摘要
稳态检测对热工过程非常重要,并在建模、优化和控制中具有广泛的应用。针对热工过程提出一种基于信号分解和统计学理论的稳态检测方法,该方法首先利用经验小波变换（EWT）这一非参数信号分解技术对热工过程信号进行分解,然后进行统计假设检验。在所提出的方法中,首先对采样数据的傅里叶谱特性进行自适应分割以获得热工过程整体运行趋势,通过对中高频信息进行信号重建获得过程的震荡信息。然后通过使用修改过的R统计检验法来对热工过程的稳定性进行检测。最后以某电厂1 000 MW机组协调系统的历史数据进行稳态检测实验,验证了该方法的有效性。
Steady state detection is very important for thermal processes and it is widely used in modeling, optimization and control. In this paper, a steady-state detection method based on signal decomposition and statistical theory is proposed for thermal processes, which utilizes a nonparametric signal decomposition technique named empirical wavelet transform（EWT） to decompose thermal process signal and then conducts a statistical hypothesis test. In the proposed method, firstly, the Fourier spectrum characteristic of the sampled data is adaptively divided to obtain the overall running trend of the thermal process, and the oscillation information of the process is obtained by performing signal reconstruction on the intermediate-high frequency information. The modified R-statistic test method is used to test the stability of the thermal process. Finally, a steady-state detection experiment was conducted with the historical data of the 1 000 MW unit coordinated control system in a certain power plant, which verifies the effectiveness of the proposed method.
作者
贾昊
董泽
闫来清
Jia Hao;Dong Ze;Yan Laiqing(Hebei Engineering Research Center of Simulation ＆ Optimized Control for Power Generation（North China Electric Power University）,Baoding 071003,China;School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2018年第10期150-157,共8页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(71471060)
中央高校基本科研业务费专项资金(2018QN096)项目资助
关键词
稳态检测
经验小波变换
R统计检验法
趋势提取
steady-state detection
empirical wavelet transform
R-statistic test method
trend extraction
