Table 1 - uploaded by David Alan Meyer
Content may be subject to copyright.
Source publication
This work is part of an effort to structurally integrate self-sensing functionality into smart composite materials using embedded microsensors and local network communication nodes. Here we address the issue of data management through the development of localized processing algorithms. We demonstrate that the two-dimensional fast Fourier transform...
Context in source publication
Context 1
... reordering is achieved for a sequence by performing the following steps for each number: transform its index into a binary representation, reverse the order of bits, and transform back to the appropriate index. Table 1 shows this process for a sequence of size N = 8. The 1D FFT can therefore be achieved by bit-reversing the input sequence, and then calculating transforms of length 2, 4, 8, . . . ...
Similar publications
Rotary encoders and resolvers are by far the most common sensors to measure joint angles in articulated robots. Since various control approaches require angular rates as well, resolvers and encoders are also employed to derive angular rate signals. Due to the involved differentiation operation, however, quantization noise may be augmented significa...
To prolong the operating time of unmanned aerial vehicles which use proton exchange membrane fuel cells (PEMFC), the performance of PEMFC is the key. However, a long-term operation can make the Pt particles of the catalyst layer and the pollutants in the feedstock gas bond together (e.g., CO), so that the catalyst loses reaction activity. The perfo...
Superelastic carbon microcoils (SE-CMC) with coil diameters of 10–15 µm and high elasticity were prepared by the Ni catalysed pyrolysis of acetylene. The SE-CMC could be extended and contracted to 5–10 times their original coil length; these effects accompanied changes in electrical parameters. The extension of the bulk SE-CMC sheets was highly sen...
Single polyps of Galaxea fascicularis were fixed to glass vials with underwater epoxy resin. After regeneration into microcolonies they were used for microsensor measurements of photosynthesis and calcification under different incubating temperatures. Gross photosynthesis was found highest at temperatures of 23 and 26°C (ca.0.022 mole O2 m-3 s-1),...
A new concept for an optical biosensor based on whispering gallery mode (WGM) excitations in clusters of spherical microresonators is presented. Clusters of microresonators offer the advantage to exhibit specific WGM spectra that can be considered as their fingerprint. Therefore, individual clusters can be traced throughout an experiment even witho...
Citations
... The special characteristic of FBG sensors and optical fibers is that they can provide structural health monitoring for the entire lifetime of the composite, both during its production phase (i.e., composite material cure monitoring) [15] and during its service life [16]. Alternatively, micro-sensors can be embedded in the composite material for assessing its health as network nodes (Fig. 4 [17]). ...
... Integration of network nodes in a composite plane[17] ...
Multifunctional materials are designed so as to meet specific requirements through tailored properties. Smart materials can
be considered as multifunctional ones that have the ability to react upon an external stimulus, simulating, in this way, the
behavior of nature’s materials. Furthermore, the introduction of biomemetics in the material science, allows the designing
of materials with similar processes as nature does: building from molecules to complete structures. This paper focuses on
the presentation of the various multifunctional materials reported in the literature and the processing means developed.
KeywordsMultifunctional materials-Smart materials-Composites-Material processing
... Here we propose a locally-performed (in situ at embedded nodes) distributed algorithm for identifying the location of defects/failures in a 2D structure. The idea is to use a distributed 2D spatial CWT, based on the Loewke et al. [15] contribution that employs a 1D FFT transform, and our own work on a distributed 2D FFT algorithm. We concentrate on local in situ processing for two primary reasons. ...
... ), the 2D DFT can be efficiently implemented using the Row-Column FFT or Radix-2 by 2 Vector-Radix FFT; see [15]. Here we use Row-Column FFT as an example. ...
... ) with butterfly operations can be performed independently and concurrently in separate processors [15], which is appropriate for distributed processing. The array multiplication process does not require communication between different processors. ...
When materials in a structure suffer damage, the mechanical response of the structure is modified, particularly in the vicinity of the damaged zones. Such local perturbations in the structural response generally are very small but they can be detected using wavelet transform techniques. To this end, a distributed two-dimensional (2D) Continuous Wavelet Transform (CWT) algorithm is developed which can use data from discrete sets of nodes and provide spatially continuous variation in the structural response parameters to monitor structural degradation. Combined with an embedded sensor network to provide nodal response signals, this algorithm has the potential for Structural Health Monitoring (SHM). The advantageous features of this algorithm are its reliance on local data, its ability to yield spatially continuous information, and its limited communication and computation requirements. The feasibility of the method is demonstrated using two illustrative examples: one is based on the crack-tip strain field of a plate subjected to bi-axial loads, and the other is based on the deflection field of a simply supported plate with defects subjected to static or impacting transverse loads (using a finite-element method (FEM) to obtain solutions). For each case, a set of discrete data is used to simulate the nodal sensor response, and then the 2D CWT is applied to detect the damage. The damage positions are accurately located and the damage severity is qualitatively assessed. In addition, a 3D data case (2D spatial signal with time history) is examined to demonstrate the feasibility of using a 3D CWT for SHM.
... Each roadblock encountered takes three cycles to recognize and process, after which the broken pathway is noted and future communications can be routed more efficiently. Despite this robustness, all algorithms we have currently explored rely on the fast Fourier transform [4], continuous wavelet transform or some other such algorithm requiring the participation of all nodes in the network -thus, excluding deduced data, the failure of a single node subverts our current data analysis. It is clear even from Figure 4 that the primary drawback to a mesh network is its expense in terms of wiring and communications. ...
We report our recent progress in integrating a network of microelectronic sensors into structural composite materials to monitor its health as well as its environment. These integrated sensors render the composite information-based, so that it can monitor and report on the external and internal local structural environment, on request or in real-time, as necessary. We are studying the structural effects of the embedded integration of these sensors/microprocessors, and develop software tools for in situ data processing and global collection of the data sensed by the network.
Integration of a structural health monitoring distributed network and sensing elements within fiber reinforced polymer composites poses many challenges not the least of which are mechanical and computational considerations. Mechanical integrity of the composite is of utmost importance in the embedding of sensing and electronic elements within a fiber reinforced polymer composite. However, it still must be considered in the context of a competing concern - the ability to effectively determine the health of the composite. This conflict is exacerbated by fiber reinforced polymer composites' highly attenuating, dispersive, and anisotropic nature. Mechanical integrity demands fewer/smaller inclusions while the second constraint requires a high density of sensing elements. Mechanical investigations including modeling, bending and tensile fatigue have been performed on fiber reinforced polymer composites with inclusions of varying dimensions, mechanical properties, and lay-up strategies. Assuming a satisfactory compromise is reached, the bandwidth requirement and processing demand of a dense sensor network lends itself well to the idea of incorporating computation at the same scale. Distributed processing with the sensors results in a decreased demand for bandwidth and less computational power needed at each node in what could be considered a parallel processing network. Several network strategies have been considered including latency: tolerance and avoidance, memory access, and architectural considerations and consequences around such structures as mesh, tree, pyramid and hypercube (multi-dimensional) and their affect on communications, algorithms and fault tolerance. The distributed network, like traditional distributed systems, allows for the inclusion of heterogeneous components. This flexibility to use multiple sensors and sensing strategies should allow at least an adaptable need-based SHM network and hopefully a more full bodied analysis of the health of the material.
A novel approach based on hidden Markov models (HMMs) is proposed for damage classification in composite structures. Time-frequency damage features are first extracted from the measured signals using the matching pursuit decomposition algorithm. The features are then incorporated as observation sequences to be modeled statistically by the HMMs. Once built, the HMMs are integrated very efficiently into a Bayesian framework for the classification of structural damage. Both discrete and continuous observation density HMMs are considered; continuous HMMs are shown to yield better accuracy, but at the cost of added computational complexity. A decision fusion procedure is employed to combine the local classification results at each sensor, significantly enhancing the overall classification performance. The utility of the proposed technique is demonstrated by its application to the classification of delamination damage, impact damage, and progressive tensile damage in laminated composites.
The highly dispersive, attenuating, heterogeneous and anisotropic nature of unidirectional fiber reinforced polymer matrix (FRP) composites places an emphasis on high density local sensing as opposed to lower density more-global sensing strategies. This thus requires a relatively high density of sensors for damage characterization and detection, which naturally implies large quantities of data requiring substantial bandwidth and processing power. Distributing processing with the sensors themselves results in a decreased demand for bandwidth and lower computational power needed at each node in what is now a distributed processing computer. Desired information, time constraints and mechanical considerations place both hard and soft constraints on our network helping to define its architecture. I will present investigated computing architectures - their benefits and limitations - as they relate to the various constraints involved, as well as our progress in damage assessment with the distributed sensing network.
