Abstract:

Fault diagnosis is an important technique to ensure chemical processes stability and safety.A fault diagnosis methodology is proposed in this paper for batch chemical processes based on artificial immune system (AIS) and dynamic time warping (DTW) algorithm.Its application to a simulated penicillin fermentation process demonstrated that the proposed AIS could meet the requirement of online dynamic fault diagnosis of batch processes and diagnose new faults through self-learning.

Key words:

人工免疫系统, 间歇化工过程, 故障诊断, 动态时间规整, 自学习

摘要：

故障诊断是保证化工过程稳定性和安全性的重要技术。本文结合动态时间规整算法提出了一个基于人工免疫系统的间歇化工过程故障诊断方法，并成功应用于青霉素发酵仿真过程的故障诊断。诊断结果显示，该方法可以满足间歇过程的在线动态故障诊断要求，并且通过自学习可以对未知故障进行诊断。

关键词:

人工免疫系统, 间歇化工过程, 故障诊断, 动态时间规整, 自学习