摘要
针对核动力装置故障和对应征兆繁多的特点,并克服传统遗传算法进行故障诊断的固有缺陷,提出了一种基于改进遗传算法和概率因果模型的故障诊断技术,构建了诊断系统。该系统主要由数据采集模块和故障诊断模块构成,具有诊断实时性强、计算速度快的特点。为验证系统的有效性,对蒸汽发生器进行了故障诊断,测试结果与相关文献结论吻合。最后还与传统遗传算法进行了比较,表明改进后的遗传算法可有效避免误诊、漏诊现象,诊断准确率较高。
Aimed at the characteristics of marine nuclear power plant that fault and corresponding sign are various, and in order to overcome inhere problem of traditional genetic algorithm, improved genetic algorithm and probability causal model were integrated to establish fault diagnosis system. The system is made up of data collection module and fault diagnosis module with high real time and speed. To validate the system, stream generator was diagnosed, and the computation result is in agreement with conclusion of some literature. At last, the comparison with tradition arithmetic was made. The results indicate that with improved genetic algorithm, mistaken diagnosis is improved effectively, and accuracy of fault diagnosis is enhanced.
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2012年第11期1357-1361,共5页
Atomic Energy Science and Technology
基金
海军医学研究所基金资助项目(12HY21)
