研究了液发推力室和涡轮泵故障监测与诊断技术，介绍了取得的主要研究成果，内容包括：试车结果统计与故障特性分析、故障模式与影响分析、故障数据库的设计与实现、状态分类与特征分析等．此外也介绍了基于人工神经网络理论的动态过程监测与诊断算法、基于时序分析的稳态过程监测与诊断算法和基于频谱方法的事后故障分析与诊断等故障监测与诊断算法．最后，介绍了所研制的工程应用系统，并给出了具体的故障监测与诊断实例 The main research results are summarized, including: statistical analysis of test results and analysis of fault characteristics, analysis of fault modes and effects, design and implementation of fault database, state classification and fault diagnosis, Feature analysis and more. In addition, the dynamic process monitoring and diagnosis algorithm based on artificial neural network theory, the steady state process monitoring and diagnosis algorithm based on time sequence analysis and the fault monitoring and diagnosis algorithm based on spectrum method afterwards are also introduced. Finally, the engineering application system developed is introduced, and examples of fault monitoring and diagnosis are given