- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
STUDY ON DETECTING VOIDS WITHIN A CONCRETE SLAB TRACK OF SHINKANSEN WITH NON-DESTRUCTIVE TESTING BY IMPACT ACOUSTICS
-
- INABA Kohko
- (公財)鉄道総合技術研究所 軌道技術研究部
-
- TAKAHASHI Takatada
- (公財)鉄道総合技術研究所 軌道技術研究部
-
- FUCHIGAMI Shota
- (公財)鉄道総合技術研究所 軌道技術研究部
-
- MOMOYA Yoshitsugu
- (公財)鉄道総合技術研究所 軌道技術研究部
-
- NAITO Hideki
- 東北大学 大学院工学研究科土木工学専攻
Bibliographic Information
- Other Title
-
- 打音法による新幹線用軌道スラブ-てん充層間の空隙検知方法に関する研究
Description
<p> A slab track is used for the primary railway track structure for shinkansen, and it is composed of a concrete bed, filling layer (cement asphalt mortar), RC track slab, and so on. It has been reported that some aged slab tracks laid after the 1980s have voids between the RC track slab and filling layer due to degradation of the filling layer. In the maintenance of the slab track, it is important to detect such voids at an early stage and repair them appropriately. In this study, we investigated a method for detecting voids by non-destructive testing by impact acoustics. As a result, we found that impact acoustics generated in this testing can be influenced by hammering position and supporting condition as well as the existence of voids. Furthermore, it was considered that supervised machined learning is an effective approach for the detection of voids. However, we do not consider the independence of learning data and test data in this study. It is necessary to be verified separately about the discrimination performance for the test data with clear independence such as the measured data from another slab tracks.</p>
Journal
-
- Journal of Japan Society of Civil Engineers, Ser. E1 (Pavement Engineering)
-
Journal of Japan Society of Civil Engineers, Ser. E1 (Pavement Engineering) 78 (1), 1-11, 2022
Japan Society of Civil Engineers
- Tweet
Details 詳細情報について
-
- CRID
- 1390572632984039296
-
- NII Article ID
- 130008161981
-
- ISSN
- 21856559
-
- Text Lang
- ja
-
- Article Type
- journal article
-
- Data Source
-
- JaLC
- Crossref
- CiNii Articles
- KAKEN
-
- Abstract License Flag
- Disallowed