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Empirical Prediction of Workshop Fitting Densities for Noise Prediction by Ray Tracing

机译:通过射线追踪进行噪声预测的车间装配密度的经验预测

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摘要

Empirical models were developed for predicting frequency-varying fitting densities in industrial workshops for use in the prediction of noise levels by a ray-tracing model. Eleven typical workshops with varying dimensions, types, quantities and distributions of fittings, in which octave-band sound-propagation curves and the fitting dimensions had been measured, were involved. The workshops were modeled and sound-propagation curves were predicted for a range of fitting densities. The predicted curves were compared with the measured curves to determine the 'best-fit' fitting density. Linear-regression analysis was then used to find empirical models for predicting the best-fit fitting densities from physical parameters calculated from the fitting and workshop dimensions. The average fitting-to-workshop height ratio, the fitting-to-workshop volume ratio and the number of fittings were the parameters that predicted the fitting density best. Preliminary validation work, involving the comparison of sound-propagation curves predicted with the empirically-predicted fitting densities by ray tracing and the curves measured in four other workshops, suggests that the empirical models are inherently valid.
机译:开发了经验模型来预测工业车间中频率变化的装配密度,以通过射线追踪模型预测噪声水平。参加了11个具有不同尺寸,类型,数量和配件分布的典型车间,其中测量了八度音传播曲线和配件尺寸。对讲习班进行了建模,并预测了一系列拟合密度下的声音传播曲线。将预测曲线与测量曲线进行比较,以确定“最佳拟合”拟合密度。然后,使用线性回归分析来找到经验模型,以根据根据装配和车间尺寸计算出的物理参数预测最合适的装配密度。平均配件与车间的高度比,配件与车间的体积比和配件数量是最能预测配件密度的参数。初步的验证工作包括比较通过射线追踪和经验预测的拟合密度预测的声音传播曲线以及在其他四个研讨会上测量的曲线,这表明经验模型具有内在的有效性。

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