Original Date: 03/08/1999
Revision Date: 01/18/2007
Information : Transitional Failure Data: Acquisition and Management
Condition based maintenance (CBM) involves more than just conducting tests on machines or determining failure/reliability measurements. Instead, true CBM identifies and tracks observables to detect faults, and can relate these variables to the overall condition and useful life of equipment. To support its expanding CBM efforts, the Applied Research Laboratory at the Pennsylvania State University (ARL Penn State) established four facilities including the Mechanical Diagnostics Test Bed (MDTB). The MDTB facility was constructed to provide data on commercial transmissions as their conditions deteriorate from new to faulted to failure.
The generation of continuous run/good-to-bad gearbox transitional data will be used to determine appropriate data fusion and approximate reasoning techniques which will result in identifying and detecting precursors to failure. The MDTB also provides a test and evaluation vehicle for emerging prognostics, time-to-failure/remaining-life prediction algorithms and advanced sensor development (Figure 3-2). The test bed consists of a 30-horsepower (HP) drive motor coupled through a torque cell to the input of a 5- to 20-HP gearbox, and a 75-HP load motor coupled through a torque cell to the output of the gearbox. Instrumentation consists of thermocouples and infrared sensors for gearbox and motor temperatures; accelerometers for gearbox and driveline vibration signatures; acoustic emission sensors for gearbox impact energy events; dielectric and debris monitors for gearbox oil quality and sampling; input/output torque cells for gearbox torque/efficiency monitoring; and current and power factor instrumentation for motor monitoring.
Although advanced methods in maintenance technology are still in their infancy, multiple new technologies are emerging and being applied to maintenance and mechanical diagnostics problems (e.g., advanced detection methods for temperature, oil analysis, and vibration signal processing). A limiting factor in the further development of CBM continues to be a lack of high fidelity data of faults as they initiate and evolve. The ARL Penn State’s MDTB effort addresses this shortcoming by providing a realistic test stand that effectively represents an operational environment and by its ability to bridge the gap between typical, university-scale, test environments and the real world. The MDTB is evolving into a method to generate realistic data sets for use in the development of CBM technology with the intention of making these sets available to industry and other researchers.
Key to the current research project is the ability to accurately monitor a system via sensors; process and fuse sensor data; and model and predict the evolution of fault conditions. The MDTB directly accommodates the need for transitional data, which tracks faults from initiation to an ultimate failure mode. Cost savings potential is quite attractive for CBM practices in the manufacturing and operational environment. A 1989 study, associated with the maintenance strategies used on rotating equipments in plants, estimated the normalized costs per year at $18 per HP for corrective, $13 per HP for preventive, and $10 per HP for CBM.
Figure 3-2. Mechanical Diagnostics Test Bed
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