Tengjiao Jiang
About
Postdoc project: Computer vision‐based structural monitoring (COSMO)
Intelligent and automated inspection methods are receiving more and more attention with the long-term operation of many transportation infrastructures. Except for the continuous degradation of the material performance, human and natural loads (e.g. repeated loads from vehicles, wind and earthquakes) will result in cumulative or sudden damage to infrastructures, threatening safe operation and possibly leading to disasters.
Dr. Tengjiao Jiang focuses on developing inspection and evaluation methods for existing railways and bridges by using computer vision (CV) and deep learning (DL). The project is funded by the Norwegian Railway Directorate.
Research interests
- Computer Vision (CV)
- Machine Learning (ML)
- Photogrammetry
- Structural Health Monitoring (SHM)
- Structural Dynamics and Signal Processing
Academic Activities
- Associate Editor of the Journal Experimental Techniques
- Chair of Session "Vision-based Monitoring of Civil Structures" at the IMAC-XLI, Austin, Texas, USA, Feb. 13–16, 2023
Research Highlights
- A robust line-tracking photogrammetry method for uplift measurements of railway catenary systems in noisy backgrounds [PDF]
- A novel line-tracking technique from noisy backgrounds [Open-source code]
Supervisors
Publications
2023
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Rønnquist, Anders.
(2023)
A robust bridge rivet identification method using deep learning and computer vision.
Engineering structures.
volum 283.
Academic article
2022
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Nåvik, Petter Juell;
Rønnquist, Anders.
(2022)
Assessment of pantograph-catenary interaction in a railway overlap section via a novel optical-based method.
Mechanism and Machine Theory.
volum 177.
Academic article
-
Jiang, Tengjiao;
Rønnquist, Anders;
Song, Yang;
Frøseth, Gunnstein Thomas;
Nåvik, Petter Juell.
(2022)
A detailed investigation of uplift and damping of a railway catenary span in traffic using a vision-based line-tracking system.
Journal of Sound and Vibration.
volum 527.
Academic article
2021
-
Song, Yang;
Jiang, Tengjiao;
Rønnquist, Anders;
Nåvik, Petter Juell;
Frøseth, Gunnstein Thomas.
(2021)
The Effects of Spatially Distributed Damping on the Contact Force in Railway Pantograph-Catenary Interactions.
IEEE Transactions on Instrumentation and Measurement.
volum 70.
Academic article
2020
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Rønnquist, Anders;
Fagerholt, Egil.
(2020)
A robust line-tracking photogrammetry method for uplift measurements of railway catenary systems in noisy backgrounds.
Mechanical systems and signal processing.
volum 144.
Academic article
Journal publications
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Rønnquist, Anders.
(2023)
A robust bridge rivet identification method using deep learning and computer vision.
Engineering structures.
volum 283.
Academic article
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Nåvik, Petter Juell;
Rønnquist, Anders.
(2022)
Assessment of pantograph-catenary interaction in a railway overlap section via a novel optical-based method.
Mechanism and Machine Theory.
volum 177.
Academic article
-
Jiang, Tengjiao;
Rønnquist, Anders;
Song, Yang;
Frøseth, Gunnstein Thomas;
Nåvik, Petter Juell.
(2022)
A detailed investigation of uplift and damping of a railway catenary span in traffic using a vision-based line-tracking system.
Journal of Sound and Vibration.
volum 527.
Academic article
-
Song, Yang;
Jiang, Tengjiao;
Rønnquist, Anders;
Nåvik, Petter Juell;
Frøseth, Gunnstein Thomas.
(2021)
The Effects of Spatially Distributed Damping on the Contact Force in Railway Pantograph-Catenary Interactions.
IEEE Transactions on Instrumentation and Measurement.
volum 70.
Academic article
-
Jiang, Tengjiao;
Frøseth, Gunnstein Thomas;
Rønnquist, Anders;
Fagerholt, Egil.
(2020)
A robust line-tracking photogrammetry method for uplift measurements of railway catenary systems in noisy backgrounds.
Mechanical systems and signal processing.
volum 144.
Academic article
Media
2020
-
Academic lectureJiang, Tengjiao; Rønnquist, Anders. (2020) Application of a Robust Photogrammetry Method in Uplift Measurements of Railway Catenary Systems in Noisy Backgrounds. IMAC XXXVIII 2020 . Society for Experimental Mechanics, Inc.; Houston, Texas. 2020-02-10 - 2020-02-13.