The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines....The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines. The fitted and forecasted results show that the length or inertia of a sequence affects its precision very much, i.e. the bigger the inertia of a sequence is, or the shorter the length of a series is, the less the errors of fitted and forecasted results are. Based on the research results, it is suggested that short series should be applied to be fitted and forecasted; for longer series, the newer datum should be applied instead of the older datum to be analyzed by non- equalinterval GM(1,1) to improve the forecasted and fitted precision, and that data sequence should be verified to satisfy the conditions of grey forecasting.展开更多
The manifold physical signals including micro resistance,infrared thermal signal and acoustic emission signal in the tensile test for double-material friction welding normative samples were monitored and collected dyn...The manifold physical signals including micro resistance,infrared thermal signal and acoustic emission signal in the tensile test for double-material friction welding normative samples were monitored and collected dynamically by TH2512 micro resistance measuring apparatus,flir infrared thermal camera and acoustic emission equipment which possesses 18 bit PCI-2 data acquisition board.Applied acoustic emission and thermal infrared NDT(non-destructive testing) means were used to verify the feasibility of using resistance method and to monitor dynamic damage of the samples.The research of the dynamic monitoring system was carried out with multi-information fusion including resistance,infrared and acoustic emission.The results show that the resistance signal,infrared signal and acoustic emission signal collected synchronously in the injury process of samples have a good mapping.Electrical,thermal and acoustic signals can more accurately capture initiation and development of micro-defects in the sample.Using dynamic micro-resistance method to monitor damage is possible.The method of multi-information fusion monitoring damage possesses higher reliability,which makes the establishing of health condition diagnosing and early warning platform with multiple physical information monitoring possible.展开更多
Oil monitoring constitutes an important and essential component of condition monitoring technologies and has distinguished advantages in revealing wear,lubrication and friction conditions of tribo-pairs.Newly develope...Oil monitoring constitutes an important and essential component of condition monitoring technologies and has distinguished advantages in revealing wear,lubrication and friction conditions of tribo-pairs.Newly developed on-line/in-line oil monitoring technologies extend the merits into real-time applications and demonstrate significant benefits in maintenance and management of equipment.This paper comprehensively reviews the progress of on-line/in-line oil monitoring techniques including sensor technologies,their scopes and industrial applications.Based on the existing developments and applications of the sensors for oil quality and wear debris measurements,the trends for future sensor developments are discussed with focuses on accurate,integrated and intelligent features along with exploring a fundamental issue,that is,acquiring the knowledge on degradation mechanisms which has not received sufficient attention until now.Current status of applications of on-line oil monitoring is also reviewed.Although limited reports have been found on this topic,increasing awareness and encouraging progress in on-line monitoring techniques are recognized in applications such as aircraft,shipping,railway,mining,etc.Key fundamental issues for further extending the on-line oil monitoring techniques in industries are proposed and they include long-term reliability of sensors in harsh conditions,and agreement with fault or maintenance determination.展开更多
文摘The basic difference non-equal interval model GM(1,1) in grey theory was used to fit and forecast data series with non-equal lengths and different inertias, acquired from oil monitoring of internal combustion engines. The fitted and forecasted results show that the length or inertia of a sequence affects its precision very much, i.e. the bigger the inertia of a sequence is, or the shorter the length of a series is, the less the errors of fitted and forecasted results are. Based on the research results, it is suggested that short series should be applied to be fitted and forecasted; for longer series, the newer datum should be applied instead of the older datum to be analyzed by non- equalinterval GM(1,1) to improve the forecasted and fitted precision, and that data sequence should be verified to satisfy the conditions of grey forecasting.
基金Project(51125023) supported by Distinguished Young Scholars of Natural Science Foundation of ChinaProject(2011CB013405) supported by the National Basic Research Program of China+1 种基金Project supported by China Equipment Maintenance ProgramProject (3120001) supported by the Natural Science Foundation of Beijing,China
文摘The manifold physical signals including micro resistance,infrared thermal signal and acoustic emission signal in the tensile test for double-material friction welding normative samples were monitored and collected dynamically by TH2512 micro resistance measuring apparatus,flir infrared thermal camera and acoustic emission equipment which possesses 18 bit PCI-2 data acquisition board.Applied acoustic emission and thermal infrared NDT(non-destructive testing) means were used to verify the feasibility of using resistance method and to monitor dynamic damage of the samples.The research of the dynamic monitoring system was carried out with multi-information fusion including resistance,infrared and acoustic emission.The results show that the resistance signal,infrared signal and acoustic emission signal collected synchronously in the injury process of samples have a good mapping.Electrical,thermal and acoustic signals can more accurately capture initiation and development of micro-defects in the sample.Using dynamic micro-resistance method to monitor damage is possible.The method of multi-information fusion monitoring damage possesses higher reliability,which makes the establishing of health condition diagnosing and early warning platform with multiple physical information monitoring possible.
基金supported by the National Natural Science Foundation of China(Grant No.51275381)the Science and Technology Planning Project of Shaanxi Province,China(Grant No.2012GY2-37)the China Scholarship Council.(Grant No.201206285002)
文摘Oil monitoring constitutes an important and essential component of condition monitoring technologies and has distinguished advantages in revealing wear,lubrication and friction conditions of tribo-pairs.Newly developed on-line/in-line oil monitoring technologies extend the merits into real-time applications and demonstrate significant benefits in maintenance and management of equipment.This paper comprehensively reviews the progress of on-line/in-line oil monitoring techniques including sensor technologies,their scopes and industrial applications.Based on the existing developments and applications of the sensors for oil quality and wear debris measurements,the trends for future sensor developments are discussed with focuses on accurate,integrated and intelligent features along with exploring a fundamental issue,that is,acquiring the knowledge on degradation mechanisms which has not received sufficient attention until now.Current status of applications of on-line oil monitoring is also reviewed.Although limited reports have been found on this topic,increasing awareness and encouraging progress in on-line monitoring techniques are recognized in applications such as aircraft,shipping,railway,mining,etc.Key fundamental issues for further extending the on-line oil monitoring techniques in industries are proposed and they include long-term reliability of sensors in harsh conditions,and agreement with fault or maintenance determination.
