Our research covers a wide range of tomography modalities and systems for industrial and medical applications
- Smart sensing systems for healthcare
- T-ray intra-oral imagers for dental care
- Soot imaging in aero-engine exhausts
- Real-time reconstruction for limited data tomography
- Laser-based combustion diagnostics
- Electrical monitoring of lung function
We have pioneered a new tomography technique to allow the imaging of various physical and chemical parameters on flexible surfaces. This has been demonstrated for temperature and deformation, resulting in a commercial carpet prototype (Smart Carpet) sensitized to image non-intrusively the deformation caused by human footprints. The work was recently covered by Reuters, New Scientist and other media. As a completely new variant of the technology, this projecty will implement a “Smart Matress” to monitor the human body position during sleep and rest, possibly providing vital signs such as pulse rate, temperature, respiration rate, as well as individual events such a coughing. Thus it will be possible for the first time to identify where on the surface the events occur.
Background and skills: Analog and digital electronics, good mathematical and algorithmic skills, experience with FPGAs and VHDL will be helpful.
This project aims to lay the foundations for the further development and exploitation of a radically new sensing and imaging modality, with its first application in dental care. The targeted methodology is sensing and fast tomography imaging, with no moving parts and based on optical fibre delivery, which can ultimately be deployed intra-orally as miniature tomographs employing non-ionising terahertz (T-ray) radiation. The project is based strongly on the dental diagnostic context. Measurements on ex-vivo tooth samples will be undertaken with the two methodologies – refractive index measurements by pulse delay and spectrally resolved narrowband THz transmission measurements, in conjunction with other characterization, such as micro X-ray CT. The project will establish the design rules for miniature tunable T-ray sources pumped through optical fibres and suitable miniature T-ray receivers. It will examine the strategy for refractive index imaging based on contrast between enamel and dentine, as well as carious tissue. A major deliverable will be a simulated model of an intra-oral T-ray imager, with indications of cost, IP position and potential for commercial take-up. Background and skills: Natural sciences/engineering, good understanding of optics and good experimental skills.
The FLITES project, funded by EPSRC, aims to establish a world-leading capability in the measurement and imaging of molecular and particulate species in gas turbine aero-engine exhausts. This currently ongoing project builds upon the expertise of the UK's world-leading groups in fibre-lasers, gas-detection opto-electronics, and tomography allied to its industrial strengths in aero-engine manufacture and aviation fuel technology. Soot will be imaged via the novel technique of near-IR long-pulse Laser-Induced Incandescence (LII), in a planar tomographic set-up previously invented in Manchester for the fluorescence case, Auto-Projection Tomography (APT). The techniques developed in the university laboratories are currently being transferred on a full-scale aero-engine mounted on a testbed at Rolls-Royce. The Project allows postgraduate work on the new LII version of APT, with emphasis on the reconstruction of the soot concentration from a limited number of LII measurements at the exhaust periphery, as well as on tasks related to the building and testing of the complete system. Background and skills: Natural sciences/engineering, good understanding of optics, good modeling and/or experimental skills.
Limited access to the imaged object degrades tomography imaging because of limited data. In such circumstances we focus only on the main constituents on the imaged scene by applying a sinusoidal Hough transformation on the measurements. By parallel computation on an FPGA, we calculate the reconstructed position of these constituents in real time for data frame rates potentially acquired at up to 40 KHz, independent of the number of these constituents and the number of the angular projections. This is improvement of between 3 to 4 orders of magnitude, at a smaller error margin, compared to sequential reconstruction algorithms.
Supervisor Paul Wright
Research opportunities are available in the application of laser-based sensing techniques to combustion diagnostics. Possible topics include the development of the necessary optical and spectroscopic approaches, design and implementation of high-performance mixed-signal measurement electronics, and modelling/analysis of the resulting data. Application areas range from laboratory scale to commercial jet engines. Students will have the opportunity to work with academic and industrial collaborators within the FLITES consortium.
Supervisor Paul Wright
We have recently developed state-of-the-art hardware for electrical measurements on human subjects. In collaboration with our School of Mathematics, we now wish to apply this technology to the monitoring of lung function in critical care scenarios. The project involves both analogue and digital electronics, including FPGA firmware design, and would be an excellent grounding for a student looking to move into electronic hardware or firmware design in the mixed-signal or medical areas.
University of Manchester has been leading in electrical capacitance tomography (ECT). Our AC-based ECT system has the highest signal-to-noise ratio (SNR) (>73 dB), and can produce images at a speed of >100 frames per second. As can see in the video it can also generate 3D images in real time. Now it is time to develop a new generation ECT system, targeting wider frequency range (100 kHz-100 MHz), enhanced SNR, faster imaging speed,compact with surface-mounted ICs and more functions for system operation, image reconstruction and data analysis. One of the targeted applications of this system is to measure gas-oil-water flows.
Gas-oil-water flow meters are highly demanded by the oil industry. Currently, all gas-oil-water flow meters rely on radioactive sources, such as X-ray, which is harmful and expensive. Based on our many year experience in ECT and multiphase flow measurement, it is possible to develop a type of non-radioactive gas-oil-water flow meter based on ECT combining with microwave and possibly other types of sensors, such as ultrasonic and Venturi. This PhD project will be part of collaboration with Schlumberger.
In the pharmaceutical industry, batch processing is adopted for production. One of the reasons is the lack of powder flow meters. To enhance the operation efficiency by continuous processing, it is necessary to develop online powder flow meters, which are in general a type of gas-solids flow meter. While electrical capacitance tomography (ECT) can measure concentration in a cross section accurately, it is possible to measure the powder velocity by cross correlation. By combining the two techniques together, the powder flow rate may be measured. This work will be supported by GEA Pharma Systems Ltd.
With ultrasonic arrays and full matrix data capture techniques, ultrasonic beams can be manipulated (e.g. focused, steered and swept) in many novel ways. The technique has wide applications in nuclear manufacturing, process engineering, medical field etc. This project intends to explore the capability of this technique for online welding inspection
The major difference between an analogue-based system and a digital-based system is the way the demodulation is implemented. This PhD project intends to build a highly integrated, Field Programmable Gate Array (FPGA)-based digital Magnetic Induction Tomography (MIT) system. Such a system will be much faster, offers improved SNR, and can be applied to various industrial and biomedical applications. Students who are interested in sensing, image reconstruction, digital electronics and signal processing are encouraged to apply.
Over 50 million smart meters are estimated to be installed in the UK with the official national smart meter roll-out from 2015 to 2020. In addition, smart meters will be installed in millions of private households worldwide. Smart meters can measure electricity consumption data at a much finer-grained temporal scale and huge amount of data will be available in the future. Processing this data can reveal valuable context information, which could form the basis for novel services and applications for utilities, regulators, and private households.
The challenge is how to best utilise the huge amount of data in terms of (1) Data exploitation to provide services to households, regulators, and utilities to improve energy efficiency, promote best practises etc. (2) The implication of this data to provide wider indicators of social- economical context of households, groups. (3) The smart meter data is likely to have sensitive information on household energy usage, social economics contexts. How to protect such information is likely to have impacts on the uptake of smart meters, information security etc.
The project aims at exploring potential uses of smart meter data. Methods from machine learning and data mining can be employed to investigate what services can be offered to utilities, regulators and households. Information security would be addressed to protect sensitive data. Students who are interested in developing a career in electrical power industries are encouraged to apply.