Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements
Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/21/7485 |
| _version_ | 1797549880504221696 |
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| author | Hua Zhao Chengjun Tan Eugene J. OBrien Nasim Uddin Bin Zhang |
| author_facet | Hua Zhao Chengjun Tan Eugene J. OBrien Nasim Uddin Bin Zhang |
| author_sort | Hua Zhao |
| collection | DOAJ |
| description | Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow. |
| first_indexed | 2024-03-10T15:21:41Z |
| format | Article |
| id | doaj.art-5f1a301d612c42da8b3a13ef356e4946 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T15:21:41Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5f1a301d612c42da8b3a13ef356e49462023-11-20T18:25:27ZengMDPI AGApplied Sciences2076-34172020-10-011021748510.3390/app10217485Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge MeasurementsHua Zhao0Chengjun Tan1Eugene J. OBrien2Nasim Uddin3Bin Zhang4Key Laboratory for Wind and Bridge Engineering of Hunan Province, College of Civil Engineering, Hunan University, Changsha 410082, ChinaKey Laboratory for Wind and Bridge Engineering of Hunan Province, College of Civil Engineering, Hunan University, Changsha 410082, ChinaCivil Engineering, University College Dublin, D04 V1W8 Dublin, IrelandDepartment of Civil, Construction and Environmental Engineering, The University of Alabama at Birmingham, 1075 13th St S, Birmingham, AL 35205, USAKey Laboratory for Wind and Bridge Engineering of Hunan Province, College of Civil Engineering, Hunan University, Changsha 410082, ChinaAccurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow.https://www.mdpi.com/2076-3417/10/21/7485axle detectionwavelet analysisbridge weigh-in-motionscalefield experiment |
| spellingShingle | Hua Zhao Chengjun Tan Eugene J. OBrien Nasim Uddin Bin Zhang Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements Applied Sciences axle detection wavelet analysis bridge weigh-in-motion scale field experiment |
| title | Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements |
| title_full | Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements |
| title_fullStr | Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements |
| title_full_unstemmed | Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements |
| title_short | Wavelet-Based Optimum Identification of Vehicle Axles Using Bridge Measurements |
| title_sort | wavelet based optimum identification of vehicle axles using bridge measurements |
| topic | axle detection wavelet analysis bridge weigh-in-motion scale field experiment |
| url | https://www.mdpi.com/2076-3417/10/21/7485 |
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