摘 要：针对柴油机颗粒捕集器功能失效的问题，应用GT-SUITE软件对柴油机颗粒捕集器进行仿真分析，研究颗粒捕集器温度、压降和碳烟浓度等与其状态的关联关系，并采用一维卷积神经网络对颗粒捕集器状态特征“自学习”,提高颗粒捕集器状态辨识的准确度。
关键词：柴油机；颗粒捕集器；故障特征；状态辨识
中图分类号：TK421+.5 文献标志码：A 文章编号：1006-3331(2022)02-0036-05
Study on State Identification of Diesel Engine DPF Based on Convolutional Neural Network
CHENG Dexin,ZHAO Shu'en,ZHANG Jun,WANG Xinwei,HU Chaochao
Abstract: According to the failure problem of the diesel particulate filter function,the authors simulate and analyze the diesel engine DPF through GT-SUITE software and study the relationship between the DPF state with its temperature,pressure drop,and soot concentration.Then,they improve the accuracy of DPF state identification through applying the one-dimensional convolutional neural network self-learning the state features.
Key words: diesel engine; DPF; fault characteristics; state identification
