摘要
失火故障是柴油机典型频发故障之一,将导致机组做功能力降低、性能下降、运行平稳性变差;机组满负荷状态发生失火故障将会导致机组超负荷,不及时发现将产生较大危害甚至危险。柴油机缸盖振动蕴含大量缸内燃烧状态信息,但易受负荷工况的影响,一般需考虑工况变化才能获得较高的准确率。通过对柴油机缸盖振动信号的深入分析,从对比两个上止点冲击振动的角度,利用VMD对非平稳信号自适应降噪的优势和Teager能量算子识别瞬态冲击的能力,提出能够很好地表征缸内爆燃状态且基本不受工况影响的无量纲特征,可以避免工况识别的困难,并有效提高失火故障诊断准确性。现场实际工程案例验证了方法的有效性,为失火故障诊断提供了一条新的特征提取思路和具体诊断方法。
Misfire failure is one of the typical failures of diesel engines,which will result in functional capacity reduction,performance degradation and poor operation stability.In the full load operation condition,it will cause the diesel engine unit overload.Misfire may cause a major failure even danger if it can’t be discovered in time.The cylinder head vibration of the diesel engine contains abundant information of combustion condition,but it is susceptible to the load condition.Generally,it is necessary to consider the change of the conditions in order to obtain higher accuracy.In this paper,vibration signal of the cylinder head is deeply analyzed.The angles of the impact vibrations of the two top dead centers are compared.Employing the advantage of the VMD in adaptive noise reduction for non-stationary signals and the ability of the Teager energy operator in recognizing the transient shocks,the dimensionless feature is proposed,which can accurately characterize the deflagration state inside the cylinder and is essentially unaffected by the operating conditions.Meanwhile,this approach can avoid the difficulty of condition identification and improve the misfire diagnostic accuracy.The actual engineering case proves the effectiveness of the proposed method.This study provides a new feature extraction method and specific diagnosis method for misfire diagnosis.
作者
霍柏琦
茆志伟
张旭东
张进杰
HUO Baiqi;MAO Zhiwei;ZHANG Xudong;HANG Jinjie(PLA Troop 92942,Beijing 100161,China;Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education,Beijing 100029,China;Beijing Key Laboratory of High-end Mechanical Equipment Health Monitoring and Self-recovery,Beijing 100029,China)
出处
《噪声与振动控制》
CSCD
2020年第1期65-68,190,共5页
Noise and Vibration Control
基金
国家重点研发计划资助项目(2016YFF0203305)
中央高校基本科研业务费专项资金资助项目(JD1912/ZY1940)
双一流建设专项经费资助项目(ZD1601)
