Machinery Lubrication magazine published by Noria Corporation
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30 January - February 2014 | www.machinerylubrication.com rithm to measure the particle's morphological characteristics. As illus- trated in Figure 3, a series of cords are drawn across the diameter and through the center of the particle at equal angular spacing. Particle size and shape measurements are then derived from these cords. All variables are then collected for each unique particle in sequence across the filter. After the particle is detected and measured, an energy dispersive X-ray spectrum is acquired at the center, perimeter or along each cord for every particle detection event. Figure 3 illustrates the dynamic scan and rotating 16-cord algorithm during the particle measurement and EDX elemental X-ray collection phase. Once particles are characterized by size, shape and elemental composition, user-defined rules place them into a "class." For instance, if the user is interested in only high iron samples, a rule can be put in place to classify all particles with high iron content. Those particles will then be grouped and reported in the assigned "class." If needed, the particles can be relocated and further examined by the operator. The system provides a customizable reporting tool and automatically generates reports of the anal- yses. A database stores all analysis results for monitoring long-term trends with engine or gearbox wear. Comparison of Traditional Methods with SEM/ EDX results Table 1 presents a side-by-side comparison of various analyt- ical methods. While each of these methods has advantages, SEM/ EDX can provide users with a comprehensive analysis as well as more knowledge in dealing with wear debris. The value of the tech- nology is that not only does it give the size, shape and chemical composition of each particle in the sample, but it also permits the user to classify each of those particles based on their chemical composition. This allows classification of the particles into various rules or classes and enables the user to instantaneously identify if particles are wear debris or just steel alloys, carbon, mineral salts or fibers. Diagnosing machine wear becomes much easier because little to no interpretation of the data is needed. In order to demonstrate the power of the knowledge gained from SEM/EDX when compared to other technologies, real- world samples were collected and tested. Three unique engine oil samples obtained from a local car dealership were submitted to an oil testing lab for analyses. For comparison purposes, several methods were chosen for third-party testing including inductively coupled plasma (ICP) elemental analysis, particle counting via pore blockage and direct-reading ferrography. Each sample was subsampled representatively and also prepared for SEM testing at an in-house laboratory. Results from the third-party laboratory were received and compiled for comparison to the SEM/EDX results. It should be noted that the purpose of the data comparisons was to demonstrate the added value and benefit of SEM/EDX testing and not to evaluate the data from the third-party lab. Particle Count results Table 2 presents the particle count data for both the SEM and pore blockage methods for three samples. The pore weAr deBrIs ANAlysIs Figure 3. Graphical representation of data f low for SEM/EDX analysis FEATUrE AUTOMATIC PArTICLE COUNTEr ANALYTICAL FErrOGrAPHY ICP ELEMENTAL ANALYSIS rDE ELEMENTAL ANALYSIS SEM/EDX Sample Preparation Requirements Usually Yes Yes No Yes Particle Detection Range (microns) 2-100 2-500 <3 <7 0.2-2,000 Individual Particle Size and Shape Usually Yes No No Yes Total Element Chemical Analyses Range No No 38 32 98 Particle Classification by Chemistry No Limited No No Yes Particle Classification by Morphology and Chemistry No Yes No No Yes Analyses Time (minutes) 5 10 3 3 10 to 30 Ease of Use (1=easy, 5=moderate, 10=difficult) 5 10 5 3 1 Particle Size Distribution Yes No No No Yes Automated Trending Yes Limited Yes Yes Yes Table 1. Comparison of various analytical methods with SEM/EDX