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在柴油机技术状态监测时,表征其技术状态的特征参数有很多,合理提取状态主元信息是一项关键的任务。分析研究了人工神经网络的信息提取原理和方法。以某型坦克柴油机为例,通过柴油机性能检测试验测取了能够反映柴油机技术状态变化的典型特征,建立了O ja神经网络信息提取模型,提取了柴油机技术状态的主元信息。分析结果表明:提取的主元信息能够反映柴油机技术状态随柴油机使用时间的变化趋势。该方法为坦克柴油机的技术状态监测与故障诊断提供了有效手段。
In the monitoring of diesel engine technology status, there are many characteristic parameters to characterize its technical status. It is a key task to reasonably extract the status of the main element information. Analyzed the artificial neural network information extraction principle and method. Taking a tank diesel engine as an example, typical characteristics reflecting the change of technical status of diesel engine were measured by diesel engine performance test. The information extraction model of Oja neural network was established, and the principal component information of diesel engine technology status was extracted. The analysis results show that the extracted main element information can reflect the changing trend of diesel engine technology status with the diesel engine usage time. The method provides an effective measure for the technical condition monitoring and fault diagnosis of tank diesel engine.