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논문 기본 정보

자료유형
학술저널
저자정보
Lee, Jae Kang (Korea Land and Geospatial Informatix Corporation) Kim, Jung Ok (Seoul National University)
저널정보
대한공간정보학회 대한공간정보학회지 한국지형공간정보학회지 제26권 제2호(통권 제84호)
발행연도
2018.6
수록면
33 - 51 (19page)
DOI
10.7319/kogsis.2018.26.2.033

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초록· 키워드

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This research introduced the expanding plan for the applicability of global navigation satellite system(GNSS). GNSS has been fast spread to various industrial application, the representative example is an application for deflection and deformation monitoring of long span bridge. The confirmation of changed displacement and stiffness should be necessary to secure the integrity and usability of bridge itself and safety of user. To do this, the accuracy of GNSS positioning solution regarded by the most fundamental data source should be converged to accuracy required. Unlike the normal geodetic surveying, GNSS observation that directly apply to bridge conducts under the convoluted environment, and also can be contaminated by various error source. Among other errors, multipath occurs the worst negative influence to GNSS positioning solution. To minimize this effect, specific error model should be employed. In the present investigation, Wavelet Transformation is apply to reduce the multipath effect induced under the bridge environment. Multipath frequency is extracted through multi‐resolution analysis(MRA) technique and is again reconstructed with free multipath. To verify algorithm introduced in this investigation, GNSS data collected from bridge in‐service has been used to conduct the verification process. In succession, two case studies have performed the bridge health monitoring system(BHMS) based on GNSS that provide more reliable and accurate positioning solution. It was able to confirm the improved results from both monitoring analysis; deflection and dynamic characteristics. Therefore, it is inevitable that the GNSS positioning solution that are more reliable and accurate can contribute on the secure safety of the bridge and users.

목차

Abstract
1. Introduction
2. Wavelet Transformation
3. Data Pre-analysis & Research Plan
4. Application of Wavelet Transformation for BHMS
5. Conclusion
References

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