| dc.description.abstract | Taiwan has a large number of bridges that play a significant role in transportation and economic development. Currently, there are 10,246 bridges in Taiwan that are over 30 years old, indicating that Taiwan′s bridges have entered a period of serious deterioration, making bridge inspection and maintenance increasingly important. Therefore, this study aims to use the Taiwan Bridge Management System (TBMS) database and big data approaches to identify the correlation between deterioration of bridge component and bridge inventory data to improve the effectiveness of bridge inspection.
The study is divided into two stages. In the first stage, 75 bridges on some provincial roads were analyzed using the regression method in R software, but due to the relatively small sample size, some correlations between inventory fields and component deterioration could not be reasonably explained. Therefore, in the second stage, a total of 2,849 bridges across central and county rivers in seven counties and cities in central and southern Taiwan, were selected and divided into three categories based on span number. Both the bridge inventory data and inspection data of various types of bridges need to be preprocessed to ensure the accuracy and usability of the data. After preprocessing, data clustering and correlation analysis were conducted using SPSS software. Research results showed a correlation between the bridge inventory fields and the deterioration of bridge components. For instance, for the first category of single-span bridges, the probabilities of deterioration of the bridge piers, girders, and bridge deck were 25%, 32.18%, 38.96%, and 28.8%, respectively, depending on the contents of the bridge inventory data..
The correlation between deterioration of bridge component and bridge inventory data found in this study can provide references for inspection personnel and bridge management agencies. When conducting regular bridge inspections or special inspections before and after flood seasons and natural disasters, inspection personnel can pay special attention to bridge components that may deteriorate according to the characteristics of the bridge inventory data. The results of this study are of great help in improving the accuracy and efficiency of bridge inspection. | en_US |