Experience using MEMS-based accelerometers in dynamic testing

Measurement of acceleration in dynamic tests is carried out routinely, and in most cases, piezoelectric accelerometers are used at present. However, a new class of instruments based on MEMS technology have become available and are gaining use in many applications due to their small size, low mass and low-cost. This paper describes a centrifuge lateral spreading experiment in which MEMS and piezoelectric accelerometers were placed at similar depths. Good agreement was obtained when the instruments were located in dense sands, but significant differences were observed in loose, liquefiable soils. It was found that the performance of the piezoelectric accelerometer is poor at low frequency, and that the relative phase difference between the piezoelectric and MEMS accelerometer varies significantly at low frequency. © 2010 Taylor & Francis Group, London.

Testing in harsh conditions: Tracking resources on construction sites with machine vision

When tracking resources in large-scale, congested, outdoor construction sites, the cost and time for purchasing, installing and maintaining the position sensors needed to track thousands of materials, and hundreds of equipment and personnel can be significant. To alleviate this problem a novel vision based tracking method that allows each sensor (camera) to monitor the position of multiple entities simultaneously has been proposed. This paper presents the full-scale validation experiments for this method. The validation included testing the method under harsh conditions at a variety of mega-project construction sites. The procedure for collecting data from the sites, the testing procedure, metrics, and results are reported. Full-scale validation demonstrates that the novel vision tracking provides a good solution to track different entities on a large, congested construction site.

Testing of Depth-Encoded Hough Voting for Infrastructure Object Detection

The lack of viable methods to map and label existing infrastructure is one of the engineering grand challenges for the 21st century. For instance, over two thirds of the effort needed to geometrically model even simple infrastructure is spent on manually converting a cloud of points to a 3D model. The result is that few facilities today have a complete record of as-built information and that as-built models are not produced for the vast majority of new construction and retrofit projects. This leads to rework and design changes that can cost up to 10% of the installed costs. Automatically detecting building components could address this challenge. However, existing methods for detecting building components are not view and scale-invariant, or have only been validated in restricted scenarios that require a priori knowledge without considering occlusions. This leads to their constrained applicability in complex civil infrastructure scenes. In this paper, we test a pose-invariant method of labeling existing infrastructure. This method simultaneously detects objects and estimates their poses. It takes advantage of a recent novel formulation for object detection and customizes it to generic civil infrastructure scenes. Our preliminary experiments demonstrate that this method achieves convincing recognition results.

UK-NEES - Distributed hybrid testing between Bristol, Cambridge and Oxford Universities: Connecting structural dynamics labs to a geotechnical centrifuge

Distributed hybrid testing is a natural extension to and builds upon the local hybrid testing technique. Taking advantage of the hybrid nature of the test, it allows a sharing of resources and expertise between researchers from different disciplines by connecting multiple geographically distributed sites for joint testing. As part of the UK-NEES project, a successful series of three-site distributed hybrid tests have been carried out between Bristol, Cambridge and Oxford Universities. The first known multi-site distributed hybrid tests in the UK, they connected via a dedicated fibre network, using custom software, the geotechnical centrifuge at Cambridge to structural components at Bristol and Oxford. These experiments were to prove the connection and useful insights were gained into the issues involved with this distributed environment. A wider aim is towards providing a flexible testing framework to facilitate multi-disciplinary experiments such as the accurate investigation of the influence of foundations on structural systems under seismic and other loading. Time scaling incompatibilities mean true seismic soil structure interaction using a centrifuge at g is not possible, though it is clear that distributed centrifuge testing can be valuable in other problems. Development is continuing to overcome the issues encountered, in order to improve future distributed tests in the UK and beyond.

Flaw sizing in pipes using long-range guided wave testing

The absence of adequate inspection data from difficult-to-access areas on pipelines, such as cased-road crossings, makes determination of fitness for continued service and compliance with increasingly stringent regulatory requirements problematic. Screening for corrosion using long-range guided wave testing is a relatively new inspection technique. The complexity of the possible modes of vibration means the technique can be difficult to implement effectively but this also means that it has great potential for both detecting and characterizing flaws. The ability to determine flaw size would enable the direct application of standard procedures for determining fitness-for-service, such as ASME B31G, RSTRENG, or equivalent for tens of metres of pipeline from a single inspection location. This paper presents a new technique for flaw sizing using guided wave inspection data. The technique has been developed using finite element models and experimentally validated on 6'' Schedule 40 steel pipe. Some basic fitness-for-service assessments have been carried out using the measured values and the maximum allowable operating pressure was accurately determined. © 2011 American Institute of Physics.

Modeling fatigue crack growth in crystalline solids with discrete dislocation plasticity

Analyses of crack growth under cyclic loading conditions are discussed where plastic flow arises from the motion of large numbers of discrete dislocations and the fracture properties are embedded in a cohesive surface constitutive relation. The formulation is the same as used to analyse crack growth under monotonic loading conditions, differing only in the remote loading being a cyclic function of time. Fatigue, i.e. crack growth in cyclic loading at a driving force for which the crack would have arrested under monotonic loading, emerges in the simulations as a consequence of the evolution of internal stresses associated with the irreversibility of the dislocation motion. A fatigue threshold, Paris law behaviour, striations, the accelerated growth of short cracks and the scaling with material properties are outcomes of the calculations. Results for single crystals and polycrystals will be discussed.

Design and testing of a 250 kW medium-speed Brushless DFIG

This paper presents the design and testing of a 250 kW medium-speed Brushless Doubly-Fed Induction Generator (Brushless DFIG), and its associated power electronics and control systems. The experimental tests confirm the design, and show the system's steady-state and dynamic performance. The medium-speed Brushless DFIG in combination with a simplified two-stage gearbox promises a low-cost low-maintenance and reliable drive train for wind turbine applications.

Half-bridge SIC inverter for hybrid electric vehicles: Design, development and testing at higher operating temperature

In recent years, Silicon Carbide (SiC) semiconductor devices have shown promise for high density power electronic applications, due to their electrical and thermal properties. In this paper, the performance of SiC JFETs for hybrid electric vehicle (HEV) applications is investigated at heatsink temperatures of 100 °C. The thermal runaway characteristics, maximum current density and packaging temperature limitations of the devices are considered and the efficiency implications discussed. To quantify the power density capabilities of power transistors, a novel 'expression of rating' (EoR) is proposed. A prototype single phase, half-bridge voltage source inverter using SiC JFETs is also tested and its performance at 25 °C and 100 °C investigated.

Design and testing of an ortho-planar micro-valve

This paper presents the production and testing of an ortho-planar one-way micro-valve. The main advantages of such valves are that they are very compact and can be made from a single flat piece of material. A previous paper presents and discusses a micro-valve assembly based on a spider spring. The present paper focuses on the valve assembly process and the valve performance.. Several prototypes with a bore of 0.2 mm have been built using two manufacturing techniques (μEDM and stereo-lithography) and tested for pressures up to 7 bars. © 2008 International Federation for Information Processing.

An example of the use of neural computing techniques in materials science - The modelling of fatigue thresholds in Ni-base superalloys

Two adaptive numerical modelling techniques have been applied to prediction of fatigue thresholds in Ni-base superalloys. A Bayesian neural network and a neurofuzzy network have been compared, both of which have the ability to automatically adjust the network's complexity to the current dataset. In both cases, despite inevitable data restrictions, threshold values have been modelled with some degree of success. However, it is argued in this paper that the neurofuzzy modelling approach offers real benefits over the use of a classical neural network as the mathematical complexity of the relationships can be restricted to allow for the paucity of data, and the linguistic fuzzy rules produced allow assessment of the model without extensive interrogation and examination using a hypothetical dataset. The additive neurofuzzy network structure means that redundant inputs can be excluded from the model and simple sub-networks produced which represent global output trends. Both of these aspects are important for final verification and validation of the information extracted from the numerical data. In some situations neurofuzzy networks may require less data to produce a stable solution, and may be easier to verify in the light of existing physical understanding because of the production of transparent linguistic rules. © 1999 Elsevier Science S.A.