基于波形和数据流的汽车电控发动机故障诊断与维修研究

Study on Fault Diagnosis and Maintenance of Electronic Control Engine Based on Waveform And Data Flow

为提高汽车电控发动机故障诊断准确性和维修效率,研究基于波形和数据流分析方法。提出了通过多维特征识别与提取、故障诊断模型设计、决策支持专家系统开发进行汽车电控发动机故障高效诊断与维修创新方法,通过对传感器故障、执行机构故障及信号处理与传输故障等常见问题详细分析。研究结果表明,该方法不仅能有效提升故障诊断准确率,还能为维修工作提供更为科学指导,提高了电控发动机维修质量,可优化电控发动机维修流程和诊断效率。

In order to improve the accuracy of fault diagnosis and maintenance efficiency of automobile electric control engine,the analysis method based on waveform and data flow is studied.This paper puts forward the innovative methods of efficient diagnosis and maintenance of electronic automobile control engine faults through multi-dimensional feature identification and extraction,fault diagnosis model design and decision support expert system development,and analyzes the common problems such as sensor fault,actuator fault and signal processing and transmission fault in detail.The results show that this method can not only effectively improve the accuracy of fault diagnosis,but also provide more scientific guidance for maintenance work,improve the maintenance quality of electronic controlled engine,and optimize the maintenance process and diagnosis efficiency of electronic controlled engine.