摘要
通过对机械设备润滑油的长期光谱跟踪检测分析,建立基于光谱分析的润滑油状态监测故障诊断数学模型。通过实验研究和机械设备润滑油油样的实际光谱检测分析相结合,根据不同机械设备的磨损特征元素确定机械设备基于油液检测光谱分析故障诊断的特征参数,以确定机械设备发生故障的时间,从而避免重大故障的突发,为机械设备实现视情维修提供理论和实际依据,提高机械设备的可靠性和可维修性。故障诊断实例证明,此特征参数具有较高的稳定性和准确性,能够有效地应用于各种机械设备的油液检测的故障诊断中。
This paper establishes a new mathematics model of fault diagnosis basis of oil spectrometric analysis by means of long time following up the mechanical equipment＇s lubrication oil. The characteristic parameter of oil spectrometric analysis has been confirmed using a new way that the laboratory experiment study and the mechanical equipment＇s lubrication oil spectrometric analysis are combined in order to confirm the time of fault and avoid serious fault. It will provide the academic and actual basis for RCM and enhance the dependability. The result of examples proves that the characteristic parameter of oil spectrometric analysis has very high stability and veracity. This method has been proved that it was effective in fault diagnosis basis of oil spectrometric analysis.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2005年第7期1125-1127,共3页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金(50276006)资助项目
关键词
油液检测
光谱分析
特征参数
故障诊断
Oil analysis
Spectrometric analysis
Characteristic parameter
Fault diagnosis
