| || Signal Processing, Wavelets and High-speed Image Interpretation of Bird Impact
Author : Karthikeyan, K.;Ramachandra, S.;Vizhian, Paul S.;Chandra, Satish
Source : Defence Science Journal ; Vol:61(1) ; 2011 ; pp 62-71
Subject : 621.38 Electronics
Keywords : Bird impact;Image processing;Signal processing;Wavelets;Simulation modules
Abstract : Bird impact on aircraft has been well documented and has been of interest for researchers in aircraft design. The process, though of very short duration, is complex in nature. A bird, which can be treated as a soft body behaves more like a fluid at high-speeds. When aircraft components become targets of bird strikes, the impact can have consequences for safety, and hence the study of the phenomena has engineering implications. In this paper, strain signals from a specially instrumented stiff fixture, high-speed imaging and wavelets are used to describe the nature of the phenomenon. Gelatin-based artificial birds were impacted on the fixture fired through an air gun at two different velocities. high-speed imaging showed different behaviours with a rebound at low-velocity (~50 m/s) and a flow behaviour at high-velocity (~100 m/s). High sampling data acquisition was used to measure the dynamic strain exerted on the fixture during bird impact. Time histories of strain signals obtained in the raw form were processed to get a Fourier spectrum and continuous wavelet transform to gain more information about different frequency patterns and the temporal distribution of the frequencies, when such impacts occurred. The frequency content for low-velocity and high-velocity impacts is characterised. It can be noted that the behaviour as described by earlier researchers was seen here as well at higher velocities, though at lower velocities, the bird behaved more like a solid. Many aircraft have approach speeds that are about 60 m/s rather than 100-200 m/s, making it important to study behaviour at lower velocities as well. The short time interval events identified in the signals provide insight into the nature of the loads on targets. This information can aid in tuning simulation models of the birds which use Lagrangian, Eulerian and smooth particle hydrodynamic models.
| || Fusion of Noisy Multi-sensor Imagery
Author : Mishra, Anima;Rakshit, Subrata
Source : Defence Science Journal ; Vol:58(1) ; 2008 ; pp 136-146
Subject : 621.38 Electronics
Keywords : Image fusion;Edge maps;Information maps;Noise filtering;Multi-resolution;Wavelets;Laplacian pyramids;Multi-sensor images
Abstract : Interest in fusing multiple sensor data for both military and civil applications has been growing. Some of the important applications integrate image information from multiple sensors to aid in navigation guidance, object detection and recognition, medical diagnosis, data compression, etc. While, human beings may visually inspect various images and integrate information, it is of interest to develop algorithms that can fuse various input imagery to produce a composite image. Fusion of images from various sensor modalities is expected to produce an output that captures all the relevant information in the input. The standard multi-resolutionbased edge fusion scheme has been reviewed in this paper. A theoretical framework is given for this edge fusion method by showing how edge fusion can be framed as information maximisation. However, the presence of noise complicates the situation. The framework developed is used to show that for noisy images, all edges no longer correspond to information. In this paper, various techniques have been presented for fusion of noisy multi-sensor images. These techniques are developed for a single resolution as well as using multi-resolution decomposition. Some of the techniques are based on modifying edge maps by filtering images, while others depend on alternate definition of information maps. Both these approaches can also be combined. Experiments show that the proposed algorithms work well for various kinds of noisy multisensor images.
| || Analysis of Acoustic Emission Signals using Wavelet Transformation Technique
Author : Rao, S.V. Subba;Subramanyam, B.
Source : Defence Science Journal ; Vol:58(4) ; 2008 ; pp 559-564
Subject : 629.7 Aeronautics;534.8 Acoustics
Keywords : Acoustic emission;Wavelets;Wavelet transform;Coherence estimation function
Abstract : Acoustic emission (AE) monitoring is carried out during proof pressure testing of pressure vessels to find the occurrence of any crack growth-related phenomenon. While carrying out AE monitoring, it is often found that the background noise is very high. Along with the noise, the signal includes various phenomena related to crack growth, rubbing of fasteners, leaks, etc. Due to the presence of noise, it becomes difficult to identify signature of the original signals related to the above phenomenon. Through various filtering/ thresholding techniques, it was found that the original signals were getting filtered out along with noise. Wavelet transformation technique is found to be more appropriate to analyse the AE signals under such situations. Wavelet transformation technique is used to de-noise the AE data. The de-noised signal is classified to identify a signature based on the type of phenomena.