6 resultados para Sky monitoring system, Ireland


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Ageing and deterioration of infrastructure is a challenge facing transport authorities. In particular, there is a need for increased bridge monitoring in order to provide adequate maintenance, prioritise allocation of funds and guarantee acceptable levels of transport safety. Existing bridge structural health monitoring (SHM) techniques typically involve direct instrumentation of the bridge with sensors and equipment for the measurement of properties such as frequencies of vibration. These techniques are important as they can indicate the deterioration of the bridge condition. However, they can be labour intensive and expensive due to the requirement for on-site installations. In recent years, alternative low-cost indirect vibrationbased SHM approaches have been proposed which utilise the dynamic response of a vehicle to carry out “drive-by” pavement and/or bridge monitoring. The vehicle is fitted with sensors on its axles thus reducing the need for on-site installations. This paper investigates the use of low-cost sensors incorporating global navigation satellite systems (GNSS) for implementation of the drive-by system in practice, via field trials with an instrumented vehicle. The potential of smartphone technology to be harnessed for drive by monitoring is established, while smartphone GNSS tracking applications are found to compare favourably in terms of accuracy, cost and ease of use to professional GNSS devices.

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The thermoforming industry has been relatively slow to embrace modern measurement technologies. As a result researchers have struggled to develop accurate thermoforming simulations as some of the key aspects of the process remain poorly understood. For the first time, this work reports the development of a prototype multivariable instrumentation system for use in thermoforming. The system contains sensors for plug force, plug displacement, air pressure and temperature, plug temperature, and sheet temperature. Initially, it was developed to fit the tooling on a laboratory thermoforming machine, but later its performance was validated by installing it on a similar industrial tool. Throughout its development, providing access for the various sensors and their cabling was the most challenging task. In testing, all of the sensors performed well and the data collected has given a powerful insight into the operation of the process. In particular, it has shown that both the air and plug temperatures stabilize at more than 80C during the continuous thermoforming of amorphous polyethylene terephthalate (aPET) sheet at 110C. The work also highlighted significant differences in the timing and magnitude of the cavity pressures reached in the two thermoforming machines. The prototype system has considerable potential for further development. 

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Ageing and deterioration of infrastructure is a challenge facing transport authorities. In
particular, there is a need for increased bridge monitoring in order to provide adequate
maintenance and to guarantee acceptable levels of transport safety. The Intelligent
Infrastructure group at Queens University Belfast (QUB) are working on a number of aspects
of infrastructure monitoring and this paper presents summarised results from three distinct
monitoring projects carried out by this group. Firstly the findings from a project on next
generation Bridge Weight in Motion (B-WIM) are reported, this includes full scale field testing
using fibre optic strain sensors. Secondly, results from early phase testing of a computer
vision system for bridge deflection monitoring are reported on. This research seeks to exploit
recent advances in image processing technology with a view to developing contactless
bridge monitoring approaches. Considering the logistical difficulty of installing sensors on a
‘live’ bridge, contactless monitoring has some inherent advantages over conventional
contact based sensing systems. Finally the last section of the paper presents some recent
findings on drive by bridge monitoring. In practice a drive-by monitoring system will likely
require GPS to allow the response of a given bridge to be identified; this study looks at the
feasibility of using low-cost GPS sensors for this purpose, via field trials. The three topics
outlined above cover a spectrum of SHM approaches namely, wired monitoring, contactless
monitoring and drive by monitoring

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Poor sleep is increasingly being recognised as an important prognostic parameter of health. For those with suspected sleep disorders, patients are referred to sleep clinics which guide treatment. However, sleep clinics are not always a viable option due to their high cost, a lack of experienced practitioners, lengthy waiting lists and an unrepresentative sleeping environment. A home-based non-contact sleep/wake monitoring system may be used as a guide for treatment potentially stratifying patients by clinical need or highlighting longitudinal changes in sleep and nocturnal patterns. This paper presents the evaluation of an under-mattress sleep monitoring system for non-contact sleep/wake discrimination. A large dataset of sensor data with concomitant sleep/wake state was collected from both younger and older adults participating in a circadian sleep study. A thorough training/testing/validation procedure was configured and optimised feature extraction and sleep/wake discrimination algorithms evaluated both within and across the two cohorts. An accuracy, sensitivity and specificity of 74.3%, 95.5%, and 53.2% is reported over all subjects using an external validation
dataset (71.9%, 87.9% and 56%, and 77.5%, 98% and 57% is reported for younger and older subjects respectively). These results compare favourably with similar research, however this system provides an ambient alternative suitable for long term continuous sleep monitoring, particularly amongst vulnerable populations.

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There have been over 3000 bridge weigh-in-motion (B-WIM) installations in 25 countries worldwide, this has led vast improvements in post processing of B-WIM systems since its introduction in the 1970’s. This paper introduces a new low-power B-WIM system using fibre optic sensors (FOS). The system consisted of a series of FOS which were attached to the soffit of an existing integral bridge with a single span of 19m. The site selection criteria and full installation process has been detailed in the paper. A method of calibration was adopted using live traffic at the bridge site and based on this calibration the accuracy of the system was determined.