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The analysis of powertrain lubricants for the purpose of detecting faults and abnormal wear patterns is a useful practice in mobile equipment applications. Unfortunately for many users, these techniques don't always transfer successfully into stationary equipment applications. In recent years, new approaches and techniques have been advanced to improve the detection of incipient and developing faults in bearings and gear units using wear debris analysis.
As opposed to the application of any singular new or emerging technology, these new methods are more systematic and functional. It begins with improvements in the sampling process to enrich the data and proceeds through the use of specific strategies and tactics. After detection is confirmed, the final analytical phase involves wear particle identification using both classic and advanced techniques.
Like so many endeavors, success depends more on the quality of execution than the strength of the underlying technologies. This idea can be concluded from the fact that while a great deal of new knowledge and technology has been advanced, for the vast majority of industrial organizations employing wear debris analysis, little has changed in either their tools or approach.
Therefore, it seems that some have found extraordinary success with even the most basic tools and techniques while others, having invested in state-of-the-art instrumentation, have experienced nothing but frustration and disillusionment.
Images Courtesy of Herguth Laboratories
The common goal when it comes to wear debris analysis is to achieve the highest level of machine reliability at the lowest possible cost. However, to reach this goal, several subsidiary objectives must be systematically targeted and achieved. These objectives will be referred to as strategies and, in sum, define the pathway for applying wear debris analysis in attaining machine reliability. The most important strategies are noted below.
Catch faults early: To minimize the cost of repair and overall business interruption resulting from machine failure, problems need to be detected at the earliest possible stage. With this simple strategy, users are aware that problems can frequently be arrested "on the run" if they have not become too advanced or complex.
When little time is remaining and a small condition anomaly has led to extensive internal surface destruction, few options remain, including the quick fix. Conversely, early detection of failure at its incipient stage often leaves a low-cost, planned and manageable remedy.
Identify precise source of fault: The ailing component or part is often difficult to identify without tearing the machine down and conducting an internal state inspection. Many different technologies and analytical methods, apart from wear debris analysis, assist in isolating or localizing the problem to a single component or internal part. Often, the wearing surface is confirmed only when the forcing function is ultimately identified.
Identify the forcing function: Machines that are operated and repaired in a similar manner tend to wear out and fail in the same way. When an abnormal wear condition has been identified, replacing the component (such as a bearing or hydraulic pump) without addressing the cause or forcing function will usually result in an identical future breakdown with similar consequences.
Treating symptoms instead of the cause is wasteful and is not best practice. Accordingly, activities that systemically seek out and correct conditions that lead to failure, including those behind any identified abnormal wear conditions, are the most dependable strategies.
Regardless of the technology deployed, it is difficult to obtain good estimates of the residual life of operating machinery. Such information is considered valuable in defining the corrective measures and urgency. When combined with all available conditional information, wear debris analysis can assist in estimating how far wear has progressed and the minimal response time needed.
With the goal and strategies of wear particle analysis defined, it is time to dig deeper into the details of how information regarding the health of a machine emerges from the oil and how it is interpreted by the analyst. It is often these details, or tactics, that will determine whether the program will realize true success. It goes without saying that those who refuse to be bothered by such details will be met with a decidedly different outcome or destiny. These details will be referred to as tactics and are described below.
It is common to be introduced to wear metal data that fails to exhibit consistent or explainable trends. The data may appear to be fragile, moving erratically without any apparent reason. There are other times when additional predictive maintenance (PdM) technologies confirm a problem, yet no measurable indication from wear metal analysis appears.
Much of these results are caused by poor data quality associated with either the sampling process or the analyses. In other cases, the data is too weak or is lost in the noise range. Most of these problems can be overcome by employing modern techniques and tactics, for example:
False positives: This can occur due to accidental entry of environmental contaminants or cross-contamination from an additional oil/liquid (either in the instrument, including its solvents/reagents, or from the sampling device). Contaminants entering during the sampling process from the work environment can be controlled by using sampling procedures that don't expose the inside of the bottle or its cap to ambient air. The clean oil sampling method and the use of properly cleaned sample bottles are recommended.
Sampling pumps and probes must be handled carefully using proper procedures to avoid mixing of the current sample with previously sampled oils. This can occur, for instance, when a tube is removed from a vacuum pump, leaving residue on the seal, which carries over to the next tube inserted. For live zone sampling, sampling taps must be thoroughly flushed in advance.
One of the most common causes of false positives occurs when bottom sediment is pulled into sample bottles. This can result in the repository of old debris misinterpreted as current wear metal production.
False negatives: The main culprit with false negatives is also the sampling process. Sampling needs to be performed to maximize data density, meaning that samples taken in quiescent zones of fluid compartments or dead fluid legs will exhibit low levels of wear metals. Samples taken while a machine is at rest or during periods of abnormally low loads may show false negatives.
Wear particle fly-by will occur in hydraulic systems if samples are taken from high-velocity lines in laminar flow, 90 degrees from the flow path. In such cases, the larger wear particles (greater than five microns) may not enter the bottle at all or in diminutive concentration.
With regard to wear metal trending, it is a mistake to sample downstream of filters, allowing important data to be stripped from the oil prior to sampling. Equally corrupt is the process of sampling large centralized reservoirs such as steam turbines, paper machine lubes and hydraulic systems. The large volumes of oil in these tanks will dilute wear metal concentrations to levels often below instrument detection limits.
The process of sampling live-zone return lines and bearing drain headers is preferred. In the laboratory, a failure to properly agitate a sample can lead to false negatives. And, it is well known that some elemental emission spectrometers have poor sensitivity to particles larger than five microns, a size range associated with advanced wear.
Normalizing data: With elemental and ferrous density analysis, the level and trend of wear metals are influenced by both the age of the oil and the makeup rate. During normal operation, oil is often lost to combustion or leakage, which carries along wear metals. The new makeup oil will effectively dilute the concentration of the remaining debris.
Additionally, because most laboratory elemental spectrometers are biased toward particles that are smaller than filters typically remove (less than five microns), stabilized concentrations of wear metals often never occur. Unlike particle counting and ferrous density analysis, material balance is not achieved between generation and removal (filtration, settling, centrifugation) with elemental spectroscopy.
Therefore, when continuous increasing wear metal levels occur, even with normal wear conditions, the true add-rate may be missed or understated. Time-based plots of wear metal trends can help reconcile the influence of oil age to better represent the rate of change (changing slope). Reporting wear metals per 100 hours on oil is another way to normalize.
Reducing data noise: Unfiltered or poorly filtered oil will eventually result in growing concentrations of wear debris. The problem is mutually compounding because the dirtier the oil, the more contaminated the oil continues to become from internal wear debris production and destruction to contaminant exclusion seals. While it is good advice to maintain clean lubricants from a proactive maintenance standpoint (affirmative action), it is equally good advice from a predictive maintenance standpoint (early wear detection).
Failure to do so usually leads to the alarm signal effectively being "lost in the sauce." This concentrated debris results in a high noise threshold, and when an incipient wear signal occurs, it will write "in the noise" and be lost (signal-to-noise is less than a ratio of 1:1). This is a persistent problem found in splash-fed gearing, crankcase lubes and bath-lubricated bearings.
Conversely, a clean oil not only provides a healthy and nonabrasive lubricating environment but also allows the wear signal (incipient debris generation) to write above the noise level (signal-to-noise is greater than 2:1). When the fluids are maintained, and if sampling is carried out in live zones (before filters, on bearing drain lines and at turbulent fluid zones), the early detection of wear anomalies is typically achieved. There is often a need for the routine use of portable filtration systems or retrofitted side-loop filters.
Once confidence can be established in the concentration and quality of the wear metals in the oil, appropriate alarms and limits can be set. These can be based on statistical information that characterizes the past normal and abnormal wear metal histories. Alarms can also be based on rate-of-change, as previously described.
In cases where a cautionary limit has been tripped, the response may be nothing more than increased sampling and paying closer attention to other nonconforming or spurious data, including temperature and vibration. If cautionary alarms are consistently reported or any single critical alarm has gone off, wear particle analysis is triggered.
To localize the source of wear metal production, information on composition is important. Many modern methods and technologies are available to accomplish this. However, they are too often misunderstood and are either not deployed or infrequently deployed. By knowing the machine metallurgy and the dominant wear metals, there is improved precision in defining the corrective action, including timing. What follows are a few methods that have been reliably applied to "breaking the code" on wear particle composition.
Elemental spectrscopy: Most laboratories employ the use of inductive coupled plasma (ICP) and spark-arc emission spectrometers. In many industrial applications, the particle size bias of these instruments limits precision in quantifying levels of active wear metals. However, on an exception basis, more advanced techniques are sometimes employed to improve the range of sensitivity with large particles.
These include acid dissolution, microwave digestion and rotrode filter methods. If wear particles are collected on a membrane or glass substrate, then X-ray diffraction, X-ray fluorescence, scanning electron microscopy and other modern instruments can be used to assess elemental constituents.
Magnetic flux and induction: The use of a powerful magnet can be instrumental in identifying the presence of ferromagnetic debris. Ferrogram makers often combine gravitational deposition with magnetic deposition to distinguish the composition of wear metals. The alignment and location of the debris are examined. Additional methods separate the magnetic debris in advance and then transfer two groups of particles (magnetic and nonmagnetic) to two membranes for analysis.
However, it is not uncommon to introduce a moving permanent magnet under the filtergram during microscopy. Particles that flicker are either magnetic or have impacted particles that are magnetic. Magnetic induction technology provides for the detection of conductive metals in oils and offers promising performance in wear particle analysis.
Heat treatment and optical methods: Many labs commonly apply a variety of optical tricks to help define the composition of wear metals on ferrograms and filtergrams. These include staining particles with colored transmitted light and performing analysis under crossed polars by using two polarizing filters with mutually perpendicular polarizing planes. Even filtergrams can be examined using transmitted light by applying a clarifying solution to heated nitrate membranes. Reflected metallurgical lighting can be useful where free (reflective) metal particles are present.
If the particles are located on a glass substrate, a common heat treatment can assist the procedure. Some metals and alloys will change color or hue from the heat (typically 330°C for 90 seconds) while others do not. For example, the color change for low-alloy steels results from a refractive oxide surface film that forms on the particles under heat, projecting a blue-tempered hue.
Figure 1. Heat-treated Babbitt Particle
Other white metals (aluminum) may appear brighter or develop a mottling color after heat treatment (Figure 1). Lead-based bearing alloys can melt and puddle depending on temperature and composition. Because of the variations in color, light and heat effects in identifying particle composition, advanced wear particle atlases are becoming increasingly useful to the microscopist.
Impaction testing and chemical microscopy: Some particles are difficult to identify on ferrograms and filtergrams based on appearance; and in such cases, it may be necessary to use mechanical and/or chemical destruction methods. Chemical microscopy is widely used in forensic science to identify compounds on areas such as clothing, skin and bullet holes.
It is one of the methods deployed to identify wear particles and other debris found on ferrograms. There are many different chemicals that can be applied; for instance, diluted sodium hydroxide will attack aluminum (a fizz results) while nitric acid turns bronze to verdigris.
Impaction testing can be applied to larger particles. Using a pointed tool, the particles in question are pressed against the ferrogram or membrane and then examined under the microscope (Figure 2). Hard, rigid particles will remain intact. More friable particles will be crushed, while others may deform plastically or simply smear under the load.
Figure 2. Particle Smear After Impaction Test
Elemental families: The exotic metallurgy found in modern machinery usually consists of numerous elemental composites. When a surface wears, the major elements appear (iron, lead, copper or aluminum). In many cases, the companion elements (sometimes called minor and trace elements) may also be present in the oil.
The relative concentration of the wear metals helps identify the composition of particles and the likely surface(s) from which they emerged. Knowledge of machine metallurgy is important to the successful application of the method. Babbitt, for instance, can be many different grades, each with different concentrations of lead, tin, copper and antimony.
There are also many different alloying metals in bronze and brass. Elemental families can also be used to identify tribological pairs and the destructive penetration of clad surfaces. For instance, the presence of iron and chromium (family members) in a diesel crankcase oil emerges from the frictional contacts between the rings and liners.
Particle shape and texture: The experienced microscopist can compile large amounts of minute information to identify the composition of wear particles. In addition to factors such as color, light effects, heat treatment and magnetism, the shape and texture of wear particles can contribute important pieces of the puzzle.
For instance, to a trained eye, shape and texture can be used to distinguish between elastomer debris, coal dust and magnetite (all of which are black). However, not all materials can be identified by shape and texture - the approach often suggesting more about what the particle is not rather than what it is. The best interpretations result from practice, training and the availability of reliable reference material such as a wear particle atlas.
Patterns and combinations: The more data and information available to the analyst, the more reliable and complete the interpretation. By using companion tests, sometimes performed on an exception basis, a conclusion may change as the information and facts build. Take for example a case where low levels of ferromagnetic debris are detected using ferrous density analysis.
When the oil is later tested using spectrometric analysis, a large amount of iron is present. Although it may be believed to be an impossible contradiction, it could be due to the presence of stainless steel particles or common nonmagnetic ferrous oxides such as goethite (rust).
A lock-step trend is a pattern where two or more parameters trend in unison, both in direction and rate. For instance, the trend of a wear cause is seen in lock-step with the trend of the wear effect. Additionally, the introduction of certain contaminants over time might show lock-step trends, as in the case of silicon and aluminum from road dust (Figure 3).
Once the composition has been identified, wear debris can contain information concerning the machine condition. However, the mechanism of wear and the forcing function may remain unclear. Attempts to make repairs or correct problems that don't remove the actual cause of the failure will inevitably cause history to repeat itself. This is often the case when an oil or bearing is changed prematurely due to noncomplying conditions.
Little information can be obtained regarding the wear mode or root cause using elemental analysis alone. However, when combined with ferrous density and analytical ferrography, a pictorial story often emerges. The most important tool is the microscope, which is used by an analyst trained in tribology.
The root cause often presents itself in the oil, making the interpretation of the wear mode a simple exercise. Water contamination explains red iron oxides, while silica dust is often the root cause of cutting wear and platelets. Other lubricant-related root causes that might define the wear mode include improper oil, high acid numbers (AN), fuel dilution, additive depletion and oxidation.
Sometimes companion technologies can detect the root cause first, such as vibration analysis, by revealing unbalance and misalignment. This evidence is then confirmed using microscopic analysis.
The application of wear particle analysis to define remaining useful life is still evolving, with much remaining to be learned. There is evidence that the rate of change in wear metal production is dependent either on the intensity of the forcing function or the overall advancement of the condition itself. In analytical ferrography, experience with past problems can be invaluable in recognizing current abnormal wear conditions and their severity levels.
Many labs keep past ferrograms on file for each machine. These ferrograms provide a quick reference to the wear particle patterns that characterize normal and abnormal conditions. Additionally, a number of grading systems using image comparitors have been established by different organizations to help simplify the process.
One chart (Figure 4) employs the influence of wear particle size and concentration. The direct reading ferrograph also offers large and small particle concentration scaling.
Figure 4. Wear Severity Characterized by Particle Size and Severity
Multiclad journal bearings, such as those commonly used in diesel/compressor crankcase applications and some turbo-machinery, can be monitored using sequential trend analysis. The wear penetration depth can be estimated based on the sequence stage (clad) of wear metal production. In Figure 5, the lead production from the bearing overlay begins to attenuate about the time the copper trend rises (bronze bearing metal). The severity and advancement of the wear condition is obvious.
Figure 5. Sequential Trends of Crankcase Journal Bearings
There are many excellent case studies that have validated the successful application of wear debris analysis in industrial machinery. For these organizations, the benefits and savings emanating from increased machine reliability is real. Success in effectively implementing such programs using wear particle analysis depends on many assorted goals, strategies and tactics. Together, they form an important plan that may depend more on technique and less on technology.
For well-engineered programs, wear particle analysis may be the most penetrating and early warning system of all maintenance technologies in use.