基于高维小波神经网络的汽车转向操纵舒适性评价
首发时间:2018-05-23
摘要:汽车方向盘的转向助力程度对转向操纵舒适性在人对整车操纵舒适性评价中具有重要意义,但是由于其复杂性和主观性等因素的影响,汽车方向盘转向操纵舒适性评价成为汽车企业和研究所的一个技术难题?针对目前汽车方向盘的转向操纵舒适性评价方法的不足,提出一种基于高维小波神经网络的汽车转向操纵舒适性评价,通过高维小波神经网络对实验的测得的人体基本参数和表面肌电信号数据参数形成的转向操纵舒适性评分构成的样本进行学习和训练,建立汽车方向盘转向操纵舒适性评价。实验结果验证了该方法的可行性和合理性?
关键词: 转向操纵舒适性;高维小波神经网络;表面肌电信号时频域特征参数
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Vehicle steering comfort evaluation based on high-dimensional wavelet neural network
Abstract:The degree of steering assistance of the steering wheel of a car has important significance in the evaluation of maneuvering comfort of the vehicle for steering comfort, but due to the influence of its complexity and subjectivity, The evaluation of the steering comfort of the steering wheel has become a technical difficulty for automobile companies and research institutes.Aiming at the shortcomings of current steering comfort evaluation method for the steering wheel of a car, a steering wheel steering comfort evaluation based on high dimensional wavelet neural network is proposed. The high-dimensional wavelet neural network is used to learn and train the comfortableness scores of the parameters of the steering comfort data measured by the experiment and the samples formed by human subjective comfort evaluation during steering, and the steering comfort of the steering wheel is evaluated. The experimental results verify the feasibility and rationality of the method.
Keywords: Steering comfort Wavelet wavelet neural network Time-frequency domain feature parameters of sEMG signals
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