基于人工神经网络的柴油机排气消声器设计-农业机械化工程专业论文.docxVIP

摘 摘 要 (噪声水平已成为衡量柴油机质量和性能的重要指标之～。排气噪声在柴 油机整机噪声中占重要比例，安装性能良好的排气消声器是控制排气噪声的 有效途径。为了克服目前排气消声器一般设计方法固有的建模假定引起的设 计误差，j，本论文尝试将人工神经网络应用于排气消声器设计问题。为了深入 考察消声器结构参数对排气噪声频谱的影响，自主开发设计了噪声数字信号 采集系统和l／3倍频程FIR数字滤波器。利用正交试验和排气噪声数字信号 处理获得了频段内声压级和柴油机燃油消耗率作为输入、结构参数作为输出 的人r利。经网络的学习样本。通过MATLAB中人工神经网络工具箱完成了网 络的训练。哄例验证了人工神经网络应用于排气消声器设计是完全可行的； 同时，通过训练后网络的具体应用，展示了人工神经网络在消声器设计方面 的优越性。太 关键词：柴油机?排气噪声i消声器，’数字信号；数字滤波：人工神经网络 AbstractThe Abstract The noise level of diesel engine has become one of important indicators on evaluation of its quality and performances．Exhaust noise is a large proportion in the overall noise of diesel engine，and the effective method of its control is the application of muffler with good performances．In this paper,ANN was applied to the muffler design with the efforts to reduce the intrinsic error that was caused by the assumption on which the muffler’S acoustic model was based．In order to deeply research the effect of structural parameters on the spectrum of exhaust noise，the author designs a system to sample the exhaust noise and 1／3 FIR octave-band filters to calculate the spectrum of the sampling—data．By the means of orthogonal planning and digital signal processing，the learning—samples were obtained The learning-samples’inputs were the sound pressure levels of 1／3 octave—bands and the specific fuel consumption of diesel engine，and its outputs were the structural parameters of muffler．Through the Neural Networks Toolbox of MATLAB，the training of an ANN was finished．The practicability of application of ANN in the muffler design was perfectly proved by the practical examples，meanwhile the application of the trained—network shows that ANN has many advantages in this area Keywords：diesel engine，exhaust noise，muffler,digital signal，digital filter, artificial neural network 第1章绪论1．1 第1章绪论 1．1 引言 由于柴油机具有燃料经济性好、可靠性高和有害排放物相对较低等优 点，它已在各个领域得到广泛应用。但随着人们环保意识的不断增强，由 它引起的噪声污染日益受到重视。噪声水平己成为衡量柴油机质量和性能 的重要指标之一。排气噪声在柴油机整机噪声中占重要比例Ⅲ，所以柴油机 排气噪声控制在柴油机降噪措施中占重要地位。 随着电子技术迅速发展，排气噪声控制出现了电