Open Cut

Wear Particle Characterisation - Auto Ident. of Wear & Contamination Particles Found in Lubrication Systems

Open Cut » Maintenance & Equipment

Published: October 97Project Number: C3050

Get ReportAuthor: Elliott Duff | CMTE

Microscopic examination of wear debris for machine condition monitoring was first introduced in the 70's It is reliable but, for the human analyst, can become a tedious and time consuming task. This has limited its widespread usage. In 1994, CMTE received an ACARP grant to demonstrate the feasibility of developing a computer based tool to automate the process

The aim of this project is to develop a computer-based pattern recognition procedure to properly identify contaminants and wear particles in lubricant oil, and to indicate the type and severity of wear. Its success will enable us to develop a system whereby such analysis can be done automatically

Equipment maintenance is 30-50% of the operation costs in the mining industry or $10-15b/year for the nation. The final aim is to create a new analytical instrument for machine condition monitoring through used oil analysis, with applications beyond the mining industry. A market size of 100+ instruments would be a conservative estimate for Australia

This was originally a two year project. It was a joint project between CMTE and ACIRL. Oil samples were collected from two 784 coal haulers at BHPAC's Goonyella mine and filtergrams were prepared by ACIRL and forwarded to a wear consultant, Mr Peter Ball of Machine Reliability Services.

A  written report was made from a visual examination of the filtergram and returned to the Goonyella mine. The filtergrams were then passed on to CMTE for image analysis. Due to the slow start of the project, and some difficulties with the filtergrams, an extension of one year was given. In this extension, no further oil samples were collected and most of the work was conducted at CMTE.


During this century there has been a gradual shift from the traditional maintenance schemes of breakdown, to preventative maintenance. Today this shift continues towards condition maintenance. It is based upon the principle that maintenance need only be performed if the machine is about to fail. This predictive ability can only be achieved with regular monitoring of the machine condition.

There are three primary components of such monitoring: performance, vibration and lubrication. In this work, we are primarily concerned with the third, and in particular, the analysis of wear and contaminant particles within the lubricating oil. Wear particles contain valuable information about the wear processes that occur within the machine.

Unfortunately, assessing this information must be done visually by highly trained operators. This makes the analysis both expensive and time consuming. To extend the benefits of such analysis to industry it is essential that it becomes automated

This project aimed to develop a computer-based pattern recognition procedure to properly identify the contaminants and wear particles and to indicate the type and severity of associated wear. Success would enable the development of a system whereby such analysis could be done automatically.


In the first year of this project a literature review was conducted to establish the nature and location of various research centres around the world which might be working on the problem. Although there are a number of groups trying to characterise wear debris, none of the work is directly related to the mining industry and little success has been achieved in regard to automation

In the same year a prototype vision system was built to acquire images of particles on a filtergram. It consisted of a standard TV camera fitted to an optical microscope and connected to a PC frame grabber. The images were acquired and processed with a number of different commercial and public domain image processing systems. Since none of these systems was able to calculate the shape and textural features needed for the classification of the wear debris, it became necessary to write our own image processing software.

In the second year of the project, over eighty oil samples, were collected from two haul trucks at Goonyella. From these samples, images were acquired and processed. In previous work, there appeared to be a clear difference between the fractal dimension of road dust and wear, but in this work, this feature alone was insufficient to classify the different types of wear debris found in used oil.

Although preliminary analysis of a number of shape and textural features showed some promise (eg the cutting particle could be easily identified from the other wear modes) there were a number of significant failures. In these failures, the software was unable to correctly segment, or interpret, the particle from the background.

In hindsight, this came as no surprise because the images were acquired with little prejudice, ie the particles were chosen randomly to duplicate the behaviour of an automated system. This meant that the particles could be poorly lit, partially out of focus, or obstructed by agglomeration. Since all of these problems will occur in an automated system they need to be resolved.

In the third year of this project, strategies for the success of the project were re-evaluated. Firstly, a high-resolution digital camera was purchased to improve the quality of the images and a further 180 images were acquired. Secondly, our focus of activity shifted from classification to segmentation.

The most significant impediment to the classification of wear debris, is not the need for more sophisticated classification rules, but the ability to segment the particle cleanly and accurately from the background. When a wear particle is generated in a machine, the texture, colour and shape of the particle reveals the wear mode that generated the particle. It is these features that identify the wear debris.

Unfortunately, we do not often get to see this particle because it has been attacked whilst it is in the lubricant. What we see on the computer screen is the result of attack whilst the particle is in the lubricant, and distortions generated by the microscope and vision system used to acquire the image. To solve this problem we need to establish the nature of any attack or distortion upon the particle. One way that this can be achieved is with a technique of over segmentation and reconstruction.

The particle is first broken up into a number of small segments. This process can be based upon the colour, texture and shape of different parts of the image. The particle is then rebuilt, starting at the central segment, based upon the relative properties of each segment. The shape and surface features of the particle are then derived from all (or part) of the rebuilt particle.

Any knowledge gained during the reconstruction is used to influence the level of confidence in the classification.

This new technique is able to double the segmentation success rate from 39% to 79% of the sample.



What has been achieved in this project is the development of a sophisticated vision system capable of analysing filtergrams found in the mining industry. It consists of a high resolution digital camera and more than 16,000 lines of image processing software. The software is based upon a technique of over segmentation and reconstruction, which is both unique and robust. This allows the software to work under a wide variety of lighting conditions, and more importantly, it enables the software to have a level of confidence in the validity of the features that it calculates. It means that the software is able to reject an image if it is too difficult to segment and lowers the chance of a false classification. Unfortunately, the delay involved in improving the software did not allow us time to develop the classification rules necessary to identify the different wear modes. Therefore, given the original aim of this project:

" to develop a computer-based pattern recognition procedure to properly identify the containments and wear particles present in lubricating oil, and to indicate the type and severity of associated wear."

then this project has not succeeded, but if we take a wider perspective and examine the overall, or commercial aim of this project:

" to develop a piece of analytical equipment that can automatically classify wear particles on a filtergram."

Then we have made a significant stride towards this goal.



Health and safety, productivity and environment initiatives.

Recently Completed Projects

C25060Development Of Borehole Shear Monitoring Device For Routine Application In Coal Mine Roadways

This project outlines the development of a cost effective, routine s...

C26063Reliable Estimation Of Horizontal Stress Magnitudes From Borehole Breakout Data

The main objective of the project is to develop a reliable and simpl...

C26053Predict Stress State And Geotechnical Conditions Near Major Geological Structures Using Microseismic Technology And Distinct Element Modelling

Stress state and geotechnical conditions often change significantly ...


Open Cut

Safety, productivity and the right to operate are priorities for open cut mine research.

Recently Completed Projects

C25031Developing Closure Criteria For River Diversions: An Alternative To Reference Sites

The use of reference sites for establishing closure criteria in area...

C25025Guidelines For Estimating Coal Measure Rock Mass Strength From Laboratory Properties - Report A Empirical Approach And Report B Synthetic Rock Mass Models

This report combined different approaches to investigate the estimat...

C27074Tyre Integrity Monitoring

Driving mine trucks with underinflated and overloaded tyres subjects...

Open Cut

Coal Preparation

Maximising throughput and yield while minimising costs and emissions.

Recently Completed Projects

C25019Adaptation Of Coal Grain Analysis To Improve Flotation Yield Estimation

This project involved sampling of full-scale flotation circuits at ...

C250083D Flotation Of Fine Particles

In this project a process for the continuous, selective agglomeratio...

C25012Dewatering Of Ultrafine Coals And Tailings By Centrifugation: Pilot Scale Studies

Dewatering of ultrafine coal and tailings is a big challenge to the ...

Coal Preparation

Technical Market Support

Market acceptance and emphasising the advantages of Australian coals.

Recently Completed Projects

C27047Combustion Characteristics Of Australian Export Thermal Coal Using Advanced Imaging Techniques

During pulverised fuel combustion, coal particles are rapidly pyroly...

C26044Physical And Chemical Interactions Occurring During Cokemaking And Their Influence On Coke Strength

This project builds onto a previous project , C24055 in which macera...

C27056Imaging Gas Penetration Inside Coals And Cokes And Determining Influence On Coke Reactivity

The suitability of cokes for use in a blast furnace is determined by...

Technical Market Support

Mine Site Greenhouse Gas Mitigation

Mitigating greenhouse gas emissions from the production of coal.

Recently Completed Projects

C27058Technological Assessment Of A Recycle Reactor For VAM Abatement

Underground coal mining emits high volumes of methane, diluted in ve...

C27008Selective Absorption Of Methane By Ionic Liquids

The connection of a ventilation air methane (VAM) abatement plant di...

C24061Proof-Of-Concept Photocatalytic Destruction Of Methane For Coal Mining Fugitive Emissions Abatement

Australia's fugitive emissions in 2015 were 41 Mt CO2-e (representin...

Mine Site Greenhouse Gas Mitigation

Low Emission Coal Use

Step-change technologies aimed at reducing greenhouse gas emissions.

Recently Completed Projects

C17060BGasification Of Australian Coals

Four Australian coals were trialled in the Siemens 5 MWth pilot scale ga...

C17060AOxyfuel Technology For Carbon Capture And Storage Critical Clean Coal Technology - Interim Support

The status of oxy-fuel technology for first-generation plant is indicate...

C18007Review Of Underground Coal Gasification

This report consists of a broad review of underground coal gasification,...

Low Emission Coal Use

Mining And The Community

The relationship between mines and the local community.

Recently Completed Projects

C16027Assessing Housing And Labour Market Impacts Of Mining Developments In Bowen Basin Communities

The focus of this ACARP-funded project has been to identify a number...

C22029Understanding And Managing Cumulative Impacts Of Coal Mining And Other Land Uses In Regions With Diversified Economies

The coal industry operates in the context of competing land-uses that sh...

C23016Approval And Planning Assessment Of Black Coal Mines In NSW And Qld: A Review Of Economic Assessment Techniques

This reports on issues surrounding economic assessment and analysis ...

Mining And The Community


National Energy Research,Development & Demonstration Council (NERDDC) reports - pre 1992.

Recently Completed Projects

1609-C1609Self Heating of Spoil Piles from Open Cut Coal Mines

Self Heating of Spoil Piles from Open Cut Coal Mines

1301-C1301Stress Control Methods for Optimised Development...

Stress Control Methods for Optimised Development and Extraction Operations

0033-C1356Commissioned Report: Australian Thermal Coals...

Commissioned Report: Australian Thermal Coals - An Industry Handbook