Correlating Data | Even a Lack of Correlation is Telling

A common problem encountered when interpreting data is determining the root cause of the data that has exceeded an alarm limit or deviated significantly from historical results. Typically one looks for a correlation between the parameter in question and other parameters found on the report, but many of these are based on misconceptions that render data interpretation more difficult, or worse – misleading.

The most prominent data on the report is the spectrometric analysis which is divided into three categories: metals, contaminants and additives. To obtain these values the sample is ionized (essentially burned) in a nearly 10,000 K plasma (hotter than the surface of the sun). Each element on the periodic table emits a unique color of light, and the instrument measures the intensity of these colors to determine the concentration (reported in part per million – ppm). A limitation to this test is that the sample must completely ionize within a very small, measured area of the plasma. As such, only particulate with 0-5 microns is accurately measured, and particles larger than 10 microns are essentially not measured at all.

Optical particle counting is performed using a visible light source, aimed through a dynamic (flowing) oil film, at a photoreceptor. Any interruption to the light (shadows) are sized and counted. The size of the particle is quantified by the diameter of a circle with equal area as the shadow; essentially the detector assumes each particle to be a sphere. The sensor is only 100 microns thick, which means very large particles will not be measured at all.

This fundamental aspect of the tests helps explain why spectrometric data may not correlate with particle count data, which measures particles from 4-100 microns. Concern may arise that this test is too limited in its scope, however it should be noted that airborne particulate (e.g. dust or fly ash), wear metals from normal wear mechanisms, and additives are well within this range. Gross contamination and wear metals from abnormal wear mechanisms may go undetected.

Therefore, high values of spectrometric metals and contaminants without an increase in particle count indicate that all the contamination and wear is definitely below 4 microns (cut-off for particle counting) and should be treated accordingly, e.g. filtration in the 1-3 micron range. On the other hand, high particle counts with little to no change in spectrometric results indicate significant contamination and severe wear that can be mitigated by different measures, e.g. coarser filtration, or followed up with other condition monitoring such as vibration analysis to check for imbalance or misalignment.

A similar relationship exists between spectrometric analysis and the Particle Quantification Index (PQI), as discussed in the accompanying eSource article,Ferrous Debris Monitoring by PQ Index”.

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