The design and development of heat extraction technologies for the utilisation of compost thermal energy

A composting Heat Extraction Unit (HEU) was designed to utilise waste heat from decaying organic matter for a variety of heating application The aim was to construct an insulated small scale, sealed, organic matter filled container. In this vessel a process fluid within embedded pipes would absorb thermal energy from the hot compost and transport it to an external heat exchanger. Experiments were conducted on the constituent parts and the final design comprised of a 2046 litre container insulated with polyurethane foam and kingspan with two arrays of qualpex piping embedded in the compost to extract heat. The thermal energy was used in horticultural trials by heating polytunnels using a radiator system during a winter/spring period. The compost derived energy was compared with conventional and renewable energy in the form of an electric fan heater and solar panel. The compost derived energy was able to raise polytunnel temperatures to 2-3°C above the control, with the solar panel contributing no thermal energy during the winter trial and the electric heater the most efficient maintaining temperature at its preset temperature of 10°C. Plants that were cultivated as performance indicators showed no significant difference in growth rates between the heat sources. A follow on experiment conducted using special growing mats for distributing compost thermal energy directly under the plants (Radish, Cabbage, Spinach and Lettuce) displayed more successful growth patterns than those in the control. The compost HEU was also used for more traditional space heating and hot water heating applications. A test space was successfully heated over two trials with varying insulation levels. Maximum internal temperature increases of 7°C and 13°C were recorded for building U-values of 1.6 and 0.53 W/m2K respectively using the HEU. The HEU successfully heated a 60 litre hot water cylinder for 32 days with maximum water temperature increases of 36.5°C recorded. Total energy recovered from the 435 Kg of compost within the HEU during the polytunnel growth trial was 76 kWh which is 3 kWh/day for the 25 days when the HEU was activated. With a mean coefficient of performance level of 6.8 calculated for the HEU the technology is energy efficient. Therefore the compost HEU developed here could be a useful renewable energy technology particularly for small scale rural dwellers and growers with access to significant quantities of organic matter

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.