In situ damage detection in frame structures through coupled response measurements

Due to the existence of global modes and local modes of the neighbouring members, damage detection on a structure is more challenging than damage on isolated beams. Detection of an artificial circumferential crack on a joint in a frame-like welded structure is studied in this paper using coupled response measurements. Similarity to real engineering structures is maintained in the fabrication of the test frame. Both the chords and the branch members have hollow sections and the branch members have smaller sizes. The crack is created by a hacksaw on a joint where a branch meets the chord. The methodology is first demonstrated on a single hollow section beam. The test results are then presented for the damaged and undamaged frame. The existence of the damage is clearly observable from the experimental results. It is suggested that this approach offers the-potential to detect damage in welded structures such as cranes, mining equipment, steel-frame bridges, naval and offshore structures. (C) 2003 Elsevier Ltd. All rights reserved.

Crack detection in welded mechanical structures using coupled vibrations

Detection of a fatigue crack in a welded frame structure is studied in this paper using coupled response measurements. Similarity to real engineering structures is maintained in the fabrication of the test frame with hollow section chords and branch members. The fatigue crack was created by a special reciprocating mechanism that generates cyclic stress on a beam member of the structure. The methodology of coupled response measurements is first demonstrated on a single hollow section beam by analytical simulation and experimental validation. The issues of using this approach for fatigue crack detection in real structures are then examined. Finally, the experimental results of the frame under different scenarioes are presented. The existence of the crack is clearly observable from the FRF plots. It is suggested that this approach offers the potential to detect cracks in welded frame structures and is a useful tool for routine maintenance work and health assessment.

Reduced inspiratory muscle endurance following successful weaning from prolonged mechanical ventilation

Study objectives: Respiratory muscle weakness and decreased endurance have been demonstrated following mechanical ventilation. However, its relationship to the duration of mechanical ventilation is not known. The aim of this study was to assess respiratory muscle endurance and its relationship to the duration of mechanical ventilation. Design: Prospective study. Setting: Tertiary teaching hospital ICU. Patients: Twenty subjects were recruited for the study who had received mechanical ventilation for a 48 h and had been discharged from the ICU. Measurements: FEV1 FVC, and maximal inspiratory pressure (Pimax) at functional residual capacity were recorded. The Pimax attained following resisted inspiration at 30% of the initial Pimax for 2 min was recorded, and the fatigue resistance index (FRI) [Pimax final/Pimax initial] was calculated. The duration of ICU length of stay (ICULOS), duration of mechanical ventilation (MVD), duration of weaning (WD), and Charlson comorbidities score (CCS) were also recorded. Relationships between fatigue and other parameters were analyzed using the Spearman correlations (p). Results: Subjects were admitted to the ICU for a mean duration of 7.7 days (SD, 3.7 days) and required mechanical ventilation for a mean duration of 4.6 days (SD, 2.5 days). The mean FRI was 0.88 (SD, 0.13), indicating a 12% fall in Pimax, and was negatively correlated with MVD (r = -0.65; p = 0.007). No correlations were found between the FRI and FEV1, FVC, ICULOS, WD, or CCS. Conclusions: Patients who had received mechanical ventilation for > 48 h have reduced inspiratory muscle endurance that worsens with the duration of mechanical ventilation and is present following successful weaning. These data suggest that patients needing prolonged mechanical ventilation are at risk of respiratory muscle fatigue and may benefit from respiratory muscle training.

Recommendations and guidelines for the performance of accurate heat transfer measurements in rapid forming processes

The published requirements for accurate measurement of heat transfer at the interface between two bodies have been reviewed. A strategy for reliable measurement has been established, based on the depth of the temperature sensors in the medium, on the inverse method parameters and on the time response of the sensors. Sources of both deterministic and stochastic errors have been investigated and a method to evaluate them has been proposed, with the help of a normalisation technique. The key normalisation variables are the duration of the heat input and the maximum heat flux density. An example of application of this technique in the field of high pressure die casting is demonstrated. The normalisation study, coupled with previous determination of the heat input duration, makes it possible to determine the optimum location for the sensors, along with an acceptable sampling rate and the thermocouples critical response-time (as well as eventual filter characteristics). Results from the gauge are used to assess the suitability of the initial design choices. In particular the unavoidable response time of the thermocouples is estimated by comparison with the normalised simulation. (c) 2006 Elsevier Ltd. All rights reserved.

A bayesian artificial neural network method to characterise laminar defects using dynamic measurements

This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.