Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Investigation of megavoltage beams and detectors for electronic portal imaging

Accuracy of dose delivery in external beam radiotherapy is usually verified with electronic portal imaging (EPI) in which the treatment beam is used to check the positioning of the patient. However the resulting megavoltage x-ray images suffer from poor quality. The image quality can be improved by developing a special operating mode in the linear accelerator. The existing treatment beam is modified such that it produces enough low-energy photons for imaging. In this work the problem of optimizing the beam/detector combination to achieve optimal electronic portal image quality is addressed. The linac used for this study was modified to produce two experimental photon beams. These beams, named Al6 and Al10, were non-flat and were produced by 4MeV electrons hitting aluminum targets, 6 and 10mm thick respectively. The images produced by a conventional EPI system (6MV treatment beam and camera-based EPID with a Cu plate & Gd2O2S screen ) were compared with the images produced by the experimental beams and various screens with the same camera). The contrast of 0.8cm bone equivalent material in 5 cm water increased from 1.5% for the conventional system to 11% for the combination of Al6 beam with a 200mg/cm2 Gd2O2S screen. The signal-to-noise ratio calculated for 1cGy flood field images increased by about a factor of two for the same EPI systems. The spatial resolution of the two imaging systems was comparable. This work demonstrates that significant improvements in portal image contrast can be obtained by simultaneous optimization of the linac spectrum and EPI detector.

Use of electronic portal imaging devices for electron treatment verification

This study aims to help broaden the use of electronic portal imaging devices (EPIDs) for pre-treatment patient positioning verification, from photon-beam radiotherapy to photon- and electron-beam radiotherapy, by proposing and testing a method for acquiring clinicallyuseful EPID images of patient anatomy using electron beams, with a view to enabling and encouraging further research in this area. EPID images used in this study were acquired using all available beams from a linac configured to deliver electron beams with nominal energies of 6, 9, 12, 16 and 20 MeV, as well as photon beams with nominal energies of 6 and 10 MV. A widely-available heterogeneous, approximately-humanoid, thorax phantom was used, to provide an indication of the contrast and noise produced when imaging different types of tissue with comparatively realistic thicknesses. The acquired images were automatically calibrated, corrected for the effects of variations in the sensitivity of individual photodiodes, using a flood field image. For electron beam imaging, flood field EPID calibration images were acquired with and without the placement of blocks of water-equivalent plastic (with thicknesses approximately equal to the practical range of electrons in the plastic) placed upstream of the EPID, to filter out the primary electron beam, leaving only the bremsstrahlung photon signal. While the electron beam images acquired using a standard (unfiltered) flood field calibration were observed to be noisy and difficult to interpret, the electron beam images acquired using the filtered flood field calibration showed tissues and bony anatomy with levels of contrast and noise that were similar to the contrast and noise levels seen in the clinically acceptable photon beam EPID images. The best electron beam imaging results (highest contrast, signal-to-noise and contrast-to-noise ratios) were achieved when the images were acquired using the higher energy electron beams (16 and 20 MeV) when the EPID was calibrated using an intermediate (12 MeV) electron beam energy. These results demonstrate the feasibility of acquiring clinically-useful EPID images of patient anatomy using electron beams and suggest important avenues for future investigation, thus enabling and encouraging further research in this area. There is manifest potential for the EPID imaging method proposed in this work to lead to the clinical use of electron beam imaging for geometric verification of electron treatments in the future.

Electronic and vibrational spectra of gaspeite

Visible, near-infrared, IR and Raman spectra of magnesian gaspeite are presented. Nickel ion is the main source of the electronic bands as it is the principal component in the mineral where as the bands in IR and Raman spectra are due to the vibrational processes in the carbonate ion as an entity. The combination of electronic absorption and vibrational spectra (including near-infrared, FTIR and Raman) of magnesian gaspeite are explained in terms of the cation co-ordination and the behaviour of CO32– anion in the Ni–Mg carbonate. The electronic absorption spectrum consists of three broad and intense bands at 8130, 13160 and 22730 cm–1 due to spin-allowed transitions and two weak bands at 20410 and 30300 cm–1 are assigned to spin-forbidden transitions of Ni2+ in an octahedral symmetry. The crystal field parameters evaluated from the observed bands are Dq = 810; B = 800 and C = 3200 cm–1. The two bands in the near-infrared spectrum at 4330 and 5130 cm–1 are overtone and combination of CO32– vibrational modes. For the carbonate group, infrared bands are observed at 1020 cm–1(1 ), 870 cm–1 (2), 1418 cm–1 (3) and 750 cm–1 (4), of which3, the asymmetric stretching mode is most intense. Three well resolved Raman bands at 1571, 1088 and 331 cm–1 are assigned to 3, 1 and MO stretching vibrations.