윤활유 분석 센서를 통한 기계상태진단의 문헌적 고찰 (윤활유 센서의 종류와 기능)
Literature Review of Machine Condition Monitoring with Oil Sensors-Types of Sensors and Their Functions
1
조회
0
다운로드
7
인용
0
참고문헌
키워드
초록
This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.
Abstract
This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.
참고문헌 (58)
- Lee, K. S., "A study on strategy of condition based maintenance for rolling stock", Proc. Spring Conf. Korean Society for Railway (2015)
- Yan, R., "Complexity as a measure for machine health evaluation", IEEE Trans. Instrum. Meas, 53, pp.1327~1334 (2004)
- García, Márquez, F. P., "Condition monitoring of wind turbines : techniques and methods", Renew Energy, 46, pp.169~178 (2012)
- Kumar, M., "Advancement and current status of wear debris analysis for machine condition monitoring : a review", Ind. Lubr. Tribol, 65, pp.3~11 (2013)
- Hong, S. H., "Literature review of machine condition monitoring with oil sensors-Types of sensors and their functions", Proc. Autumn Conf. Korean Tribol. Soc (2019)
- Khan, M. A., "Wear debris : basic features and machine health diagnostics", Insight NonDestr. Test Cond. Monit, 48, pp.470~476 (2006)
- Younus, A. M. D., "Intelligent fault diagnosis of rotating machinery using infrared thermal image", Expert Syst. Appl, 39, pp.2082~2091 (2012)
- Hong, S. H., "Literature review of machine condition monitoring with oil sensors-Application cases", Proc. Conf. Korean Tribol. Soc (2020)
- Hong, S. H., "Machine condition monitoring system with ferrous wear debris sensor", Proc. Autumn Conf. Korean Tribol. Soc (2019)
- Flanagan, I. M., "Wear-debris detection and analysis techniques for lubricant-based condition monitoring", J. Phys. E. Sci. Instrum, 21, pp.1011~1016 (1988)
- Du, L., "High throughput wear debris detection in lubricants using a resonance frequency division multiplexed sensor", Tribol. Lett, 51, pp.453~460 (2013)
- Cao, W., "Multi sensor information integration for online wear condition monitoring of diesel engines", Tribol. Int, 82, pp.68~77 (2015)
- Shen, M. X., "Effect of abrasive size on friction and wear characteristics of nitrile butadiene rubber(NBR)in two-body abrasion", Tribol. Int, 103, pp.1~11 (2016)
- Zhu, X., "Lubricating oil condition sensors for online machine health monitoring –A review", Tribol. Int, 109, pp.473~484 (2017)
- "Gill Sensors & Controls. Oil debris sensor"[URL]
- Murali, S., "Capacitive Coulter counting : detection of metal wear particles in lubricant using a microfluidic device", Smart Mater. Struct, 18, pp.37001~ (2009)
- Wen, Z., "Applications of electrostatic sensor for wear debris detecting in the lubricating oil", J. Inst. Eng. Ser. C, 94, pp.281~286 (2013)
- Liu, Y., "Research on an on-line wear condition monitoring system for marine diesel engine", Tribol. Int, 33, pp.829~835 (2000)
- Keller, M. A., "Monitoring of ester base lubricants by dielectric constant", Lubr. Eng, 45, pp.347~351 (1989)
- Du, L., "Real-time monitoring of wear debris in lubrication oil using a microfluidic inductive Coulter counting device", Microfluid Nanofluidics, 9, pp.1241~1245 (2010)
- Du, L., "Inductive Coulter counting : detection and differentiation of metal wear particles in lubricant", Smart Mater. Struct, 19, pp.57001~ (2010)
- "MetalSCAN MS4000"[URL]
- Du, L., "A high throughput inductive pulse sensor for online oil debris monitoring", Tribol. Int, 44, pp.175~179 (2011)
- Du, L., "Parallel sensing of metallic wear debris in lubricants using under-sampling data processing", Tribol. Int, 53, pp.28~34 (2012)
- Du, L., "Improving sensitivity of an inductive pulse sensor for detection of metallic wear debris in lubricants using parallel LC resonance method", Meas. Sci. Technol, 24, pp.75106~ (2013)
- Nemarich, C. P., "Online wear particle monitoring based on ultrasonic detection and discrimination", Mater. Eval, 50, pp.525~530 (1988)
- Xu, C., "Ultrasonic echo waveshape features extraction based on QPSO-matching pursuit for online wear debris discrimination", Mech. Syst. Signal Process, 60, pp.301~315 (2015)
- Du, L., "An integrated ultrasonic–inductive pulse sensor for wear debris detection", Smart Mater. Struct, 22, pp.25003~ (2013)
- Hamilton, A., "Development of a novel wear detection system for wind turbine gearboxes", IEEE Sens. J, 14, pp.465~473 (2014)
- Wu, T., "Imaged wear debris separation for on-line monitoring using gray level and integrated morphological features", Wear, 316, pp.19~29 (2014)
- Markova, L. V., "On-line monitoring of the viscosity of lubricating oils", J. Frict. Wear, 31, pp.433~442 (2010)
- Markova, L. V., "On-line acoustic viscometry in oil condition monitoring", Tribol. Int, 44, pp.963~970 (2011)
- Saluja, A., "Measurement of fluid viscosity at microliter volumes using quartz impedance analysis", AAPS PharmSciTech, 5, pp.e47~ (2004)
- Salzer, S., "Tuning fork for noise suppression in magnetoelectric sensors", Sens. Actuators A Phys, 237, pp.91~95 (2016)
- Heinisch, M., "Application of resonant steel tuning forks with circular and rectangular cross sections for precise mass density and viscosity measurements", Sens. Actuators A Phys, 226, pp.163~174 (2015)
- Effects of oxygenates on soot processes in DI diesel engines : experiments and numerical simulations, "Mueller, C. J.", SAE, 1791~, pp.SAE Technical Papers, Vol.1 (2003)
- Laget, O., "Experimental and numerical investigations on the mechanisms leading to the accumulation of particulate matter in lubricant oil", SAE Int. J. Engines, 9(4), pp.2030~2043 (2016)
- George, S., "Effect of diesel soot contaminated oil on engine wear", Wear, 262, pp.1113~1122 (2007)
- Ulrich, C., "Simultaneous estimation of soot and diesel contamination in engine oil using electrochemical impedance spectroscopy", Sens. Actuators B Chem, 127, pp.613~618 (2007)
- Mortier, R. M., "Chemistry and technology of lubricants" (2010), Springer
- Holzki, M., "Evanescent-fieldfiber sensor for the water content in lubricating oils with sensitivity increase by dielectrophoresis", Sens. Actuators A Phys, 184, pp.93~97 (2012)
- Holzki, M., "Evanescent-fieldfiber sensor for the water content in lubricating oils with sensitivity increase by dielectrophoresis", Sens. Actuators A Phys, 184, pp.93~97 (2012)
- Smiechowski, M. F., "Iridium oxide sensors for acidity and basicity detection in industrial lubricants", Sens. Actuators B Chem, 96, pp.261~267 (2003)
- Soleimani, M., "Base oil oxidation detection using novel chemical sensors and impedance spectroscopy measurements", Sens. Actuators B chem, 199, pp.247~258 (2014)
- Soleimani, M., "Engine oil acidity detection using solid state ion selective electrodes", Tribol. Int, 65, pp.48~56 (2013)
- Moon, S-I., "Multiwall carbon nanotube sensor for monitoring engine oil degradation", Electrochem Solid-State Lett, 9, pp.H78~ (2006)
- Ippoliti, L., "Investigation on an oil aeration measurement technique for the study of pump performance in an aircraft engine lubrication system", ASME Turbo Expo 2015: Turbine Technical Conference and Exposition (2015)
- Kimura, Y., "Bubble behavior in engine lubricant", Int. J. Automot. Eng, 2, pp.149~153 (2011)
- "Lubricant aeration"[URL]
- Tandon, N., "Condition monitoring of electric motor ball bearings for the detection of grease contaminants", Tribol. Int, 40, pp.29~36 (2007)
- Zhao, M., "Multi-fault detection of rolling element bearings under harsh working condition using imf-based adaptive envelope order analysis", Sensors, 14, pp.20320~20346 (2014)
- He, Y., "Failure analysis of journal bearing used in turboset of a power plant", Mater. Des, 52, pp.923~931 (2013)
- "Online condition monitoring of grease in rolling bearings"[URL]
- Aranzabe, A., "Comparing different analytical techniques to monitor lubricating grease degradation", NLGI Spokesm, 70, pp.17~30 (2006)
- Wu, T., "Progress and trend of sensor technology for on-line oil monitoring", Sci. China Technol. Sci, 56, pp.2914~2926 (2013)
- Preethichandra, D. M. G., "Actual condition monitoring of engine oil through an intelligent multi-functional sensing approach", Proceedings of the 26th annual conference of the IEEE industrial electronics society, 2000, pp.2383~2387 (2000), IECON
- Duchowski, J. K., "A novel approach to predictive maintenance : a portable, multi-component MEMS sensor for on-line monitoring of fluid condition in hydraulic and lubricating systems", Tribol. Trans, 49, pp.545~553 (2006)
- Zhu, X., "A microsensor array for quantification of lubricant contaminants using a back propagation artificial neural network", J. Micromech. Microeng, 26, pp.65005~ (2016)
