Discerning Anti-Foam Particles Vs. Water and Other Solid Contaminants

1. Discerning Anti-Foam Particles Vs. Water and Other Solid Contaminants STLE Proceedings

2. Introduction • Monitoring the condition of lube oils is complicated by the addition of additives that improve performance. • Non-visual particle counters can mistakenly count anti-foams and polymer additions as contaminants in the oil leading to inaccurate information of the oil’s actual condition. • Counting water droplets is not sufficient in assessing its presence. Equal counts of water droplets with varying size distributions equate to vastly different water volumes, and therefor water must be detected and reported in terms of volume and not count.

3. Fundamentals of Vision • A rugged, high pressure fused glass to metal boundary is the optimal construction. This allows the light and lens to see the process and can be polished to a high finish which does not allow the process oil to adhere. • Controlled Illumination – Consistent, bright illumination is required to achieve repeatable performance. Particle focus and thresholds depend on this. LED technology provides illumination in terms of years and remains consistent within a couple percent. • Lab/Field instruments preserve the same measurement zone allowing results to be compared.

4. Typical Vision System Flow Body Camera Light Light Pipe

5. Fused Glass Lens

6. How to Distinguish Different Particles Lube oil with solids and water suspended

7. Particle Identification • The added dimension of vision enables particle identification. The system is able to determine shape characteristics such as the major and minor axes as well as perimeter and area. From this data a general shape can be determined. • By manipulating the basic parameters listed above the added features of aspect ratio and circularity, amongst others, can also be determined.

8. Circularity • A ratio of Area vs Perimeter (4*Pi*A/P^2) • A solid (2D) sphere = 1 • A transparent sphere (Water) ~ 0.25 • A solid square ~ 0.78 • A needle shape where R = 6r ~ 0.4 Add to these Aspect Ratio qualifiers and it is straightforward to distinguish them.

9. Status of Particle Identification • The following descriptions given are for information purposes only, however there is current work in ASTM to standardize these definitions to allow for better reporting of oil condition and equipment wear and causes which will improve maintenance.

10. Types of “Hard” Particles • Cutting • Sliding • Fatigue • Non-Metallic The following descriptions given are for information purposes only, however there is current work in ASTM to standardize these definitions to allow for better reporting of oil condition and equipment wear and causes which will improve maintenance.

11. Cutting Particles • These particles are generally created when a hard, or sharp, edge cuts into another material surface forming a chip that is longer than wide with some curl to it. • Detection of this type points to poor fit of moving components. Continued detection may indicate pending failure.

12. Sliding Particles • These particles are characterized by long, parallel striations indicating two surfaces rubbing against each other. • These instances may devolve into cutting wear should the abrasion be severe enough. • Consider lubrication fluids with better properties.

13. Fatigue Particles • These particles appear as being as long as wide, however with jagged edges. • Many times the particles are created from wear of bearing or rolling surfaces. • Check bearing surfaces for wear as this type of damage can also cause damage to the roller.

14. Non Metallic Solids • These particles show some translucence to them unlike metal particles. • This is a broad category and may include glass or ceramic, thin plastics or even non oil liquid droplets (water). • Shape will vary depending on the material

15. Typical Filter Set Current ASTM standard does not recommend particle shape limits. This chart includes Canty’s recommendations for classifying.

16. Types of “Soft” Particles • Water (in oil) • Oil (in water) • Gas • Antifoam Soft particles require further filtering to distinguish between them. This can include parameters such as # holes, % Filled, etc…

17. Typical “Soft” Particles Images Antifoam Droplets Gas Bubbles Water / Oil Droplets ***Images not to scale***

18. Distinguishing Between Solid and Soft Particles • Shape – in order to classify particles the instrument must be able to distinguish shape. For instance, solid contaminant particles are almost never spherical while water droplets are almost always spherical. • Machine Learning – going beyond simplified imaging filters for shape comparison is a form of AI where the instrument can be trained to classify different types of particles. This is especially of value when classifying particles that don’t neatly fit into a mathematical filter and provides a significant improvement to ease of use.

19. Training a Particle Classifier - Steps • Run an analysis containing a variety of particles belonging to each desired class. The software captures an image of every in-focus particle it sees.

20. Training a Particle Classifier - Steps • Open a training software that allows the user to create each class • For each class created, the user selects examples of particles belonging to that class

21. Training a Particle Classifier - Steps • After training is complete, user runs the classification to see how well the training worked. • If desired, the user can select more examples of particles after the initial training to increase accuracy of the classification

22. Training a Particle Classifier - Benefits • Training the software using example particles eliminates the need for users to come up with particle filters – this greatly increases the ease of use of the system • The software is capable of using far more complicated sets of shape filters that allows for it to more accurately classify particles than the basic filters imposed by a typical user can.

23. Reporting of Data • ASTM D8072 applies to vision instruments • Format similar to ISO4406 except there is an inclusion at the end for water ppm: D7596 17/14/13 – 5 First entry is the ASTM standard used for testing. The first 3 numbers reported indicate the >4, >6, and >14 solid particle count ranges while the last number is the water content in parts per million.

24. Typical Particle Summary by Size

25. Typical ppmL Particle Data

26. Reporting of Data • What data needs to be reported and how it is reported will depend on where and what analysis is taking place. • Online systems have the capability of outputting via 4-20mA (limited based on scaling), Modbus, OPC, and Excel/csv files • Laboratory systems have those same capabilities, but a majority of labs prefer to just use Excel/csv reports.

27. Conclusion • Vision offers the best way to determine the condition of lube oil on line or in the lab. • The ability to classify particles in real time provides clues to system wear in an objective, consistent way that other technologies, or human inspection, can’t provide.