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In the mining sector, there are growing calls for the ability to monitor the health of operational assets like structures, mobile underground machinery, and complex stationary equipment. This work focuses on the development of a software architecture to monitor the entire range of industrial and mining equipment - all the while acknowledging the more generic problem of intelligent signal processing having applicability to a much broader class of problem. The implementation of condition monitoring for mobile underground mining equipment relies on previous work by the authors in advancing condition-monitoring techniques for vari able speed and load machinery. The design will permit flexible run-time system configuration with a variety of choices in signal processing and intelligent analysis techniques; it has been demonstrated to work well with an implementation in MATLAB object-oriented programming (OOP) from data collected on a real gearbox subject to varying loads and speeds. This success justifies the advancement of a full-fledged prototype in LabVIEW OOP. The aim is the development of the data analysis layer; the result should integrate seamlessly with such developing industrial standards as the International Rock Excavation Data Exchange Standard (IREDES).