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How is oil analysis used for condition monitoring?


Oil analysis: How, why and when?

Oil analysis was first used in 1946, when the US railroad industry analyzed diesel engine lubricant to detect component wear and tear. Spent oil was shipped to researchers who used a spectrograph to detect individual chemical elements such as iron and copper. The technique began expanding to other industries in the late 1950s, as handheld spectrometers were developed that could analyze samples on the spot.

Oil analysis sensor technology

Oil sensors come in many different types. Some measure the oil’s dielectric constant, which changes as the oil degrades or becomes contaminated. (A substance’s dielectric constant reflects its ability to keep an electric field from forming in it.) Other oil sensors measure optical characteristics and compare them to model conditions to assess the oil’s quality (a technique called Fourier transform infrared spectroscopy). Still others use magnetic fields to detect and classify metallic particles in the oil (a sign of wear). And still others again use x-ray emissions to detect the presence of foreign elements.

Oil sensors need to be placed on or near the asset that is being monitored. For this reason, oil analysis sensors are not suited to monitoring assets that are:

  • inaccessible (such as underground pumps)
  • remote or widely spaced (such as offshore wind turbines)
  • situated in hard-to-reach places
  • situated in hazardous environments, such as ATEX zones
  • situated in harsh conditions, such as hot strip steel mills where extreme temperatures can damage the sensors and the resultant flow of data


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Oil analysis performance in fault detection

Below is a P-F curve demonstrating how oil analysis compares to other monitorización de la condición techniques when it comes to fault detection in advance of an asset breakdown. This is a P-F curve for bearing failure in a specific production system.

For more information on the accuracy of oil analysis in comparison to other monitorización de la condición techniques, download the guía comparativa de condition monitoring.

pf curva vibración blog post 460w


Un ejemplo de curva P-F para el fallo de un rodamiento en un sistema de producción específico. Las ubicaciones de las distintas tecnologías en la curva serán diferentes para cada equipo, entorno de producción y modo de fallo, así que asegúrese de calcularla para los activos y tipos de degradación específicos que desee supervisar.

Using oil analysis for fault detection: general rules of thumb

Every production system is different, meaning there’s no one-size-fits-all condition monitoring technology. However, we can state some general rules of thumb when it comes to areas where oil analysis is strong or weak in fault detection.

Fuerte en la supervisión:

  • in noisy or vibrating environments
  • un motor que impulsa muchos activos
  • averías mecánicas
  • assets driven by direct current (DC)
  • rotating machinery (with the caveat that not all assets have oil that can be analyzed)
  • maquinaria que gira muy lentamente

Débil (o no posible) en la supervisión:

  • activos remotos o inaccesibles
  • activos situados en zonas ATEX u otras condiciones difíciles
  • fugas
  • fallos eléctricos
  • perspectivas energéticas

Compare oil analysis and other condition monitoring techniques

Download the condition monitoring comparison guide for a full comparison of oil analysis and other major techniques.

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