应用灰色系统理论对叉车声品质分析与预测建模

Sound Quality Analysis and Prediction Modeling of Forklift Trucks Based on Grey System Theory

为了研究灰色系统理论在声品质预测建模方面应用的有效性,对5款3吨位叉车在怠速和额定转速工况下的30个车内外辐射噪声样本进行了研究。以烦躁度为主观评价指标,采用等级评分法进行了主观评价实验。运用Artemi S软件分析计算了主要心理声学客观参数。选取了响度、尖锐度、粗糙度和抖动度为主要分析对象;运用灰色系统理论算法分析了烦躁度与心理学客观参数的相关性,得到各相关系数。证明了所取心理学客观参数与烦躁度之间具有较高的相关性。基于灰色系统理论的GM(0,N)模型,建立了烦躁度的预测模型,并对预测模型进行了误差检验。结果表明基于灰色系统理论所建立的烦躁度预测模型具有较高的精度,即预测值能够较接近人的主观感受。

To discuss the application effectiveness of grey system theory in sound quality prediction modeling, 30 radiation noise samples of 5 different 3 tonnage forklifts under the conditions of idle and rated speed were taken as the research object, and subjective evaluation experiment was carried out with grading method taking annoyance as subjective evaluation index;the primary objective psychology acoustical parameters were calculated with ArtemiS, and the loudness, sharpness, roughness and fluctuation were selected as the main analysis object;by using the grey system theory, the correlation between the annoyance and the objective parameters of psychology was analyzed, and the correlation coefficient was obtained;it was proved that the correlation between the objective parameters and the annoyance was high.Based on the GM（0,N） model of grey system theory, the prediction model of annoyance was established, and the error test of the prediction model was carried out;results showed that the prediction model based on grey system theory had higher accuracy, that was to say and the prediction of value was more close to human＆#39;s subjective feelings.