The Experts below are selected from a list of 270 Experts worldwide ranked by ideXlab platform
Laibin Zhan - One of the best experts on this subject based on the ideXlab platform.
-
A Web-Based Intelligent System for Used-Oil Analysis
2008Co-Authors: Jianchun Fan, Xuehong Zhao, Laibin ZhanAbstract:The Analysis of Oil in an operating machine is considered as a very useful means to assess the condition of the machine. However, classical techniques of Oil Analysis are strongly dependent on the analyst's expertise to perform wear particle inspection, condition classification, colligation of the test results by ferrography, AES, and physical or chemical detection and interpretation of the possible existing faults in a machine. To solve these problems and realize the intelligence of Oil Analysis, a Web-based intelligence system for Oil Analysis is developed. This system is composed of an automatic ferroscope controlled by a computer to obtain improved wear debris images, a platform to process the images and to connect the field analyst with the experts in machine diagnosis through internet, and an intelligent software platform to evaluate the tribological conditions and diagnose the faults. A discussion covers the framework of the system; the improved wear debris analyzer; and the intelligent diagnosis system. This is an abstract of a paper presented at the World Tribology Congress III (Washington, DC 9/12-16/2005).
-
A Web-Based Intelligent System for Used-Oil Analysis
World Tribology Congress III Volume 2, 2005Co-Authors: Xuehong Zhao, Laibin ZhanAbstract:The Analysis of Oil in an operating machine is considered as a very useful means to assess the condition of the machine. However, classical techniques of Oil Analysis are strongly dependent on the analyst’s expertise to perform wear particle inspection, condition classification, colligation of the test results by ferrography, AES. and physical or chemical detection and interpretation of the possible existing faults in a machine. To solve these problems and realize the intelligence of Oil Analysis, a Web-based intelligence system for Oil Analysis has been devised. This system is composed of an automatic ferroscope controlled by a computer to obtain improved wear debris images, a platform to process the images and to connect the field analyst with the experts in machine diagnosis through internet and an intelligent software platform to evaluate the tribological conditions and diagnose the faults. Furthermore, some intelligent diagnosis methods used in the system are introduced.Copyright © 2005 by ASME
P E Irving - One of the best experts on this subject based on the ideXlab platform.
-
a comparative experimental study on the diagnostic and prognostic capabilities of acoustics emission vibration and spectrometric Oil Analysis for spur gears
Mechanical Systems and Signal Processing, 2007Co-Authors: P E IrvingAbstract:Prognosis of gear life using the acoustic emission (AE) technique is relatively new in condition monitoring of rotating machinery. This paper describes an experimental investigation on spur gears in which natural pitting was allowed to occur. Throughout the test period, AE, vibration and spectrometric Oil samples were monitored continuously in order to correlate and compare these techniques to natural life degradation of the gears. It was observed that based on the Analysis of root mean square (rms) levels only the AE technique was more sensitive in detecting and monitoring pitting than either the vibration or spectrometric Oil Analysis (SOA) techniques. It is concluded that as AE exhibited a direct relationship with pitting progression, it offers the opportunity for prognosis.
Xuehong Zhao - One of the best experts on this subject based on the ideXlab platform.
-
A Web-Based Intelligent System for Used-Oil Analysis
2008Co-Authors: Jianchun Fan, Xuehong Zhao, Laibin ZhanAbstract:The Analysis of Oil in an operating machine is considered as a very useful means to assess the condition of the machine. However, classical techniques of Oil Analysis are strongly dependent on the analyst's expertise to perform wear particle inspection, condition classification, colligation of the test results by ferrography, AES, and physical or chemical detection and interpretation of the possible existing faults in a machine. To solve these problems and realize the intelligence of Oil Analysis, a Web-based intelligence system for Oil Analysis is developed. This system is composed of an automatic ferroscope controlled by a computer to obtain improved wear debris images, a platform to process the images and to connect the field analyst with the experts in machine diagnosis through internet, and an intelligent software platform to evaluate the tribological conditions and diagnose the faults. A discussion covers the framework of the system; the improved wear debris analyzer; and the intelligent diagnosis system. This is an abstract of a paper presented at the World Tribology Congress III (Washington, DC 9/12-16/2005).
-
A Web-Based Intelligent System for Used-Oil Analysis
World Tribology Congress III Volume 2, 2005Co-Authors: Xuehong Zhao, Laibin ZhanAbstract:The Analysis of Oil in an operating machine is considered as a very useful means to assess the condition of the machine. However, classical techniques of Oil Analysis are strongly dependent on the analyst’s expertise to perform wear particle inspection, condition classification, colligation of the test results by ferrography, AES. and physical or chemical detection and interpretation of the possible existing faults in a machine. To solve these problems and realize the intelligence of Oil Analysis, a Web-based intelligence system for Oil Analysis has been devised. This system is composed of an automatic ferroscope controlled by a computer to obtain improved wear debris images, a platform to process the images and to connect the field analyst with the experts in machine diagnosis through internet and an intelligent software platform to evaluate the tribological conditions and diagnose the faults. Furthermore, some intelligent diagnosis methods used in the system are introduced.Copyright © 2005 by ASME
Bernardo Tormos - One of the best experts on this subject based on the ideXlab platform.
-
FUZZ-IEEE - An Optimization Approach to Fuzzy Diagnosis: Oil Analysis Application
2007 IEEE International Fuzzy Systems Conference, 2007Co-Authors: Antonio Sala, Bernardo Tormos, J.c. Ramirez, M. YagoAbstract:This paper discusses a knowledge-base encoding methodology for diagnostic tasks. It transform "expert"-provided rules into algebraic expressions so inference of the "possible" disorders is carried out via associated constrained optimisation problems. In this way, the need of conventional fuzzy inference systems or "uncertain"-logic schemes is no longer present in the particular setting in this paper. An Oil-Analysis diagnosis case study is presented as an application example, with actual experimental data. The problem is solved by efficient linear programming tools, in principle able to cope with large-scale problems. The only software used was Mathematica reg 5.2.
-
ICINCO - Fuzzy Diagnosis Module Based on Interval Fuzzy Logic: Oil Analysis Application
Informatics in Control Automation and Robotics II, 2007Co-Authors: Antonio Sala, Bernardo Tormos, V. Macián, Emilio RoyoAbstract:This paper presents the basic characteristics of a prototype fuzzy expert system for condition monitoring applications, in particular, Oil Analysis in Diesel engines. The system allows for reasoning under absent or imprecise measurements, providing with an interval-valued diagnostic of the suspected severity of a particular fault. A set of so-called metarules complements the basic fault dictionary for fine tuning, allowing extra functionality. The requirements and basic knowledge base for an Oil Analysis application are also outlined as an example.
-
A Fuzzy Diagnosis Module for Oil Analysis in Industrial Diesel Engines
IFAC Proceedings Volumes, 2004Co-Authors: Antonio Sala, Bernardo Tormos, V. MaciánAbstract:Abstract This paper presents the basic characteristics of a prototype fuzzy expert system being developed in order to improve the performance of a binary-logic based software on the particular application of Oil Analysis of Diesel engines (for industrial and transport fleet use). The system allows for reasoning under absent or imprecise measurements, providing with an interval-valued diagnostic of the suspected severity of a particular fault. A set of so-called metarules complements the basic fault dictionary for fine tuning, allowing extra functionality such as linear transformations of membership prior to logic operations, discarding previous conclusions in some circumstances and introducing the possibility of detecting contradiction between different diagnostic alternatives for the same fault.
-
analytical approach to wear rate determination for internal combustion engine condition monitoring based on Oil Analysis
Tribology International, 2003Co-Authors: V. Macián, Bernardo Tormos, Pablo Olmeda, L MontoroAbstract:Abstract Wear has important, negative effects on the functioning of engine parts. Additionally, this situation is very difficult to evaluate accurately in Oil Analysis for engine condition monitoring. Original Equipment Manufacturers (OEM), lubricant suppliers and Oil Analysis laboratories provide specific guidelines for wear metal concentrations. These limits provide good general guidelines for interpreting Oil Analysis data, but do not take into account common factors that influence the concentration of wear debris and contaminants in an Oil sample. These factors involve Oil consumption, fresh Oil additions, etc., and particular features such as engine age, type of service, environmental conditions, etc. In this paper, an analytical approach to enable a more accurate wear determination from engine Oil samples is developed. The above factors are taken into account and an improved maintenance program for internal combustion engines based on Oil Analysis is developed.
L Montoro - One of the best experts on this subject based on the ideXlab platform.
-
analytical approach to wear rate determination for internal combustion engine condition monitoring based on Oil Analysis
Tribology International, 2003Co-Authors: V. Macián, Bernardo Tormos, Pablo Olmeda, L MontoroAbstract:Abstract Wear has important, negative effects on the functioning of engine parts. Additionally, this situation is very difficult to evaluate accurately in Oil Analysis for engine condition monitoring. Original Equipment Manufacturers (OEM), lubricant suppliers and Oil Analysis laboratories provide specific guidelines for wear metal concentrations. These limits provide good general guidelines for interpreting Oil Analysis data, but do not take into account common factors that influence the concentration of wear debris and contaminants in an Oil sample. These factors involve Oil consumption, fresh Oil additions, etc., and particular features such as engine age, type of service, environmental conditions, etc. In this paper, an analytical approach to enable a more accurate wear determination from engine Oil samples is developed. The above factors are taken into account and an improved maintenance program for internal combustion engines based on Oil Analysis is developed.
