Development of Oil Quality Estimator Using Machine Vision System

Abstract

The conventional method of observing the oil quality through color was previously used to identify the current state of the car. The usual method implemented to determine its quality was usually inaccurate that results in pre-mature periodic maintenance of the car. This has resulted in additional expenses failing to optimize the oil's lifespan. To optimize the car's performance while reducing the cost, a study developing machine vision system to scan the car oil's engine using the software LabVIEW (Laboratory Virtual Instrument Engineering Workbench) to provide the car owners the easiest way to monitor the quality of the oil. In the software's failure modes are essential for cost-effective oil monitoring techniques to help to protect important industry assets, minimize breakdowns and lessen maintenance costs. The effective indicator of oil degradation process is the measurement of the complex permittivity and viscosity of the lubricant. It is helpful in maintaining the condition of the oil to select the adequate replacement of oil maintenance schedule through image processing with the use of how much light of LED can pass through the oil sample. The system computes the light intensity of the scanned sample oil and thus produces an output indicating whether the car was needed for periodic maintenance.