Anti-Dissipative Schemes for Advection and Application to Hamilton–Jacobi–Bellmann Equations

We propose two new antidiffusive schemes for advection (or linear transport), one of them being a mixture of Roe’s Super-Bee scheme and of the “Ultra-Bee” scheme. We show how to apply these schemes to treat time-dependent first order Hamilton–Jacobi–Bellman equations with discontinuous initial data, possibly infinitely-valued. Numerical tests are proposed, in one and two space dimensions, in order to validate the methods AMS subject classifications. Primary 65M12, Secondary 58J47     

An Efficient Data Structure and Accurate Scheme to Solve Front Propagation Problems

In this paper, we are interested in some front propagation problems coming from control problems in d-dimensional spaces, with d≥2. As opposed to the usual level set method, we localize the front as a discontinuity of a characteristic function. The evolution of the front is computed by solving an Hamilton-Jacobi-Bellman equation with discontinuous data, discretized by means of the antidissipative Ultra Bee scheme. We develop an efficient dynamic storage technique suitable for handling front evolutions in large dimension. Then we propose a fast algorithm, showing its relevance on several challenging tests in dimension d=2,3,4. We also compare our method with the techniques usually used in level set methods. Our approach leads to a computational cost as well as a memory allocation scaling as O(N _nb ) in most situations, where N _nb is the number of grid nodes around the front. Moreover, we show on several examples the accuracy of our approach when compared with level set methods.     

Induction motor stator faults diagnosis by a current Concordia pattern-based fuzzy decision system

This paper deals with the problem of detection and diagnosis of induction motor faults. Using the fuzzy logic strategy, a better understanding of heuristics underlying the motor faults detection and diagnosis process can be achieved. The proposed fuzzy approach is based on the stator current Concordia patterns. Induction motor stator currents are measured, recorded, and used for Concordia patterns computation under different operating conditions, particularly for different load levels. Experimental results are presented in terms of accuracy in the detection of motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia patterns.     

Deformation textures in wire drawn perlitic steel

In this study, we followed the deformation microstructure and texture evolution during the cold wire drawing of a perlitic steel wire intended for civil engineering applications. The deformation level effect on the microstructure evolution and on the texture evolution is characterized. Wire drawing induces the lengthening of the perlitic grains along the drawing axis and leads to a strong hardness increase. X-ray texture measurements were performed. The reference state (initial wire) revealed an isotropic texture. The quantitative analysis show the development of the α fibre (<110>//ND (ND // wire) with the deformation. Moreover, the {001}?<?110?>?orientation (rotated Cube) is also present. The experimental techniques used in this study are the: Optical Microscopy (OM), the Electron Back Scattered Diffraction (EBSD), the X-ray diffraction, the Neutron diffraction and the Vickers microhardness.     

Multi-objective optimization by a new hybridized method: applications to random mechanical systems

In this article two linear problems with random Gaussian loading are transformed into multi-objective optimization problems. The first problem is the design of a pillar geometry with respect to a compressive random load process. The second problem is the design of a truss structure with respect to a vertical random load process for several frequency bands. A new algorithm, motivated by the Pincus representation formula hybridized with the Nelder–Mead algorithm, is proposed to solve the two multi-objective optimization problems. To generate the Pareto curve, the normal boundary intersection method is used to produce a series of constrained single-objective optimizations. The second problem, depending on the frequency band of excitation, can have as Pareto curve a single point, a standard Pareto curve, or a discontinuous Pareto curve, a fact that has been reported here for the first time in the literature, to the best of the authors’ knowledge.     

2001 Middle-East Power Systems Conference 29-31 December 2001 Helwan, Cairo, Egypt

This letter presents a method for induction motor on-line rotor resistance estimation. This is important in vector control, if high-performance torque control is needed. For this purpose, a fuzzy logic technique is used to estimate the rotor resistance. The fuzzy estimator (FE) principle design is then presented, and simulations demonstrate the effectiveness of the proposed method.     

Minimum time control problems for non-autonomous differential equations

In this paper, we investigate a minimum time problem for controlled non-autonomous differential systems, with dynamics depending on the final time. The minimal time function associated to this problem does not satisfy the dynamic programming principle. However, we will prove that it is related to a standard front propagation problem via the reachability function. Two simple numerical examples are given to illustrate our approach.     

A Fuzzy-Based Approach for the Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor Drive

This paper investigates the use of fuzzy logic for fault detection and diagnosis in a pulsewidth modulation voltage source inverter (PWM-VSI) induction motor drive. The proposed fuzzy technique requires the measurement of the output inverter currents to detect intermittent loss of firing pulses in the inverter power switches. For diagnosis purposes, a localization domain made with seven patterns is built with the stator Concordia current vector. One is dedicated to the healthy domain and the six others to each inverter power switch. The fuzzy bases of the proposed technique are extracted from the current analysis of the fault modes in the PWM-VSI. Experimental results on a 1.5-kW induction motor drive are presented to demonstrate the effectiveness of the proposed fuzzy approach.     

Modified risk graph method using fuzzy rule-based approach

The risk graph is one of the most popular methods used to determine the safety integrity level for safety instrumented functions. However, conventional risk graph as described in the IEC 61508 standard is subjective and suffers from an interpretation problem of risk parameters. Thus, it can lead to inconsistent outcomes that may result in conservative SILs. To overcome this difficulty, a modified risk graph using fuzzy rule-based system is proposed. This novel version of risk graph uses fuzzy scales to assess risk parameters and calibration may be made by varying risk parameter values. Furthermore, the outcomes which are numerical values of risk reduction factor (the inverse of the probability of failure on demand) can be compared directly with those given by quantitative and semi-quantitative methods such as fault tree analysis (FTA), quantitative risk assessment (QRA) and layers of protection analysis (LOPA).