Behavioural Modelling, Simulation, Test and Diagnosis of MEMS using ANNs

The design of Micro-Electrical-Mechanical Systems requires that the entire system can be modelled and simulated. Additionally, behaviour under fault conditions must be simulated to determine test and diagnosis strategies. While the electrical parts of a system can be modelled at transistor, gate or behavioural levels, the mechanical parts are conventionally modelled in terms of partial differential equations (PDEs). Mixed-signal electrical simulations are possible, using e.g. VHDL-AMS, but simulations that include PDEs are prohibitively expensive. Here, we show that complex PDEs can be replaced by black-box functional models and, importantly, such models can be characterized automatically and rapidly using artificial neural networks (ANNs). We demonstrate a significant increase in simulation speed and show that test and diagnosis strategies can be derived using such models

ANN based modeling, testing and diagnosis of MEMS

New concepts of simulation, testing and diagnosis of MEMS are proposed, intended to boost the time to market and dependability of such systems. Black-box modeling of non-electronic parts is introduced using artificial neural networks, so enabling radically faster simulation without concurrent algorithms and parallel computation. A Jumped model of the capacitive transducer, being the part of a micro-electro-mechanical capacitive pressure sensing system, is created using an ANN. Faults are then introduced to the sensing system and simulation of the fault-free and faulty circuits are demonstrated

Efficient and realistic statistical worst case delay computation using VHDL

A method for worst case path-delay estimation in complex digital circuits is presented. It has been named Statistical Static Timing Analysis Using a Standard Logic Simulator (SSTA for SLog). It enables acceleration of algorithmically simple but computationally expensive and time-consuming Monte-Carlo simulations. The technique deals with fabrication-dependent delay variations of a particular technology. It applies a realistic rise/fall delay model with fanout dependent delays based on technology and implementation data

Analogue electronic circuit diagnosis based on ANNs

Feed-forward artificial neural networks (ANNs) have been applied to the diagnosis of nonlinear dynamic analogue electronic circuits. Using the simulation-before-test (SBT) approach, a fault dictionary was first created containing responses observed at all inputs and outputs of the circuit. The ANN was considered as an approximation algorithm to capture mapping enclosed within the fault dictionary and, in addition, as an algorithm for searching the fault dictionary in the diagnostic phase. In the example given DC and small signal frequency domain measurements were taken as these data are usually given in device’s data-sheets. A reduced set of data per fault (DC output values, the nominal gain and the 3 dB cut-off frequency, measured at one output terminal) was recorded. Soft (parametric) and catastrophic (shorts and opens) defects were introduced and diagnosed simultaneously and successfully. Large representative set of faults was considered, i.e., all possible catastrophic transistor faults and qualified representatives of soft transistor faults were diagnosed in an integrated circuit. The generalization property of the ANNs was exploited to handle noisy measurement signals

Fault diagnosis in digital part of mixed-mode circuit

In this paper artificial neural networks (ANNs) are applied to diagnosis of catastrophic defects in the digital part of a nonlinear mixed-mode circuit. The approach is demonstrated on the example of a relatively complex sigma-delta modulator. A set of faults is selected first. Then, fault dictionary is created. by simulation, using the response of the circuit to an input ramp signal. It is represented in a form of a look-up table. Artificial neural network is then trained for modeling (memorizing) the look-up table. The diagnosis is performed so that the ANN is excited by faulty responses in order to present the fault codes at its output. There were no errors in identiting the faults during diagnosis

Computer integrated analogue electronics laboratory for undergraduate teaching

Computer system for laboratory exercises in basic analogue electronics was developed. It is aimed to emphasize the learning of electronic component and circuit behavior and to develop other praxis to teaching measurement skills. Hardware part of the system is based on PC computers with acquisition cards and circuits whose parameters are measured. The software part is realized using LabVIEW programming tool. The main goal of this system is to simplify manipulation of instruments, faster measurement and acquisition of the results, providing students to concentrate on measurement essence

Procedural Analog Design (PAD) tool

This paper presents a new Procedural Analog Design tool called PAD. It is a chart-based design environment dedicated to the design of analog circuits aiming to optimise design and quality by finding good tradeoffs. This interactive tool allows step-by-step design of analog cells by using guidelines for each analog topology. At each step, the user modifies interactively one subset of design parameters and observes the effect on other circuit parameters. At the end, an optimised design is ready for simulation (verification and fine-tuning). Furthermore, PAD provides a layout generator for matched substructures such as current mirror, cascode stage, differential pair, etc. The analog basic structures calculator embedded in PAD uses the complete set of equations of the EKV MOS model, which links the equations for weak and strong inversion in a continuous way[1,2]. The present version of PAD covers the procedural design of transconductance amplifiers (OTAs) and different operational amplifiers topologies