6 resultados para Application performance monitoring.

em CORA - Cork Open Research Archive - University College Cork - Ireland


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Embedded wireless sensor network (WSN) systems have been developed and used in a wide variety of applications such as local automatic environmental monitoring; medical applications analysing aspects of fitness and health energy metering and management in the built environment as well as traffic pattern analysis and control applications. While the purpose and functions of embedded wireless sensor networks have a myriad of applications and possibilities in the future, a particular implementation of these ambient sensors is in the area of wearable electronics incorporated into body area networks and everyday garments. Some of these systems will incorporate inertial sensing devices and other physical and physiological sensors with a particular focus on the application areas of athlete performance monitoring and e-health. Some of the important physical requirements for wearable antennas are that they are light-weight, small and robust and should also use materials that are compatible with a standard manufacturing process such as flexible polyimide or fr4 material where low cost consumer market oriented products are being produced. The substrate material is required to be low loss and flexible and often necessitates the use of thin dielectric and metallization layers. This paper describes the development of such a wearable, flexible antenna system for ISM band wearable wireless sensor networks. The material selected for the development of the wearable system in question is DE104i characterized by a dielectric constant of 3.8 and a loss tangent of 0.02. The antenna feed line is a 50 Ohm microstrip topology suitable for use with standard, high-performance and low-cost SMA-type RF connector technologies, widely used for these types of applications. The desired centre frequency is aimed at the 2.4GHz ISM band to be compatible with IEEE 802.15.4 Zigbee communication protocols and the Bluetooth standard which operate in this band.

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In this paper, a wireless sensor network mote hardware design and implementation are introduced for building deployment application. The core of the mote design is based on the 8 bit AVR microcontroller, Atmega1281 and 2.4 GHz wireless communication chip, CC2420. The module PCB fabrication is using the stackable technology providing powerful configuration capability. Three main layers of size 25 mm2 are structured to form the mote; these are RF, sensor and power layers. The sensors were selected carefully to meet both the building monitoring and design requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks. Experiments show that the developed mote works effectively in giving stable data acquisition and owns good communication and power performance.

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The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

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The effects of vehicle speed for Structural Health Monitoring (SHM) of bridges under operational conditions are studied in this paper. The moving vehicle is modelled as a single degree oscillator traversing a damaged beam at a constant speed. The bridge is modelled as simply supported Euler-Bernoulli beam with a breathing crack. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. The unevenness of the bridge deck is modelled using road classification according to ISO 8606:1995(E). The stochastic description of the unevenness of the road surface is used as an aid to monitor the health of the structure in its operational condition. Numerical simulations are conducted considering the effects of changing vehicle speed with regards to cumulant based statistical damage detection parameters. The detection and calibration of damage at different levels is based on an algorithm dependent on responses of the damaged beam due to passages of the load. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are considered. Sensitivity of calibration values is studied. The findings of this paper are important for establishing the expectations from different vehicle speeds on a bridge for damage detection purposes using bridge-vehicle interaction where the bridge does not need to be closed for monitoring. The identification of bunching of these speed ranges provides guidelines for using the methodology developed in the paper.

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The use of structural health monitoring of civil structures is ever expanding and by assessing the dynamical condition of structures, informed maintenance management can be conducted at both individual and network levels. With the continued growth of information age technology, the potential arises for smart monitoring systems to be integrated with civil infrastructure to provide efficient information on the condition of a structure. The focus of this thesis is the integration of smart technology with civil infrastructure for the purposes of structural health monitoring. The technology considered in this regard are devices based on energy harvesting materials. While there has been considerable focus on the development and optimisation of such devices using steady state loading conditions, their applications for civil infrastructure are less known. Although research is still in initial stages, studies into the uses associated with such applications are very promising. Through the use of the dynamical response of structures to a variety of loading conditions, the energy harvesting outputs from such devices is established and the potential power output determined. Through a power variance output approach, damage detection of deteriorating structures using the energy harvesting devices is investigated. Further applications of the integration of energy harvesting devices with civil infrastructure investigated by this research includes the use of the power output as a indicator for control. Four approaches are undertaken to determine the potential applications arising from integrating smart technology with civil infrastructure, namely • Theoretical analysis to determine the applications of energy harvesting devices for vibration based health monitoring of civil infrastructure. • Laboratory experimentation to verify the performance of different energy harvesting configurations for civil infrastructure applications. • Scaled model testing as a method to experimentally validate the integration of the energy harvesting devices with civil infrastructure. • Full scale deployment of energy harvesting device with a bridge structure. These four approaches validate the application of energy harvesting technology with civil infrastructure from a theoretical, experimental and practical perspective.

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The use of energy harvesting materials for large infrastructure is a promising and growing field. In this regard, the use of such harvesters for the purpose of structural health monitoring of bridges has been proposed in recent times as one of the feasible options since the deployment of them can remove the necessity of an external power source. This paper addresses the performance issue of such monitors over the life-cycle of a bridge as it deteriorates and the live load on the structure increases. In this regard, a Lead Zirconate Titanate (PZT) material is considered as the energy harvesting material and a comparison is carried out over the operational life of a reinforced concrete bridge. The evolution of annual average daily traffic (AADT) is taken into consideration, as is the degradation of the structure over time, due to the effects of corrosion. Evolution of such harvested energy is estimated over the life-cycle of the bridge and the sensitivity of harvested energy is investigated for varying rates of degradation and changes in AADT. The study allows for designing and understanding the potential of energy harvesters as a health monitor for bridges. This paper also illustrates how the natural growth of traffic on a bridge over time can accentuate the identification of damage, which is desirable for an ageing structure. The paper also assesses the impact and effects of deployment of harvesters in a bridge as a part of its design process, considering performance over the entire life-cycle versus a deployment at a certain age of the structure.