Analog Electronic Circuits Research Articles

Multi Frequency Approach to Analog Fault Diagnosis using Pole Sensitivity Analysis

In this paper an efficient algorithm using multi-frequency approach has been applied to fault diagnosis of analog electronic circuits using Pole Sensitivity analysis. In this paper, after application of the multi frequency approach to the pole sensitivity analysis the results show that the fault diagnosis of the circuit has increased. This has been proved by taking two circuits a second order Sallen Key Filter and RC Ladder network.

Fuzzy classifier for fault diagnosis in analog electronic circuits

Many studies have presented different approaches for the fault diagnosis with fault models having ±50% variation in the component values in analog electronic circuits. There is still a need of the approaches which provide the fault diagnosis with the variation in the component value below ±50%. A new single and multiple fault diagnosis technique for soft faults in analog electronic circuit using fuzzy classifier has been proposed in this paper. This technique uses the simulation before test (SBT) approach by analyzing the frequency response of the analog circuit under faulty and fault free conditions. Three signature parameters peak gain, frequency and phase associated with peak gain, of the frequency response of the analog circuit are observed and extracted such that they give unique values for faulty and fault free configuration of the circuit. The single and double fault models with the component variations from ±10% to ±50% are considered. The fuzzy classifier along the classification of faults gives the estimated component value under faulty and faultfree conditions. The proposed method is validated using simulated data and the real time data for a benchmark analog circuit. The comparative analysis is also presented for both the validations.

SU‐E‐T‐661: Nonlinear Continuous Method for Non‐Negatively Constrained Inverse Problem of IMRT Planning

Purpose: The intensity‐modulated radiation therapy (IMRT) is an effective therapeutic technique for the treatment of tumors in the human body without inflicting serious damage to normal tissues. IMRT plans include an optimization strategy for minimizing an objective function of radiation beam weights. We present a novel approach for solving non‐negatively constrained inverse problems in IMRT treatment planning, based on the idea of continuous‐time dynamical methods using nonlinear differential equations. Our method can compute a feasible solution without the second derivative of an objective function, which is required for gradient‐based optimization algorithms such as conjugate gradient and steepest descent methods. Methods: We first consider the stability of an equilibrium, which corresponds to the desired planning in the IMRT system, by the use of Lyapunov's stability theorem. Then we perform some phantom experiments using phantom data simulating a clinical setup. Results: We prove theoretically that a Kullback‐Leibler (KL) divergence can be a Lyapunov function for the IMRT planning system, in consistent case. It means that the KL‐divergence measure decreases along the solution to the differential equation. Additionally, we show that the intensity of any radiation beam is not negative. Because the planning system can be created as an analog electronic circuit, its implementation in actual hardware yields dramatically faster planning as a physical phenomenon with real parallel computing, than software‐based iterative methods. Conclusion: The proposed method provides not only the reduction of a computational cost but also no production of a solution with an unphysical negative radiation beam coefficient in solving IMRT planning inverse problems. Moreover the theoretical results on convergence properties of solutions are confirmed by numerical experiments. Based on the results, we found that we can obtain a feasible solution violating the physical dose constraints minimally, even if the system is inconsistent.

THEORY AND EXPERIMENT OF A FIRST-ORDER CHAOTIC DELAY DYNAMICAL SYSTEM

We report the theory and experiment of a new time-delayed chaotic (hyperchaotic) system with a single scalar time delay and a nonlinearity described by a closed form mathematical function. Detailed stability and bifurcation analyses establish that with the suitable delay and system parameters, the system shows a stable limit cycle through a supercritical Hopf bifurcation. Numerical simulations exemplify that the system depicts mono-scroll and double-scroll chaos and hyperchaos for a range of delay and other system parameters. Nonlinear behavior of the system is characterized by Lyapunov exponents and Kaplan–Yorke dimension. It is established that, for some suitably chosen system parameters, the system shows hyperchaos even for a small or moderate time delay. Finally, the system is implemented in an analogue electronic circuit using off-the-shelf circuit elements. It is shown that the behavior of the time delay chaotic electronic circuit qualitatively agrees well with our analytical and numerical results.

Sequences of gluing bifurcations in an analog electronic circuit

We report on the experimental investigation of gluing bifurcations in the analog electronic circuit which models a dynamical system of the third order: Lorenz equations with an additional quadratic nonlinearity. Variation of one of the resistances in the circuit changes the coefficient at this nonlinearity and enables transition from the Lorenz route to chaos to a different scenario which leads, through the sequence of homoclinic bifurcations, from periodic oscillations of the voltage to the chaotic state. A single bifurcation "glues" in the phase space two stable periodic orbits and creates a new one, with the doubled length: a bifurcation sequence results in the birth of the chaotic attractor.

A high sensitivity fiber optic macro-bend based gas flow rate transducer for low flow rates: Theory, working principle, and static calibration

A novel fiber optic macro-bend based gas flowmeter for low flow rates is presented. Theoretical analysis of the sensor working principle, design, and static calibration were performed. The measuring system consists of: an optical fiber, a light emitting diode (LED), a Quadrant position sensitive Detector (QD), and an analog electronic circuit for signal processing. The fiber tip undergoes a deflection in the flow, acting like a cantilever. The consequent displacement of light spot center is monitored by the QD generating four unbalanced photocurrents which are function of fiber tip position. The analog electronic circuit processes the photocurrents providing voltage signal proportional to light spot position. A circular target was placed on the fiber in order to increase the sensing surface. Sensor, tested in the measurement range up to 10 l min(-1), shows a discrimination threshold of 2 l min(-1), extremely low fluid dynamic resistance (0.17 Pa min l(-1)), and high sensitivity, also at low flow rates (i.e., 33 mV min l(-1) up to 4 l min(-1) and 98 mV min l(-1) from 4 l min(-1) up to 10 l min(-1)). Experimental results agree with the theoretical predictions. The high sensitivity, along with the reduced dimension and negligible pressure drop, makes the proposed transducer suitable for medical applications in neonatal ventilation.

Neural Network based Fault Diagnosis in Analog Electronic Circuit using Polynomial Curve Fitting

studies have been presented for the fault diagnosis of electronic analog circuits with worst case fault models using ±50% variation in the parametric values of the components. The study of for parametric fault detection in electronic analog circuits -faults as small as 10% or less was uncovered. The use of the neural network for parametric fault diagnosis in an analog circuit, based upon the polynomial curve fitting coefficients of the output response of an analog circuit is presented in this study. Building upon the theory of polynomial coefficients we propose a parametric fault diagnosis methodology. A polynomial of suitable degree is fitted to the output frequency response of an analog circuit. The coefficients of the polynomial attain different values under faulty and non faulty conditions. Using these features of polynomial coefficients, a BPNN is used to detect the parametric faults. Simulation results are presented for a benchmark bi quad filter circuit. Single resistance and capacitance faults of ±1% to ±50% deviation from nominal values were correctly diagnosed. KeywordsNetwork, Parametric faults, Analog circuit, Curve fitting, Polynomial coefficients.

Trend of Nonlinear Electronic Circuit

Nonlinear electronic circuit is widely used in many fields of electronic devices. The importance of nonlinear electronic circuit is increasingly recognized with improvement in the speed and precision of electronic devices, and the development and expansion of use. Here, I give a trend of nonlinear electronic circuit which is introduced for the purpose of contributing to development of a nonlinear electronic circuit from a viewpoint of analog electronic circuit technology including new fields, such as chaos, neuro, and a neural network. From now on, nonlinear electronic circuit will become more important for the electronics, and the circuit technology will be utilized for many fields.

Oscillation-based analog diagnosis using artificial neural networks based inference mechanism

In this paper, Oscillation-Based Diagnosis (OBD) of analog electronic circuits, derived from Oscillation-Based Test (OBT), is described for the first time. OBT is an effective and simple solution to the testing problem of continuous time analog filters. The inadequacy of using an infinite-gain model of the op-amps is demonstrated and a practical implementation of the theoretical concept of OBT is discussed. A realistic model of the op-amp is therefore implemented. A fault dictionary is created and used to perform diagnosis, with artificial neural networks (ANNs) as classifiers. The robustness of the ANN diagnostic concept is demonstrated by the addition of white noise to the “measured” signals. The effectiveness of OBD is demonstrated by testing and diagnosis of a second order notch cell, realized with one operational amplifier. Single soft and catastrophic faults are considered in detail and an example of the diagnosis of double soft faults is also presented.

Dynamical Bayesian inference of time-evolving interactions: From a pair of coupled oscillators to networks of oscillators

Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski et al. [Phys. Rev. Lett. 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

Prognostics Method for Analog Electronic Circuits


 
 
 Analog electronic circuits are an integral part of many industrial systems. Failure in such analog circuits during field operation can have severe economic implications. The presence of an expert system that can provide advance warnings on circuit failures can minimize the downtime and improve the reliability of electrical systems. Through successive refinement of circuit’s response to a sweep signal, features are extracted for fault prognosis. From the extracted features, a fault indicator is developed. An empirical model is developed based on the degradation trend exhibited by the fault indicator. Particle filtering approach is used for model adaptation and remaining useful performance estimation. This framework is completely automated and has the merit of implementation simplicity. The proposed framework is demonstrated on two analog filter circuits.
 
 

Reduction of Electromagnetic Interference Susceptibility in Small-Signal Analog Circuits Using Complementary Split-Ring Resonators

Low-frequency analog and digital electronic circuits are susceptible to electromagnetic interference in the radiofrequency (RF) range. This disturbance is produced when the coupled RF signal is rectified by the nonlinear behavior of the semiconductors used in the small-signal analog input stage of the electronic system. Circuits based on operational amplifiers are usually employed for such input stages. These circuits present an amplitude modulation demodulation produced by the nonlinearity of internal transistors. Such a phenomenon generates demodulated signals in the low-frequency range. In this paper, this effect is suppressed by combining the conventional printed circuit board layout with complementary split-ring resonators (CSRRs). CSRRs are constitutive elements for the synthesis of metamaterials with negative effective permittivity, which are mainly excited to the host line by means of electric coupling. Electromagnetic simulations and experimental results show an effective rejection of the undesired RF demodulation effect with no extra cost in terms of the device area or manufacturing process.

Small wind turbine emulator with armature controlled separately excited DC motor via analogue electronic circuit

In this paper, a small wind turbine emulator (WTE) using separately excited DC motor is modelled, designed, simulated, implemented and tested. A 1 HP separately excited DC motor is used to emulate the characteristics of the rotor of small wind turbine. The DC motor is driven by a thyristor bridge with closed-loop cascaded PI controller for armature control. A separately excited DC generator with a variable resistive load is directly coupled to the DC motor. A small cheap analogue electronic circuit, with less interfacing, is used to generate a specific reference wind turbine speed based on the wind turbine rotor characteristics and the mechanical wind power available. Simulation and experimental results are compared to proof the validity and accuracy of the WTE.

Review of “Analysis and application of analog electronic circuits to biomedical instrumentation” by Robert B Northrop

Review of “Analysis and application of analog electronic circuits to biomedical instrumentation” by Robert B Northrop

Microcontroller Based Maximum Power Point Tracking For Photovoltaic Solar Panel

Many papers are published in the past and at present time which operate the solar photovoltaic (PV) panel at its maximum power point, by implementing an analogue or digital electronic circuits which are known as maximum power point trackers (MPPT). The main purpose of the researches are to obtain maximum power from the (PV) solar panel under different atmospheric conditions. In this paper a digital technique based on microcontroller type 8051 is used to design and implement the (MPPT) using maximum power point voltage method. The proposed (MPPT) consists of three major units (i) the solar (PV) panel (ii) the DC/DC step down inverter (iii) the control unit and computation of maximum power point based on microcontroller

A two-variable silicon neuron circuit based on the Izhikevich model

The silicon neuron is an analog electronic circuit that reproduces the dynamics of a neuron. It is a useful element for artificial neural networks that work in real time. Silicon neuron circuits have to be simple, and at the same time they must be able to realize rich neuronal dynamics in order to reproduce the various activities of neural networks with compact, low-power consumption, and an easy-to-configure circuit. We have been developing a silicon neuron circuit based on the Izhikevich model, which has rich dynamics in spite of its simplicity. In our previous work, we proposed a simple silicon neuron circuit with low power consumption by reconstructing the mathematical structure in the Izhikevich model using an analog electronic circuit. In this article, we propose an improved circuit in which all of the MOSFETs are operated in the sub-threshold region.

Contactless Measurement of Sheet Resistance Using Impulse Voltage

A novel method for the contactless sheet resistance measurement is presented. The sheet resistance of a silicon wafer has been conventionally measured using the four-point probe technique. However, the high mechanical pressure of the probe causes pitting and structural damage in semiconductor wafers. Therefore, to prevent such damage, a contactless measurement technique was devised that employs electromagnetic induction. The conventional contactless method is implemented using high frequency sinusoidal magnetic excitation with a Robinson marginal oscillator as an excitation current supply. However, the oscillator gain drifts due to an increase in temperature during continuous scanning of the wafer, which causes an error in the resistance measurement. The proposed method does not require an analogue electronic circuit; therefore, more precise measurement is expected. This novel method utilizes an impulse voltage to generate an eddy current in the sheet under test. However, no high voltage source is required, because the impulse voltage is generated by cutting off the DC current flowing through the winding of a ferrite core facing the sheet.

Soft Fault Clustering in Analog Electronic Circuits with the Use of Self Organizing Neural Network

Soft Fault Clustering in Analog Electronic Circuits with the Use of Self Organizing Neural NetworkThe paper presents a methodology for parametric fault clustering in analog electronic circuits with the use of a self-organizing artificial neural network. The method proposed here allows fast and efficient circuit diagnosis on the basis of time and/or frequency response which may lead to higher production yield. A self-organizing map (SOM) has been applied in order to cluster all circuit states into possible separate groups. So, it works as a feature selector and classifier. SOM can be fed by raw data (data comes from the time or frequency response) or some pre-processing is done at first. The author proposes conversion of a circuit response with the use of e.g. gradient and differentiation. The main goal of the SOM is to distribute all single faults on a two-dimensional map without state overlapping. The method is aimed for the development stage because the tolerances of elements are not taken into account, however single but parametric faults are considered. Efficiency analyses of fault clustering have been made on several examples e.g. a Sallen-Key BPF and an ECG amplifier. Testing procedure is performed in time and frequency domains for the Sallen-Key BPF with limited number of test points i.e. it is assumed that only input and output pins are available. A similar procedure has been applied to a real ECG amplifier in the frequency domain. Results prove a high efficiency in acceptable time which makes the method very convenient (easy and quick) as a first test in the development stage.

Application of the particle in a box electronic circuit in a spread spectrum communication system

A spread spectrum communication system based on the electronic model of the particle in a box system is proposed. This electronic system allows a robust and simple electronic emulation of the mechanical behaviour of the collisions of a particle inside a box, exhibiting rich chaotic behaviour. The required non-linearity to emulate the box walls is implemented in a simple way when compared with other analogue electronic chaotic circuits. In this system, a stream of binary data is transformed in the frequency modulated signal by the binary frequency shift keying (BFSK) modulator. The chaotic signal of the particle in a box electronic circuit is used to generate a broadband signal in the voltage controlled oscillator (VCO) of the transmitter. The frequency hopping signal sent to receiver is generated by mixing the binary frequency shift keying and the broadband signal. The demodulation process is done when the VCOs of transmitter and receiver are synchronised by a phase locked loop (PLL) circuit. The performance of the demodulation process is verified through the eye pattern technique applied on the recovered bit stream. A binary data stream was sent through a transmission channel with the following lengths: 2,000 metres and 8,000 metres. The experimental results demonstrated that the particle in a box electronic circuit can be used in a spread spectrum communication system.

A Trial of Educating Students through Their Failures

As the proverb says, failure teaches success. Most engineers who belong to the new product development sections in manufacturing companies have experienced failure, and have turned their failures into opportunities. However, it is difficult to teach students something from failure in a lecture. Hands-on education is one of the solutions. In this paper, a trial in the class of Analog Electronic Circuits is reported. Some extra-curricular tasks with the possibility to cause failure were assigned to the students. The results of the questionnaire conducted by the students show that the proposed practical method has successfully reminded them of the meaning of learning.