A study of the effect of contaminant particles in lubricants using wear debris and vibration condition monitoring techniques (original) (raw)
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An integrated approach to fault diagnosis of machinery using wear debris and vibration analysis
Wear, 2003
Vibration and wear debris analyses are the two main condition monitoring techniques for machinery maintenance and fault diagnosis. In practice, these two techniques are usually conducted independently, and can only diagnose about 30-40% of faults when used separately. However, recent evidence shows that combining these two techniques provides greater and more reliable information, thereby resulting in a more effective maintenance program with large cost benefits to industry.
CONDITION MONITORING OF LUBRICANTS USING WEAR DEBRIS ANALYSIS
Condition monitoring or predictive maintenance is the most commonly used technique to eliminate the failure of a machine and thereby increasing production time. This is a non-destructive method to foresee the problems within the machine well in advance. There area number of valid techniques available for condition monitoring. In this work a device has been fabricated and tested to identify the wearer particles which are present in the lubricating oil. Oil samples are collected at a regular intervals and tested for presence of worn out particles and hence leading to health assessment of the machine. The worn out particles both ferrous and non-ferrous can be identified with a photo diode which in turn activate a LED and also a circuit to give sound alarm. The device can also detect the ferrous particles with the help of a magnet, which encloses the oil tube.
Wear debris: basic features and machine health diagnostics
Insight - Non-Destructive Testing and Condition Monitoring, 2006
Modern high speed and power machinery components like gears, bearings, pumps, hydraulics and motors normally suffer from wear phenomena during operation. The study of wear debris can help estimate the condition of the surface of a component, so its basic features may be used to diagnose component health prior to failure. In this paper, a review is presented of the current literature related to wear debris and its analysis. The basic features of wear debris are highlighted, and their possible potential to diagnose the health of machine components is discussed. The basic features of wear debris have been classified with respect to the approach of measurement for component health diagnostics. In addition, each feature has been detailed with its possible measurement descriptors, its trend during machine component operation, and its distinct health diagnostics capability. Finally the paper proposes advances in machine component health diagnostics solution, by optimising the diagnostic capabilities of basic wear debris features.
Influence of Contamination of Gear Oils in Relation to Time of Operation on Their Lubricity
Applied Sciences, 2021
The quality and reliability of consumables, including gear oils, results in the failure-free operation of the transmission components in heavy trucks. It is known that oil viscosity is essential for all lubricated tribopairs for wear and friction reduction in all vehicles with a gearbox. Viscosity may be influenced by the contamination that wear products can impart on the oil. Oil contamination can also affect lubrication efficiency in the boundary friction conditions in gearboxes where slips occur (including bevel and hypoid gearboxes). The present research focused on this issue. An obvious hypothesis was adopted, where it was theorized that exploiting the contaminants that are present in gear oil may affect how the lubricating properties of gear oils deteriorate. Laboratory tests were performed on contaminants that are commonly found in gear oil using the Parker Laser CM20. The study was designed to identify a number of different solid particles that are present in oil. At the sec...
Mechanical Systems and Signal Processing, 2011
The monitoring of progressive wear in gears using various non-destructive technologies as well as the use of advanced signal processing techniques upon the acquired recordings to the direction of more effective diagnostic schemes, is the scope of the present work. For this reason multi-hour tests were performed in healthy gears in a single-stage lab scale gearbox until they were seriously damaged. Three on-line monitoring techniques are implemented in the tests. Vibration and acoustic emission recordings in combination with data coming from oil debris monitoring (ODM) of the lubricating oil are utilized in order to assess the condition of the gears. A plethora of parameters/features were extracted from the acquired waveforms via conventional (in time and frequency domain) and nonconventional (wavelet-based) signal processing techniques. Data fusion was accomplished in the level of integration of the most representative among the extracted features from all three measurement technologies in a single data matrix. Principal component analysis (PCA) was utilized to reduce the dimensionality of the data matrix whereas independent component analysis (ICA) was further applied to identify the independent components among the data and correlate them to different damage modes of the gearbox. Finally heuristic rules based on characteristic values of the resulted independent components were set, realizing thus a health monitoring scheme for gearboxes.
Control Systems and Optimization Letters, 2023
Every year high costs are expending to repair rotating machinery in factories and industrial centers due to failures. Most failures happen suddenly while by condition monitoring of systems prognosis and diagnosis are possible. By condition monitoring, the failures can be detected and solved in the early stages. Gearboxes are an element used widely, and applying condition monitoring for them makes a significant benefit for saving budget due to prognosis and removing failure before progress. The current paper aims to present a condition monitoring system for gearbox which is able to inspect lubricant by oil temperature and pH. Moreover, it can detect some defects in the gearbox by vibration analyses such as unbalance, bent shaft, looseness in bearing housing, and whirl of oil. The evaluation of the system shows that its accuracy is proper for use in gearboxes.
Extraction of causalities and rules involved in wear of machinery from lubricating oil analysis data
Recently, methods in order to diagnose wear con- ditions of the equipments have been established. Lublicating oil analysis is one of these methods. However, since relations between events in wear are complex, its diagnosis relies on judgment by experts at this moment. In order to solve this prob- lem, a purpose of this study is to support its diag- nosis by generating a automatic diagnosis model. In this paper, we proposed a method that gener- ate the model in order to predict wear conditions of the equipments. First, the causalities in wear were extracted from the diagnosis reports which ex- perts described considerations for wear conditions of the equipments using text mining. Second, the equipments which has similar features were classi- fied using clustering and the rule of each cluster was extracted using decision tree from analysis data re- lated to lubricating oil and equipments. Finally, the models were generated by combining the causali- ties and the rules. Although the results of evalua- tion indicated that automatic diagnosis is possible, it will be necessary to diagnose the more detailed wear conditions of machinery in the future tasks.
Condition Monitoring of Variable Speed Worm Gearbox Lubricated with Different Viscosity Oils
Applied Mechanics and Materials, 2015
Over the years, condition monitoring of gear transmission systems have captured significant worldwide attention from both industries and academia. This is in light of the fact that an effective condition monitoring techniques will unquestionably extend the life span of the rotating equipment. In this research, both the vibration and temperature monitoring techniques were utilized to characterize the vibration behavior of worm gear as function of gear lubricant's viscosity. Three different types of lubricant's viscosity; VG100, VG460 and VG680 were used in the study to serve the sliding friction of worm gears. The predetermined speeds of electric motor at 900, 1150 and 1400 rpm were introduced to the gearbox prior to the measurement of vibration signal and temperature profile. The results revealed that a lubricant with higher viscosity contributes to less vibration amplitude. At 1150 rpm, it was recorded that the vibration amplitudes are higher compare to the other motor speeds, for all lubricant's types. In this case, VG100 showed the highest vibration amplitude followed by VG460 and VG680. This result was corroborated well with the obtained temperature profiles which are 35.0°C, 35.7°C and 39.3°C for the respective VG100, VG460 and VG680. Thus, concludes the correlation between the lubrication's viscosity, vibration level, temperature profile and worm gear speed.
Detection and Diagnosis of Gear Tooth Wear through Metallurgical and Oil Analysis
Tribology Online, 2010
Gear teeth wear, in most cases, by a smooth process giving initially good contact conditions, followed by a very slow and gradual process. Further, continuous progression of tooth wear may cause unfavorable changes of surface topography, thereby, giving rise to worsened contact situations. The metal removed from the worn teeth surfaces enter into the machine system and can, in turn, cause failure of other components, finally resulting in a severe form of tooth failure. The causes and subsequent prevention of the damage due to wear can be studied by oil/wear particle analysis of lubricants under operating conditions. This paper describes the results of experimental studies performed for evaluation of lubricant film thickness, wear particle analysis based on their morphology, metal composition analysis of lubricants using X-ray fluorescence, atomic absorption spectrometry (AAS) and Energy dispersive spectrometry (EDS). These results have been correlated with wear.
2017
Tribotechnical diagnostics as an integrated conception deals with the assessment of lubricants properties, monitoring of behaviour and consequences of the lubricant degradation process during its work in the machine lubrication system. For tribodiagnostic of friction pairs of aircraft engine are used three basic methods dealing with the qualitative and quantitative determination of wear particles, which are in oil of the lubrication system. Concentration of elements was determined by optical emission spectrometry with rotating disc electrode (RD OES) application, categorization of particles by dimension and quantity was performed by method of optical shading. By usage of ferrographic analysis was studied morphology of wear particles. On particular example of monitoring of aircraft engine is typified mode of notice its condition with aim increasing the safety of operation and reduction ecological load by prolongation duration of renewal lubrication system given by manufacturer of dev...