Elimination of Wire-Generated Error Signals From Dynamic Strain Measurements

Legacy processes sometimes include steps that have no clear justification and add unnecessary cost that too often no one can explain. An example of this is the costly step of adding temporary copper leads for engine strain gage calibration. In an attempt to eliminate temporary leads, gage calibration was performed with the permanent type-K thermocouple engine lead wire. This cost saving effort resulted in uncovering a source of measurement noise and error signals in engine development data. Subsequent laboratory studies showed that type-K thermocouple wire produces sinusoidal error signals as a function of vibration input. These error signals have the potential to add coherently to the strain gage information causing the measured amplitude to be either higher or lower as a function of phase between the signals. The laboratory studies also compared different wire alloys and their associated signal generating properties in order to identify suitable replacement wire. Final validation of the new lead wire was accomplished by running an engine test and producing a back-to-back comparison of type-K to the replacement lead wire. This test compared pairs of dynamic strain gages on separate airfoils installed at the same locations. Test data recorded with the gage excitation current turned off showed the replacement wire eliminated all wire-generated signals above 0.25 ksi (1,724 kPa), while the type-K leads generated signals up to 2.5 ksi (17,237 kPa). Test data with strain gages energized showed a dramatic reduction in false signals and noise with the replacement lead wire. The data collected through the type-K wire illustrates the potential for making poor design choices when wire-generated signals are undetected in the data. This work resulted in measurable cost savings (millions of dollars) by introducing a replacement for type-K wire which eliminated the need for temporary leads. While the cost avoidance here can be difficult to estimate, preventing a field failure resulting from erroneous data could result in orders of magnitude more cost saving.