Fault diagnosis using partial syndromes: a modified Hopfield neural network approach

This paper presents a modified Hopfield neural network (HNN) for solving the system-level fault diagnosis problem which aims at identifying the set of faulty nodes. This problem has been extensively studied in the last three decades. Nevertheless, identifying the set of all faulty nodes using only partial syndromes, i.e. when some of the testing or comparison outcomes are missing prior to initiating the diagnosis phase, remains an outstanding research issue. The new HNN-based diagnosis algorithm does not require any prior learning or knowledge about the system, nor about any faulty situation, hence providing a better generalisation performance. Results from a thorough simulation study demonstrate the effectiveness of the HNN-based fault diagnosis algorithm in terms of diagnosis correctness, diagnosis latency and diagnosis scalability, for randomly generated diagnosable systems of different sizes and under various fault scenarios. We have also conducted extensive simulations using partial syndromes. Simulations showed that the HNN-based diagnosis performed efficiently, i.e. diagnosis correctness was around 99% when at most half of the test or comparison outcomes are missing, making it a viable alternative to existing diagnosis algorithms.     

Some investigations into the optimal dimensional synthesis of parallel robots

In this paper, we will perform a comparison between two approaches of dimensional synthesis of parallel robots. The first one concerns the single-objective optimization approach; in this case, the dimensional synthesis is expressed by taking into account only one performance criterion but enables to get a final solution if it exists. The second one concerns the multi-objective optimization approach; it enables to simultaneously take into account several performance criteria. However, this approach appears to provide a set of solutions instead of a single expected final solution which should directly enable to carry out the structural synthesis. In fact, the search of a single final solution is postponed to a further step where the designers have to impose and/or restrict certain parameters. And we will establish if it is really necessary to make a multi-objective optimization approach or if a single-objective is sufficient to reach the objectives set in the specifications (user requirements). A discussion is proposed concerning the arising questions related to each approach and leading to the optimal dimensional synthesis. The PAR2 robot with two degree-of-freedom is used to exemplify the analysis and the comparison of the two approaches. The proposed comparison can be applied to any classes of parallel robots.     

Efficient synthesis of novel 2,3-dihydro-1,3,5,4-thiadiazaphosphole derivatives

The condensation of various thiosemicarbazones with methyl thiophene-2-carboximidate afforded the corresponding intermediates 2a–2h. Subsequent cyclization of the latter compounds with hexamethylphosphorous triamide constitutes a new route to the synthesis of novel highly functionalized thiadiazaphosphole derivatives 4a–4h. This method offers significant advantages such as efficiency, high yields and mild reaction conditions.     

Electrical conductivity and percolation threshold of hybrid carbon/polymer composites

The electrical conductivity and percolation threshold of single and hybrid carbon filled composites are experimentally investigated. Polystyrene, carbon fiber (CF) and carbon black (CB) at three CF/CB ratios of 1.67, 3.33, 6.67 were compounded in a twin screw extruder micro‐compounder and compression molded into sheets. The through‐plane and in‐plane electrical conductivity of the composites are measured by 2 and 4 probe techniques. The percolation threshold of the single filler and hybrid composites are determined from the experimental results using a percolation model. The hybrid composites have a higher value of electrical conductivity and lower percolation threshold than the single CF filler composite except for the CF/CB ratio of 6.67. The percolation threshold for the cases of single filler and hybrid composites are modeled. The hard core / soft shell model is used and it is assumed that the percolation in a particle filled system depends on the ratio of tunneling distance to particle diameter. This ratio is determined by modeling single filler composites using the experimental data and kept constant in the modeling of the hybrid system. Finite size scaling is used to determine the percolation threshold for the infinite size hybrid system containing (nanosize) particles and micron size fibers for three CF/CB ratios. The simulation results show that the percolations of hybrid composites have the same trends observed in the experimental results. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41744.     

One-pot lithium bromide-catalyzed reaction of polyoxyethylene diglycidyl ether with carbon disulfide: synthesis of new polyoxyethylene epoxyoxathiolane-2-thione

A simple and highly efficient regio- and chemio-specific synthesis of polyoxyethylene epoxyoxathiolan-2-thione was realized from a one-pot reaction of polyoxyethylene diglycidyl ether and carbon disulfide using lithium bromide as a catalyst. The unsymmetrical obtained products were fully characterized by ¹H, ¹³C NMR and high-resolution mass spectra data.     

Iterative PET Image Reconstruction Using Translation Invariant Wavelet Transform

The present work describes a Bayesian maximum a posteriori (MAP) method using a statistical multiscale wavelet prior model. Rather than using the orthogonal discrete wavelet transform (DWT), this prior is built on the translation invariant wavelet transform (TIWT). The statistical modeling of wavelet coefficients relies on the generalized Gaussian distribution. Image reconstruction is performed in spatial domain with a fast block sequential iteration algorithm. We study theoretically the TIWT MAP method by analyzing the Hessian of the prior function to provide some insights on noise and resolution properties of image reconstruction. We adapt the key concept of local shift invariance and explore how the TIWT MAP algorithm behaves with different scales. It is also shown that larger support wavelet filters do not offer better performance in contrast recovery studies. These theoretical developments are confirmed through simulation studies. The results show that the proposed method is more attractive than other MAP methods using either the conventional Gibbs prior or the DWT-based wavelet prior.     

Inelastic initial local buckling of skew thin thickness-tapered plates with and without intermediate supports using the isoparametric spline finite strip method

In this paper, skew isotropic plates subjected to in-plane loadings are analyzed using a stability analysis based on the isoparametric spline finite strip method, which includes inelasticity. Using this method, the initial inelastic local buckling of skew plates with or without intermediate line supports is studied based on Ramberg–Osgood representation of the stress–strain curve using the deformation theory of plasticity. Stiffness and stability matrices are formulated by energy expressions using the small deflection theory. The effect of tapered section on the local buckling of skew plates is taken into account. Finally, the inelastic local buckling loads of these plates are obtained and the results are compared with known solutions in the literature.     

Matrix formulation of fuzzy rule-based systems

In this paper, a matrix formulation of fuzzy rule based systems is introduced. A gradient descent training algorithm for the determination of the unknown parameters can also be expressed in a matrix form for various adaptive fuzzy networks. When converting a rule-based system to the proposed matrix formulation, only three sets of linear/nonlinear equations are required instead of set of rules and an inference mechanism. There are a number of advantages which the matrix formulation has compared with the linguistic approach. Firstly, it obviates the differences among the various architectures; and secondly, it is much easier to organize data in the implementation or simulation of the fuzzy system. The formulation will be illustrated by a number of examples.