摘要(英) |
The major management problem of the Taiwan Bridge Management System (TBMS) is existing of incomplete or error data input by the users. A set of error data detection mechanisms help both in increasing reliability of system data and in effectiveness of bridge maintenance. Therefore, this research aims at establishing such error data detection mechanisms to screen out for correction obvious errors exist in the inventory and in the inspection databases of the TBMS. Furthermore, error proof data input mechanisms are also generated in this research to prevent inputting of incorrect data in the future.
For the inventory database, this study categorizes error data patterns of basic data into two types; wrong input of data and data conflicts between fields. After expert interviews were conducted and typical values for bridge attributes were collected, reasonable intervals of various fields and valid relationships among data fields were summarized to become rules for finding error data in the inventory database. In the aspect of detecting possible inspection data, this study classifies bridges into several types first and then uses a cluster analysis method to group bridges with similar characters. In a group, possible D values for various components are analyzed from which components with possible wrong D inspection values can be found.
Several tests were performed in the TBMS using the mechanism generated by this research; typos and unreasonable data both in the bridge inventory and in the bridge inspection database were actually found and corrected accordingly. These tests prove that results of this research are meaningful and useful in maintaining the TBMS. |
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