Early detection of abnormal wear debris particulate is essential to predictive maintenance of high value equipment for military, mining and marine applications. With the advances in instrumentation and electronics, a new approach to machine condition abnormality detection and monitoring is presented. Filter Particle Quantification (FPQ) is a technique to concentrate debris for elemental analysis. Particles larger than 4 microns are measured and elemental data is derived from the patch. This solvent-free, two-step approach provides insight into machine conditions in a consistent, easy to use method that lends itself to mobile oil analysis tools that can be brought to equipment. This presentation will describe what and who benefits from expeditionary oil analysis, examples of failure detection, and provides an overview of an expeditionary fluid analysis tool. This tool includes a novel approach to wear debris with lubricant condition measurements.
- Discover a new approach to machine condition abnormality detection and monitoring.
- Understand why oil analysis is an essential part of a comprehensive PdM program
- Learn how mobile oil analysis eliminates costly delays in obtaining lab results.
Daniel P. Walsh is Spectro Inc.'s Director of Product Management responsible for driving the product pipeline and ultimately delivering instruments and tools that meet and exceed customers' oil analysis needs. Prior to this role, Daniel held the position of Spectro Inc.'s U.S. Sales Manager. For almost 15 years Daniel worked at BTS, a division of Bently Nevada, as Technical Director and General Manager of the oil and fuel analysis laboratory. He began his career as a Metallurgical Test Engineer at Pratt & Whitney in Hartford Connecticut. Daniel has presented several papers at industry conferences, including Lubmat, EPRI, Noria, STLE and Pittcon. He holds a BS in Materials Science and Engineering from the University of Limerick, and an MSc in Engineering Management from Tufts University. He also is a STLE Certified Lubrication Specialist.