A low cost, compact, real-time, and quick measurement optical device based on the absorbance of white light, which comprised of photodiodes in a 3-element color-sensor, feedback diodes, water and temperature sensing element, and so on, was developed and tested in low absorption mineral oil. The device, a deviation from conventional electrical, mechanical, and electrochemical techniques, uses color ratio (CR) and total contamination index (TCI) parameters based on transmitted light intensity in RGB wavelengths for oil condition monitoring. Test results showed that CR corroborated CIE chromaticity ( - Coordinates) and increased with oil degradation unlike Saturation and Hue . CR was found to be independent of the particulate contaminants of oil, but dependent on chemical degradation. TCI depended on both chemical degradation and particulate contaminants in oil, being most sensitive in the blue wavelength range and least in the green. Furthermore, results agreed with those of viscometry, total acid number (TAN), and UV-VIS photospectrometry. CR and TCI gave clearer indication of oil degradation than key monitoring parameters like TAN and were found to be effective criteria for characterizing the degradation of hydraulic mineral oils. 1. Introduction 1.1. Background Oil contamination could be chemical (oxidative and thermal degradation , dissolved and emulsified water) or physical (from wear particles, dust, free water, and air). Besides, oil can also degrade by photodegradation (from exposure to the sun ultraviolet rays) [2, 3]. As oils degrade in service, chemical and physical changes inevitably occur. These include change in acidity due to oxidation and additive depletion, viscosity change due to formation of higher molecular weight components, and increased interfacial wear of mating pairs. These changes affect the oil performance. Oil performance characteristics can be detected by total acidity number (TAN), viscometry, UV-VIS photospectrometry, and so forth. However, these methods mainly measure a single parameter and assume no machinery malfunctions during the measurements. Single parameter sensors only provide a narrow view of a lubricant quality. Hence, finding a set of measurands that unambiguously identifies the emergence of oil degradation is important. This set of measurements must satisfy statistical criteria so that rational limits can be set on deviations. Subsequently, development of reliable sensor to quantify these measurands becomes imperative. To increase measured data adequacy and reliable estimation of tribocondition, development
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