Using statistical inverse methods for detecting defects in electronic components

The thermal modeling of electronic components is mandatory to optimize the cooling design versus reliability. Indeed most of failures are due to thermal phenomena [1]. Some of them are neglected or omitted by lack of data: ageing, manufacturing issues like voids in glue or solder joints, or material properties variability. Transient measurements of the junction-to-board temperature supply real thermal behavior of the component and PCB assembly to complete these missing data[2]. To complement and supplement the numerical model, inverse methods identification based on a statistical deconvolution approach, such as Bayesian one, is applied on these measurements to extract a Foster RC thermal network. The identification algorithm performances have been demonstrated on numerical as well as experimental dataset. Furthermore defects or voids can be detected using the extracted Foster RC networks.

Gupta Transform Approach to the Series RL and RC Networks with Steady Excitation Sources

The analysis of electric networks circuits is an essential course in engineering. The response of such networks is usually obtained by mathematical approaches such as Laplace Transform, Calculus Approach, Convolution Theorem Approach, Residue Theorem Approach. This paper presents a new integral transform called Gupta Transform for obtaining the complete response of the series RL and RC networks circuits with a steady voltage source. The response obtained will provide electric current or charge flowing through series RL and RC networks circuits with a steady voltage source. In this paper, the response of the series RL and RC networks circuits with steady excitation source is provided as a demonstration of the application of the new integral transform called Gupta Transform.

Realization of Cole–Davidson Function-Based Impedance Models: Application on Plant Tissues

The Cole–Davidson function is an efficient tool for describing the tissue behavior, but the conventional methods of approximation are not applicable due the form of this function. In order to overcome this problem, a novel scheme for approximating the Cole–Davidson function, based on the utilization of a curve fitting procedure offered by the MATLAB software, is introduced in this work. The derived rational transfer function is implemented using the conventional Cauer and Foster RC networks. As an application example, the impedance model of the membrane of mesophyll cells is realized, with simulation results verifying the validity of the introduced procedure.

Model Order Reduction for Lumped RC Transmission Lines

<div>We start with a detailed review of the PACT approach for model order reduction of RC networks. We then develop a method that uses PACT as a preprocessing step to transform a generic lumped RC transmission line of some nominal order, based on a nominal (r,c) setting, into a parameterized circuit captured in a SPICE sub-circuit description. Then, given any other lumped RC line of the same order, we pass its (r,c) setting as parameters to this sub-circuit so as to automatically transform and reduce the line into a reduced order model without having to rerun PACT. In this way, we effectively characterize lumped RC transmission lines in a way that allows them to be reduced on-the-fly without any expensive processing.</div>

Model Order Reduction for Lumped RC Transmission Lines

<div>We start with a detailed review of the PACT approach for model order reduction of RC networks. We then develop a method that uses PACT as a preprocessing step to transform a generic lumped RC transmission line of some nominal order, based on a nominal (r,c) setting, into a parameterized circuit captured in a SPICE sub-circuit description. Then, given any other lumped RC line of the same order, we pass its (r,c) setting as parameters to this sub-circuit so as to automatically transform and reduce the line into a reduced order model without having to rerun PACT. In this way, we effectively characterize lumped RC transmission lines in a way that allows them to be reduced on-the-fly without any expensive processing.</div>