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The statistical properties of raw knock signal time histories

机译：原始爆震信号时间历史的统计特性

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Traditional processing of knock signals reduces each recorded time history to a single sca-lar knock intensity metric for each engine firing, thereby losing all information relating to the phasing and evolution of knock over the combustion period. In this work, a statistical analysis of raw knock cylinder pressure and accelerometer signal time histories has been performed showing how the nonstationary stochastic characteristics of these signals evolve as a function of crank angle, and as a function of spark timing. The data are shown to closely approximate a cyclically independent process whose 2-dimensional covariance function captures both the non-stationary deterministic processes taking place within a cycle as well as the stationary random variations from one cycle to the next. A (time-varying) dual-Gaussian model for the distribution of these cyclic variations was fitted to the data, thereby enabling them to be characterized as the sum of knocking and non-knocking populations. The parameters of the model, which describe these populations sep-arately, provide further empirical insight into the knock process.
机译：爆震信号的传统处理将每个录制的时间历史减少到每个发动机射击的单个SCA-LAR敲击强度度量，从而丢失与燃烧时段的敲打和演变有关的所有信息。在这项工作中，已经进行了对原始爆震缸压力和加速度计信号时间历史的统计分析，示出了这些信号的非间接随机特性如何随着曲柄角的函数而发展，以及作为火花正时的函数。该数据被示出为密切地近似于循环独立的过程，其二维协方差函数捕获在循环内发生的非静止确定性过程以及从一个循环到下一个周期的固定随机变化。用于分布这些循环变化的（时变）双高声模型被装配到数据，从而使它们表征为爆震和非敲击群体的总和。模型的参数，它描述了这些人群的SEP-artely，为爆震过程提供了进一步的实证洞察。

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