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Robotic aided hazardous gas detection using laser absorption spectroscopy

Project Description

Toxic and hazardous chemical species, including but not limited to COx, NH3, NOx, H2S, SOx, and hydrocarbons, are ubiquitous, predominantly emitted by anthropogenic activities, and pose serious risks to human health and the environment. Thus, the remote sensing of these chemicals, especially in the gas or vapour phase, are of extreme importance.

As a sensitive, fast-response and cost-effective optical sensing technique, laser absorption spectroscopy (LAS) has been widely applied on trace gas detection. Traditional line-of-sight LAS measurement using optical cell is challenging to obtain the spatial resolution. Single ended LAS sensors acquire the return signal to come from scattering off the far wall of the device, allowing remote detection of the hazardous gases. Aided with robotic arm, the single ended LAS sensor enable spontaneously tracing the source of the hazardous gases to ensure clean air in indoor, outdoor, and industrial environments.

The objectives of this PhD projects are:

1 Design of the lightweight single ended LAS sensor.
2 Integration of the developed sensor with the robotics.
3 Optimal control of the robotic arm for fast recognition of the hazardous gas source.
4 Field experiments of tracing the hazardous gas source using the developed system.

During the project, the PhD candidate will be trained to design optical sensors and develop control algorithms for the robotics. Most critical processes in the development is the signal processing of the ultra-weak reflected optical signal and the optimal control of the robotics. The candidate should also be fully motivated and confident with trouble shooting in the experiments.

In addition, the successful candidate will have the opportunity to present innovative results in international conferences, to publish high-impact journal papers, and, eventually, to deliver advanced sensors for hazardous gas detection.

Technical Queries directed to Dr Chang Liu on

This project is also supervised by Dr Adam Stokes and Dr Yunjie Yang.

Funding Notes

Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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