A Novel Approach to Predictive Maintenance: A Portable, Multi-Component MEMS Sensor for On-Line Monitoring of Fluid Condition in Hydraulic and Lubricating Systems

Abstract

On-going pressure to reduce operating costs and increasing concerns about the environment are forcing industrial equipment operators to condition monitoring procedures and improve maintenance practices to achieve optimal fluid and component service life. Realization of these goals without compromising system performance or component life often requires that new and more sophisticated condition monitoring devices need to be used. Increasingly, these can be installed directly in-line, which eliminates delays associated with off-line analysis, decreases response time, and facilitates the decisionmaking process should remedial action prove necessary. This paper describes operational principles of a rugged microelectromechanical system (MEMS) sensor that comprises four sensing elements suitable for in-line condition monitoring of hydraulic and lubricating oils. Preliminary laboratory data suggest that the sensor exhibits an excellent correlation with conventional laboratory viscosity and acid number (AN) data.

Using Terahertz Time-Domain Spectroscopy to Discriminate among Water Contamination Levels in Diesel Engine Oil

“…Sensor systems studied have included electromechanical (Cheek and Mowery, 1989;Duchowski and Mannebach, 2006;Price and Clarke, 1991;Soleimani et al, 2013;Wang et al, 1994;Wang, 2002) and resonating sensors (Agoston et al, 2005;Jakoby et al, 2003;Milpied et al, 2010;Mohammed and Hassan, 2013). Infrared (Blanco et al, 1998;Borin and Poppi, 2005;Kasberger et al, 2011) and hyperspectral (Lulu et al, 2014) spectroscopy techniques have also been used.…”

“…Infrared (Blanco et al, 1998;Borin and Poppi, 2005;Kasberger et al, 2011) and hyperspectral (Lulu et al, 2014) spectroscopy techniques have also been used. The oil conditions these sensors attempted to monitor were acidity (Agoston et al, 2005;Moon et al, 2006;Soleimani et al, 2013;Wang et al, 1994;Wang, 2002), antioxidants (Cheek and Mowery, 1989;Price and Clarke, 1991), viscosity (Duchowski and Mannebach, 2006;Jakoby et al, 2003;Schmitigal and Moyer, 2005), and contaminants of fuel, water, or antifreeze (Borin and Poppi, 2005). No single sensor has been preferred, and researchers have indicated that some combination would be required for monitoring oil condition (Milpied et al, 2010;Schmitigal and Moyer, 2005).…”

Distinguishing Gasoline Engine Oils of Different Viscosities Using Terahertz Time-Domain Spectroscopy

“…Sensor systems researched have included infrared [2][3][4], hyperspectral [5], resonating [6][7][8][9][10], and electrochemical [11][12][13][14][15][16]. These sensors have attempted to monitor oil conditions such as viscosity [7,8,12,17]; acidity [6,[14][15][16]18]; fuel, water, or antifreeze contamination [3]; and antioxidants [11,13].…”

Multi-channel IR sensor system for determination of oil degradation

“…Therefore these values are difficult to interpret and to relate to the results of laboratory analysis. Multi-sensor systems combining several "indirect" sensors to obtain a more accurate assessment of the oil condition have been reported (Duchowsky and Mannebach, 2006), but their uptake in real applications is slow due to the ambiguity of the measurement results.…”

“…Kudlaty et al (2003) showed a measurement set-up for lubricating oils based on attenuated total reflection (ATR) with a pyroelectric detector and a chopper wheel with two integrated narrow band-pass IR filters. Endisch and Koch (2007) demonstrated a set-up with a movable gradient filter, a reference filter, two infrared detectors and a ZnSe fluid measurement cell with variable thickness allowing a low resolution spectral analysis of the IR transmission spectrum for lubricating oils. Later, Wiesent et al (2010) demonstrated a similar set-up with a detector array combined with the gradient filter to avoid the need for movable parts.…”