基于动态模型的磨机健康指标构建及应用

IF 5.7 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Weiming Yin, Yefa Hu, Guoping Ding, Wen-bin Xu, Lei Feng, Xue-liang Chen, Xifei Cao
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引用次数: 0

摘要

煤机作为燃煤电厂的重要辅机,其运行状态的实时监控对电厂的安全稳定运行至关重要。本文提出了一种新的煤机健康指标构建方法,并设计了基于健康指标的设备运行状态监测方法。首先,建立了考虑干燥力、通风力和磨矿力共同影响的改进磨机动力学模型,设计了基于遗传算法的模型结构和参数同步优化方法;然后利用设计的距离测量方法计算模型输出与实际值之间的偏差,并根据动态模型与实际运行状态的关系设计典型故障特征因子。将偏差与特征因子融合计算出HI值。最后,将HI值应用于运行状态评价、故障诊断和趋势预测过程中,取得了良好的应用效果。研究结果表明,所建立的HI值能及时、准确地反映磨机的运行状况,基于该值设计的监测方法具有较好的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health indicator construction and application of coal mill based on the dynamic model
As the vital auxiliary machine of the coal-fired power plant, monitoring the real-time operating status of coal mills is critical to the secure and stable operation of the power plant. In this study, a new method of construction of the coal mill health indicator (HI) is proposed, and the operation condition monitoring approaches of the device are designed based on the HI value. Firstly, an improved coal mill dynamic model considering the joint influence of drying force, ventilation force, and grinding force is established, and a synchronous optimization approach of model structures and parameters based on the genetic algorithm is designed. Then the deviation between the model output and the actual value is computed by the designed distance measuring approach, and the typical fault characteristic factors are designed based on the relation between the dynamic model and the actual operating state. And the HI value is calculated by fusing the deviation with the characteristic factors. Finally, the HI value is applied to the process of operation condition evaluation, fault diagnosis, and trend prediction, and has obtained favorable application effects. The results of this research show that the established HI value can reflect the operating status of the coal mill promptly and accurately, and the monitoring method designed based on the values have satisfactory practicality.
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来源期刊
CiteScore
12.80
自引率
12.10%
发文量
181
审稿时长
4.8 months
期刊介绍: Structural Health Monitoring is an international peer reviewed journal that publishes the highest quality original research that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.
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