Oil condition monitoring is a vital part of integrated asset health management. With an increasing impetus toward real-time decision making, delays incurred in offline laboratory oil analysis are becoming less acceptable. At present, several oil quality parameters can be monitored by commercially available sensors, and active research and development programmes are being pursued by both academic and industrial researchers to develop robust, cost effective sensors for the remaining key parameters. Published (active) ASTM methods or practices do not yet cover the sensor technologies employed or under development, although work is in progress to address this deficit. This paper presents an overview of currently available oil condition sensors and looks at some recent developments, particularly in the following three areas: contamination by metallic wear debris, measurement of total water content, and determination of in-service oil viscosity. In each case, quite different technological solutions have been adopted. Where applicable, alignment and overlap with existing ASTM methods and practices will be reviewed and future directions indicated. Recent improvements in the sensitivity of inductive particle counters have enabled the detection of individual ferrous particles down to the sub- 100 μm diameter regime and close to the 100 μm diameter mark for non-ferrous metals. Experiences of particle counters in wind turbine applications have shown the potential for enormous benefits in failure prevention. One standard practice covering the installation, operation, and requirements of such devices is published and a second is currently in draft mode. Online sensors utilising infrared transmission measurements recently have been developed by two independent companies. The systems are targeted primarily at marine diesel engine installations, although the method is not restricted solely to these applications. Maximum water content measurable depends on both the optical path length and the cleanliness of the oil. For marine applications a practical upper measurement limit of 1 % by volume has been adopted. In the system described here, a correction methodology, correlating to an accepted Deutsches Institut fu¨r Normung-Fourier transform infrared standard, has been adopted to cope with oils contaminated by soot. Soot loading increases the opacity of the oil, causing a concomitant reduction in the maximum water content measurable. The correction procedure increases the accuracy of the water content measurement and additionally provides a determination of the soot content. Commercially available viscosity sensors include both the oscillating piston type and high frequency oscillating crystal designs; however, a cost effective device employing a low amplitude, mid-frequency vibrating sensor element has been developed recently. Key features include accurate measurements over a very wide viscosity range and an operating range that covers combustion engine oil temperatures and pressures. Correlation with existing ASTM methods and practices is presently limited to calibration aspects only.
[1]
Thomas Gürtler,et al.
Oil-Quality Prediction and Oil-Level Detection with the TEMIC QLT-Sensor Leads to Variable Maintenance Intervals
,
1997
.
[2]
B. Jakoby,et al.
Evaluation of a vibrating micromachined cantilever sensor for measuring the viscosity of complex organic liquids
,
2005
.
[3]
A. Drews,et al.
Standard Test Method for Kinematic Viscosity of Transparent and Opaque Liquids (the Calculation of Dynamic Viscosity)
,
1998
.
[4]
Brian Flynn,et al.
An online wear debris monitor
,
1992
.
[5]
S. Rich,et al.
A New Method for Continuous Viscosity Measurement. General Theory of the Ultra‐Viscoson
,
1953
.
[6]
B. Jakoby,et al.
Viscosity sensors for engine oil condition monitoring—Application and interpretation of results
,
2005
.
[7]
J. L. Miller,et al.
In-line oil debris monitor for aircraft engine condition assessment
,
2000,
2000 IEEE Aerospace Conference. Proceedings (Cat. No.00TH8484).
[8]
Joel Schmitigal,et al.
Evaluation of Sensors for On-Board Diesel Oil Condition Monitoring of U.S. Army Ground Equipment
,
2005
.
[9]
Lawrence C. Lynnworth,et al.
Ultrasonic measurements for process control
,
1989
.
[10]
Horst Mannebach,et al.
A Novel Approach to Predictive Maintenance: A Portable, Multi-Component MEMS Sensor for On-Line Monitoring of Fluid Condition in Hydraulic and Lubricating Systems
,
2006
.
[11]
Aw Drews,et al.
Standard Test Method for Acid Number of Petroleum Products by Potentiometric Titration
,
1998
.