Abstract
In this paper, RTK-GPS system was used for movement data collection. Two identification models namely; Multi input-single output (MISO) robust fit regression and Neural Network Auto-Regression Moving Average with eXogenous input (NNARMAX) models were used for the identification of these data. The analysis of test results indicate that: (1) the NNARMAX [4 4 1 1] and [5 4 1 5] models defined by taking into account the results of robust regression analysis estimate structural movements more accurately than the NNARMAX [0 1 0 0] model, and (2) the robust fit regression models have good capacities for mapping relationship of applied loads effects factors and displacements of tower. However, temperature and humidity effects on the entire modal shapes are insignificant and (3) the traffic loads are the main factor affects tower bridge displacement.
| Original language | English |
|---|---|
| Pages (from-to) | 531-539 |
| Number of pages | 9 |
| Journal | Measurement: Journal of the International Measurement Confederation |
| Volume | 47 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2014 |
| Externally published | Yes |
Keywords
- ARMAX
- Bridge
- GPS
- Identification
- Neural network
- Robust fit regression
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