A convolutional neural network aided physical model improvement for AC solenoid valves diagnosis

This paper focuses on the development of a physics-based diagnostic tool for alternating current (AC) solenoid valves which are categorized as critical components of many machines used in the process industry. Signal processing and machine learning based approaches have been proposed in the literature to diagnose the health state of solenoid valves. However, the approaches do not give a physical explanation of the failure modes. In this work, being capable of diagnosing failure modes while using a physically interpretable model is proposed. Feature attribution methods are applied to CNN on a large data set of the current signals acquired from accelerated life tests of several AC solenoid valves. The results reveal important regions of interest on current signals that guide the modeling of the main missing component of an existing physical model. Two model parameters, which are the shading ring and kinetic coulomb forces, are then identified using current measurements along the lifetime of valves. Consistent trends are found for both parameters allowing to diagnose the failure modes of the solenoid valves. Future work will consist of not only diagnosing the failure modes, but also of predicting the remaining useful life

Domain Adaptive Transfer Learning for Fault Diagnosis

Thanks to digitization of industrial assets in fleets, the ambitious goal of transferring fault diagnosis models fromone machine to the other has raised great interest. Solving these domain adaptive transfer learning tasks has the potential to save large efforts on manually labeling data and modifying models for new machines in the same fleet. Although data-driven methods have shown great potential in fault diagnosis applications, their ability to generalize on new machines and new working conditions are limited because of their tendency to overfit to the training set in reality. One promising solution to this problem is to use domain adaptation techniques. It aims to improve model performance on the target new machine. Inspired by its successful implementation in computer vision, we introduced Domain-Adversarial Neural Networks (DANN) to our context, along with two other popular methods existing in previous fault diagnosis research. We then carefully justify the applicability of these methods in realistic fault diagnosis settings, and offer a unified experimental protocol for a fair comparison between domain adaptation methods for fault diagnosis problems.Comment: Presented at 2019 Prognostics and System Health Management Conference (PHM 2019) in Paris, Franc

A generalisation of a partition theorem of Andrews to overpartitions

In 1969, Andrews proved a theorem on partitions with difference conditions which generalises Schur's celebrated partition identity. In this paper, we generalise Andrews' theorem to overpartitions. The proof uses q-differential equations and recurrences

Resolving Architectural Mismatches of COTS Through Architectural Reconciliation

The integration of COTS components into a system under development entails architectural mismatches. These have been tackled, so far, at the component level, through component adaptation techniques, but they also must be tackled at an architectural level of abstraction. In this paper we propose an approach for resolving architectural mismatches, with the aid of architectural reconciliation. The approach consists of designing and subsequently reconciling two architectural models, one that is forward-engineered from the requirements and another that is reverse-engineered from the COTS-based implementation. The final reconciled model is optimally adapted both to the requirements and to the actual COTS-based implementation. The contribution of this paper lies in the application of architectural reconciliation in the context of COTS-based software development. Architectural modeling is based upon the UML 2.0 standard, while the reconciliation is performed by transforming the two models, with the help of architectural design decisions.

The behavior of statically-indeterminate structural members and frames with cracks present

Arts et Métiers ParisTech, invitation en tant que professeur invité de Paul C. Paris au LAMEFIPCrack stability is discussed as affected by their presence in statically-indeterminate beams, frames, rings, etc. loaded into the plastic range. The stability of a crack in a section, which has become plastic, is analyzed with the remainder of the structure elastic and with subsequent additional plastic hinges occurring. The reduction of energy absorption characteristics for large deformations is also discussed. The methods of elastic–plastic tearing instability are incorporated to show that in many cases the fully plastic collapse mechanism must occur for complete failure.The authors acknowledge Arts et Metiers Paris Tech and Foundation Arts et Metiers for the financial support of the Prof. P.C. Paris’ stay at LAMEFIP in 2008 and 2009. The encouragement of Prof. Ivan Iordanoff, Director of LAMEFIP, is also acknowledged with thanks

On the characterization of models of H*: The semantical aspect

We give a characterization, with respect to a large class of models of untyped lambda-calculus, of those models that are fully abstract for head-normalization, i.e., whose equational theory is H* (observations for head normalization). An extensional K-model $D$ is fully abstract if and only if it is hyperimmune, {\em i.e.}, not well founded chains of elements of D cannot be captured by any recursive function. This article, together with its companion paper, form the long version of [Bre14]. It is a standalone paper that presents a purely semantical proof of the result as opposed to its companion paper that presents an independent and purely syntactical proof of the same result

The design of surfaces, between empathy and new figuration

Nowadays design languages seem anew defined through images and figures that appear increasingly distant from abstraction. In the time that we live in, where it is prevailing a dominance of individual needs rather common desires, an abandon of abstraction in favour of new figuration, stimulates the opportunity to investigate a new dyad, ‘Project and Empathy’; these terms could summarize well the expanded modality of physical and psychological interaction between people – as individual – and artefacts, through the increasing role of surfaces. The whole world of postmodern image, especially through the digital technologies, tends to offer hyper realistic aesthetic simulacra, altered nature: this is the current world of extension of feelings and sense, in which we are immersed daily. This condition affect the approaches to design, which require a new thinking around technologies, method and tools from training to practice the activity of design: a new attitude for materiality of things, beyond the immateriality of digital reality

Irreducible Coxeter groups

We prove that a non-spherical irreducible Coxeter group is (directly) indecomposable and that a non-spherical and non-affine Coxeter group is strongly indecomposable in the sense that all its finite index subgroups are (directly) indecomposable. We prove that a Coxeter group has a decomposition as a direct product of indecomposable groups, and that such a decomposition is unique up to a central automorphism and a permutation of the factors. We prove that a Coxeter group has a virtual decomposition as a direct product of strongly indecomposable groups, and that such a decomposition is unique up to commensurability and a permutation of the factors

From braid groups to mapping class groups

This paper is a survey of some properties of the braid groups and related groups that lead to questions on mapping class groups