Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

Current transients in the small salient-pole alternator caused by sudden short-circuit and synchronisation events

Small salient-pole machines, in the range 30 kVA to 2 MVA, are often used in distributed generators, which in turn are likely to form the major constituent of power generation in power system islanding schemes or microgrids. In addition to power system faults, such as short-circuits, islanding contains an inherent risk of out-of-synchronism re-closure onto the main power system. To understand more fully the effect of these phenomena on a small salient-pole alternator, the armature and field currents from tests conducted on a 31.5 kVA machine are analysed. This study demonstrates that by resolving the voltage difference between the machine terminals and bus into direct and quadrature axis components, interesting properties of the transient currents are revealed. The presence of saliency and short time-constants cause intriguing differences between machine events such as out-of-phase synchronisations and sudden three-phase short-circuits.

Structural basis for the platelet-collagen interaction - The smallest motif within collagen that recognizes and activates platelet glycoprotein VI contains two glycine-proline-hydroxyproline triplets

Collagen-related peptide is a selective agonist for the platelet collagen receptor Glycoprotein VI. The triple helical peptide contains ten GPO triplets/strand (single letter amino acid nomenclature, where O is hydroxyproline) and so over-represents GPO compared with native collagen sequence. To investigate the ability of Glycoprotein VI to recognize GPO triplets in a setting more representative of the collagens, we synthesized a set of triple helical peptides containing fewer GPO triplets, varying their number and spacing within an inert (GPP)(n) backbone. The adhesion of recombinant human Glycoprotein VI ectodomain, like that of human platelets, to these peptides increased with their GPO content, and platelet adhesion was abolished by the specific anti-Glycoprotein VI-blocking antibody, 10B12. Platelet aggregation and protein tyrosine phosphorylation were induced only by cross-linked peptides and only those that contained two or more GPO triplets. Such peptides were less potent than cross-linked collagen-related peptide. Our data suggest that both the sequences GPOGPO and GPO center dot center dot center dot center dot center dot center dot center dot center dot center dot GPO represent functional Glycoprotein VI recognition motifs within collagen. Furthermore, we propose that the (GPO)(4) motif can support simultaneous binding of two glycoprotein VI molecules, in either a parallel or anti-parallel stacking arrangement, which could play an important role in activation of signaling.

Application of Nonlinear PCA for Fault Detection in Polymer Extrusion Processes

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

The triazatruxene derivative azatrux binds to the parallel form of the human telomeric G-quadruplex under molecular crowding conditions: Biophysical and molecular modeling studies

The present study has employed a combination of spectroscopic, calorimetric and computational methods to explore the binding of the three side-chained triazatruxene derivative, termed azatrux, to a human telomeric G-quadruplex sequence, under conditions of molecular crowding. The binding of azatrux to the tetramolecular parallel [d(TGGGGT)](4) quadruplex in the presence and absence of crowding conditions, was also characterized. The data indicate that azatrux binds in an end-stacking mode to the parallel G-quadruplex scaffold and highlights the key structural elements involved in the binding. The selectivity of azatrux for the human telomeric G-quadruplex relative to another biologically relevant G-quadruplex (c-Kit87up) and to duplex DNA was also investigated under molecular crowding conditions, showing that azatrux has good selectivity for the human telomeric G-quadruplex over the other investigated DNA structures. (C) 2011 Elsevier Masson SAS. All rights reserved.

A structural analysis of G-quadruplex/ligand interactions

This focused review article discusses in detail, all available high-resolution small molecule ligand/G-quadruplex structural data derived from crystallographic and NMR based techniques, in an attempt to understand key factors in ligand binding and to highlight the biological importance of these complexes. In contrast to duplex DNA, G-quadruplexes are four-stranded nucleic acid structures folded from guanine rich repeat sequences stabilized by the stacking of guanine G-quartets and extensive Watson-Crick/Hoogsteen hydrogen bonding. Thermally stable, these topologies can play a role in telomere regulation and gene expression. The core structures of G-quadruplexes form stable scaffolds while the loops have been shown, by the addition of small molecule ligands, to be sufficiently adaptable to generate new and extended binding platforms for ligands to associate, either by extending G-quartet surfaces or by forming additional planar dinucleotide pairings. Many of these structurally characterised loop rearrangements were totally unexpected opening up new opportunities for the design of selective ligands. However these rearrangements do significantly complicate attempts to rationally design ligands against well defined but unbound topologies, as seen for the series of napthalene diimides complexes. Drawing together previous findings and with the introduction of two new crystallographic quadruplex/ligand structures we aim to expand the understanding of possible structural adaptations available to quadruplexes in the presence of ligands, thereby aiding in the design of new selective entities. (C) 2011 Elsevier Masson SAS. All rights reserved.