Search results

Engine oil degrades in quality during its use and after certain period of time the oil needs to be changed depending upon its condition. The purpose of this paper is to design and develop an online condition monitoring device for engine oil.

Based on the previous works in this line and some testing of used oils in the laboratory, the correlation of change in colour with other properties were identified. An optical colour sensor was then designed and developed which can transform the darkness of oil colour into electrical resistance. A series of tests were undertaken to calibrate the system for its correctness.

This type of sensor provides the information about the condition of the oil and also can inform about the probable time for drain‐off of the oil.

Engine oil changes are normally done by schedules which are highly conservative and cost the user as the oil is changed when it could be still used for some time. Use of an online sensor will minimize the cost on lubricants to some extent.

The device is of great value to the users of IC engines as it not only reduces the cost on lubricants but also informs the user about the present condition of the oil.

The purpose of this paper is to present a data fusion methodology for online oil condition and wear particles monitoring for assessment of a mechanical spur gear transmission system.

In this work, a background understanding of the tribological phenomena behind oil degradation and wear on the contact surface of mechanical elements is presented. Experimental results were obtained from oil continuously sampled from an operating a single-stage gearbox. Sampling was done by a multi-sensor automated prototype and online analysis performed by algorithms implemented in a C-code programmed graphical user interface.

Two sets of experiments were performed to observe different fault events frequently occurred in an industrial environment. Fault detection was achieved in appropriate time under constant operating conditions. Under variable operating conditions, same results were obtained by adjusting analysis parameters to critical operation conditions.

The value of this research work is the integration of the hardware and software necessary for online monitoring of oil condition and mechanical wear. The setup integrates online sampling with data acquisition, wireless communication, change detection and fault recognition computation. The approach has application in non-destructive online condition-based maintenance.

The purpose of this paper is to present an optical technique for the condition monitoring of synthetic hydraulic oil; a deviation from the current techniques based on electrical principles which could be masked by wear particles and polar contaminants in oil.

Color‐change detecting device was developed using light‐emitting diodes, optic fibers and photodiodes of three‐color‐sensing elements. Color ratio (CR) and total contamination parameters based on transmitted light intensity in red, green, and blue wavelengths were used for oil chemical and particulate contamination assessment.

CR criterion was found independent of the particulate contamination of oil; but depended on chemical degradation. Total contamination index of the device depended on both the chemical degradation and particulate contamination of the oil, being most sensitive in blue wavelength, and least in the red. Test results for synthetic hydraulic oils monitored corroborated with results of viscosity, total acid number, RDE emission spectrometry, particulate counts and UV‐Vis photospectrometry. CR showed a clearer indication of oil degradation, compared to key monitoring parameters such as total acid number, viscosity, RDE emission spectrometry and particle counts.

This paper demonstrates how oil chemical degradation and total contamination could be detected through the device, before incipient wear occurs at tribological interfaces. The results showed that the color‐change parameters are effective criteria for the condition monitoring of synthetic hydraulic oils.

In order to find the relationship between operation machine status and oil monitoring information, the oil monitoring information characteristics abstraction and fault diagnostic system is established. The purpose of this paper is to find an effective method to monitor and diagnose the machine running status, and consequently, serve the industry.

The operation status information of equipments is obtained through applying the methods of statistical, trend, entropy and clustering characteristics as a whole; and the multi‐characteristic integration method is established based on the existing literature, industry practices and oil characteristic analysis.

Using multi‐characteristic integration method, an oil monitoring and diagnostic system is established based on the above status information. This multi‐characteristic integration method is applied to D‐100/8 air compressor sets in the status monitoring project of a shipbuilding company. The analysis conclusions of the operation status can be obtained promptly and accurately by the method, and can provide guidance for the equipment maintenance.

A novel comprehensive oil monitoring data processing method are presented in this paper, which can scientifically distill latent laws among the monitoring information and detect accurately the measurement index of the fault states and abnormity data.

This paper describes the development of the use of lubricant analytical programmes and trend analysis to optimise oil change intervals and to predict equipment failure. The various analytical methods are covered, as are the most frequently occurring lubricant applications where such condition monitoring programmes are most appropriate.

Discusses work completed at Cardinal River Coals in Canada to improve the existing oil analysis condition monitoring program being undertaken for wheel motors. Oil analysis results from a fleet of 55 haul truck wheel motors were analyzed along with their respective failures and repairs over a nine‐year period. Detailed data cleaning procedures were applied to prepare data for modeling. In addition, definitions of failure and suspension were clarified depending on equipment condition at replacement. Using the proportional hazards model approach, the key condition variables relating to failures were found from among the 19 elements monitored, plus sediment and viscosity. Those key variables were then incorporated into a decision model that provided an unambiguous and optimal recommendation on whether to continue operating a wheel motor or to remove it for overhaul on the basis of data obtained from an oil sample. Wheel motor failure implied extensive planetary gear or sun gear damage necessitating the replacement of one or more major internal components in a general overhaul. The decision model, when triggered by incoming data, provided both a recommendation based on an optimal decision policy as well as an estimate of the unit’s remaining useful life. By optimizing the times of repair as a function both of age and condition data a 20‐30 percent potential savings in overhaul costs over existing practice was identified.

Apart from the basic material properties of liquid lubricants, such as, e.g., the viscosity and density of the hydraulic fluid, it is also important to have information regarding the electrical properties of the fluid used. The latter is closely related to the purpose, type, structure, and conditions of use of a hydraulic system, especially the powertrain design and fluid condition monitoring. The insulating capacity of the hydraulic fluid is important in cases where the electric motor of the pump is immersed in the fluid. In other cases, on the basis of changing the electrical conductive properties of the hydraulic fluid, we can refer its condition, and, on this basis, the degree of degradation.

The paper first highlights the importance of knowing the electrical properties of hydraulic fluids and then aims to compare these properties, such as the breakdown voltage of commonly used hydraulic mineral oils and newer ionic fluids suitable for use as hydraulic fluids.

Knowledge of this property is crucial for the design approach of modern hydraulic compact power packs. In the following, the emphasis is on the more advanced use of known electrical quantities, such as electrical conductivity and the dielectric constant of a liquid.

Based on the changes in these quantities, we have the possibility of real-time monitoring the hydraulic fluid condition, on the basis of which we judge the degree of fluid degradation and its suitability for further use.

The paper aims to monitor the condition of heavy Earth-moving machines (HEMMs) used in open cast mines by lube oil analysis.

Oil samples at periodic interval were collected from the HEMM engine (Model No: BEML BH50M). Ferrography and Field Emission Scanning Electron Microscopy have been used for the wear particle analysis present in oil samples. Viscosity analysis and Fourier transform infrared spectroscopy have been done to investigate the degradation in quality and changes as compared to the initial structural properties of the lubricants.

The results obtained indicates wear in cylinder liner and piston ring. Copper, cast iron, alloy steel and ferrous oxide have been found as rubbing wear particles and cutting wear particles. Contamination level has also been found to be increasing in consecutive older oil samples. Chemical properties degraded with usage time and variations in oxidation and soot level have also been observed in every sample.

The results will be very much useful to maintenance teams of mining industry for early prediction of any impending failure of the machines, for example, diesel dilution, severe wear of the piston or cylinder liner leading to seizure can be predicted.

The HEMMs are an important piece of equipment in coal mining. Proper condition monitoring of HEMM is required to reduce the break down and down time to increase production.

The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.

A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.

It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.

There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).

This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.

The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.

This paper sets out to develop a reliable analysis method based upon a low‐cost procedure to monitor the wear condition of low‐speed and heavily loaded rolling element bearing.

Special solvents for grease are invented and new test methods, including spectroscopy and ferrography of used grease, are developed to monitor the wear condition of a deferred bearing of ladle turret in continuous casting.

According to the analytical results, the service life of the ladle turret bearing in No. 1 continuous casting machine is extended to 14 years and significant expense is saved, which proved that it is feasible for grease analysis to be used in the condition monitoring of low speed and heavily loaded rolling element bearing, especially those deferrable bearings.

The fault mechanism of the huge bearing is not estimated.

One useful analysis method to monitor the wear condition of low speed and heavily loaded rolling element bearing is reported, and it can be used in other industrial fields.

This paper provides a way of studying condition monitoring of low‐speed and heavily loaded rolling element bearings.