Research on deformation monitoring along Metro Line Based on Beidou super CORS

Supervisors

Principal supervisor: Professor/Dr Lei Fan (XJTLU)

Co-supervisor: Professor/Dr Qing Wang (JITRI)

Co-supervisor: Professor/Dr Cheng Zhang (XJTLU)

Co-supervisor: Professor/Dr Daniel Arribas-Bel (UoL)

According to the urgent demand for high-precision positioning in the construction, operation and maintenance of super urban rail transit, the project plans to establish a global series of positioning systems for super Urban Rail Transit under the unified space-time benchmark. The system is based on Beidou technology to build a super CORS network covering rail transit lines, Realize real-time and high-precision monitoring of the settlement and deformation of the main infrastructure (including important buildings) along the rail transit, and establish a unified aboveground and underground space-time benchmark based on Beidou + pseudosatellite. The number of simultaneous online users of the system can reach 1000, and the number of simultaneous monitoring stations shall not be less than 600; The self-developed real-time deformation monitoring data processing algorithm has a horizontal accuracy of 2.5-5mm and an elevation accuracy of 8-10mm. Beidou super CORS system will be used to monitor the settlement and deformation of main infrastructure (including important buildings) along the subway 24 hours a day, and serve as the benchmark for transmitting the unified coordinates and timing of the road network to the subway (underground). The system will comprehensively enhance the operation safety of rail transit.

For more information about doctoral scholarship and PhD programme at Xi’an Jiaotong-Liverpool University (XJTLU): Please visit

http://www.xjtlu.edu.cn/en/study-with-us/admissions/entry-requirements

http://www.xjtlu.edu.cn/en/admissions/phd/feesscholarships.html

Requirements:

The candidate should have a first class or upper second class honours degree, or a master’s degree (or equivalent qualification) in Surveying, Civil Engineering, Remote Sensing or Geography, with relevant knowledge and skills required by the project.

Evidence of good spoken and written English is essential. The candidate should have an IELTS score of 6.5 or above, if the first language is not English. This position is open to all qualified candidates irrespective of nationality.

Degree: 

The student will be awarded a PhD degree from the University of Liverpool (UK) upon successful completion of the program.

Supervisor Profile:

Principal Supervisor:

Dr Lei Fan is Assistant Professor within Department of Civil Engineering at Xi'an Jiaotong Liverpool University. He obtained his first degree (BEng) in Hydraulics from Sichuan University, China, and an MSc degree in Civil Engineering from University of Nottingham, UK. He received a scholarship from EPSRC to carry out his PhD research in University of Southampton, UK. During his PhD study, he was supported financially by the EPSRC funding to study at Massachusetts Institude of Technology (MIT) as a visiting researcher. He also worked as a consulting engineer for Ramboll (Gifford) and Atkins in the UK for over 2.5 years. His main research interests include lidar and photogrammetry techniques, point cloud data, machine learning, deformation monitoring, semantic segmentations, monitoring of civil engineering structures and geohazards.

JITRI co-supervisor:

Professor Qing Wang is a professor in Institute of Instrumentation Science and Engineering of Southeast University, and the Head of Institute of Applied Technology for Future Cities in Suzhou. His more information can be found at: https://ins.seu.edu.cn/68/32/c2346a26674/pagem.psp

How to Apply:

Interested applicants are advised to email Lei.Fan@xjtlu.edu.cn (XJTLU principal supervisor’s email address) or (JITRI supervisor’s email) the following documents for initial review and assessment (please put the project title in the subject line).

• CV
• Two reference letters with company/university letterhead
• Personal statement outlining your interest in the position
• Proof of English language proficiency (an IELTS score of 6.5 or above)
• Verified school transcripts in both Chinese and English (for international students, only the English version is required)
• Verified certificates of education qualifications in both Chinese and English (for international students, only the English version is required) 
• PDF copy of Master Degree dissertation (or an equivalent writing sample) and examiners reports available