基于车内噪声水平的路面预养护指标阈值确定方法研究

为了消除车内噪声对人心理和生理的危害,提出了一种基于车内噪声水平的沥青路面预防性养护指标阈值的确定方法。通过多层前向反馈神经网络构建了车内噪声和国际平整度指数的关系模型;依据噪声分级和危害标准,确定了国际平整度指数指标预防性养护的噪声阈值标准;对比分析了国际平整度指数指标预防性养护的规范阈值标准和噪声阈值标准的养护需求。结果表明,前向反馈神经网络能够较好地根据车内噪声水平预测沥青路面国际平整度指数。噪声阈值标准相对于规范阈值标准,对沥青路面国际平整度指数提出了更高的要求。

Research on Threshold Determination Method of Preventive Maintenance Index for Asphalt Pavement Based on In-vehicle Noise Level

In order to eliminate the harmfulness of noise to people"s psychology and physiology, this paper proposes a method to determine the threshold of preventive maintenance index of asphalt pavement based on the in-vehicle noise level. The multi-layer forward feedback neural network is used to establish the relation model between in-vehicle noise and international roughness index (IRI). The noise threshold standard of preventive maintenance index (IRI) is determined according to noise classification and hazard criteria. Maintenance requirements resulting from the IRI threshold standards based on noise level and the IRI threshold standards based on current guidelines is compared and analyzed. Results show that the forward feedback neural network can predict the international roughness index of asphalt pavement better based on the in-vehicle noise level. Compared with the threshold standard based on current guidelines, threshold standard based on noise level puts forward a higher requirement for the international roughness index of asphalt pavement.