LDR | | 02054nmm uu200421 4500 |
001 | | 000000332897 |
005 | | 20240805171808 |
008 | | 181129s2017 |||||||||||||||||c||eng d |
020 | |
▼a 9780355784879 |
035 | |
▼a (MiAaPQ)AAI10800390 |
035 | |
▼a (MiAaPQ)0803vireo:18992Allard |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
082 | 0 |
▼a 624 |
100 | 1 |
▼a Allard, Austin J. |
245 | 10 |
▼a Vehicle-Borne Autonomous Railroad Bridge Impairment Detection Systems. |
260 | |
▼a [S.l.] :
▼b Texas A&M University.,
▼c 2017 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2017 |
300 | |
▼a 303 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B. |
500 | |
▼a Adviser: Gary T. Fry. |
502 | 1 |
▼a Thesis (Ph.D.)--Texas A&M University, 2017. |
520 | |
▼a Timber railroad bridges have been exposed to increasingly large axle loadings accompanied by a steady increase in the amount of railcar traffic over the past 50 years. In addition to mechanical loading, there exists a number of environmental con |
520 | |
▼a This research examines an automated impairment detection system positioned on a railcar capable of traversing multiple bridges along a track to aid in determining critical bridges that need to be inspected. The technology and techniques presente |
520 | |
▼a The objective of the research is to develop technology that will autonomously detect structural impairments in timber railroad bridges using data gathered from rail vehicles that cross the bridges. This was accomplished by recording the behavior |
590 | |
▼a School code: 0803. |
650 | 4 |
▼a Civil engineering. |
650 | 4 |
▼a Mechanical engineering. |
690 | |
▼a 0543 |
690 | |
▼a 0548 |
710 | 20 |
▼a Texas A&M University.
▼b Civil Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-08B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0803 |
791 | |
▼a Ph.D. |
792 | |
▼a 2017 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997780
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자 |