Li Fan, Upadhyaya Belle R, Coffey Lonnie A
Department of Nuclear Engineering, University of Tennessee, Knoxville, TN 37996-2300, USA.
ISA Trans. 2009 Apr;48(2):213-9. doi: 10.1016/j.isatra.2008.10.014. Epub 2008 Dec 11.
This paper presents an incipient fault diagnosis approach based on the Group Method of Data Handling (GMDH) technique. The GMDH algorithm provides a generic framework for characterizing the interrelationships among a set of process variables of fossil power plant sub-systems and is employed to generate estimates of important variables in a data-driven fashion. In this paper, ridge regression techniques are incorporated into the ordinary least squares (OLS) estimator to solve regression coefficients at each layer of the GMDH network. The fault diagnosis method is applied to feedwater heater leak detection with data from an operating coal-fired plant. The results demonstrate the proposed method is capable of providing an early warning to operators when a process fault or an equipment fault occurs in a fossil power plant.
本文提出了一种基于数据处理分组方法（GMDH）技术的早期故障诊断方法。GMDH算法提供了一个通用框架，用于描述化石电厂子系统的一组过程变量之间的相互关系，并以数据驱动的方式用于生成重要变量的估计值。本文将岭回归技术纳入普通最小二乘（OLS）估计器中，以求解GMDH网络各层的回归系数。该故障诊断方法应用于利用运行中的燃煤电厂的数据进行给水加热器泄漏检测。结果表明，该方法能够在化石电厂发生过程故障或设备故障时向运行人员提供早期预警。
