Structural Health Monitoring (SHM) is widely used to monitor the short and long-term behavior of intelligent structures. This monitoring can help prolong the useful service lives and identify deficiencies before possible damage of such structures. The sensing systems that are usually deployed are intended to faithfully relay readings that reflect the true conditions of these structures. Unfortunately, this is seldom the case due to the presence of errors in the collected data. The electrical strain gauges used in SHM environments for instrumentation purposes are susceptible to numerous sources of error. Apparent strain is known to be the most serious of all such errors. However or whichever way temperature variations of the gauge’s environment occurs, apparent strain is introduced. This work focuses on modeling apparent strain in an SHM environment using National Instruments’ (NI) hard and software. The results of this work are applicable for thermal compensation in current test programs.

Structural Health Monitoring (SHM) is widely used to monitor the short and long-term behavior of intelligent structures. This monitoring can help prolong the useful service lives and identify deficiencies before possible damage of such structures. The sensing systems that are usually deployed are intended to faithfully relay readings that reflect the true conditions of these structures. Unfortunately, this is seldom the case due to the presence of errors in the collected data. The electrical strain gauges used in SHM environments for instrumentation purposes are susceptible to numerous sources of error. Apparent strain is known to be the most serious of all such errors. However or whichever way temperature variations of the gauge’s environment occurs, apparent strain is introduced. This work focuses on modeling apparent strain in an SHM environment using National Instruments’ (NI) hard and software. The results of this work are applicable for thermal compensation in current test programs.