Daniel Massicotte

High-Speed OQPSK and Efficient Power Transfer Through Inductive Link for Biomedical Implants

Biomedical implants require wireless power and bidirectional data transfer. We pursue our previous work on a novel topology for a multiple carrier inductive link by presenting the fabricated coils. We show that the coplanar geometry approach is better suited for displacement tolerance. We provide a theoretical analysis of the efficiency of power transfer and phase-shift-keying communications through an inductive link. An efficiency of up to 61% has been achieved experimentally for power transfer and a data rate of 4.16 Mb/s with a bit-error rate of less than 2 × 10-6 has been obtained with our fabricated offset quadrature phase-shift keying modules due to the inductive link optimization presented in this paper.

Incorporation of a positivity constraint into a Kalman-filter-based algorithm for correction of spectrophotometric data

The results of spectrophotometric measurements are subject to systematic errors of instrumental type which may be partially corrected provided a mathematical model of the instrumental imperfections is identified. It is assumed that this model has the form of an integral, convolution-type equation of the first kind. The correction of the results of the measurements subject to random measurement errors consists in the numerical solution of this equation on the basis of these results. A new method for solving the problem of correction is proposed; it is based on application of the Kalman filter modified in such a way that the negative values of the solution are prohibited. The efficiency of this regularization method is demonstrated. It is studied using both synthetic and real data. >

Wavelet-transform-based method of analysis for Lamb-wave ultrasonic NDE signals

A new acoustic nondestructive method using Lamb waves as a probe is presented. These waves are generated and received by an ElectroMagnetic Acoustic Transducer (EMAT). The position of flaws in the structure under test is computed from the time of arrival of the main peak of the reflected signal. Due to the noisy nature of the received signal, we use a wavelet transform algorithm to extract the required time information. The main advantage of such a multi-scale method of signal analysis is to be suitable for peak detection problems especially in highly noisy environments. We explain how we proceed to do the feature extraction, and we propose two methods for reconstructing the image of the inspected structure. Results of real-world ultrasonic Lamb waves signal analysis are presented. In addition, to test the noise robustness of the method, the case of synthetic noisy signals is also treated.

Ultrasonic NDE of composite material structures using wavelet coefficients

Abstract A wavelet-based method is proposed to perform the analysis of NDE ultrasonic signals received during the inspection of reinforced composite materials. The non-homogenous nature of such materials induces a very high level of structural noise which greatly complicates the interpretation of the NDE signals. By combining the time domain and the classical Fourier analysis, the wavelet transform provides simultaneously spectral representation and temporal order of the signal decomposition components. To construct a C-scan image from the wavelet transform of the A-scan signals, we propose a selection process of the wavelet coefficients, followed by an interpretation procedure based on a windowing process in the time–frequency domain. The proposed NDE method is tested on cryogenic glass/epoxy hydrogen reservoir samples.

Neural classification of Lamb wave ultrasonic weld testing signals using wavelet coefficients

This paper presents an ultrasonic nondestructive weld testing method based on the wavelet transform (WT) of inspection signals and their classification by a neural network (NN). The use of Lamb waves generated by an electromagnetic acoustic transducer (EMAT) as a probe allows us to test metallic welds. In this work, the case of an aluminum weld is treated. The feature extraction is made by using a method of analysis based on the WT of the ultrasonic testing signals; a classification process of the features based on a neural classifier to interpret the results in terms of weld quality concludes the process. The aim of this complete process of analysis and classification of the testing ultrasonic signals is to lead to an automated system of weld or structure testing. Results of real-world ultrasonic Lamb wave signal analysis and classifications for an aluminum weld are presented; these demonstrate the feasibility and efficiency of the proposed method.

Joint transmit antenna selection and user scheduling for Massive MIMO systems

It is largely accepted that the innovative technology of large-scale multiantenna systems (named Massive multiple input multiple output (MIMO) systems) will very probably be deployed in the fifth generation of mobile cellular networks. In order to render this technology feasible and efficient, many challenges have to be investigated before. In this paper, we consider the problem of antenna selection and user scheduling in Massive MIMO systems. Our objective is to maximize the sum of broadcasting data rates achieved by all the mobile users in one cell served by a massive MIMO transmitter. The optimal solution of this problem can be obtained through a highly complex exhaustive brute force search (BFS) over all possible combinations of antennas and users. This BFS solution cannot be implemented in practice even for small size systems because of its high computational complexity. Therefore, in this paper, we propose an algorithm that efficiently solves the problem of joint antenna selection and user scheduling. The proposed algorithm aims to maximize the achievable sum-rate and to benefit from both the spatial selectivity gain and multi-user diversity gain offered by the antenna selection and user scheduling, respectively. Compared with the optimal solution obtained by the highly complex BFS, the conducted performance evaluation and complexity analysis show that the proposed algorithm is able to achieve near-optimal performance with low computational complexity.

Low complexity adaptation of MIMO MMSE receivers, implementation aspects

In this paper we propose two algorithms for adaptation of linear and successive interference cancellation (SIC) MIMO receivers based on the MMSE criterion. The algorithms are compared to the so-called fast V-BLAST algorithm in terms of implementation simplicity and the required number of arithmetic operation. We conclude that both proposed algorithm offer advantages over the algorithm fast V-BLAST. When compared to the latter, the first proposed algorithm has much simpler implementation but the same arithmetic complexity, while the second proposed algorithm lowers by 33% the required number of arithmetic operations

Kalman-filter-based algorithms of spectrometric data correction-Part I: an iterative algorithm of deconvolution

This series of two papers aims to present the different solutions of the problem of improving the resolution of spectrometric measurements via numerical processing of spectrometric data subject both to systematic instrumental errors and to random measurement errors. It is assumed that the model of the spectrometric data has the form of a convolution-type equation of the first kind. The method for improving the resolution consists in numerically solving this equation using the acquired data. In this first paper of the series, an algorithm of correction is proposed which is based on the iterative use of the Kalman filter incorporating a non-negativity constraint. Its applicability to the problem of correction is assessed not only from a purely metrological point of view (accuracy, resolution) but also with respect to its suitability for implementation as a VLSI processor dedicated to measuring systems. For this latter reason a time-invariant model of the data and a steady-state version of the Kalman filter is used. The efficiency of this approach to correction is demonstrated using both synthetic and real-world data.

Novel coils topology intended for biomedical implants with multiple carrier inductive link

Biomedical implants require wireless power and bidirectional data transfer. We propose a novel topology for a multiple carrier inductive link and compare two geometries for it. The orthogonal approach and the coplanar approach are these geometries. The principal challenge with multiple carriers is minimization of crosstalk, especially of power into data under lateral misalignment of the inner and outer coils. We show that a coplanar design allows keeping coupling of power into data under 15 % with respect to the data coupling, even under lateral misalignments over 5 mm. In comparison, the orthogonal geometry reaches over 50 % of parasitic coupling after a displacement of only 3 mm.

Neural-network-based method of calibration and measurand reconstruction for a high-pressure measuring system

The problem of applying the neural networks for static calibration of measuring systems and for measurand reconstruction is addressed. A multilayered neural network based method for the static calibration of this system is proposed. The functioning of the calibrated measuring system is based on three fiber-optic transducers whose static characteristics are nonmonotonic and significantly influenced by temperature. The applicability of the proposed calibration method is demonstrated in the case under consideration using synthetic and real data. The neural network is designed and implemented in a general purpose microcontroller. In comparison with the spline-based method of calibration, for the same reference data, the proposed method allows obtention of a better quality of calibration and, most important, when calibrated, the multilayered neural network does not require the measurement of temperature for pressure reconstruction.