Oil property sensing array based on a general regression neural network

Abstract Online monitoring of multiple lubricant properties is critical in maintaining and extending the health of high-speed rotating and reciprocating machinery used in many of the nation’s key industries including aerospace, manufacturing, and energy. There have been many efforts on the development of sensors focused on measuring specific chemical/physical properties of lubricant oil. One long-standing challenge for these property sensors is the overlapping output problem (cross-sensitivity), meaning they cannot provide accurate measurements. Here we demonstrated a capacitive oil property sensor array based on a new general regression neural network (GRNN) for measuring acid, base, and water content in lubricant oil. Results showed that the GRNN can pinpoint individual oil properties from the overlapped sensor array’s responses with high accuracy and speed.

[1]  V. M. Makarenko,et al.  On-line monitoring of the viscosity of lubricating oils , 2010 .

[2]  Jie Wang,et al.  Tribological and wear performances of graphene-oil nanofluid under industrial high-speed rotation , 2019, Tribology International.

[3]  Jiang Zhe,et al.  Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method , 2013 .

[4]  Manel del Valle,et al.  Simultaneous Determination of Zn(II), Cu(II), Cd(II) and Pb(II) in Soil Samples Employing an Array of Potentiometric Sensors and an Artificial Neural Network Model , 2012 .

[5]  B. Sharma,et al.  Chemically functionalized vegetable oils , 2005 .

[6]  Jiang Zhe,et al.  A microsensor array for quantification of lubricant contaminants using a back propagation artificial neural network , 2016 .

[7]  Junqi Guo,et al.  A New Approach of Intelligent Physical Health Evaluation based on GRNN and BPNN by Using a Wearable Smart Bracelet System , 2018, IIKI.

[8]  Cheng Liang,et al.  A Novel Method to Detect Functional microRNA Regulatory Modules by Bicliques Merging , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[9]  Fang Wang,et al.  The Study of GRNN for Wind Speed Forecasting Based on Markov Chain , 2015 .

[10]  F. C. Oliveira,et al.  Improving time series forecasting: An approach combining bootstrap aggregation, clusters and exponential smoothing , 2018, International Journal of Forecasting.

[11]  B. Jakoby,et al.  Viscosity sensors for engine oil condition monitoring—Application and interpretation of results , 2005 .

[12]  R. E. Cantley,et al.  The Effect of Water in Lubricating Oil on Bearing Fatigue Life , 1977 .

[13]  Rob J Hyndman,et al.  Automatic Time Series Forecasting: The forecast Package for R , 2008 .

[14]  Alan F. Smeaton,et al.  A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring , 2012, Sensors.

[15]  M. F. DeVries,et al.  Neural Network Sensor Fusion for Tool Condition Monitoring , 1990 .

[16]  Ling Qiao,et al.  Application of improved GRNN model to predict interlamellar spacing and mechanical properties of hypereutectoid steel , 2020 .

[17]  Guiming Chen,et al.  Application of oil analysis to the condition monitoring of large engineering machinery , 2009, 2009 8th International Conference on Reliability, Maintainability and Safety.

[18]  P. M. Ku.  Gear Failure Modes—Importance of Lubrication and Mechanics , 1976 .

[19]  Gerardo Ornelas-Vargas,et al.  A comparison of back propagation and Generalized Regression Neural Networks performance in neutron spectrometry. , 2016, Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine.

[20]  Wuqiang Yang,et al.  Planar capacitive sensors – designs and applications , 2010 .

[21]  Denis Flandre,et al.  High-sensitivity capacitive humidity sensor using 3-layer patterned polyimide sensing film , 2003, Proceedings of IEEE Sensors 2003 (IEEE Cat. No.03CH37498).

[22]  Ping Chen,et al.  Risk prediction and factors risk analysis based on IFOA-GRNN and apriori algorithms: Application of artificial intelligence in accident prevention , 2019, Process Safety and Environmental Protection.

[23]  S. Cadirci,et al.  Experimental and numerical investigation of lubrication system for reciprocating compressor , 2019 .

[24]  Robert W. Bruce.  CRC Handbook of Lubrication : Theory and Practice of Tribology, Volume II: Theory and Design , 2010 .

[25]  A. Zhigljavsky,et al.  Forecasting European industrial production with singular spectrum analysis , 2009 .

[26]  Dimitrios Peroulis,et al.  High temperature dynamic viscosity sensor for engine oil applications , 2012 .

[27]  Shuvo Roy,et al.  Electrochemical detection and characterization of proteins. , 2006, Biosensors & bioelectronics.

[28]  Jiang Zhe,et al.  An integrated lubricant oil conditioning sensor using signal multiplexing , 2014 .

[29]  E. Curcio,et al.  Energy Harvesting from Brines by Reverse Electrodialysis Using Nafion Membranes , 2020, Membranes.

[30]  J. Verhaar,et al.  Femoral revision surgery with impaction bone grafting: 31 hips followed prospectively for ten to 15 years. , 2012, The Journal of bone and joint surgery. British volume.

[31]  Vadim F. Lvovich,et al.  Electrochemical monitoring of water–surfactant interactions in industrial lubricants , 2002 .

[32]  Jacek M. Zurada,et al.  Computational properties and convergence analysis of BPNN for cyclic and almost cyclic learning with penalty , 2012, Neural Networks.

[33]  Pietro Siciliano,et al.  Analysis of CO and CH4 gas mixtures by using a micromachined sensor array , 2001 .

[34]  Leslie R. Rudnick,et al.  Synthetics, Mineral Oils, and Bio-Based Lubricants : Chemistry and Technology , 2005 .

[35]  Kensall D. Wise,et al.  A high-speed capacitive humidity sensor with on-chip thermal reset , 2000 .

[36]  Mark A Haidekker,et al.  A ratiometric fluorescent viscosity sensor. , 2006, Journal of the American Chemical Society.

[37]  B. B. V. L. Deepak,et al.  Application of GRNN for the prediction of performance and exhaust emissions in HCCI engine using ethanol , 2016 .

[38]  T. Colclough.  Role of additives and transition metals in lubricating oil oxidation , 1987 .

[39]  Ramiro C. Martins,et al.  Friction torque of thrust ball bearings lubricated with wind turbine gear oils , 2013 .

[40]  James E. Amonette,et al.  Detection of trace levels of water in oil by photoacoustic spectroscopy , 2001 .

[41]  Xu Fan,et al.  A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting , 2017 .

[42]  J. Y. Wira,et al.  Performance, emissions and lubricant oil analysis of diesel engine running on emulsion fuel , 2016 .

[43]  B. Jakoby,et al.  Evaluation of a vibrating micromachined cantilever sensor for measuring the viscosity of complex organic liquids , 2005 .

[44]  R. Shubkin.  Synthetic lubricants and high-performance functional fluids , 1992 .

[45]  Byeong Kwon Ju,et al.  Multiwall Carbon Nanotube Sensor for Monitoring Engine Oil Degradation , 2006 .

[46]  Donald F. Specht,et al.  A general regression neural network , 1991, IEEE Trans. Neural Networks.

[47]  Vadim F. Lvovich,et al.  Iridium oxide sensors for acidity and basicity detection in industrial lubricants , 2003 .

[48]  Hongjie Wang,et al.  Preparation and properties of PTFE hollow fiber membranes for desalination through vacuum membrane distillation , 2013 .

[49]  Hengchang Dai,et al.  Application of back-propagation neural networks to identification of seismic arrival types , 1997 .

[50]  Jiang Zhe,et al.  Parallel Sensing of Metallic Wear Debris in Lubricants Using Undersampling Data Processing , 2012 .

[51]  Chen Wang,et al.  Research and application of a combined model based on multi-objective optimization for multi-step ahead wind speed forecasting , 2017 .

[52]  U. Kaatze.  Complex Permittivity of Water as a Function of Frequency and Temperature , 1989 .

[53]  A. Rudnitskaya,et al.  Detection of copper, lead, cadmium and iron in wine using electronic tongue sensor system. , 2014, Talanta.

[54]  R. Kauffman,et al.  Rapid Determination of Remaining Useful Lubricant Life , 1993 .

[55]  G. Krauss,et al.  Adjunctive rufinamide in Lennox‐Gastaut syndrome: a long‐term, open‐label extension study , 2010, Acta neurologica Scandinavica.