基于自我调节学习的柴油机故障诊断研究  

Diesel Engine Fault Diagnosis Based on Self-regulated Learning

作　　者：张翠侠[1] 

机构地区：[1]宿州学院,安徽宿州234000

出　　处：《河北北方学院学报（自然科学版）》2012年第4期30-32,37,共4页Journal of Hebei North University:Natural Science Edition

基　　金：宿州学院硕士科研启动基金项目(批准号2009YSS06);国家自然科学基金资助项目(60864003)

摘　　要：针对柴油机故障原因和故障征兆之间非线性、多变量和模糊的关系,结合柴油机故障实际运行情况和大量专业人员经验知识,提出了一种基于自我调节学习的柴油机故障诊断方法,建立基于灰靶理论的故障诊断模型,利用实时反馈的更新自我调节柴油机故障统计数据和专业人员经验知识构造柴油机故障征兆标准模式,通过对故障征兆和诸故障原因靶心距排序,诊断出柴油机故障的原因并及时维修,反馈更新后再实时自我调节学习故障征兆标准模式。应用结果证明了其实用性和有效性,为同类故障诊断提供了一个新的思路。Aiming at nonlinear,multivariable and fuzzy relationship between diesel engine fault causes and fault symptoms,a diesel engine fault diagnosis method based on self-regulated learning was proposed combining the practical operation of diesel engine fault with lots of professional knowledge and experience.Firstly,fault diagnosis model based on gray target theory was bulit,and then diesel engine fault signs standard mode was constructed using diesel engine fault statistics and professional knowledge.Finally,the reason for a diesel engine failure was diagnosed and repaired timely through sorting bull＇s-eye distance of the fault symptoms and the fault causes,and self-regulated learning fault symptom standard mode after feedback and update.Its practicability and validity had been indicated by its application result,providing a new way of thinking for the same fault diagnosis.

关 键 词：柴油机 故障诊断 自我调节 灰靶理论 

分 类 号：TK427[动力工程及工程热物理—动力机械及工程] TK428