What is in this article?:
The most common source of system impairment is fluid contamination. Without proper preventive measures and fluid conditioning, component failure can result.
Manufacturers' recommendations can be augmented by information that is available from other sources. For example, OEMs and research laboratories have carried out projects to analyze the sensitivity of pumps, valves, and other components to contaminants. As a result, guidelines and standards for hydraulic-fluid cleanliness have been published. These guidelines attempt to interrelate diverse factors such as:
- fluid lubricity (e.g., water-base fluids have lower lubricity than oil)
- abrasiveness of the contaminants commonly found in hydraulic systems
- system duty cycle and cycle rate (high pressure and high cycle rates, combined with contaminants, lead to earlier fatigue failures)
- component replacement cost
- design life objective in terms of mean time before failure (MTBF); a common goal today is 10,000 hours or more, and
- degree of risk associated with contaminant-related failures (high risk of personal injury or high cost of lost production dictates a need for cleaner fluid.)
The International Standards Organization (ISO) recommends cleanliness levels for various types of components, see the table below. The levels are stated in terms of industry standards that have been recognized for the past 20 years. Many fluid power designers apply these recommendations as rules of thumb. Many specifiers now accept and use ISO 4406 (see table on page A/99) as a means of designating the fluid cleanliness required for their systems.
Importance of records
Still, component manufacturers' and industry guidelines should be modified by experience. That requires gathering enough operating and maintenance data over sufficient time and from enough systems to provide confidence to make decisions. The data gathered should include the results of regular fluid analysis on systems. The categories of data collected might include:
Fluid variables - flow, pressure, temperature, and viscosity for circuit branches with the most sensitive or expensive components.
Fluid analysis - particle counts in various size ranges (e.g., >2, >5, >15, >25, >50, and >100 µm), spectrochemical analysis (e.g., most likely metals and other contaminants), and water content (% by volume).
Filtration information - model number and manufacturer for the filter(s) and element(s) protecting the circuit for which other data was gathered; element performance ratings in terms of beta ratios and dirt-holding capacity.
Maintenance data - date system placed in service; dates and descriptions of routine maintenance performed (including element replacements); reading of the filter element condition indicator (e.g., "needs replacement" or "in bypass"); dates and descriptions of component failures, including manufacturers' names and model numbers; failure mode analysis (e.g., fracture, corrosion, wear, etc.) also would be very helpful in determining if contamination was a factor in any failures.
PC data base and statistical analysis programs also can be used to correlate failures with fluid contamination levels. This will create a picture of the contamination tolerance of the most sensitive components. It also allows for the calculation of MTBFs for specific components, certain circuit branches, or the system as a whole.
Obviously, this is data the user must collect. Still, manufacturers can monitor warranty claims as an opportunity to capture some of this data, and create a clearer picture of component sensitivity. That may cover only the first year or two of service. A close relationship with customers and distributors can provide an opportunity to gather similar data over longer periods of time as replacement parts are ordered.
Descriptive factors for particles
Particulate contamination may be characterized by the following identification factors.
agglomeration the tendency of particles to bond together. This action is generally detrimental in fluid-contamination control.
compaction degree of packing from sedimentation process. As void spaces decrease and bulk density increases, silt condition intensifies.
concentration weight per unit volume of fluid or number of particles greater than given size per unit volume of fluid.
density mass of particle per unit of volume. Density affects the rate at which particles settle out from the fluid.
dispersion the tendency of particles to remain separated. This is a factor in particle separation and analysis.
hardness resistance to abrasion and the particles potential to abrade exposed surfaces.
settling terminal velocity of particles controls the degree of particle suspension provided by the flowing fluid.
shape degree of irregularity of particle structure or topography. A factor important to the cutting or abrading ability of the particle.
size structural extent of particle as defined by geometric, derived, and hydrodynamic diameters. Such diameters have significance on a statistical basis.
size distribution frequency of occurrence of each particle size in the population. Cumulative particle size distribution curves are the most popular type in fluid-contamination control.
size limits the size range in which only fractureless deformation occurs and the lower filtration limit of interest.
state condition where size and shape cannot be altered without forceful shearing of crystalline or molecular bonds. A concept important to the understanding of particle generation and growth.
transport the life force needed to overcome the buoyant weight of the particle. When this is achieved, the flow conduit does not retain particles on its surface.
Contamination - dynamic, not static
Another reason for regular fluid analysis is that the contamination level changes with time, and varies by location in the system. At any point, the amount of contamination present in the fluid depends on three factors:
1. How contamination much was in the fluid when the system was started
2. How much was added to the fluid from all sources during operation (Ingression rate is the term used to describe the amount of contaminant entering the fluid per unit of time.)
3. How much contamination left the fluid due to all removal mechanisms (settling, and filtration or separation)
These three factors account for the total mass of contaminant in a system at any time. That mass can be calculated using a material-balance equation:
CT = Ct + Ca - Cs
C is contaminant
T is any point in time
t is time since start of process
Ca is amount added since t
Cs is amount removed since t
The term material balance is used because the equation calculates the net difference between the amount of material or contaminant entering and leaving the fluid, and adds this difference to what was already there. The calculation applies to a specific location in the system.
In a circulating system, contaminants not removed will appear at the filter inlet again, along with new contaminant added to the fluid. This is called a multipass system because the fluid and contaminant make multiple passes through the filter. As a result, the contaminant concentration in the system fluctuates continuously.
If we consider the initial start-up of a system, the contaminants already present are there as a result of manufacturing processes or have entered with new fluid. (Each milliliter of fluid out of the original barrel typically contains at least 2,500 particles that are 5 mm and larger in diameter.) A few minutes after start-up, the particulate level will be considerably higher due to flushing action of the fluid as it flows through new components and piping to pick up debris. Eventually, more particles enter the system through the reservoir breather and imperfect seals. Still more will be added over time due to internal wear.
Fluid cleanliness required for typical hydraulic components
|Component type|| Fluid classification |
|Vane and piston pumps/motors||16/13|
|Directional and pressure control valves||16/13|
|Flow control valves and cylinders||18/15|
|Aircraft test stands||13/10|
|Metal working||17/14 - 16/13|
|Mobile equipment||18/15 - 16/13|
|New unused oil||18/15|
Estimating ingression rate
Assume that a new hydraulic system has been flushed properly before being put into service. If the system has a multipass filtration system with a given flow rate, the eventual stabilized level of contaminants will depend on the system's ingression rate and filter media removal efficiency. If filter efficiency is too low, the contaminant level will continue to increase due to the wear particles generated within the system and new particles entering from outside the system. (This is the scenario in most automobile lubrication systems, and why motor oil should be changed periodically.) If filter efficiency is high enough, the contaminant level will decrease and become stabilized, extending the service life of the hydraulic fluid. Because operating conditions vary, this is a kind of dynamic stability. The contaminant level varies within a range determined by these conditions.
Therefore, to select the appropriate filter media, it is necessary to have some idea of the ingression rate. Of course the ingression rate probably varies at different locations in the system, and depends on these factors:
- concentration of ambient airborne contaminants (which enter through worn filler/breathers, loose fittings, leaking seals, etc.)
- use or absence of an air-filter element in the reservoir breather
- number of components in the system or circuit branch
- types of components that make up the system, particularly if there are rotating components such as pumps and motors (some types wear faster than others)
- fluid velocity (because higher velocity often may accelerate wear - after flushing is completed)
- system pressure (because higher pressure also tends to increase wear rates)
- fluid temperature (excessive heat can cause fluid and additives to break down, creating contamination), and
- the filter media used (more-efficient media results in lower contaminant levels and reduced wear rates).
This parade of factors makes accurate estimation of ingression rates difficult. An estimate can be made by conducting particle counts on fluid samples taken from a system with known operating conditions and filtration efficiency. (In multibranch circulating systems, the reservoir frequently is picked as a convenient location from which to take samples.) Then, by using a simple filtration model based on the material-balance equation, an ingression rate can be inferred. Filtration specifiers can construct their own estimates using the same technique. Such an estimate may be more accurate than one of the averages published in a table. Computerized filtration models also are available that allow a large number of variables to be quickly manipulated in a kind of ingression-rate What if? analysis.