A NEW METHOD TO SEPARATE TEMPERATURE EFFECT FROM LONG-TERM STRUCTURAL HEALTH MONITORING DATA

A new Adaptive Bandwidth Filter Method (ABFM) is proposed to separate the temperature effects from structural health monitoring signals. Using multi-scale analysis method, temperature are divided into daytime temperature variations, abrupt temperature drops and seasonal temperature fluctuations. Each category is associaed with distinct time scale. Daytime temperature effect does not couple with the other effects, and temperature is linearly related with structural effect proved by principle of virtual work. The ABFM adopts particle swarm optimization algorithm to adjust the frequency bandwidth of the daytime temperature effect. Therefore, the relationship between the temperature and the structure effect can be statistically determined more accurately. Simulation and experimental results show that the ABFM is advantageous over wavelet analysis in considering separating temperature effects.