中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (1): 85-91.doi: 10.16265/j.cnki.issn1003-3033.2022.01.012

• 安全工程技术 • 上一篇    下一篇

基于广义极值分布的流化床压力波动风险预警

张进春(), 陈昕, 张文俊, 吴士龙   

  1. 河南理工大学 能源科学与工程学院,河南 焦作 454000
  • 收稿日期:2021-10-25 修回日期:2021-12-14 出版日期:2022-01-28 发布日期:2022-07-28
  • 作者简介:

    张进春(1978—),男,河南浚县人,博士,副教授,主要从事能源装备可靠性分析与风险管理等方面的研究。E-mail:
    张进春 副教授

  • 基金资助:
    国家自然科学基金资助(51774113); 河南省科技攻关项目(172102210288); 河南省高等学校重点科研项目(15B410001)

Risk warning of pressure fluctuation in fluidized beds based on generalized extreme value distribution

ZHANG Jinchun(), CHEN Xin, ZHANG Wenjun, WU Shilong   

  1. School of Energy Science and Engineering, Henan Polytechnic University, Jiaozuo Henan 454000,China
  • Received:2021-10-25 Revised:2021-12-14 Online:2022-01-28 Published:2022-07-28

摘要:

为预警气泡运动所引起的流化床粉煤气化压力波动风险,提出预测压力波动极值以及压力波动重现水平的方法;首先采用自相关分析法将压力波动母样本数据合理分段,再用区间极值法统计子样本的压力波动极值数据,以广义极值(GEV)分布方法建立GEV分布模型和Gumbel分布模型,并经过模型诊断选择最优模型;然后通过子样本与母样本的参数关系得到母样本极值分布参数,进而基于母样本极值分布参数得到压力波动极值的期望值;最后以母样本极值分布参数为中心进行贝叶斯推断,得到压力波动的重现水平。结果表明:采用GEV分布法得到的估计极值误差率控制在±10%以内,平均误差率控制在-1.7%~3.7%以内;有95%的信心认为压力波动重现水平将处于置信区间内。

关键词: 流化床, 压力波动, 广义极值(GEV), 风险预警, 重现水平

Abstract:

In order to forewarn pressure fluctuation risks of pulverized coal gasification in fluidized beds caused by bubble movement, a method to predict extreme value and return level of pressure fluctuation was proposed. Firstly, pressure fluctuation data of parent sample were segmented reasonably by autocorrelation analysis method, and interval extreme value method was employed to calculate extreme value data for sub-samples. Secondly, GEV distribution model and Gumbel distribution model were established through GEV distribution method, and an optimal model was selected by model diagnosis. Then, extreme distribution parameters of parent sample were obtained from parametric relationship between it and sub-samples, and expected value of extreme pressure fluctuation was acquired based on extreme value distribution parameters of parent sample, from which, return level of pressure fluctuation was also obtained by Bayesian inference. The results show that the error rate of extreme value obtained by utilizing GEV distribution is controlled within ±10%, with its average error rate within -1.7%-3.7%. It can be believed with 95% confidence that return level of pressure fluctuation will be maintained within confidence interval.

Key words: fluidized bed, pressure fluctuation, generalized extreme value (GEV), risk warning, return level