Condition Monitoring of a Single Cylinder Engine Running on Gasoline and Gasoline-Ethanol Blend Using Wear Particle Analysis Technique

2013 ◽  
Author(s):  
Sayed Y. Akl ◽  
Ahmed A. Abdel-Rehim
Keyword(s):  
Wear Rate ◽  
Internal Combustion Engines ◽  
Wear Particle ◽  
Predictive Maintenance ◽  
Particle Analysis ◽  
Moderate Increase ◽  
Oil Analysis ◽  
Wear Particle Analysis ◽  
Used Oil ◽  
Analysis Technique

Analytical techniques performed on oil samples for lubricated machines can be classified in two categories; used oil analysis and wear particle analysis. Used oil analysis determines the condition of the lubricant itself, determines the quality of the lubricant, and checks its suitability for continued use. Wear particle analysis determines the mechanical condition of machine components that are lubricated. Through wear particle analysis, you can identify the composition of the solid material present and evaluate particle type, size, concentration, distribution, and morphology, thus indicating the machine condition and its predictive maintenance. The above mentioned techniques are suitable methods for the detection of abnormal wear occurring in internal combustion engines, especially for engines running on different fuels. These techniques provide cheap, fast and easy to use predictive maintenance methods which can replace other conventional methods. The objective of the present study is to apply wear particle analysis technique as an engine monitoring technique to compare two new and identical engines running on gasoline (Engine 1) and gasoline-ethanol blend (Engine 2). The two engines were tested for a total running period of 850 hours. Spectrometric and ferrographic analysis were used for the comparison where quantitative and qualitative changes in the concentration and size distribution of different particles were analyzed and compared to baseline values. Results showed an increase of wear rate for the engine running on gasoline-ethanol blend compared to the engine running on gasoline only. Two contents of ethanol were used where 10% content showed a moderate increase of wear rate; however 20% content showed a dramatic increase of wear rate. The predominant wear particles were the ferrous particles and aluminum particles indicating the wear of piston elements and piston rings. Corrosive wear was also highly remarked which indicates a chemical reaction in the presence of ethanol.

Fault diagnosis through Ferrography (Wear Particle Analysis)

2021 ◽  
pp. 303-322
Author(s):  
Anadi Sinha
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Wear Particle ◽  
Stage Ii ◽  
Lubricating Oil ◽  
Particle Analysis ◽  
Wear Particle Analysis ◽  
Analysis Technique ◽  
Detection And Diagnosis

The purpose of Plant Predictive Maintenance (PDM) programme is to improve Reliability of machineries through early detection and diagnosis of equipment problems, and degradation prior to equipment failure. Ferrography (Wear Particle Analysis) is one of the PDM techniques which allows detection, identification and evaluation of the degradation at the very incipient stage so that degradation is timely attended and mitigatory actions initiated. Ferrography is a Wear Particle Analysis technique based upon systematic collection and analysis of sample of lubricating oil from rotating and reciprocating machines. Ferrography analysis is conducted in 2 phases: Stage I – Quantitative, and Stage II – Qualitative. After Stage II analysis, recommendation is issued based on wear rating (Normal, Marginal, or Critical) so that operator can take timely action. Presently, 21 Nuclear Power Plants are operational in India and Forced Shutdown is a very costly affair. Lube oil of around 60 equipment from Indian Nuclear Power Plants is examined quarterly for Ferrography analysis, and failure of several equipment is avoided due to timely action. This paper will elaborate on the basic principles of Ferrography, and how systematic implementation of Ferrography has helped in avoiding forced failure of equipment, and hence prevent Forced Shutdown.

An Experimental Investigation of Industrial Gearbox Condition Using Wear Particle Analysis Technique

2016 ◽  
Author(s):  
Sayed Y. Akl ◽  
Sherif Abd El-Ghafar ◽  
Hamed Mosleh
Keyword(s):  
Condition Monitoring ◽  
Cost Effective ◽  
Wear Particle ◽  
Morphological Data ◽  
Lubricating Oil ◽  
Particle Analysis ◽  
Limit Values ◽  
Wear Particle Analysis ◽  
Analysis Technique ◽  
Wear Modes

In different lubricated machines as engines and gearboxes, the generated wear particles analysis is considered as an effective tool for condition monitoring of these machines. Wear particle analysis as a nondestructive evaluation technique is an effective method to determine the lubricating oil conditions within different lubricated machines, thus monitoring wear modes and imminent failures in these machines. Machine condition monitoring is a cost-effective and reliable system to predict mechanical behavior and efficiency of power plant systems. Qualitative, quantitative and morphological data could be obtained from the wear particle analysis through the periodically taken samples of the lubricant. Different methods are used to detect and analyze wear debris in the lubricant oil, such as ferrograhy, spectrometry, filtergram, particle counters and recently Laser oil analyzer and time-dependent limits monitor factors. The objective of the present work is to apply wear particle analysis technique for condition monitoring of an industrial gearbox transmission over one year period. This transmission belongs to one of the largest carpet manufacturing plant in the world. The chosen gearbox for condition monitoring was a new gearbox installed to the rug textile machine. The gearbox components are elasto-hydrodynamically lubricated with mineral-based oil. The function of the gearbox is to drive the motion (forward and backward) of the knife to cut the fibbers of the carpet during the operation. Periodic oil samples were taken and analyzed through spectrometric technique while selective samples were chosen to be analyzed through ferrography technique. Spectrometric and ferrographic analysis were used where quantitative and qualitative changes in the concentration and size distribution of different particles were analyzed and compared to baseline and limit values. In addition to the sampling process, the gearbox performance was also monitored through measuring the oil temperature that was recorded just after the oil sample intake. The oil temperature is an indication for the gearbox loading which in its turn indicates any failure if it occurs. Results were analyzed, discussed and correlated to the gearbox performance. Also, recommendations were given for better performance based on the investigation and justification of the relevant results.

Condition Monitoring of a Gear-Box Using Wear Particle Analysis Technique

2015 ◽  
Vol 1125 ◽  
pp. 511-515 ◽  
Author(s):  
Sayed Y. Akl ◽  
Ahmed A. Abdel-Rehim
Keyword(s):  
Condition Monitoring ◽  
Wear Particle ◽  
Complete Information ◽  
Lubricating Oil ◽  
Particle Analysis ◽  
Wear Particle Analysis ◽  
Iron Aluminum ◽  
Analysis Technique ◽  
Gear Box ◽  
Wear Modes

Wear particle analysis as a nondestructive evaluation technique is an effective method to determine the lubricating oil conditions within different lubricated machines, thus monitoring wear modes and imminent failures in these machines, such as gear-boxes and engines. Ferrographic analysis of wear particles in lubricating oil could give complete information about ferrous and non-ferrous solid debris present in the oil sample. Spectrometric oil analysis could give a direct measure of elemental metal content in the oil such as Iron, Aluminum, Lead and Cupper. These techniques provide cheap, fast and easy methods to use predictive maintenance methods which can replace other conventional methods. The objective of the present study is to apply wear particle analysis technique for condition monitoring of an industrial gear-box transmission over two year’s period of time. This gear-box belongs to one of the machines of the Oriental Weavers Company (OWC), one of the largest carpet manufacturers in the world. Spectrometric and ferrographic analysis were used where quantitative and qualitative changes in the concentration and size distribution of different particles were analyzed and compared to baseline values.

Oil film lifetime and wear particle analysis of laser-patterned stainless steel surfaces

Wear ◽  
2015 ◽  
Vol 334-335 ◽  
pp. 1-12 ◽  
Author(s):  
Andreas Rosenkranz ◽  
Tobias Heib ◽  
Carsten Gachot ◽  
Frank Mücklich
Keyword(s):  
Stainless Steel ◽  
Wear Particle ◽  
Particle Analysis ◽  
Wear Particle Analysis ◽  
Oil Film ◽  
Steel Surfaces

Expert-Free Wear Particle Morphology Analysis (Keynote)

2005 ◽  
Author(s):  
G. W. Stachowiak
Keyword(s):  
Condition Monitoring ◽  
Classification System ◽  
Particle Morphology ◽  
Wear Particle ◽  
Particle Analysis ◽  
Machine Condition ◽  
Wear Particle Analysis ◽  
Analysis Process ◽  
Machine Condition Monitoring ◽  
Morphology Analysis

Since the early 1970s wear particles have been used as indicators of the health status of industrial machinery. Their quantity, size and morphology was utilized in machine condition monitoring to diagnose and predict the likelihood or the cause of machine failure. In particular, the wear particle morphology was found useful as it contains the vast wealth of information about the wear processes involved in particle formation, and the wear severity. However, the application of wear particle morphology analysis in machine condition monitoring has limitations. This is due to the fact that the process largely depends on the experience of the technicians conducting the analysis. Research efforts are therefore directed towards making the whole wear particle analysis process experts-free, i.e. automated. To achieve that a detailed database of wear particle morphologies, generated under different operating conditions and with different materials for sliding pairs, must be assembled. Next, the reliable and accurate methods allowing for the description of 3-D wear particle morphology must be found. Multiscale and nonstationary characteristics of wear particle surface topographies must be accounted for. Finally, a reliable wear particle classification system must be developed. This classification system must be reliable and robust hence the selection of appropriate classifiers becomes a critical issue. It is hoped that the system, once fully developed, would eliminate the need for experts in wear particle analysis and make the whole analysis process less time consuming, cheaper and more reliable. In this presentation it is shown how the problems leading towards the development of such system are gradually overcome. Also, the recent advances towards the development of expert-free wear particle morphology system for the application in machine condition monitoring are presented.

Wear Particle Characterization and Severity Evaluation of Perodua Myvi 1.3L Automatic Transmission (AT) Fluid

2013 ◽  
Vol 393 ◽  
pp. 913-918
Author(s):  
Syazuan Abdul Latip ◽  
Salmiah Kasolang ◽  
Siti Khadijah Alias ◽  
Amirul Abd Rashid ◽  
Abdul Hakim Abdullah ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Automatic Transmission ◽  
Surface Characteristics ◽  
Wear Particle ◽  
Wear Behaviour ◽  
Particle Analysis ◽  
Wear Particles ◽  
Wear Particle Analysis ◽  
Roughness Analysis ◽  
Operating Distance

s. This paper investigates the characteristic and severity level of both wear and wear particles occurred in Perodua MyVi 1300cc automatic transmission (AT) mechanism via wear particle analysis approach. The analyses deployed were based on ferrographic and surface roughness analysis. The work of analysis strictly conducted on automatic transmission fluid (ATF) Perodua original equipment manufacturer (OEM) (ATF-3) series via continuous endurance dynamometer basis at the operating speed of 3000rpm. The operating mileage tested ranged from 0km up to 10,000km maximum operating distance. The wear particle generated at each operating mileage of 1,500km, 3,000km, 4,500km, 7,000km and 10,000km was accordingly analyzed morphologically and qualitatively. Ferrographic analysis is by principal has been recognized as one of the most reliable analysis incorporated with wear particle analysis (WPA) concern [1]. In concern of this study, it is applied to examine the morphology, mode and characteristic of wear particles generated. The surface roughness analysis meanwhile conducted to qualitatively evaluate and predict the wear condition of components within the AT mechanism via qualitative surface texture analysis of the wear particles. The outcome from the investigation done on the wear particles surface characteristics could interpret the wear behaviour and progress (stage/phase) as the surface characteristics of the wear particles do depict the surface characteristics of the wear components [2, 3].

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