scholarly journals Mechanical tests, wear simulation and wear particle analysis of carbon-based nanomultilayer coatings on Ti6Al4V alloys as hip prostheses

RSC Advances ◽  
2018 ◽  
Vol 8 (13) ◽  
pp. 6849-6857 ◽  
Author(s):  
Ji Li ◽  
Ketao Wang ◽  
Zhongli Li ◽  
J. P. Tu ◽  
Gong Jin ◽  
...  
Keyword(s):  
Magnetron Sputtering ◽  
Bias Voltage ◽  
Wear Particle ◽  
Mechanical Tests ◽  
Particle Analysis ◽  
Wear Simulation ◽  
Hip Prostheses ◽  
Wear Particle Analysis ◽  
Carbon Based ◽  
Medical Grade

Carbon-based nanomultilayer coatings were deposited on medical-grade Ti6Al4V alloy using a magnetron sputtering technique under a graded bias voltage.

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.

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].

Quantitative wear particle analysis for osteoarthritis assessment

2017 ◽  
Vol 231 (12) ◽  
pp. 1116-1126
Author(s):  
Meizhai Guo ◽  
Megan S Lord ◽  
Zhongxiao Peng
Keyword(s):  
Wear Debris ◽  
Wear Particle ◽  
Degradation Process ◽  
Cartilage Degradation ◽  
Degenerative Joint Disease ◽  
Joint Disease ◽  
Particle Analysis ◽  
Wear Particles ◽  
Wear Particle Analysis ◽  
Invasive Method

Osteoarthritis is a degenerative joint disease that affects millions of people worldwide. The aims of this study were (1) to quantitatively characterise the boundary and surface features of wear particles present in the synovial fluid of patients, (2) to select key numerical parameters that describe distinctive particle features and enable osteoarthritis assessment and (3) to develop a model to assess osteoarthritis conditions using comprehensive wear debris information. Discriminant analysis was used to statistically group particles based on differences in their numerical parameters. The analysis methods agreed with the clinical osteoarthritis grades in 63%, 50% and 61% of particles for no osteoarthritis, mild osteoarthritis and severe osteoarthritis, respectively. This study has revealed particle features specific to different osteoarthritis grades and provided further understanding of the cartilage degradation process through wear particle analysis – the technique that has the potential to be developed as an objective and minimally invasive method for osteoarthritis diagnosis.

Integration of neural networks and expert systems for microscopic wear particle analysis

1998 ◽  
Vol 11 (3-4) ◽  
pp. 213-227 ◽  
Author(s):  
Ken Xu ◽  
A.R. Luxmoore ◽  
L.M. Jones ◽  
Farzin Deravi
Keyword(s):  
Neural Networks ◽  
Expert Systems ◽  
Wear Particle ◽  
Particle Analysis ◽  
Wear Particle Analysis
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