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A Novel Inverse Filtering Method for Systems with Multiple Input Signals (ICCAS 2018)

机译:一种用于多输入信号系统的新型逆滤波方法(ICCAS 2018)

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摘要

The initial motivation of this paper is the multiple cylinder pressure (CP) signals estimation in modern engines using inverse filtering. Inverse filtering is a common method for input signal estimation of single-input (SI) systems while there exist some problems estimating inputs of multiple-input (MI) systems if the output number is less than the input number, such as ill-conditioned inversion of the transfer function matrix. To deal with these problems, in this paper we introduce a novel inverse filtering approach for MI systems by converting a MI system into a SI system using delay systems and afterwards using the Kalman filter to estimate the inputs. However, it requires that the input signals have to be periodic in angle domain with same shapes, and there has a fixed and known phase difference between every two adjacent signals. These requirements are reasonable and practical for many kinds of signals in rotating machineries, e.g., the CP signals of different cylinders in an engine under stationary conditions. Finally, numerical simulations were carried out to demonstrate the performance of the proposed inverse filtering algorithm.
机译:本文的初始动机是使用逆滤波的现代发动机多缸压力(CP)信号估计。逆滤波是用于单输入(SI)系统的输入信号估计的一种常用方法,而如果输出数小于输入数,则存在估计多输入(MI)系统的输入的一些问题,例如病态反演。传递函数矩阵为了解决这些问题,在本文中,我们介绍了一种针对MI系统的新型逆滤波方法,该方法是通过使用延迟系统将MI系统转换为SI系统,然后再使用Kalman滤波器来估计输入。然而,这要求输入信号必须在角域中具有相同形状的周期性,并且在每两个相邻信号之间具有固定的已知相位差。这些要求对于旋转机械中的多种信号是合理且实用的,例如,在固定条件下发动机中不同气缸的CP信号。最后,通过数值仿真证明了所提出的逆滤波算法的性能。

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