research aiming to optimize the design of vehicle body structures.

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Section: Modal Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Vehicle Interior Noise Prediction Based on Elman Neural Network

Zhou

Liu

et al. 2021

Applied Sciences

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“…Immersion means that any type of computer can build a virtual world based on VR technology. Human-computer interaction indicates that participating users can get corresponding feedback in the virtual world [ 7 , 8 ]. Through the effective simulation of the natural world, VR technology can provide sufficient imagination environment and space for participating users [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Teaching and Curriculum of the Preschool Physical Education Major Direction in Colleges and Universities under Virtual Reality Technology

Wang

Rahman

Hooi

2022

Computational Intelligence and Neuroscience

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The present work aims to study the influence of virtual reality (VR) technology on the teaching and curriculum of preschool physical education in colleges and universities and establish a virtual teaching model suitable for the college teaching system. The classroom teaching situation of using VR technology in physical training of preschool education major direction in colleges and universities is investigated using the questionnaire survey and teaching experiment. Firstly, the feasibility of applying VR technology to teaching is proved by analyzing the relevant education theories. Secondly, the experimental research method is designed to verify the application effect of VR technology in teaching behavior. Finally, the collected data is sorted out to judge the method’s feasibility. The experimental results demonstrate that 88.0% of the respondents are curious about the application of VR, and 88.6% of the respondents can accept the application of VR in sports dance teaching. Besides, 89.1% claimed that VR technology could enhance students’ understanding of knowledge, and 93.0% thought that VR applications would not interfere with teachers’ explanations. In addition, 80.0% thought that virtual teaching could stimulate students’ interest in learning, 75.0% said that VR application could attract students’ attention, and 63.0% believed that VR application could improve learning efficiency. The preliminary investigation suggests that introducing VR technology can reduce the work intensity of teachers, and the students participating in the survey are optimistic about the application of VR technology in preschool physical education. The formal test based on a t-test indicates that the average score of the experimental group is 3.18 points higher than that of the control group, and there are significant differences in technology between the control group and the experimental group. VR technology can improve students’ technical level, enhance self-confidence, and improve students’ grades. To sum up, this study provides a reference for developing virtual teaching mode and applying VR technology to physical education.

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“…Virtual reality (VR), [1][2][3][4][5][6][7][8] as the term suggests, is the simulation of a real environment, or the creation of a fictional world using visual, auditory, tactile, and other stimuli, for a specific purpose. Kim Pallister, the Director of Content Strategy for Intel's Visual Computing Team, vividly describes how VR works by deceiving the senses.…”

Section: Introductionmentioning

confidence: 99%

The environmental navigation using geometric virtual reality

Tsai

et al. 2018

Advances in Mechanical Engineering

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This article explores the construction of a geometric virtual reality platform for the environmental navigation. Nonpanoramic photos and wearable electronics with Bluetooth wireless transmission functions are used to combine the user's actions with the virtual reality environment in a first-person virtual reality platform. The 3ds Max animation software is used to create three-dimensional models of real buildings. These models are combined with the landscape models in Unity3d to create a virtual campus scene that matches real landscape. The wearable device included an ATMega168 chip as a microcontroller; it was connected to a three-axis accelerometer, a gyroscope, and a Bluetooth transmitter to detect and transmit various movements of the user. Although the development of the mechatronics, software, and engineering involved in the three-dimensional animation are the main objective, we believe that the methods and techniques can be modified for various purposes. After the system architecture was created and the operations of the platform were verified, wearable devices and virtual reality scenes are concluded to be able to be used together seamlessly.

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RETRACTED ARTICLE: Research on the virtual reality of vibration characteristics in vehicle cabin based on neural networks

Cited by 6 publications

References 9 publications

Vehicle Interior Noise Prediction Based on Elman Neural Network

Vehicle Interior Noise Prediction Based on Elman Neural Network

Teaching and Curriculum of the Preschool Physical Education Major Direction in Colleges and Universities under Virtual Reality Technology

The environmental navigation using geometric virtual reality

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