Metal oxide gas sensor array for the detection of diesel fuel in engine oil

Institute of Microelectronics and Microsystems (CNR-IMM)-Lecce Via Monteroni, 73100 Lecce, Italy
Sensors and Actuators B: Chemical 01/2008; DOI: 10.1016/j.snb.2007.12.029

ABSTRACT We developed a novel method to detect the presence of unburned diesel fuel in lubricating oil for internal combustion engine. The method is based on the use of an array of different gas microsensors based on metal oxide thin films deposited by sol–gel technique on Si substrates. The sensor array, exposed to the volatile chemical species of different diesel fuel engine oil samples contaminated in different percentages by diesel fuel, resulted to be appreciably sensitive to them. Principal component analysis (PCA) and self-organizing map (SOM) applied to the sensor response data set gave a first proof of the sensor array ability to discriminate among the different diesel fuel diluted lubricating oils. Moreover, in order to get information about the headspace composition of the diesel fuel-contaminated engine oils used for gas-sensing tests, we analysed the engine oil samples by static headspace solid phase micro-extraction/gas chromatograph/mass spectrometer (SHS-SPME/GC/MS).

  • [Show abstract] [Hide abstract]
    ABSTRACT: Purpose – The purpose of this paper is to develop new knowledge in experimental characterization of contaminants in engine lubricants, using surface plasmon resonance (SPR) sensing that can be applicable for on-line condition monitoring of lubricant quality and engine component performance. Design/methodology/approach – The effect of change in optical properties (e.g. transparency, absorption, and refractive index) of engine lubricants caused by the introduction of contaminants, such as gasoline, coolant, and water, on the surface plasmon resonance characteristics is analyzed experimentally. In SPR measurement, variations in both the refractive index and absorption cause changes in the SPR curve, which is the dependence of reflectivity vs incidence angle. The SPR characteristics (e.g. refractivity) of engine lubricant contaminated by gasoline, water and coolant at different concentration are measured as a function of resonance angle and analyzed with respect to different concentration (1%-10%) of contaminants. Also, pattern recognition analysis between fresh and used engine lubricants is performed, to show applicability of Bayesian classification methodology for on-line monitoring and predicting engine lubricant condition. Findings – It was shown experimentally that attenuation of surface plasmons due to introduction of contaminants to the engine lubricant leads to a noticeable change in resonance angle and reflectivity minimum of the SPR curve due to an increase in the dielectric permittivity. In addition, the changes in the SPR characteristics were observed between fresh and used engine lubricant, causing resonance angle and reflectivity minimum of the SPR curve to shift. Practical implications – The knowledge generated in this study lays the informational basis to further develop an on-line system for engine lubricant condition monitoring using miniaturized SPR sensors fully suitable for on board applications. Originality/value – SPR characterization is originally applied for analysis of optical properties of engine lubricants caused by the introduction of contaminants, such as gasoline, coolant, and water.
    Industrial Lubrication and Tribology 01/2013; 65(1):61-68. · 0.40 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this work we proposed a system based on metal oxide gas micro-sensors to estimate diesel or gasoline contamination in different engine oil samples. The gas-sensing layers (undoped, Pt, Pd, Rh-doped SnO2, In2O3 and mixed In2O3-SnO2) have been synthetized by the sol-gel method and deposited by spin-coating onto 2 mm times 2 mm silicon substrates equipped by Pt heater on the back and Pt interdigitated electrodes on the front. The sensor array has been exposed to no-used and used commercial engine oil samples contaminated with different amounts of unburned fuel. The results of data analysis (DWT-based feature extraction, PCA and Gaussian mixture model classifier (GMM)) showed that different fuel contaminated used engine oils can be discriminated and successfully classified by the sensor array.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Engine oil experiences a number of thermal and oxidative phases that yield acidic products in the matrix consequently leading to degradation of the base oil. Generally, oil oxidation is a complex process and difficult to elucidate; however, the degradation pathways can be defined for almost every type of oil because they mainly depend on the mechanical status and operating conditions. The exact time of oil change is nonetheless difficult to predict, but it is of great interest from an economic and ecological point of view. In order to make a quick and accurate decision about oil changes, onboard assessment of oil quality is highly desirable. For this purpose, a variety of physical and chemical sensors have been proposed along with spectroscopic strategies. We present a critical review of all these approaches and of recent developments to analyze the exact lifetime of automotive engine oil. Apart from their potential for degradation monitoring, their limitations and future perspectives have also been investigated.
    Analytical and Bioanalytical Chemistry 07/2012; 404(4):1197-209. · 3.66 Impact Factor

Full-text (2 Sources)

Available from
May 21, 2014