Dielectric spectroscopic sensor for particle contaminant detection in hydraulic fluids

Authors

  • Safal Kshetri Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA
  • Brian L. Steward Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA
  • Stuart J. Birrell Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA

DOI:

https://doi.org/10.1080/14399776.2016.1210422

Keywords:

Dielectric sensor, dielectric spectroscopy, ISO 4406 fluid cleanliness code, particle contaminants

Abstract

A practical contaminant sensor was developed that used dielectric spectroscopy to estimate levels of particles in hydraulic fluids. This dielectric sensor was designed for installation on off-highway vehicles to provide on-line estimates of hydraulic fluid cleanliness. Tests were performed using iron powder and ISO test dust as hydraulic fluid contaminants to investigate the performance of the sensor. An eight-channel particle counter was used for calibration of the dielectric sensor. Partial least squares regression models were developed to investigate the relationship between dielectric spectra and contaminant particle counts. The root mean square error of calibration (RMSEC) and root mean square error of cross validation (RMSECV) for the sensor with a central rod diameter of 6.35 mm were 1.1 and 1.39 of adjusted ISO fluid cleanliness codes, respectively, for iron powder. For a 17.7 mm diameter central rod, the respective RMSEC and RMSECV values were 0.62 and 0.83 for iron powder, and 1.29 and 1.48 for ISO test dust. The hydraulic fluid cleanliness level relative to particular particle contaminants can be determined by continuously monitoring fluid properties. The sensor shows good potential for estimating the cleanliness level of hydraulic fluid in the context of particle contaminants.

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Author Biographies

Safal Kshetri, Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA

Safal Kshetri is a PhD student in Agricultural and Biosystems Engineering at Iowa State University. He received his BS in Biological and Agricultural Engineering from the University of Idaho and his MS in Agricultural and Biosystems Engineering from Iowa State University. His research interests include mechatronics, automation, and computational intelligence.

Brian L. Steward, Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA

Brian L. Steward is a professor of Agricultural and Biosystems Engineering at Iowa State University. He received his BS and MS in Electrical Engineering from South Dakota State University, and his PhD in Agricultural Engineering from the University of Illinois at Urbana-Champaign. His research and teaching areas include dynamic systems modeling and simulation, fluid power engineering and technology, computational intelligence, and sustainable engineering. He has over 200 technical publications and presentations including 40 refereed journal articles..

Stuart J. Birrell, Agricultural and Biosystems Engineering, Iowa State University, Ames, IA, USA

Stuart J. Birrell is the Kinze Manufacturing professor of Agricultural and Biosystems Engineering at Iowa State University. His degrees, all in Agricultural Engineering, include BS from the University of Natal (1984), MS (1987) and PhD (1995) from the University of Illinois. His research focuses on harvest technologies, biomass harvesting and logistics, and sensor development for advanced machinery control and in precision agriculture. He is author or co-author of over 140 technical papers.

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Published

2018-12-23

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Original Article

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