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投稿时间：2020-10-26
投稿时间：2020-10-26
中文摘要: 为提高电厂引风机故障预警的准确性，提出了一种基于多元状态估计技术（MSET）和偏离度函数法的引风机故障预警方法。通过引风机正常运行状态下的多变量数据，建立了MSET模型，得到了模型运算的最优估计值。利用偏离度函数判断出实际值与最优估计值之间的偏离度，较直观地反映出故障发展过程。应用该方法对华能浙江某热电厂引风机的故障问题进行了验证，结果表明，该方法能够及时发现引风机的异常，实现引风机的故障预警。
Abstract:In order to improve the accuracy of the fault warning of the induced draft fan in the power plant, a method based on multivariate state estimation technology (MSET) and deviation degree function for the early warning of induced draft fan failure is proposed.The MSET model is established based on the multivariate data under the normal operation of the induced draft fan, and the optimal estimated value calculated by the model is obtained.The deviation degree between the actual value and the optimal estimated value is judged by the deviation degree function, which can intuitively reflect the failure development process.The sliding window method is used to determine the fault warning threshold.Once the deviation exceeds this threshold, an alarm will be issued to inform the staff to solve the problem.The fault problem of the induced draft fan of a thermal power plant in Huaneng Zhejiang is proven with this method.The research results show that this method can detect the abnormality of the induced draft fan in time and realize the early warning of the induced draft fan failure.
keywords: plant induced draft fan multivariate state estimation technology deviation degree function sliding window method fault early warning
文章编号：20212004 中图分类号：TK228 文献标志码：
基金项目:
引用文本：
常志,鲍克勤,傅望安.基于MSET的电厂引风机故障预警[J].上海电力大学学报,2021,37(2):121-126.
CHANG Zhi,BAO Keqin,FU Wang'an.MSET-Based Early Warning of Power Plant Induced Draft Fan Failure[J].Journal of Shanghai University of Electric Power,2021,37(2):121-126.
常志,鲍克勤,傅望安.基于MSET的电厂引风机故障预警[J].上海电力大学学报,2021,37(2):121-126.
CHANG Zhi,BAO Keqin,FU Wang'an.MSET-Based Early Warning of Power Plant Induced Draft Fan Failure[J].Journal of Shanghai University of Electric Power,2021,37(2):121-126.