Predictive maintenance of a compressor

How does a compressor work in a refrigeration system?

Any industrial plant or commercial area that require refrigeration will have, with a few minor exceptions, one or more compressors installed. These devices are one of the cornerstones of any refrigeration plant, as they generate the necessary work to move the circuit’s gas from a lower-pressure zone to a higher-pressure one, thus creating two differentiated areas, but how exactly do they work?

Generating cold consists, in simple terms, in absorbing a room’s heat to reduce its temperature and, subsequently, evacuating it. To achieve this, we usually resort to refrigerants, fluids that are circulated through a closed circuit to create high and low pressure zones, which are separated by the expansion valve. There, the saturated (or subcooled) refrigerant loses its pressure, causing an isoenthalpic pressure drop that provokes that the refrigerant become a two-phase flow that consists of liquid and vapour (80% and 20%, approximately). Finally, once the mixture enters the evaporator, it absorbs heat energy from the surroundings.

In the case of those machines that base their functioning on the refrigerants’ change of state, the compressor must increase their pressure so that outside temperature is enough to trigger this change.

Why is the predictive maintenance for air compressors important?

Once this is understood, it is possible to realise that compressors are crucial for any industrial or commercial refrigeration system. In particular, its maintenance is essential, among other things, to:

  • Extend the useful life of the installation’s components.
  • Avoid production stoppages.
  • Avoid product loss.
  • Increase energy efficiency.
  • Reduce the company’s environmental impact.

Consequently, it is not advisable to opt for a corrective kind of maintenance in cases in which the installation must be available most of the time and/or in which this equipment’s failure could put production and/or personal safety at risk. In these contexts, the organisation should consider taking preventive or predictive maintenance actions, although the latter is the most common one among Industry 5.0 companies. Thanks to the latter, not only do they manage to anticipate possible errors, but they also have the capability to know the state of their installation at all times, which helps to design much more effective maintenance plans.

Predictive and preventive maintenance techniques for compressors

We could mention numerous techniques aimed at monitoring the variables that have a major impact on the compressor’s performance; however, experts recommend the following maintenance tasks.

Predictive maintenance vibration analysis

Predictive maintenance vibration analysis is a type of action that can be applied to multiple components. However, it has proven to be especially useful to analyse the compressors’ status, as they are part of a closed circuit and this kind of test allows us to know, without accessing the inside of the circuit, if the play between pieces has increased, if there is any component that has loosened, if the system has been overstressed, etc.

Moreover, predictive maintenance vibration analysis takes into account those characteristics of the machinery that may affect their vibration (such as rotational speed, type of support or type of gear) to detect anomalies and diagnose them. Vibrometers (the devices that indicate the vibrations’ value) can be used to identify them, but, nowadays, sensors can be programmed to collect this same information in real time and on a continuous basis. This provides more reliable data, as it is always extracted from the same point, the sensors are always calibrated and there is no human intervention.

Different methods can be used for this purpose, such as applying a fast transformation algorithm, creating a digital reconstruction of the signal (thanks to the installation of accelerometers) or calculating the expected vibration spectrum. However, the most common ones are listed below.

  • Wave-form analysis: it takes into consideration the vibration’s magnitude and time as variables.
    • Phase analysis: it measures the time difference between two vibration waves that have the same period.
    • Spectral analysis: it studies the vibration’s magnitude with respect to frequency.
  • Vibration sensors: they transform vibrations into electrical signals.
    • Speed
    • Acceleration
    • Displacement: it measures the movement between the bearings and the shaft.

Noise analysis for predictive maintenance

Noise analysis is particularly useful for industrial plants, since, like vibration analysis, it allows to know the machinery’s state without halting production and avoiding the manipulation of the devices. Ultrasound analysis makes it possible to detect noises that may be generated both by the compressor or by its components, which may be caused by leaks, problems in the electrical circuit or by mechanical malfunctions, among others.

These systems combine machine learning, IoT, algorithms and big data analysis to obtain information remotely and in real time. Therefore, sensors must be installed in the machinery in order to study the sound waves generated as a result of the compressor’s operation, which have certain characteristics. Then, the monitoring systems record these ultrasounds and, when their acoustic characteristics change, this variation is analysed to identify the potential problems that may be behind it.

In combination with vibration analysis, this system allows technicians to carry out a highly effective predictive maintenance on equipment that, due to its function and/or price, should not be manipulated and/or cannot be stopped frequently.

Lubricant analysis (condition monitoring)

Generally speaking, the analysis of lubricants is aimed at ensuring that they be in good condition, which has a direct impact on the product’s own lifespan and, therefore, on costs savings and on the company’s environmental footprint. Indirectly, however, this kind of maintenance also helps to preserve the compressor’s components.

Some of the variables that are measured are: the lubricant’s status and the presence of pollutants and of contamination produced by worn components. This is possible thanks to the assessing of parameters such as the presence of water and nonferrous particles, the dielectric constant, the viscosity, etc.

  • Oil condition. It is necessary to check the lubricant’s condition to see if it needs to be replaced or to schedule its replacement. This is particularly important, as a poor condition can lead to important failures.
  • Presence of contaminants. Due to the lubricant’s function, it will become contaminated with water, dirt, etc. As a consequence, the technician should try to determine the amount of solids (through nonferrous particle indicators and other methods) and water (measuring humidity) present in the mixture.
  • Presence of worn components. Machines deteriorate, thus producing ferrous and nonferrous debris. Its analysis can be very useful to detect the equipment’s corrosion.

Some of the most common techniques for assessing these parameters are listed below.

  • Count of particles. This analysis measures the amount of contaminants and particles present in 1ml of fluid, categorising the latter into 5 classes according to their size. This not only determines the condition of the oil, but it also indicates the level of contamination caused by the process, by filtration and by insulation. This count can be done by microscope, but spectrometric analyses can be more effective.
  • Spectrometry. It is able to differentiate 3 types of elements: additives, debris and contaminants, so it is easier to know if the pollutants are environmental or if they are produced by the process or by the deficient handling of the lubricant.
  • X-ray spectroscopy. It is not limited to particles smaller than 8 microns. However, it has the disadvantage that its results are not very reliable for elements below Mg. (12).
  • Direct reading ferrography. A magnetic field is used to attract the lubricant’s pollutants, which will be distributed along a glass tube according to their characteristics and dimensions. Subsequently, an optical analysis is applied to obtain the necessary information about the deposits.
  • Karl Fischer. This a method to measure the amount of water or moisture present in the lubricant. It should be noted that this type of contamination can cause serious failures, as it prevents the lubricant from doing its job and can lead to corrosion, blockages, pickling, vapour locks, etc.
  • Acidity. This analyses the concentration of acidic elements, which may indicate a high rate of oxidation. This, in turn, can lead to the corrosion of the elements with which the lubricant is in contact.
  • Viscosity. This studies the lubricant’s resistance to flow, which gradually increases due to evaporation and to the existence of pollutants. Viscosimeters are the tools used to measure changes in viscosity and, if they determine that it has increased or decreased (by more than 20% or 10%, respectively) from the initial values, the lubricant should be changed.

Predictive maintenance for air compressors’ main components

These predictive maintenance techniques can also be applied to some of the compressors’ most important components, such as the electric motor that powers them or their bearings. For this reason, now we will offer an overview of industrial electric motor preventive maintenance and bearing maintenance.

Industrial electric motor preventive maintenance

These devices, which are used to convert electrical energy into mechanical power, have many components (spools, poles, switches, etc.), so there are numerous tests available to assess their functioning.

  • Insulation resistance. This consists in assessing the electrical resistance of an element that is placed between two conductors. This calculation is made by measuring the current produced after applying direct voltage to this element and its result will depend on the voltage applied, as well as on contamination and on temperature. This test can be used to identify faults such as:
    • An increase in conductive current.
    • An excess of capacitive current.
    • An augmentation of the absorption current, which is associated with the depolymerisation of the insulators.
  • Electrical winding resistance. The ammeter-voltmeter method is used to study the electrical resistance by applying a current similar to the rated current. This reveals whether the resistance of the windings has decreased (which may be indicative of short-circuits) or whether, on the contrary, it has increased (which may be a symptom of poor-quality welds).
  • Influence of the rotor. This analyses the stator’s inductance, as well as the variables that may affect the rotor (such as eccentricity, magnetic defects, its alignment, etc.)
  • Starting test. This checks the current at startup to make sure that the peak value is from 7 to 10 times higher than the current’s magnitude at its steady state.
  • Frequency. Maximum and minimum values, as well as a “zone of risk”, are established in order to know when the motor should be checked. This test is also used to measure the motor’s eccentricity, for which 4 non-harmonic peaks are compared to the mains frequency.

Bearing maintenance

The functioning of the bearings is subject to the effect of multiple variables. The most important of these is mechanical stress, which means that proper lubrication is key, as we have explained above. However, there are other factors that must be also taken into account to ensure their effectiveness.

Firstly, they should be inspected to make sure there are no crackings. These can be provoked by stress, corrosion or wear, so it is advisable to manufacture the bearing-race from stress free materials. In addition, their coating should be improved to resist spallation and be non-porous.

Although it may seem obvious, it is also important to check that the shafts are properly aligned. Alignment faults can be detected by noise and vibration analyses, as well as by monitoring energy consumption.

Carrying out heat measurements, cleaning the bearings and monitoring the lubrication are also extremely advisable. Furthermore, it is important to look for evidence of electrical discharge machining, which are microscopic wholes caused by the discharge of shaft voltage through the bearings. Finally, a microscope can be used to identify grey lines around the bearing, so that it is possible to know whether these are provoked by mechanical processes or by electrical discharge machining.


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