论文标题
引擎敲击的统计模拟器
Statistical Simulator for the Engine Knock
论文作者
论文摘要
本文提出了一个基于混合物密度网络（MDN）和接受拒绝方法的发动机敲击的统计模拟器。提出的模拟器可以生成与输入信号相对应的随机敲击强度信号。产生的敲击强度与真实发动机具有一致的概率分布。首先，使用实验数据进行统计分析。从分析结果中，对敲击强度的统计特性进行了一些重要的假设。关于在离散时间索引上作为随机变量的敲击强度，如果发动机的输入相同，则它是独立的，并且相同分布。高斯混合模型（GMM）可以近似敲击强度的敲敲强度的概率分布。 GMM的参数是输入的函数。基于这些假设，制定了两个用于建立统计模拟器的子问题：一个是通过绝对连续函数近似从输入到敲击强度分布的参数的函数；另一个是设计一个随机数生成器，以输出与给定分布一致的随机数据。将MDN应用于近似敲击强度的概率密度，而接受置换算法用于随机数发生器设计。在基于数据的验证中评估了所提出的方法。
This paper proposes a statistical simulator for the engine knock based on the Mixture Density Network (MDN) and the accept-reject method. The proposed simulator can generate the random knock intensity signal corresponding to the input signal. The generated knock intensity has a consistent probability distribution with the real engine. Firstly, the statistical analysis is conducted with the experimental data. From the analysis results, some important assumptions on the statistical properties of the knock intensity are made. Regarding the knock intensity as a random variable on the discrete-time index, it is independent and identically distributed if the input of the engine is identical. The probability distribution of the knock intensity under identical input can be approximated by the Gaussian Mixture Model(GMM). The parameter of the GMM is a function of the input. Based on these assumptions, two sub-problems for establishing the statistical simulator are formulated: One is to approximate the function from input to the parameters of the knock intensity distribution with an absolutely continuous function; The other one is to design a random number generator that outputs the random data consistent with the given distribution. The MDN is applied to approximate the probability density of the knock intensity and the accept-reject algorithm is used for the random number generator design. The proposed method is evaluated in experimental data-based validation.
