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在柴油发动机气缸压力的识别过程中 ,针对缸盖振动信噪比较低的问题 ,提出了对 RBF网络训练样本进行时域统计平均降噪的方法 ,同时在对燃烧始点的辨识中应用了 Kaiser差分器。时域统计平均有效提高了信号的信噪比 ,对柴油发动机气缸压力的恢复获得了很好的结果 ;Kaiser差分器有效提高了对燃烧始点的辨识。通过实践证明 ,该计算方法可以有效地从柴油发动机缸盖振动信号恢复气缸压力 ,并进一步辩识燃烧始点。
In the process of diesel engine cylinder pressure identification, aiming at the low signal-to-noise ratio of cylinder head vibration, a method of time-average statistical noise reduction for RBF network training samples is proposed. At the same time, Kaiser Differentiator. The time-domain statistic effectively improves the signal-to-noise ratio of the signal, and obtains good results for the recovery of the cylinder pressure of the diesel engine. The Kaiser differential effectively improves the identification of the starting point of the combustion. It is proved by practice that the calculation method can effectively recover the cylinder pressure from the vibration signal of diesel engine head cover and further identify the starting point of combustion.