Isidro Sergio Durazo-Cardenas

Experimental characterisation of macro fibre composites and monolithic piezoelectric transducers for strain energy harvesting

μCompact and lightweight energy harvesters are needed to power wireless sensor nodes (WSNs). WSNs can provide health monitoring of aircraft structures, improving safety and reducing costs by enabling predictive maintenance. A simple solution, which meets the requirements for lightness and compactness, is represented by piezoelectric generators fixed to the surface of the wing (i.e. the wing skin). Such piezoelectric patches can harvest the strain energy available when the wing is flexed, as occurs, for example, in the presence of gust loading. For this study, monolithic piezoelectric sheets and macro fibre composite (MFC) generators were fixed to plates made of two materials commonly used for aircraft wing skin: Al-2024 aluminium alloy and an epoxy-carbon fibre composite. The plates then underwent harmonically varying loading in a tensile testing machine. The power generation of the harvesters was measured at a selection of strain levels and excitation frequencies, across a range of electrical loads. The optimal electrical load, yielding maximum power extraction, was identified for each working condition. The generated power increases quadratically with the strain and linearly with the frequency. The optimal electrical load decreases with increasing frequency and is only marginally dependent on strain. Absolute values of generated power were highest with the MFC, reaching 12mW (330μW/cm2) under 1170μstrain peak-to-peak excitation at 10Hz with a 66kΩ load. Power generation densities of 600μW/cm2 were achieved under 940μstrain with the monolithic transducers at 10Hz. It is found that MFCs have a lower power density than monolithic transducers, but, being more resilient, could be a more reliable choice. The power generated and the voltage outputs are appropriate for the intended application.

The performance of a porous ceramic hydrostatic journal bearing

Abstract The performance of a porous-ceramic hydrostatic journal bearing manufactured by the starch consolidation (SC) technique has been examined using a highly instrumented test rig. The results have been compared with those of a 5-recess hydrostatic bearing of the same size and comparable design, under the same testing conditions. The SC porous-ceramic bearing showed an improved performance over the conventional hydrostatic bearing. Static and rotational stiffness were 95 per cent and over 150 per cent higher, respectively. In addition, the porous ceramic bearing exhibited a more economic performance with a 64 per cent lower flowrate and pumping power than the hydrostatic bearing. In terms of heat generation, the porous ceramic bearing showed 50 per cent lower temperature rise.

Data Fusion Strategy for Precise Vehicle Location for Intelligent Self-Aware Maintenance Systems

Nowadays careful measurement applications are handed over to Wired and Wireless Sensor Network. Taking the scenario of train location as an example, this would lead to an increase in uncertainty about position related to sensors with long acquisition times like Balises, RFID and Transponders along the track. We take into account the data without any synchronization protocols, for increase the accuracy and reduce the uncertainty after the data fusion algorithms. The case studies, we have analysed, derived from the needs of the project partners: train localization, head of an auger in the drilling sector localization and the location of containers of radioactive material waste in a reprocessing nuclear plant. They have the necessity to plan the maintenance operations of their infrastructure basing through architecture that taking input from the sensors, which are localization and diagnosis, maps and cost, to optimize the cost effectiveness and reduce the time of operation.

An Intelligent Framework and Prototype for Autonomous Maintenance Planning in the Rail Industry

This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries.

Analysis of infrared optical polishing effluents and reduction of COD and TSS levels by ultrafiltration and coagulation/flocculation

AbstractSamples of polishing effluent produced during infrared optics manufacture were analyzed. Their particle size, composition, Zeta potential, chemical oxygen demand (COD), total suspended solids (TSS), and settleable solids were determined. Feasibility of treatment methods such as ultrafiltration (UF) and coagulation/flocculation was investigated to reduce both COD and TSS. It was found that effluents consisted of a suspension of micro- and nanoparticles. Effluent particle size distribution reflected the removal rate of the originating polishing process. Their composition was primarily germanium and other polished substrates as well as polishing abrasives. The effluent Zeta potential was highly negative and prevented particle settling. COD of all specimens was very high, which prevented sewage discharge. Laboratory-scale trials using UF showed substantial COD abatement of up to 74.1%. TSS was reduced to zero after UF. Comparable coagulation/flocculation COD abatement was demonstrated for the highest ...