通过对故障模拟实验结果的分析，进一步建立起供热管网故障诊断的系统专家知识库。
The expert KBS of heating pipe network failure diagnosis system was established via the results of failure simulating experiments.
绕过传统的通过求解微分方程确定温度的方法，利用人工神经网络来预测管网系统的终端温度，从而为供热管网终端泄漏诊断提供参考依据。
The artificial neural network method was used to anticipate the terminal temperature of the heat pipe network, and the diagnosis can accord to the anticipation result.
为建立供热管网的在线优化运行、故障实时诊断以及仿真分析和培训系统，必须建立一种高精度的蒸汽供热管网动态仿真模型。
An accurate steam heating network simulation model is necessary to build a optimal system for realtime default detection and for analysis and training.
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