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Various methods for evaluating the effectiveness of debris resistant bearings have been proposed for development. Once evaluation methods are well established to select bearings, the user is faced with assessing severity and detrimental effects of a specific application's lubricant contamination on bearing performance. Many analysis tools have been suggested for determining this impact, including particle analysis for size distribution, type of material and contamination level. A novel approach for determining severity of damage has been investigated which attempts to integrate these typical tools with actual damage to functional surfaces. It seeks to provide a practical approach and is appropriately labeled Debris Signature Analysis. Results of actual assessments will be discussed and the assessment method described.

The use of composite materials in the automotive industry has become increasingly widespread. With this increase in use, techniques for non-destructive testing (NDT) have become more and more important. Various optical NDT inspective methods such as holography, moiré techniques, and shearography have been used for material testing. Among these methods, shearography appears to be most practical. Shearography has a simple optical setup due to its “self-referencing” system, and it is relatively insensitive against rigid-body motions. Measurements of displacement derivatives, and thus strain directly, rather than the displacement itself is achieved through this method. Therefore shearography detects defects in objects by correlating anomalies of strain which are usually easier than correlating the anomalies of the displacement itself, as in holography. To date shearography has shown potential as a NDT tool for identifying defects in small structures.

Repair and remanufacture has become an accepted method to extend bearing useful life in many applications, including positions within off-highway construction and mining vehicles. However, it has not been an easy task for equipment owners to become confident in the use of repaired bearings, nor has it been an easy task for engineers to select the positions best suited for repair, as robust analytical methods to predict performance are not available. This has lead to many field test campaigns of repaired bearings on different bearing positions until the equipment owners gain enough confidence to make it part of their normal operating procedures. This paper aims to reduce the test and validation cycle that occurs with the use of repaired and remanufactured bearings by developing analytical methods to predict bearing performance. Life prediction algorithms are presented covering the different levels of repair available.