Fibre-optic strain sensor system with temperature compensation for arch bridge condition monitoring

This paper presents an innovative sensor system, created specifically for new civil engineering structural monitoring applications, allowing specially packaged fiber grating-based sensors to be used in harsh, in-the-field measurement conditions for accurate strain measurement with full temperature compensation. The sensor consists of two fiber Bragg gratings that are protected within a polypropylene package, with one of the fiber gratings isolated from the influence of strain and thus responding only to temperature variations, while the other is sensitive to both strain and temperature. To achieve this, the temperature-monitoring fiber grating is slightly bent and enclosed in a metal envelope to isolate it effectively from the strain. Through an appropriate calibration process, both the strain and temperature coefficients of each individual grating component when incorporated in the sensor system can be thus obtained. By using these calibrated coefficients in the operation of the sensor, both strain and temperature can be accurately determined. The specific application for which these sensors have been designed is seen when installed on an innovative small-scale flexi-arch bridge where they are used for real-time strain measurements during the critical installation stage (lifting) and loading. These sensors have demonstrated enhanced resilience when embedded in or surface-mounted on such concrete structures, providing accurate and consistent strain measurements not only during installation but subsequently during use. This offers an inexpensive and highly effective monitoring system tailored for the new, rapid method of the installation of small-scale bridges for a variety of civil engineering applications.

Condition monitoring and diagnostics of power transformers

This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

Condition monitoring and diagnostics of power transformers

This paper addresses the subject of condition monitoring and diagnostics of power transformers. The main results of two reliability surveys, carried out under the auspices of CIGRE and IEEE in order to assemble objective data on the performance of transformers in service, are presented, providing useful information on the main causes of transformer failures, the most likely affected components and the related outages times. A survey of the most important methods, actually in use, for condition monitoring and diagnostics of power transformers is also given, which stresses the need for the development of new diagnostic methods, that can be applied without taking the transformers out of service, and that can also provide a fault severity criteria, in particular for determining transformers windings integrity. Preliminary results, concerning the on-going research activity on the development of a new approach for inter-turn winding fault diagnosis in three-phase transformers, are also reported in the paper.

Some questions of condition monitoring of turbopropengine transmission

The mathematical model of the transmission of the turbine engine was made ... (texto em russo)

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.

Application of a model updating technique for health condition monitoring and damage detection of flexible structures

This paper discusses the application of a damage detection methodology to monitor the location and extent of partial structural damage. The methodology combines, in an iterative way, the model updating technique based on frequency response functions (FRF) with monitoring data aiming at identifying the damage area of the structure. After the updating procedure reaches a good correlation between the models, it compares the parameters of the damage structure with those of the undamaged one to find the deteriorated area. The influence of the FEM mesh size on the evaluation of the extent of the damage has also been discussed. The methodology is applied using real experimental data from a spatial frame structure.

A numerical methodology for the multi-objective optimization of the DI Diesel engine combustion

DI Diesel engine are widely used both for industrial and automotive applications due to their durability and fuel economy. Nonetheless, increasing environmental concerns force that type of engine to comply with increasingly demanding emission limits, so that, it has become mandatory to develop a robust design methodology of the DI Diesel combustion system focused on reduction of soot and NOx simultaneously while maintaining a reasonable fuel economy. In recent years, genetic algorithms and CFD three-dimensional combustion simulations have been successfully applied to that kind of problem. However, combining GAs optimization with actual CFD three-dimensional combustion simulations can be too onerous since a large number of calculations is usually needed for the genetic algorithm to converge, resulting in a high computational cost and, thus, limiting the suitability of this method for industrial processes. In order to make the optimization process less time-consuming, CFD simulations can be more conveniently used to generate a training set for the learning process of an artificial neural network which, once correctly trained, can be used to forecast the engine outputs as a function of the design parameters during a GA optimization performing a so-called virtual optimization. In the current work, a numerical methodology for the multi-objective virtual optimization of the combustion of an automotive DI Diesel engine, which relies on artificial neural networks and genetic algorithms, was developed.

Gasoline emissions dominate over diesel in formation of secondary organic aerosol mass

Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

Ultrasonic acoustic emissions in drought-stressed trees - more than signals from cavitation?

Ultrasonic acoustic emission (UAE) in trees is often related to collapsing water columns in the flow path as a result of tensions that are too strong (cavitation). However, in a decibel (dB) range below that associated with cavitation, a close relationship was found between UAE intensities and stem radius changes. • UAE was continuously recorded on the stems of mature field-grown trees of Scots pine (Pinus sylvestris) and pubescent oak (Quercus pubescens) at a dry inner-Alpine site in Switzerland over two seasons. The averaged 20-Hz records were related to microclimatic conditions in air and soil, sap-flow rates and stem-radius fluctuations de-trended for growth (ΔW). • Within a low-dB range (27 ± 1 dB), UAE regularly increased and decreased in a diurnal rhythm in parallel with ΔW on cloudy days and at night. These low-dB emissions were interrupted by UAE abruptly switching between the low-dB range and a high-dB range (36 ± 1 dB) on clear, sunny days, corresponding to the widely supported interpretation of UAE as sound from cavitations. • It is hypothesized that the low-dB signals in drought-stressed trees are caused by respiration and/or cambial growth as these physiological activities are tissue water-content dependent and have been shown to produce courses of CO2 efflux similar to our courses of ΔW and low-dB UAE.

On the cup anemometer working condition monitoring

The analysis of the harmonic terms related to the rotational speed of a cup anemometer is a way to detect anomalies such as wear and tear, rotor non-symmetries (rotor damage) or problems at the output signal system. The research already done in this matter at the IDR/UPM Institute is now taken to cup anemometers working on the field. A 1-2 year testing campaign is being carried out in collaboration with Kintech Engineering. 2 Thies First Class Advanced installed at 58 m and 73 m height in a meteorology tower are constantly monitored. The results will be correlated to the anemometer performance evolution studied through several calibrations planned to be performed along the testing campaign.

Preparation, characterisation and testing of CuO/Ce0.8Zr0.2O2 catalysts for NO oxidation to NO2 and mild temperature diesel soot combustion

CuO/ceria-zirconia catalysts have been prepared, deeply characterised (N2 adsorption–desorption isotherms at −196 °C, XRD, Raman spectroscopy, XPS, TEM and H2-TPR) and tested for NO oxidation to NO2 in TPR conditions, and for soot combustion at mild temperature (400 °C) in a NOx/O2 stream. The behaviour has been compared to that of a reference Pt/alumina commercial catalyst. The ceria-zirconia support was prepared by the co-precipitation method, and different amounts of copper (0.5, 1, 2, 4 and 6 wt%) were loaded by incipient wetness impregnation. The results revealed that copper is well-dispersed onto the ceria-zirconia support for the catalysts with low copper loading and CuO particles were only identified by XRD in samples with 4 and 6% of copper. A very low loading of copper increases significantly the activity for the NO oxidation to NO2 with regard to the ceria-zirconia support and an optimum was found for a 4% CuO/ceria-zirconia composition, showing a very high activity (54% at 348 °C). The soot combustion rate at 400 °C obtained with the 2% CuO/ceria-zirconia catalyst is slightly lower to that of 1% Pt/alumina in terms of mass of catalyst but higher in terms of price of catalyst.

Emissions from the Pyrolysis and Combustion of Different Wastes

Paper submitted to the 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 23-26 October 2013.

Pollutant emissions during the pyrolysis and combustion of flexible polyurethane foam

Thermal decomposition of flexible polyurethane foam (FPUF) was studied under nitrogen and air atmospheres at 550 °C and 850 °C using a laboratory scale reactor to analyse the evolved products. Ammonia, hydrogen cyanide and nitrile compounds were obtained in high yields in pyrolysis at the lower temperature, whereas at 850 °C polycyclic aromatic hydrocarbons (PAHs) and other semivolatile compounds, especially compounds containing nitrogen (benzonitrile, aniline, quinolone and indene) were the most abundant products. Different behaviour was observed in the evolution of polychlorodibenzo-p-dioxins and furans (PCDD/Fs) at 550 °C and 850 °C. At 550 °C, the less chlorinated congeners, mainly PCDF, were more abundant. Contrarily, at 850 °C the most chlorinated PCDD were dominant. In addition, the total yields of PCDD/Fs in the pyrolysis and combustion runs at 850 °C were low and quite similar.

Condition monitoring of pipelines

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Active oxygen by Ce–Pr mixed oxide nanoparticles outperform diesel soot combustion Pt catalysts

A Ce0.5Pr0.5O2 mixed oxide has been prepared with the highest surface area and smallest particle size ever reported (125 m2/g and 7 nm, respectively), also being the most active diesel soot combustion catalyst ever tested under realistic conditions if catalysts forming highly volatile species are ruled out. This Ce–Pr mixed oxide is even more active than a reference platinum-based commercial catalyst. This study provides an example of the efficient participation of oxygen species released by a ceria catalyst in a heterogeneous catalysis reaction where both the catalyst and one of the reactants (soot) are solids. It has been concluded that both the ceria-based catalyst composition (nature and amount of dopant) and the particle size play key roles in the combustion of soot through the active oxygen-based mechanism. The composition determines the production of active oxygen and the particle size the transfer of such active oxygen species from catalyst to soot.