Original Date: 11/03/1996
Revision Date: 01/18/2007

Condition-based maintenance offers a less costly, but more challenging methodology than traditional corrective and preventative maintenance practices. Typically, rotating equipment condition assessment relies on multiple sensor vibration analysis. To complement this analysis, Oak Ridge Centers for Manufacturing Technology (ORCMT) has proposed a non-contact, strain-sensing element for peak torsional strain monitoring.

Typical techniques of rotating condition assessment include vibration, thermographic, and oil analyses. In most predictive maintenance programs, these techniques are not implemented continuously, but rather on a weekly or monthly sampling schedule. Although sample monitoring can reduce maintenance costs, continuous monitoring can more efficiently record the true usage levels of equipment and detect problems associated with peak loading.

ORCMT has successfully completed an initial feasibility study for a transformation-induced plasticity (TRIP) steel sensor to measure peak strain (Figure 3-8). The special crystal structure of the steel material responds to peak strains by changing from paramagnetic to ferromagnetic, and possesses memory to indicate the maximum value of the strain. In rotating machinery, slip rings transfer signal transmissions from moving to stationary parts. However, slip rings have industry-wide reliability and data fidelity problems. TRIP sensors use magnetic field detection (inherently non-contact) which makes them attractive for maximum torque measurements in rotary applications.

TRIP sensing has been successfully demonstrated for bridges, mining applications, and airframes. Possible benefits of this novel technique include improved condition-based maintenance monitoring and the ability to record peak torque histories for operational machinery.

For more information see the Point of Contact for this survey.