应用人工神经元网络进行pH中和过程故障诊断  

Fault diagnosis of pH neutralization process using artificial neural networks

作　　者：邹志云[1] 于德弘[1] 于鲁平[2] 冯文强[2] 郭宁[2] 吴春华[2] 

机构地区：[1]西安交通大学现代设计及转子轴承系统教育部重点实验室,陕西西安710049 [2]防化研究院,北京102205

出　　处：《计算机与应用化学》2008年第2期193-197,共5页Computers and Applied Chemistry

基　　金：国家留学基金项目(21302095)

摘　　要：应用NeurOn-Line神经元网络应用系统开发技术和G2实时智能专家系统开发技术,开发了一套pH中和过程的故障诊断系统。先简单描述了该pH中和过程及其建模,然后详细论述了该故障诊断系统在NeurOn-Line和G2软件平台上的设计和编程开发情况。共进行了pH中和过程的正常运行模式,pH传感器测量值偏高、pH传感器测量值偏低和碱液浓度变稀三种故障模式的仿真和诊断。仿真结果表明该故障诊断系统能快速准确诊断出pH中和过程的正常运行和故障模式。The fault diagnosis system of a pH neutralization process is developed using the hybrid approach of NeurOn-Line neural net- works application and G2 real-time knowledge based intelligent expert system building technology. Firstly, a brief description and modeling of the pH neutralization process is presented. Then the fault diagnosis system is designed and programmed in detail in the NeurOn-Line and G2 environment. Normal operation mode and three fault operation modes of the pH neutralization process including pH sensor biased high, pH sensor biased low, and base reagent diluted is simulated and diagnosed. Simulation results demonstrate that these normal and fault operation modes can be quickly and accurately classified.

关 键 词：故障诊断 神经元网络 PH控制 仿真 实时智能专家系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]