CAJ | 학술논문

为保障核电站安全经济运行，需及时准确地识别核电站出现的异常。本文通过处理关键变量的时间序列数据，对瞬态过程进行识别：利用模糊熵度量时间序列复杂度的能力，判断系统是否处于正常状态；进而利用互模糊熵度量两时间序列相似度的能力，对出现的瞬态进行类型识别。利用模块式高温气冷堆核电站仿真机的数据验证了本方法的可行性和有效性，结果表明本文方法可有效进行瞬态识别，且不需复杂的训练过程。
위보장핵전참안전경제운행，수급시준학지식별핵전참출현적이상。본문통과처리관건변량적시간서렬수거，대순태과정진행식별：이용모호적도량시간서렬복잡도적능력，판단계통시부처우정상상태；진이이용호모호적도량량시간서렬상사도적능력，대출현적순태진행류형식별。이용모괴식고온기랭퇴핵전참방진궤적수거험증료본방법적가행성화유효성，결과표명본문방법가유효진행순태식별，차불수복잡적훈련과정。
For safe and economical operation of nuclear power plants (NPPs) ,the occur-ring anomalies should be promptly and correctly identified .In this paper ,the transients were identified by processing time series of critical variables .First ,based on its ability to measure the complexity of time series ,the fuzzy entropy (FuzzyEn) was used to determine whether the system was in normal state . Then cross fuzzy entropy was employed for classifying the occurring transients , using its ability to characterize the similarity between two time series .The feasibility and effectiveness were verified by simulator data of pebble-bed modular high temperature gas-cooled reactor nuclear power plant (HTR-PM ) .It is demonstrated that the proposed method is effective for transient identification and it dispenses with a complex training phase .