Piotr Jantos

The Influence of Global Parametric Faults on Analogue Electronic Circuits Time Domain Response Features

This paper presents an analysis of an influence of global parametric faults (GPF) on analogue integrated circuits (AIC) time domain (TD) response features, such as overshoot, delay time, rise time, maxima and minima, first differential maxima and minima. The novel approach is the analysis of relations and superrelations between features which are discussed in details. The presented results should increase testability and diagnosability of the global parametric faults on a production line of analogue and mixed electronic circuits. The observed AIC faults belong to parametric ones and are caused by technological process. GPF influence on aforementioned features is presented with the use of an exemplary circuit. A research presented in this paper may be used as an introduction to a fault driven test (FDT) diagnosis with the use of simulation before test (SBT) methods.

A global parametric faults diagnosis with the use of artificial neural networks

A method of a global parametric faults diagnosis in analogue integrated circuits is presented in this paper. The method is based on basic features calculated from a circuits under test time domain response to a voltage step, i.e. locations of maxima and minima of circuit under test response and its first order derivative. The testing and diagnosis process is executed with the use of an artificial neural network. The neural network is supplied with extracted basic features. After evaluation and discrimination, the neural network outputs indicate the circuit state. The proposed diagnosis method has been verified with the use of exemplary integrated circuits — an operation amplifier µA741 and an integrated band-pass filter.

Global parametric faults identification with the use of Differential Evolution

This paper presents a novel method to a multiple parametric faults diagnosis (global parametric faults - GPF) in analogue integrated circuits (AIC). The method is based on features of AIC time domain response to voltage step excitation, i.e. AIC response and its first order derivative maxima and minima locations. A circuit states classification is acquired with the use of linear evolutionary classifier which parameters are determined with the use of Differential Evolution. Selected AIC response features distributions are approximated with geometric figures based on polynomial functions. The proposed diagnosis method has been applied for a GPF diagnosis in an exemplary integrated circuit - operational amplifier µ4741.

Gene Expression Programming-Based Method of Optimal Frequency Set Determination for Purpose of Analogue Circuits’ Diagnosis

This paper presents a method for optimal frequency search with the use of Gene Expression Programming (GEP). It includes a brief summary of material of analogue circuits fault diagnosis and introduction to GEP. Developed method belongs to SBT diagnosis routines’ group. Frequency responses for chosen hard faults of a circuit under test as well as for an intact circuit are simulated before test. There are ambiguity sets provided to avoid a fault tolerance masking effect.

Automated method for passive filters design based on evolutionary computations and Monte Carlo analysis

This paper describes the heuristic technique of analog filters design. After desired frequency response definition for a filter, the evolutionary system searches for adequate connections for its circuit. The circuit is constructed with the use of elementary blocks which contain two elements (resistance and reactance). The final values for all elements of the filter are searched locally by means of Monte Carlo analysis. The proposed solution can be especially suitable to special filters designing, i.e. these ones, for which amplitude responses have not typical shapes.