Logic Design for Linear Regression Model Using ASIC in Engine Oil Degradation Monitoring System

Authors

  • M. F. M. Idros Electronic Architecture and Application (EArA) Research Group, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia
  • A. H. A. Razak Electronic Architecture and Application (EArA) Research Group, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia
  • M. F. Azmi Electronic Architecture and Application (EArA) Research Group, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia
  • S.I. Suliman Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia
  • A. K. Halim Electronic Architecture and Application (EArA) Research Group, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia
  • N. Khairudin Electronic Architecture and Application (EArA) Research Group, Faculty of Electrical Engineering, Universiti Teknologi MARA Malaysia, 40450 Shah Alam, Selangor, Malaysia

Keywords:

Oil Condition Monitoring, Resistive Sensor, Indium Tin Oxide, Oil Degradation Sensing,

Abstract

A degradation analysis in automotive engine oil is concerned with the unrespectable cost of equipment for data storage. System-on-Chip gives possible cost effective in reducing the bulky equipment and reliance on labor. This article discusses a new technique of degradation monitoring where an engine oil degradation model is used and translated into the logic gate based on the Least Square Method of statistical analysis. The degradation model is based on the optical properties where the percentage transmittance of light is varied due to the increase of contaminates contents in the engine oil at a certain period. A linear regression model is chosen in register-transfer level (RTL) development of the digital circuit design. In the algorithm development, the data set are collected at every one hour up to 300 hours and stored in a temporary register. Linear regression is implemented at every 5 data to obtain the degraded condition based on the variation of the slope.

References

M.F.M.Idros, S. H. Ali, and S. Islam, "Quantitative Analysis of Spectroscopy’s Study for Engine Oil Degradation Monitoring Due to Temperature Effect," in 2012 Third International Conference on Intelligent Systems Modelling and Simulation, 2012, pp. 278 - 282.

M. A. Al-Ghouti and L. Al-Atoum, "Virgin and recycled engine oil differentiation: A spectroscopic study," Journal of Environmental Management, vol. 90, pp. 187-195, 2009.

Y. Felkel, N. Dörr, F. Glatz, and K. Varmuza, "Determination of the total acid number (TAN) of used gas engine oils by IR and chemometrics applying a combined strategy for variable selection," Chemometrics and Intelligent Laboratory Systems, vol. 101, pp. 14-22, 2010.

S. S. Wang, "Engine oil condition sensor: method for establishing correlation with total acid number," Sensors and Actuators B: Chemical, vol. 86, pp. 122-126, 2002.

S. Shirley and S. Donald, "Automotive Engine Oil Condition Monitoring," in Tribology Data Handbook, ed: CRC Press, 1997.

M.F.M.Idros, S. H. Ali, and S. Islam, "Optical analysis for condition based monitoring of oxidation degradation in lubricant oil," in Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on, 2012, pp. 735-740.

M.F.M.Idros, S. H. Ali, and S. Islam, "Design of Intelligent SoC Controller for Engine Oil Sensing and Monitoring System," Asian Journal of Scientific Research, vol. 5, pp. 70-77, 2012.

P. S. M. Saurabh Kumar, "Online condition monitoring of engine oil," Industrial Lubrication and Tribology, vol. 57, pp. 260-267, 2005.

A. Agoston, N. Dörr, and B. Jakoby, "Corrosion sensors for engine oils— laboratory evaluation and field tests," Sensors and Actuators B: Chemical, vol. 127, pp. 15-21, 10/20/ 2007.

S. S. Wang and Y. Lin, "A new technique for detecting antifreeze in engine oil during early stage of leakage," Sensors and Actuators B: Chemical, vol. 96, pp. 157-164, 11/15/ 2003.

G. Cocco. (2004) Motorcycle Design and Technology Handbook. Motor Books Workshop.

M.F.M.Idros, H. Hashim, S. Islam, and S. H. Ali, "Capability of Optical Approach in Condition Based Monitoring of Lubricant Oil," Sensors & Transducers Journal, vol. 17, pp. 125-134, 2012.

A. Mujahid and F. Dickert, "Monitoring automotive oil degradation: analytical tools and onboard sensing technologies," Analytical and Bioanalytical Chemistry, vol. 404, pp. 1197-1209, 2012/09/01 2012.

B. L. De Rivas, J. Vivancos, J. Ordieres-meré, and S. F. Capuz-rizo, “Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models,” Chemom. Intell. Lab. Syst., 2016.

S. A. M. Al Junid, Z. A. Majid, and A. K. Halim, “Development of DNA sequencing accelerator based on Smith Waterman algorithm with heuristic divide and conquer technique for FPGA implementation,” in 2008 International Conference on Computer and Communication Engineering, 2008, pp. 994–996.

S. a. M. Al Junid, M. a. Haron, Z. A. Majid, A. K. Halim, F. N. Osman, and H. Hashim, “Development of Novel Data Compression Technique for Accelerate DNA Sequence Alignment Based on Smith-Waterman Algorithm,” in 2009 Third UKSim European Symposium on Computer Modeling and Simulation, 2009, pp. 181–186.

S. A. M. Al Junid, N. Md Tahir, Z. Abd Majid, Z. Othman, and K. K. Mohd Shariff, “Reducing memory complexity using data minimization technique on FPGA,” in 2012 International Conference on Computer & Information Science (ICCIS), 2012, pp. 431–434.

S. A. M. Al Junid, Z. A. Majid, and A. K. Halim, “High speed DNA sequencing accelerator using FPGA,” in 2008 International Conference on Electronic Design, 2008, pp. 1–4.

S. A. M. Al Junid, N. M. Tahir, Z. A. Majid, F. N. Osman, and K. K. M. Shariff, “Comparative study for DNA data minimization technique on FPGA,” in 2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012), 2012, pp. 765–767.

S. A. M. Al Junid, N. M. Tahir, Z. A. Majid, A. K. Halim, and K. K. M. Shariff, “Improved data minimization technique in reducing memory space complexity for DNA local alignment accelerator application,” in 2012 International Symposium on Computer Applications and Industrial Electronics (ISCAIE), 2012, pp. 153–156.

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Published

2017-09-01

How to Cite

M. Idros, M. F., A. Razak, A. H., Azmi, M. F., Suliman, S., Halim, A. K., & Khairudin, N. (2017). Logic Design for Linear Regression Model Using ASIC in Engine Oil Degradation Monitoring System. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-8), 67–71. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2629