Category: Used Oil Analysis

From Measurement to Action

Start measuring the air in your system. The most useful air-in-oil measurement is not the one that produces the largest number of parameters. It......

The 360 Approach – One Shared Data Language Across the Lubrication Value Chain

At Deepfluid, they have adopted a 360 approach where they can assist all the stakeholders involved in the lubricant industry as it relates to......

Case Study – From Abnormal Air-in-Oil Data to a Targeted Seal Investigation

Deepfluid’s direct measurement system can be used not only to analyze the interaction between oil and air during operation but also to monitor the......

One Portfolio for Controlled and Dynamic Evidence

The Deepfluid portfolio applies this methodology through three connected solutions.   The Air-in-One Lab Analyzer establishes controlled references. The Optical Inline Sensor captures dynamic......

One Shared Data Language – From Lab to Field

Particularly for OEMs, it is important to be able to transition the product from the lab to the testing phase, then into the field.......

AIR as a Practical Lab-to-Field Framework

The Deepfluid AIR Framework turns insights from bubble-level evidence into three entirely new practical engineering questions and metrics: 1 Air Intake Air Intake describes......

How Air in Oil gets Measured

Typically, oil condition monitoring is performed through standardized laboratory tests at specified intervals. A representative sample is taken on-site from the system being monitored and analyzed in the......

Role of Condition Monitoring, Human & Organizational Factors in Oil Failures

Choosing the right oil for the system is just one part of the puzzle. How do we know the oil is performing when it’s......

Common Modes of Failure for Lubricants

Regardless of the oil selected, common modes of failure can occur with every lubricant. These include: contamination, improper storage and handling practices, and environmental......

Critical Condition Monitoring Tests for Compressor Oils

To ensure these oils remain healthy (and not contaminated or degraded), a few basic tests can be performed on all compressors, regardless of type (reciprocating, screw, refrigerant, etc.). These include:...

How to identify the Root Causes of ESD in Lubrication

Thus far, all the prevention methods have focused on the physical roots of ESD. We did not explore some of the human or systemic roots that are also accountable for ESD. In this section, we will develop a logic tree designed to address a critical failure occurring in a plant. This will be used as an example of the logic tree, which can be developed when investigating the root causes of ESD...

What are Effective Strategies to Prevent ESD in Lubrication?

ESD occurs when there is a buildup of static in the oil; therefore, one of the best methods of preventing it is to ensure that the static levels remain low or are dissipated before they have a chance to wreak havoc on the system. The simplest and most common way of reducing this static is the installation of antistatic filters. These filters can help to remove static from the system before it builds up to dangerous levels, where it can burn the membranes or develop varnish...

Understanding Electrostatic Spark Discharge and Its Impact on Lubrication Systems

Electrostatic Spark Discharge typically occurs when static is built up in an oil at a molecular level, causing it to discharge in the system and create free radicals, which increase the opportunity for varnish to form. This usually occurs at temperatures of around 10,000 °C...

Interpreting the Oil Analysis Report in Practice

According to the report, samples have been collected over a period of time. This helps with the trending of the data, so we can spot when the values start varying from the “normal levels”. The reference values are also provided in the first column to help users determine whether these values fall within tolerance limits or not. Typically, the lab will provide some type of traffic light system...

How to Interpret Your Oil Analysis Results

Depending on the application and operating environment, certain conditions may be met that can be interpreted as unusual. Still, if you’re familiar with your system, you will understand the reason behind the numbers...

Why Different Oils Require Different Tests

Oil analysis reports often wear an invisible cloak, and only if we have a wizard capable of revealing what the numbers mean, they will......

Sensors vs Traditional Oil Analysis

In this age of AI, it seems that everyone is moving towards sensors and online data. Oil analysis sensors aren’t far behind in this......

How do you set oil-analysis limits for diesel fleets?

What Baselines should you use? Global oil suppliers have baseline or tolerance limits that are used when providing guidelines to customers about their equipment.......

Which parameters should you track in oil analysis?

      Every type of equipment will have different tests that should be performed to monitor its health. We will break down a......

What are the risks of pushing oil drain intervals beyond manufacturer limits?

Pushing drain intervals can lead to increased wear, contamination buildup, reduced lubricant efficacy and much more. There is always a danger in pushing limits;......

What are the safety and environmental benefits of extending oil drain intervals?

Extending intervals reduces waste oil volume, lowers exposure risk, cuts disposal cost...

How much money can you save by extending oil drain intervals?

Before diving further into the condition monitoring aspect, we need to answer the question, “Are there any real benefits to extending the oil drain......

What is condition monitoring and why does it matter in lubrication systems?

Condition monitoring began as a way to detect anomalies in our equipment using various types of technologies. These include: vibration, ultrasound, infrared, oil analysis,......

How to measure the Success of an Oil Analysis Program?

Documentation is always critical especially when we’re trying to build a case to implement some new measures. If previous failures have been documented, then the associated downtime and expenses such as additional labour, parts or expedited shipping and handling should also be taken account of...

How to Implement Oil Analysis for a mixed fleet

Ideally, the main objective of this program is to be able to monitor the health of the assets and prevent or reduce the possibility of a major failure or unplanned downtime. While it would be great to monitor the health of all the assets, this may not be entirely necessary...

How to read an Oil Analysis report

While oil analysis can help our teams identify more information about the condition of the oil, we still need to ensure that they can read the oil analysis report and put measures in place to deal with the issues which may arise...

What is Oil Analysis?

Inside the implementation of oil analysis for a mixed fleet of equipment, the impact of this program and ways the success of this method can be measured...

The Hybrid approach – Sensors & Labs

The article by Sanya Mathura and Neil Conway examines the merging both sensors and info from real labs to gauge the health of the oil...

Emerging technology – FluidInspectIR®

The article by Sanya Mathura and Neil Conway examines the emerging technology of FluidInspectIR and gauges its performance against actual lab tests...

Revolutionizing oil analysis: Traditional vs Cutting edge technology

The article by Sanya Mathura and Neil Conway examines the ongoing relevance of oil analysis, highlighting its evolution and current methods. It discusses traditional standards and the need for updates in response to modern equipment demands. The authors emphasize the importance of new technologies in improving the efficiency and accuracy of oil testing processes...

Is Oil analysis still relevant today?

Advancements in AI, machine learning, and sensors complement, rather than replace, traditional oil analysis. While models interpret data, human oversight remains crucial for decisions, especially in novel scenarios. Sensors provide early warnings, but labs ensure precise results. Oil analysis has evolved, using technology to enhance machine reliability and operational efficiency...

Oil analysis vs Other technologies

Oil analysis is akin to blood testing for machines, identifying wear particles and contaminants. Complementary methods like vibration, ultrasound, and thermography assess mechanical issues, providing a holistic view of machine health. By combining these technologies, asset reliability and maintenance are enhanced, leading to more precise diagnostics and better overall equipment performance...

Why oil analysis?

The P-F curve illustrates the expected functional failure point of a component. Among various monitoring technologies, oil analysis is a top method for early failure detection, identifying contaminants and metals. Standards for oil analysis, set by OEMs and bodies like ASTM, ensure global consistency. Reporting formats may vary, but the tests follow the same standards...

What is oil analysis?

Oil analysis is akin to blood tests for the human body, assessing the condition of machine oil and the health of machinery. It identifies wear, degradation, and additive depletion, offering valuable insights for maintenance planning. This process helps operators and maintenance personnel ensure machinery longevity and efficiency. More details are available in Engineering Maintenance Solutions Magazine...

Additives and their properties

Properties of Additives in Lubricants Each lubricant has a varying percentage of additives as not all lubricants are created equally. Lubricants are designed based......

When should an oil sample be taken?

“When should an oil sample really be taken?” In used oil analysis, oil samples can be taken at any time, but one should always......

Oxidation

What is Oxidation? One of the major types of oil degradation is Oxidation. But what is it exactly, as applied to a lubricant? Oxidation......

ISO 4406

A lot of people get confused when reading the ISO 4406 rating. The rating specifies a range of the number of particles of certain......

Lubrication failures in Ammonia plants

Quite often, when lubrication failures occur, the first recommended action is to change the lubricant. However, when the lubricant is changed, the real root......

Lubrication failures in Industrial plants

When failures occur in industrial plants, the first culprit to be suspected is usually the lubricant. However, should this be the first area that......

How can a lubricant fail?

How can a lubricant fail? This question has caused many sleepless nights and initiated countless discussions within the industrial and even transportation sectors. Before......

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From Measurement to Action

Start measuring the air in your system. The most useful air-in-oil measurement is not the one that produces the largest number of parameters. It is the one that supports a better engineering process.

  • Define a representative baseline.
  • Detect a meaningful deviation.
  • Interpret it together with fluid, component, and operating context.
  • Investigate the most plausible mechanism.
  • Verify whether the intervention changed the measured behavior.

Many practitioners only view air as an issue when they see foam. By this time, it is too late and damage has already occurred to the system. Even small bubbles can have system consequences, as shown in the diagram below.

figure 6
Figure 6: System-level consequences which can be detected by the presence of small bubbles through deepfluid’s technology

Many operators are not aware of the impacts of air-in-oil and quite often, it is labelled as something else. However, it usually shows up as a foam problem, unexpected NVH, control instability, temperature problem, cavitation problem, pump problem or an oil problem. The key is to monitor these effects in different settings.

Starting with studying air release, dispersion and formulation effects under controlled conditions in the lab. Moving to the testing phase where bubble behaviour is related to operating conditions, design changes and system response. Then finally to the field where changes can be tracked over time to support root-cause analysis and confirm any improvements.

This is the benefit of using the deepfluid technology as it can capture data from the various phases to bring about actionable insights to improve the reliability of operating systems.

The 360 Approach – One Shared Data Language Across the Lubrication Value Chain

At Deepfluid, they have adopted a 360 approach where they can assist all the stakeholders involved in the lubricant industry as it relates to the oil being in the equipment. It connects formulation development, laboratory testing, component testing, system validation, field operation, maintenance, troubleshooting, and verification of corrective actions.

With the 360 approach, various stakeholders can be involved to ensure that the lubricant is fully assessed in different situations, from the testing and development of the lubricant to its actual application in the component then finally to the end user by ensuring they get the results they need.

An additive supplier may investigate formulation effects. A lubricant manufacturer may compare air-release and foam behavior. A filter or seal supplier may study aeration or air ingress. An OEM may correlate bubble behavior with efficiency, thermal management, or NVH. An operator may investigate an abnormal field deviation. An external oil laboratory or research institution may provide controlled reference analysis.

The questions differ, but the underlying air-in-oil metrics can remain comparable.

Not one product for every stakeholder, but one measurement logic that allows different stakeholders to work on the same fluid-system question from different positions in the value chain.

The 360 approach ensures that all aspects are taken into consideration for the oil, from the lab testing to the field development, with all the stakeholders involved. This guarantees that the final product is reliable and the user should have a valuable experience.

Case Study – From Abnormal Air-in-Oil Data to a Targeted Seal Investigation

Deepfluid’s direct measurement system can be used not only to analyze the interaction between oil and air during operation but also to monitor the overall system behavior and the reliability of the installed components.

The leak-tightness of hydraulic circuits is essential and critical for the safe operation of these systems. Leaks can allow air and particles to be drawn into the system under negative pressure and oil to be forced out of the system under positive pressure. The presence of air significantly alters operating behavior by changing viscosity, density, fluid level, and lubricating film thickness. These factors can lead to damage such as pitting, scuffing, and micro-dieseling.

If an operator or service technician frequently inspects an application’s oil tank—either directly or through large sight glasses—high air content can be detected by significant cloudiness in the oil.

However, if the application’s oil tank is located in a hard-to-reach position, operates autonomously, or is only accessed during shutdown, such extreme conditions are detected very late, in the laboratory—if at all—before costly damage occurs. This is the case with the operation of wind turbines. Although speed, torque, temperature, particle content, and potential oil leaks are detected, suction-side air ingress, for example, cannot be detected.

figure 5A
Figure 5A. Recurring Air-in-Oil Deviation During Gearbox Operation. A synchronized view of air content, pressure context, and bubble population illustrates how recurring events can support a targeted investigation of possible suction-side or sealing-related air ingress.

In the case study presented, a defective shaft seal was detected through direct measurement on a supply pump for the injection lubrication system of a wind turbine, based on an iteratively and periodically occurring very high air content and loud noise. A minor issue that can have serious financial consequences.

Risks posed by excessive air content and their costs, using a 2.5 MW turbine as an example:

  • Higher operating temperature, which requires additional cooling
  • Increased cooling capacity (between 4.9 kW and 9.4 kW) due to reduced thermal conductivity (0.14 W/(mK) → 0.125 W/(mK)), costing between 7k€ and 10k€ per year
  • Change in friction conditions in conjunction with increased cooling capacity: 43k€–82k€ per year
  • Risk of faster oil aging due to accelerated oil oxidation and thermal oil oxidation: 1 additional oil change (24k€–60k€)
  • Total mechanical failure of the main gearbox renders the entire system uneconomical.

In this component, there was persistently high air content which we are able to identify and link to abnormal ingress of air into the lubrication system. However, we also saw the pressure drop during pump operation. This was an indicator for suction-side or sealing-related air ingress. We also noticed a dense bubble population which indicates critical oil-air dispersion under operating conditions. There was a deviation from a similar gearbox indicating that this was a system-specific malfunction rather than normal behaviour.

If these were not identified at this early stage, the equipment would run the risk of micro-dieseling, cavitation, oxidation and temperature increase. This would lead to mechanical damage in the gearbox or oil supply components, eventually leading to reduced lubrication reliability and accelerated wear.

One Portfolio for Controlled and Dynamic Evidence

The Deepfluid portfolio applies this methodology through three connected solutions.

 

The Air-in-One Lab Analyzer establishes controlled references.

The Optical Inline Sensor captures dynamic behavior.

visiQ connects both into a comparable engineering process.

 

figure 4
Figure 4. One Measurement Logic from Lab to Field. From Lab to Field does not mean that laboratory, test-rig, and operating conditions are identical. It means that the same Air Intake, Retention, and Release logic—and the same bubble-level metrics—can be applied across different environments and compared within one engineering workflow.

Deepfluid Air-in-One Lab Analyzer

The Deepfluid Air-in-One Lab Analyzer combines air release, foam, and time-resolved bubble behavior within one integrated and automated workflow.

Defined aeration, fluid handling, automated temperature conditioning, optical measurement, foam observation, data transfer, and cleaning can be connected into repeatable test sequences. A fully automated AIR test can capture the complete progression from baseline through Air Intake and Retention to Air Release.

Throughout this sequence, the system measures the physical development of the oil-air dispersion rather than only recording a final release time or foam volume, including Air Content, Bubble Size and Bubble Size Distribution, Bubble Count and Bubble Population, Oil-Air Interfacial Area, and time-resolved Intake, Retention, and Release behavior.

The Air-in-One Lab Analyzer also supports automated test campaigns. Lubricant and additive developers can compare fluid candidates, formulation variants, additive packages, antifoam concentrations, temperature profiles, or aeration durations using the same test logic and evaluation structure.

This makes it possible to investigate not only whether a fluid meets a defined air-release or foam specification, but also why different formulations produce different Air Intake, Retention, Release, and foam responses. Engineers can examine how the bubble population develops before visible foam forms, how much air remains dispersed after aeration stops, and how temperature or formulation changes influence the subsequent recovery.

The approach is not intended to replace standardized ISO or ASTM air-release or foam tests. These methods remain essential for reproducible specification checks and lubricant qualification. The Air-in-One Lab Analyzer adds a complementary, process-aligned R&D perspective that goes beyond a single pass/fail value.

It enables lubricant developers, test engineers, and technical decision-makers to investigate the mechanisms behind Air-in-Oil behavior, compare formulations under application-related conditions, and develop a more complete understanding of Air-in-Oil Contamination before it becomes a field troubleshooting issue.

Standardized tests confirm whether a requirement is met. The AIR workflow helps engineers understand how the result develops—and how that behavior translates from Lab to Field. It is not a replacement for the standardized tests but rather a tool to understand Air-in-Oil Contamination from an R&D perspective.

Deepfluid Optical Inline Sensor

The Deepfluid Optical Inline Sensor transfers the AIR Framework into dynamic test and operating environments.

Instead of recording only a single air-content value, it can capture complete Intake, Retention, and Release behavior over defined time windows. Engineers can observe when a bubble population begins to form, how rapidly it develops, which size classes dominate, how much air remains dispersed after the operating state changes, and how quickly the system returns toward its baseline.

This adds a time-resolved view of transient events. A load change, speed ramp, thermal transition, pressure drop, component-switching event, or start-stop cycle can be evaluated as a complete AIR sequence rather than as an isolated data point.

The sensor can be used in representative inline or bypass configurations, subject to application-specific review. All device configurations have also been developed for demanding high-pressure applications above 150 bar.

When bubble-level data are combined with temperature, pressure, speed, load, flow, efficiency, vibration, or noise, the measurement supports direct comparison between fluids, components, machine variants, and operating conditions. It can also be used to verify whether a design change or corrective action altered the measured Air Intake, Retention, or Release behavior.

The sensor does not automatically diagnose a root cause. It records how the dispersed air phase responds to a defined event, operating state, or intervention and provides evidence for a more focused engineering assessment.

visiQ by Deepfluid

visiQ by Deepfluid provides the common comparison and reporting layer.

Devices and measurement sessions can be assigned to projects, enabling structured data management across development programs, test campaigns, and field investigations. Evidence Snapshots remain linked to the corresponding measurement points and operating context.

The platform supports machine-to-machine, system-to-system, component-to-component, fluid and formulation, and before-and-after comparisons.

For example, the same machine and lubricant can be evaluated under different ambient conditions or load cycles. Conversely, different components can be compared under the same operating profile, or similar machines can be benchmarked across locations. This helps engineering teams distinguish more systematically between fluid-related, component-related, system-related, and environment-related differences.

visiQ also supports automated reporting, reducing the effort required to compile recurring test results, before-and-after comparisons, and structured project summaries.

One Shared Data Language – From Lab to Field

Particularly for OEMs, it is important to be able to transition the product from the lab to the testing phase, then into the field. In the lab, they can control the operating conditions, study the air intake and release, dispersion and formulation effects. Afterwards, they can relate bubble behaviour to operating conditions, design changes and system response. Finally, they can execute in the field and track the changes over time to support any root cause analysis for the future and confirm improvements. This is a movement from controlled conditions in the lab to dynamic conditions in testing to finally real-world conditions in the field.

Typically, conventional sensors will give parameters such as a change in dielectricity, a foam tendency, some noise or vibration and an oil condition change just as a result, without knowing the root cause. However, with Deepfluid, they are able to actually make physical behaviour visible and directly explainable. The size and shape of a bubble can be seen, classified and quantified. This allows for the actual oil-air contact surface area to be determined, and this can be trended over time to establish patterns.

What Recurring Patterns Can Bubble-Level Data Reveal?

Direct optical measurement does not identify a root cause on its own. Its practical value lies in revealing repeatable physical patterns that can be compared with operating conditions, representative baselines, and similar systems.

Examples include:

  • An increasing population of small bubbles under steady load may be consistent with continuous air ingress or churning.
  • Recurring air-content spikes synchronized with pump starts, pressure drops, or speed changes may point to an event-related source of Air Intake.
  • A shift toward larger bubbles following a load or pressure transition may reflect bubble expansion, coalescence, or the beginning of Air Release.
  • A slow return to baseline after an operating event indicates that air remains retained in the fluid-system combination or is released only gradually.
  • Similar Air Content with different bubble-size distributions, bubble counts, or oil-air interfacial areas shows that the physical state of the dispersion is not necessarily the same.
  • Different AIR profiles under comparable operating conditions can help distinguish normal system behavior from a machine-, component-, or environment-specific deviation.

Before-and-after measurements add another practical dimension. By repeating the same operating cycle after a change to a seal, reservoir, component, fluid, or control strategy, engineers can verify whether the intervention altered Air Intake, Retention, or Release behavior.

These observations should be treated as investigation signals rather than automatic diagnoses. Their meaning becomes clearer when bubble-level evidence is evaluated together with pressure, temperature, load, speed, flow, vibration, noise, and a representative baseline.

AIR as a Practical Lab-to-Field Framework

The Deepfluid AIR Framework turns insights from bubble-level evidence into three entirely new practical engineering questions and metrics:

1 Air Intake

Air Intake describes not only how quickly air enters the fluid system and under what conditions it is generated or introduced, but also how much air the oil can actually absorb over a specific period of time.

2 Air Retention

Air Retention describes how much air remains dispersed, how long it remains in the system, and how the bubble population changes.

3 Air Release

Air Release describes how quickly and completely the fluid-system combination returns toward its baseline after aeration or an operating-state change. By having the Air Intake value, Deepfluid addresses a new question that has not yet been covered by conventional air release laboratory tests: “At what initial air content by volume does my air-release measurement actually begin?”

AIR is not an abstract research model. It is a practical structure for planning tests, defining measurement windows, comparing fluids, evaluating component and design variants, analyzing operating states, and verifying corrective actions.

figure 3
Figure 3. The AIR Framework: Intake, Retention, and Release. The AIR Framework structures air-in-oil behavior as a time-resolved sequence. In controlled testing, aeration duration, temperature conditioning, measurement intervals, and recovery phases can be defined; the same logic can be applied to operating events in testing and field environments.

In the laboratory, air release no longer has to be viewed only as a single endpoint under one fixed condition. Individually defined aeration durations, automated temperature conditioning, and time-resolved optical measurement make it possible to run a fully automated AIR test.

Such a sequence can establish a bubble-level baseline before aeration, follow the bubble population during a defined Air Intake phase, quantify Air Retention after the air supply stops, and measure the Air Release curve over time. The same workflow can connect air content, bubble-size distribution, and bubble-population dynamics with subsequent foam formation and foam decay.

This makes it possible to compare different fluids, additive concentrations, temperatures, or aeration durations within structured, automated test campaigns. The laboratory therefore moves closer to application-related questions without giving up controlled and repeatable conditions.

In testing and field operation, the same AIR logic can be applied to defined operating windows. A cycle may begin at a stable baseline, follow an increase in air content during a load, speed, pressure, or temperature change, quantify how much air remains dispersed, and measure recovery afterward.

The resulting bubble-level metrics can be related to operating data such as temperature, pressure, speed, load, flow, efficiency, vibration, or noise.

The conditions are not identical across lab, testing, and field environments but the measurement logic is.

AIR turns air release from a single laboratory result into a practical understanding of the full cycle around how air enters, remains, and leaves a fluid system.

How Air in Oil gets Measured

Typically, oil condition monitoring is performed through standardized laboratory tests at specified intervals. A representative sample is taken on-site from the system being monitored and analyzed in the laboratory under controlled conditions. This allows for a detailed analysis of numerous parameters that reflect the condition of the oil, such as viscosity, density, and air release behaviour in accordance with DIN ISO 9120.

However, when the sample is pulled from the equipment, it must travel some distance to the lab. During this transit, the oil sample may lose some characteristics that defined the system in which it was operating. While this does not corrode the integrity of the sample, it may not define an accurate representation of system conditions.

In the laboratory, it is not possible to correlate the oil’s interaction with the system’s behavior, which is characterized by constantly changing process conditions such as pressure, temperature, flow rates and air-contents. As these process conditions change, the measurable properties of the oil also change proportionally, and these properties directly determine the efficiency and service life of both the system and the oil. Comprehensive monitoring of the system’s condition can therefore only be achieved through laboratory analysis in conjunction with field measurements.

This approach allows for direct measurement of how the oil interacts with the equipment and generates data points that were previously unthinkable. This enables operators to make predictions that can extend the service life of the oils and make plant operations more efficient or less prone to errors.

 

What Gets Measured

It is well known that, during the operation of hydraulic systems and transmissions, air is inevitably though unintentionally mixed into the oil. The air content alters the oil’s properties by creating a multiphase mixture, thereby influencing measurable operating parameters in both the short term (efficiency, NVH, temperature) and the long term (oxidation, additive depletion, oil aging).

The Deepfluid bubble profiling technology combines an intelligent vision module and an intelligent LED system. This captures real-time images of the fluid as it flows through the device. Through the use of computer vision-based image processing, each air bubble is identified, sized and classified on a continuous basis. This allows trends and patterns to be recognized and established. No on-line calibration and constant re-calibration is required for this equipment, and it can work across various types of oils with different viscosity ranges and colors or aging-states.

The Deepfluid optical approach evaluates bubbles within a defined size range of 8 to 500 micrometers and generates time-resolved information such as:

  • air content,
  • bubble-size distribution,
  • bubble count,
  • bubble-population dynamics,
  • oil-air contact surface / interfacial area, and
  • transient air events.
figure 1
Figure 1. Same Air Content. Different Bubble Behavior. Two fluid states can show the same volumetric air content while differing in bubble-size distribution, bubble count, oil-air interfacial area, and release tendency. Air content alone does not fully describe an oil-air dispersion.

Until now, measuring air content has been possible primarily through indirect analytical methods. In this approach, the conductivity of the oil, excluding air content, was referenced to the conductivity of the oil-air mixture during operation. This allows for the analysis of air content percentages under constant conditions. The biggest problem with this measurement is the change in the oil during continuous operation of the system, since water content, particle content, temperature, and additive content are constantly changing, making continuous measurement during operation impossible.

As shown above in Figure 1, the traditional method of measuring the air volume does not accurately depict what is happening in the oil. The air volume of 0.65% only measures one aspect of the oil. With the direct measurement by Deepfluid, users can get deeper insights and explore another dimension of oil condition monitoring by measuring the bubble diameters during operation and compare it with the same technology in a lab-based air-in-oil analysis. Based on this information, short term behaviour (density change, viscosity change, lubricant film thickness, Air-Intake, Air-Release-Behaviour, thermal conductivity and NVH) as well as long term response (oxidation, additive depletion, mechanical robustness, risk of pitting) can be detected and their respective influence targeted.

A key feature is the availability of so-called Evidence Snapshots. Each calculated measurement point can be linked to an optical image of the fluid at that moment. Engineers can review the underlying image, verify the detected bubble population, and relate an unusual value to the physical condition on which it is based.

This creates point-level traceability between the calculated metric and the visible evidence.

Evidence Snapshots do not replace numerical specifications for repeatability, accuracy, or measurement uncertainty. They add transparent verification and support more informed technical discussion between lubricant developers, test engineers, component specialists, and reliability teams.

figure 2
Figure 2. From Optical Evidence to Quantitative Bubble-Level Data. Direct optical measurement links calculated air-in-oil metrics to the underlying fluid image. Evidence Snapshots provide point-level traceability between air content, bubble-population data, and the recorded physical condition.

The optical approach has also been demonstrated with visually challenging fluids, including dark, aged, and soot-loaded engine oil. As with any optical method, application limits must be understood. However, Deepfluid’s bubble-level analysis is not restricted to transparent new oils.

The objective is not to replace conventional oil analysis, pressure, temperature, vibration, or standardized air-release and foam testing. It is to add direct evidence about the dispersed air phase and its dynamics.

Role of Condition Monitoring, Human & Organizational Factors in Oil Failures

Choosing the right oil for the system is just one part of the puzzle. How do we know the oil is performing when it’s in the system? This is where condition monitoring can work hand in hand to help ensure that the oil does not fail the asset.

If a proper oil analysis program does not exist, operators will not know whether the oil is properly lubricating the asset. They will also not be aware of whether the oil is breaking down too quickly and failing to protect the asset. Oil analysis can also alert operators to signs of wear in the asset, so they can fix them before they turn into functional failures.

An oil analysis program that lives in a drawer protects assets about as well as no program at all.

There is also the possibility that an oil analysis program exists but is not top of mind, or that its results are put in a drawer. This can also cause the asset to fail even though the correct oil is being used. Apart from the aforementioned factors, if operators are not warned of the impending failure of the oil, this can result in production losses, increased downtime, and, in some extreme cases, the complete loss of the asset if it has failed beyond repair.

Incorrect sampling is another area in which the actual condition of the asset is not reported. Even with the correct oil used, if a sample is collected from a dead leg or an area that is not truly representative of the conditions inside the component, its actual condition will not be known. With incorrect data about the component, the asset can be misdiagnosed or treated for symptoms that do not exist, which can lead to its detriment.

Human and Organizational Factors

Not all failures occur at the equipment level; human and organizational factors can also cause the asset to fail even when the correct oil is used. If humans aren’t properly trained in oil sampling techniques or storage and handling practices, these can affect the asset’s functionality. We often forget that, at the heart of it all, lies the human factor, which is partially governed by the organization’s systems.

Training needs are an organizational factor that is often overlooked when considering how an asset can fail. However, if operators have not been trained in condition monitoring techniques, they will not be able to read oil analysis reports or take appropriate actions to protect the asset. Training can help bridge some competency gaps that directly impact asset performance.

It doesn’t matter what oil is in the system if no one is trained to monitor it – or motivated to care.

Culture is another factor swept under the rug. If the culture doesn’t exist to look after the assets, it doesn’t matter what type of oil is placed in the system; the asset will fail eventually. The performance of the asset does not only rely on using the correct oil. By implementing a culture of Asset ownership, where operators look after the asset and are accountable for its performance, assets are optimized to provide the functionality they should. This is one way to ensure the right oil is used to enable the assets’ performance.

Another area of concern is the documentation of maintenance procedures. If maintenance procedures are not adequately documented, someone new to the operation may not be aware of the correct practice. This, coupled with a lack of training, can spell disaster for the equipment. In these cases, even though the right oil was selected, the wrong practice or lack thereof can fail the asset.

Turning the “Right oil” into the “Right Outcome.”

As explained in this article, improper practices can jeopardize the asset’s health, even when the right oil is used. However, if all the right things align, we can have an asset that lasts for its expected lifetime or beyond.

This starts with selecting the right oil based on the application, environmental conditions, and OEM recommendations. If we follow this up with good storage and handling practices, proper condition-monitoring programs, documentation, and training, we can look toward a longer-lasting asset. The right oil enables reliability – but only disciplined practices deliver it.

Find out more in the full article, "When 'Right oil, Wrong practice' still fails assets" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd. 

Common Modes of Failure for Lubricants

Regardless of the oil selected, common modes of failure can occur with every lubricant. These include: contamination, improper storage and handling practices, and environmental factors as shown in Figure 4.

Figure 4: Common modes of failure for lubricants
Figure 4: Common modes of failure for lubricants

Contamination can be defined as any foreign particle entering the system. This includes any gases, liquids, or solids. Especially when the lubricant system runs alongside the process side, process gases and liquids can leak into the oil. These contaminants can influence the oil’s degradation, leading to deposits or chemical reactions that break it down. Common process contaminants include ammonia or treated water.

The biggest threat to the right oil is often what gets added to it – whether it’s process contamination or the wrong oil during a top-up.

Another liquid that can contaminate oil is another oil. During top-ups, operators can add the wrong oil to the system, causing contamination and, depending on the oil, a possible shutdown. Adding motor oil to hydraulic oil can be catastrophic, as the additive packages work differently and the motor oil additives may counteract the hydraulic additives, removing them from the oil, leaving the asset open to wear and failure. Despite selecting the correct lubricant for your system, adding the wrong oil (mistakenly) will shorten its lifecycle and cause the asset to fail.

Bad storage and handling practices can also erode your oil, regardless of the oil you choose. Turbine and hydraulic oils are used in precise equipment. As such, they need to be clean and free of dirt or other contaminants. However, if oils are not stored correctly, contaminants can enter and contaminate the oil.

Simple techniques, such as transferring oil from larger storage containers (pails, drums, or totes) into smaller, more manageable containers (2-3 liters or less), can introduce contaminants into the oil if not done correctly. If oils are to be transferred to another storage container, the storage container must be clean. The transfer process should use clean hoses (not previously used for another lubricant) and be completed in a dust-free environment.

If you wouldn’t use a dirty needle for a blood transfusion, why would you use a dirty hose for an oil transfer?

The transfer of oils from one container to the next can be thought of as a blood transfusion. Would you use dirty needles or vials to transport the blood to be placed into another human? Similarly, oil can be likened to the equipment’s lifeblood and should be treated accordingly. Just as we observe sterile practices for blood transfusions, we should also observe similar types of practices for oil transfers.

Environmental and operational factors can also influence lubricant degradation. As stated earlier, all lubricants can degrade over time under harsh conditions. The lubricant formulation largely influences this, as does whether it was blended to withstand those conditions.

Oxidation can easily occur when temperatures increase, free radicals are present, or when wear metals are present. Thermal degradation occurs when the temperatures exceed 200°C. On the other hand, microdieseling occurs in the presence of entrained air, despite the lubricant used in the system, as shown in Figure 5.

Figure 5: Lubricant Degradation Processes
Figure 5: Lubricant Degradation Processes

Any of these degradation mechanisms can occur regardless of the type of oil chosen. Hence, it is essential to remember that operational conditions and environmental factors can heavily influence oil degradation, even when the oil is appropriate for the system.

Find out more in the full article, "When 'Right oil, Wrong practice' still fails assets" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd. 

Critical Condition Monitoring Tests for Compressor Oils

To ensure these oils remain healthy (and not contaminated or degraded), a few basic tests can be performed on all compressors, regardless of type (reciprocating, screw, refrigerant, etc.). These include:

  • Viscosity – this is key as some of the gases can easily affect the viscosity, which (if decreased) will not provide adequate separation for the interacting surfaces and cause wear. Generally, a ±10% limit is used (though OEMs may use different values).
  • Acid Number – if this begins increasing, then we have an accumulation of acids in the oil, which can be because of contamination. For most compressors, a 0.2 mg KOH/g increase is the warning limit, but for refrigeration compressors, the limit is tighter at +0.1 mg KOH/g. Always check with your OEM for these limits.
  • Water content – changes by OEM and refrigerant type, as the different gases will have varied tolerances.
  • Wear metals – these values will vary as per OEM, as well, since they are all designed with different types of metals. Users should look for trends or significant increases in these values to indicate wear.

Some specialty tests for compressors include:

  • MPC (Membrane Patch Colorimetry) – this helps to measure if there is any potential for the oil to form varnish. Given the high temperatures these types of equipment endure and the potential for contamination, the oil is at risk of forming varnish. While limits will vary by OEM, some general guidelines to follow are 0-20 Normal, 20-30 Warning, >30 Action required
  • RULER® (Remaining Useful Life Evaluation Routine) – this quantifies the remaining level of antioxidants in the oil. When oxidation occurs, the antioxidants get depleted. As such, by monitoring antioxidant levels, one can easily determine whether oxidation is happening in the oil. The general rule of thumb is that if the level falls below 25%, there are not enough antioxidants to keep the oil healthy and prevent degradation.
  • Air Release (DIN ISO 9120) – measures the ability of the oil to allow air to escape and not keep the air in the oil. If air bubbles remain in the oil, this can be devastating, as it can lead to micropitting, cavitation, or increased oxidation. Users can trend the values; if they increase, it indicates that the air is taking longer to be released, which means it is staying in the oil and in the system longer.
  • Particle Count – this can identify if there are any contaminants in the system. These oils must be kept clean, and OEMs typically specify target cleanliness levels.

Compressors are critical equipment, and we must understand how they work and the lubricant specifications required. Monitoring their health can also help us avoid unnecessary downtime and keep our facilities running.

References

  1. Mang, T., & Dresel, W. (2007). Lubricants and Lubrication. Weinheim: WILEY-VCH Verlag GmbH & Co. KGaA.
  2. Totten, G. E. (2006). Handbook of Lubrication and Tribology – Volume 1 Application and Maintenance – Second Edition. Boca Raton: CRC Press.
  3. Shell Lubricants. (2025, November 08). The Shell Corena range. Retrieved from Shell Lubricants Compressor Oils: https://www.shell.com/business-customers/lubricants-for-business/products/shell-corena-compressor-oils/_jcr_content/root/main/containersection-0/simple_1354779491/promo_1484925192/links/item0.stream/1759302155345/17be2a9a74057f321bb209128933f68f8b88ca70/s
  4. ExxonMobil. (2025, November 08). Refrigeration Lubricant Selection for Industrial Systems. Retrieved from ExxonMobil Lubricants: https://www.mobil.com/lubricants/-/media/project/wep/mobil/mobil-row-us-1/new-pdf/refrigeration-lubricant-selection-for-industrial-systems.pdf
  5. Chevron Lubricants. (2025, November 08). Optimizing compressor performance and equipment life through best lubrication practices Chevron. Retrieved from Chevron Lubricants: https://www.chevronlubricants.com/content/dam/external/industrial/en_us/sales-material/all-other/Whitepaper_CompressorOils.pdf

Find out more in the full article, "Compressor Oil, Types, Applications and Performance Drivers" featured in Precision Lubrication Magazine by Sanya Mathura, CEO & Founder of Strategic Reliability Solutions Ltd.