The formation of varnish in lubrication systems is a widespread problem impacting many industries. Varnish will increase component wear, reduce equipment performance and waste valuable maintenance resources. In order to increase equipment reliability, end users have searched for tools to predict the formation of system varnish. Unfortunately, traditional lubricant analysis methodologies have proven to be of little value in detecting the specific contaminants that lead to varnish deposits. This article introduces Quantitative Spectrophotometric Analysis (QSA) as an effective tool to measure the varnish potential in lubricating oils.

This article reviews the mechanism of varnish formation and the detrimental impacts of varnish in lubricating systems. Common oil analysis methodologies are examined to reveal why they are ineffective in predicting varnish. The last two sections describe the QSA test and provide evidence of its effectiveness in a correlation study with systems known to have varnish contamination.

Varnish Formation
Lubricant varnish is defined as a thin insoluble film that develops throughout the internals of a machine’s lubrication system over time. It is a considered a contaminant, comprised predominantly of oil degradation by-products and depleted additive molecules. While a variety of mechanisms contribute to oil degradation, the three most common are oxidation, thermal degradation and chemical degradation.


Figure 1. Mechanism of Varnish Adsorption onto Metal Surfaces

Oil decomposition by-products, also referred to as soft contaminants, are the result of lubricant degradation and form as polar components. Soft contaminants are incompatible with the nonpolar lubricant environment and will adsorb onto dipolar metallic surfaces to form varnish as shown in Figure 1. These soft contaminants often condense on valve spools and sleeves, bearing surfaces, gears and other internal surfaces of the lubricant system.

Figures 2 through 5. Polymerized Oil Degradation By-products at 500X

Figures 2 through 5 show varnish as viewed under a microscope at 500X. The lighting on the slides has been altered to highlight the varnish components in the field of view.

The Impact of Varnish in a Lubrication System
Varnish films appear in wide range of colors and consistencies, ranging from black tar-like lacquer to opaque petroleum jelly-like deposits. The presence of varnish in hydraulic and other close tolerance system components causes serious problems. Following are a few of the most common:

  • Reduced clearance zones affecting lubrication regimes. This often means a transition from hydrodynamic lubrication to mixed or boundary conditions, both of which increase wear rates of pumps, bearings and gears.
  • Increased friction in components. This friction results in higher energy requirements and can cause valves to stick or seize.
  • Higher operating temperatures. Varnish acts as an insulator, lowering the effect of heat exchangers and reducing the ability of the lubricant to cool.
  • Restriction or impedance of oil flow. Varnish can cause valves, strainers, filters and small orifices to clog.
  • Increased wear rates. Varnish captures hard contaminants, creating an abrasive surface that accelerates wear. Varnished surfaces often appear like sandpaper when examined under a microscope.

The consequences of varnish contamination are serious. Varnish has caused unplanned outages at power generation facilities, erratic crown control in paper machines, increased scrap parts in plastic injection molding machines, higher operating temperatures and wear rates in gas compressors and a host of other costly problems across a wide range of industries.

Ineffectiveness of Current Oil Analysis Tests to Predict Varnish
Due to the potentially high costs associated with varnish, it is important for maintenance and reliability personnel to have a predictive tool to measure a lubricant’s varnish potential. Determining the varnish potential of a fluid enables the user to investigate the root cause and implement corrective action before a catastrophic failure occurs. However, routine oil analysis programs often fail to identify varnish potential. The following list identifies many of the commonly performed oil analysis testing methodologies with an explanation of why they are ineffective at determining a lubricant’s varnish potential.

Spectrometry or Elemental Analysis
(AA, RDE, ICP, XRF)

Spectrograph analysis will determine the metallic elements in a sample. Although some metal contaminants can act as a catalyst in lubricant degradation, the by-products responsible for varnish are often nonmetallic and therefore cannot be directly identified or measured using this method.

Water Content
(Karl Fischer, Crackle)

Although this test is useful in detecting conditions that may accelerate oil degradation, the presence of water does not have a direct correlation to the varnish potential of a lubricant.

Viscosity (ASTM D445)
A lubricant’s viscosity can increase from hydrocarbon chain polymerization. While a useful indicator that degradation is occurring, varnish typically occurs long before a meaningful change in viscosity. Therefore, varnish propensity cannot be determined from changes in viscosity alone.

Acid Number
(ASTM D644, D974)

Acid number measures the lubricant’s acidic constituents. This test is ineffective for directly measuring all forms of varnish potential, because some of the by-products produced during oxidative, thermal and chemical degradation are nonacidic.

Infrared Analysis
(Fourier Transform Infrared)

Infrared analysis will show the molecular fingerprint of a lubricant. New molecular species result from oil degradation. Infrared analysis can be useful in pointing to potential root causes, but the data produced is difficult to interpret and quantify, making it noneffective at quantifying the varnish potential of a lubricant when used alone.

ISO Particle Count (Automatic Laser, Pore-blockage Particle Counter, Manual)
Most reliability engineers rely on particle count to determine the cleanliness of their lubricant. Because varnish precursors are insoluble in the lubricant, it would seem that this test would detect increases in soft contaminant levels and be useful in detecting varnish potential. Unfortunately, soft contaminants are typically less than one micron. In fact, the vast majority of insoluble contaminants in lubricants are under the detection limits of the ISO particle count test, as the new ISO 11171 standard reports particulate greater than four microns.

The data in Table 1 was obtained by performing specialized membrane filtration techniques on used lubricants. The percentages are expressed by weight, following a gravimetric patch test procedure. Note: Amounts of insolubles less than 0.22 micron were agglomerated prior to membrane filtration.

Total Insoluble Contaminants as Measured by Weight

Sample
No.
>5.0 µm <5.0 >0.45 µm <0.45 >0.22 µm <0.22 µm
1 14.91% 28.85% 29.96% 26.28%
2 16.73% 29.48% 27.06% 26.73%
3 10.48% 25.98% 25.76% 37.79%
4 11.21% 38.91% 27.40% 22.47%
5 12.67% 22.35% 28.26% 36.72%
6 9.60% 27.77% 26.47% 36.16%
7 7.51% 15.21% 22.17% 55.11%
8 19.67% 8.20% 40.98% 31.15%
9 11.11% 22.22% 30.56% 36.11%
10 1.20% 3.61% 4.82% 90.36%
11 4.72% 3.98% 25.13% 66.18%
12 16.51% 10.40% 26.91% 46.18%
13 21.43% 21.43% 27.14% 30.00%
14 7.35% 22.06% 21.66% 48.92%
15 5.81% 27.15% 50.37% 16.67%
16 9.31% 26.47% 35.29% 28.92%
17 21.45% 35.94% 38.26% 4.35%
Table 1. Particle Size Distribution in Used
Lubricants Obtained from Power Plants

Figure 6 illustrates that 88 percent of contaminants (by weight) are not accounted for when running an ISO particle count. Figure 6 represents an average of the 17 samples analyzed.


Figure 6. Percentage of Insoluble Contaminants
Identified in ISO 11171 Particle Counts

Rotating Pressure Vessel Oxidation Test (ASTM D2272)
The RPVOT test measures an oil’s resistance to oxidation. This information is sometimes interpreted as a lubricant’s remaining useful life and is calculated by dividing the in-service sample result by the new oil result. RPVOT values are highly influenced by the type and quantity of antioxidants present in the oil. It would be logical to assume that RPVOT values have a direct association with the amount of degradation that has occurred in the fluid. However, there is strong evidence to suggest that this is not the case.

A recent study comparing RPVOT to the sludging tendencies of turbine lubricants demonstrates the ineffectiveness of the test to predict a fluid’s varnish potential. Researchers tested lubricants representing various base stocks and additive types. Their findings are reported in Figure 7.

RPVOT Oils
Dry-TOST Values (min)
Weight of Filter Residue (mg/kg)
Test Judgement
at 25% RPVOT
A
285
O
30
B
350
O
35
C
350
X
680
D
365
X
800
E
430
X
200
F
595
X
550
G
620
O
30
H
640
X
930
I
660
X
270
J
820
O
41
K
1,300
X
200
L
1,480
X
772
M
1,510
O
52
N
1,520
X
150
O
1,620
X
520
P
1,770
X
1,700
Q
1,780
X
430
R
1,820
O
13
S
2,300
X
1,020
T
2,480
O
60
O: Good sludge resistance X: Poor sludge resistance
Figure 7. Comparison of RPVOT Values and Sludge (Varnish) Tendencies

As can be seen, oil A has a low RPVOT value of 280 minutes yet also reports low sludge resistance. In contrast, oils P and S have high RPVOT values of 1,770 and 2,300 respectively, yet their sludge resistance is the worst of all of the oils tested.

What about trending RPVOT values over time? The same research demonstrated that this is not an effective way of predicting varnish potential. Figure 8 shows three lubricants that fail the sludge limit test with RPVOT values between 70 and 85 percent of new.


Figure 8. Three Oils that Failed the Sludge Test with
High RPVOT Values Compared to New Oil

Quantitative Spectrophotometric Analysis
QSA purposely isolates and measures the specific lubricant degradation by- products that are responsible for the formation of varnish. The process begins by treating the lubricant sample with a specific chemical mixture designed to isolate and agglomerate insoluble by-product material (including submicron species). Next, a separation process extracts the varnish-forming insoluble degradation by-products (soft contaminants) and concludes with a quantitative measurement of the isolated contaminant. The concentration of the contaminant directly correlates to the varnish potential of the fluid. A rating of 1 to 100 indicates the propensity of the lubricant to form sludge and varnish.

Correlation between QSA and Real-world Varnish Issues
Large-frame gas turbine applications are among the most severe environments for lubricating oils. Peak-load combustion turbines operated in a cyclical mode intensify the already harsh environment even further due to rapid heating and cooling of the fluid and components.

 

One of the major operational problems in large-frame gas turbines is electrohydraulic servovalve stiction. Stiction can be described as the sticking or erratic action of hydraulic components due to the combination of reduced spool clearances and increased friction caused by varnish. Severe stiction can produce a unit trip, leading to an unscheduled shutdown. The costs associated with a unit trip are not limited to replacement parts and maintenance personnel but extend into lost time and production revenue. Stiction in inlet guide vane (IGV) valve positioners is common causes of unit trips. An example of varnish on an IGV valve positioner from a large-frame gas turbine is illustrated in Figure 9.


Figure 9. Varnish Formation on Inlet Guide
Vane (IGV) Valve from a Gas Turbine

The power generation industry presents a model environment for the study of lubricant varnish. For the purposes of this article, the authors chose this market as an ideal application to correlate their test results of QSA to verify varnish problems occurring in the field.

Thirty-five ISO 32 turbine oil samples of various oil manufacturers were obtained from generating plants located throughout the United States. At all locations, traditional oil analysis methodologies (spectrograph, particle count, acid number, etc.) had historically produced normal results. Nine of the samples submitted were from gas turbines that experienced typical symptoms of varnish contamination ranging from elevated bearing temperatures and sticking IGV valves to unit trips. A breakdown of the samples is shown in Table 2.

Sample Identification
Number of Samples
Obtained from systems with documented
severe varnish-related problems
9
Undiagnosed fluid condition
26
Total samples
35
Table 2. Gas Turbine Lubricant –
Sample Identification

QSA was performed on all samples to identify their varnish potential rating (VPR). The higher the VPR value, the higher the lubricant’s propensity to produce deposits. The samples with the nine highest VPR values correctly matched those samples identified by the users as severe. Although QSA does not replace routine oil analysis, it fills a missing information gap by allowing reliability engineers to measure the varnish potential of their lubricants. The predictive ability of QSA provides an essential enhancement to monitoring hydraulic, turbine, paper machine, compressor and gear oils.

Varnish is comprised mainly of oil degradation by-products, which are polymerized oil additives and degraded base stock. Although there are a variety of mechanisms that degrade a lubricant, oxidation, thermal degradation and chemical degradation are the three most common. This article described how routine oil analysis will not determine the varnish potential of a lubricant. QSA measures the level of otherwise undetected insoluble components in an oil sample and directly relates this value to the varnish potential of a lubricant. QSA has a direct correlation to real-world varnish problems, as demonstrated in a study of 35 gas turbine oils, confirming the test procedure as an excellent addition to a predictive maintenance program.

Acknowledgment
Particle distribution data was produced by Evan Zabawski, Environmental Power and Technologies.

References

  1. Thompson, B. and Livingstone, G. “Using Quantitative Spectrophotometric Analysis (QSA) as a Predictive Tool to Measure Varnish Potential.” 2004 International Maintenance Conference Proceedings, December 2004.
  2. Yano, A., Watanabe, S. and Miyazaki, Y. “Study on Sludge Formation During the Oxidation Process of Turbine Oils.” Tribology Transactions 47:111-122, January 2004.