Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Passive solar options for reducing heating demand and maintain indoor climate in a multifamily house in Sweden

This research was carried out by studying possible renovation of a two-storey detached multifamily building by using passive solar design options in a cold climate in Borlänge, Sweden where the heating Degree Days are 4451 (base 20°C). Borlänge`s housing company, Tunabyggen, plans to renovate the project house located inthe multicultural district, Jakobsgårdarna. The goal of the thesis was to suggest a redesign of the current building, decrease the heating energy use, by applying passive solar design and control strategies, in a most reasonable way. In addition ensure a better thermal comfort for the tenants in the dwellings. Literatures have been studied, from which can be inferred that passive design should be abasic design consideration for all housing constructions, because it has advantages to ensure thermal comfort, and reduce the energy use. In addition further savings can be achieved applying different types of control strategies, from which the house will be more personalized, and better adapted to the user’s needs.The proposed method is based on simulations by using TRNSYS software. First a proper building model was set up, which represents the current state of the project building. Then the thermal insulation and the windows were upgraded, based on today's building regulations. The developments of the passive solar options were accomplished in two steps. First of all the relevant basic passive design elements were considered, then those advantages were compared to the advantages of applying new conventional thermostat, and shading control strategies.The results show that there is significant potential with the different types of passive solar design; their usage depends primarily on the location of the site as well as the orientation of the project building. Applying the control strategies, such as thermostat, and shading control, along the thermal insulation upgrade, may lead to significant energy savings (around 40 %), by comparison to the reference building without any upgrade.