A novel prediction method about single components of analog circuits based on complex field modeling.

To address the challenge of accurately diagnosing the fault severity in permanent magnet synchronous motors (PMSM) under inter-turn short circuit conditions, a new fault severity diagnosis and prediction method is developed to evaluate the fault turn ratio based on d-axis and q-axis currents and rotating coordinate transformation. Firstly, the stator current under the inter-turn short circuit fault condition is analyzed. Then, the second-order harmonic components of daxis and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$q$</tex>-axis currents related to inter-turn short-circuit faults are extracted by performing a rotational coordinate system transformation, and the fault indicator is established. Finally, a series of experiments have been conducted to establish the functional relationship between the fault turn ratio and fault indicator, and a correction factor related to the motor speed is proposed to enhance the accuracy of fault turn ratio evaluation, thus establishing the prediction method for the fault turn ratio. The verification results have demonstrated that the proposed fault severity diagnosis and prediction method can successfully detect the occurrence of inter-turn short-circuit faults and accurately evaluate the fault turn ratio and exhibit strong robustness to speed variations.

In order to meet the electricity requirements and improve the quality of distribution networks, it is essential to improve the reliability level of the power system. This paper established several mathematical models based on circuit analysis and computer simulation to realize the evaluation of distribution network reliability. Firstly, the Sequential Monte Carlo method was utilized to simulate the indicators of series and parallel circuits, and the Entropy Weight Method was adopted to weight the indicators. Then, simulation results were comprehensively evaluated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the evaluation model of distribution network reliability was obtained. The established mathematical model provided some guidance to construct an industrial distribution network and improve the reliability level of the power system.

This paper describes CODAC, a CAD tool for characterization and analysis of analog and digital circuits. It is based primarily on the industry standard electrical simulator, SPICE. CODAC provides a powerful C like language for specifying the characterization problem. In addition to providing an extensive library of built-in analysis functions it also supports a procedural interface that facilitates the definition of customized analysis functions. A capability to distribute in parallel the large number of simulation runs for an extensive circuit analysis (e.g. Monte Carlo analysis) is provided which significantly reduces overall cycle time. CODAC is being successfully used for circuit analysis and as a part of analog and digital library development flow at Texas Instruments.

In this work an MLP is used to detect faults and identify the faulty component in simple analog circuits. An extensive analysis of the MLP outputs as a function of the component variations is performed. Results obtained were satisfactory pointing out the artificial neural network approach as very suitable to this sort of analysis.

Our objective was to develop a Fuzzy logic (FL) based industrial two-shaft gas turbine gas path diagnostic method based on gas path measurement deviations. Unlike most of the available FL based diagnostic techniques, the proposed method focused on a quantitative analysis of both single and multiple component faults. The data required to demonstrate and verify the method was generated from a simulation program, tuned to represent a GE LM2500 engine running at an existing oil & gas plant, taking into account the two most common engine degradation causes, fouling and erosion. Gaussian noise is superimposed into the data to account measurement uncertainty. Finally, the fault isolation and quantification effectiveness of the proposed method was tested for single, double and triple component fault scenarios. The test results show that the implanted single, double and triple component fault case patterns are isolated with an average success rate of 96 %, 92 % and 89 % and quantified with an average accuracy of 83 %, 80 % and 78.5 %, respectively.

The overall architectural complexity of autonomous underwater vehicles continuous to increase, enlarging the probability of fault occurrence in subsystems. Estimating the thrust loss by particle filter provided a useful method to detect the fault in propeller subsystem. In order to detect the fault in propellers as early as possible, the particle filter direct prediction method could amplify the fault trend and detect the fault earlier, but at the same time increase the possibility of false diagnosis. Therefore, a more accurate fault diagnosis method was required to discover the fault early and decrease the occurrence of false diagnosis. In this paper, an improved particle filter prediction method was proposed, combining the advantage of grey prediction to forecast the motion state, reducing the uncertainty in particle filter direct prediction process. Besides, the Gaussian kernel function was applied to judge the credibility of the prediction result, decreasing the possibility of the false diagnosis. In the experiments with simulated working conditions data and a section of actual sea trial data with propeller fault, the proposed method detected the fault earlier compared with the original particle filter method, and reduced the false diagnosis rate compared with the particle filter direct prediction method. The results show that the proposed method is effective in detecting the fault early with low false diagnosis.

This paper proposes a new hierarchical circuit modeling and simulation technique in s-domain for linear analog circuits. The new algorithm can perform circuit complexity reduction by deriving the exact or approximate admittances in rational form in the reduced circuit matrix and deriving the circuit characteristics for very large linear analog and interconnect circuits. We characterize some theoretical results regarding the conditions on the generations of canceling terms during the general hierarchical circuit analysis and propose an explicit de-cancellation scheme to remove canceling terms based on a new hierarchical symbolic analysis framework. The resulting algorithm can be used for modeling and simulation of linear analog and interconnect circuits in both frequency and time domain.

Three-phase induction motors are among the most frequently used motors in industrial areas due to their simple structure, low cost, power specifications, etc. Electric energy consumption from these motors accounts for 68% of the energy used by all motors. The faults that occur in these motors over time decrease motor efficiency and result in significant energy consumption. In this study, a new method based on spectral subtraction (SS) was suggested for determining broken rotor bar (BRB) faults in these motors. The traditional method of motor current signature analysis via Fast Fourier Transform (FFT) is hard to use to diagnose BRB faults because the sideband characteristics used as a fault indicator are also seen in the healthy state at low amplitude levels. In the proposed fault detection method, the FFT of both healthy case and faulty case current signals were calculated and then the SS signal is obtained by subtracting the FFT of the healthy motor from the faulty motor for each time step. In the residual SS signal, fault detection was performed by examining the amplitude levels of the harmonic component of the BRB fault. Experimental results indicate that BRB faults can be successfully detected in squirrel-cage rotor induction motors using the suggested method.

Hybrid system models exploit the modelling abstraction that fast state transitions take place instantaneously so that they encompass discrete events and the continuous time behaviour for the while of a system mode. If a system is in a certain mode, e.g. two rigid bodies stick together, then residuals of analytical redundancy relations (ARRs) within certain small bounds indicate that the system is healthy. An unobserved mode change, however, invalidates the current model for the dynamic behaviour. As a result, ARR residuals may exceed current thresholds indicating faults in system components that have not happened. The paper shows that ARR residuals derived from a bond graph cannot only serve as fault indicators but may also be used for bond graph model-based system mode identification. ARR residuals are numerically computed in an off-line simulation by coupling a bond graph of the faulty system to a non-faulty system bond graph through residual sinks. In real-time simulation, the faulty system model is to be replaced by measurements from the real system. As parameter values are uncertain, it is important to determine adaptive ARR thresholds that, given uncertain parameters, allow to decide whether the dynamic behaviour in a current system mode is the one of the healthy system so that false alarms or overlooking of true faults can be avoided. The paper shows how incremental bond graphs can be used to determine adaptive mode-dependent ARR thresholds for switched linear time-invariant systems with uncertain parameters in order to support robust fault detection. Bond graph-based hybrid system mode identification as well as the determination of adaptive fault thresholds is illustrated by application to a power electronic system easy to survey. Some simulation results have been analytically validated.

Attainable accuracy of short-term prediction of atmosphere density for operational determination and prediction of close Earth satellite orbits is estimated in this paper. Using available atmospheric models short-term variations of atmospheric parameters are represented generally as a function of the 10.7 cm solar flux F 10.7 and the planetary geomagnetic index a p (or A p ). Using such models the accuracy of description of atmosphere density changes within the interval of AES orbit determination and prediction depends considerably on the accuracy of predicted quantities F 10.7, a p or A p . Various methods of prediction are considered here and their accuracies are compared. Errors of atmosphere density prediction are recalculated from errors of predicted quantities F 10.7, a p and A p . In this case empirical relationships between variations of the quantities F 10.7, a p , A p and corresponding atmospheric density changes calculated from AES drag data are used. The prediction intervals considered are from some hours up to three days. Some tables and diagrams given allow estimation of the accuracy obtainable of atmosphere density calculations for the altitudes of 150–350 km.

This article deals with a new approach to an intelligent analog circuit design. The iterative closed loop design methodology adopts an expert system approach to provide topological synthesis, the SPICE circuit simulator to evaluate the circuit performance and a new approach of the diagnostic expert system to provide advice on how to improve the design. Unlike previous design methods, this approach introduces formal circuit representation for both numerical and heuristic knowledge of the design system. The predicate logic circuit representation is proposed to introduce a new concept of a formal analog circuit description language. The language syntax and semantics provide precise symbolic description of analog circuits functionality at different levels of hierarchy and connectivities together with transistor sizes of CMOS circuits at the transistor level. Different levels of hierarchy with circuit structures and performance parameters are presented in detail. It is shown how sentence conversion rules of language grammar can be used to derive transistor level circuits from input performance specifications through all intermediate levels of hierarchy. The implementation of the methodology and associated experimental results for CMOS operational amplifier designs are presented.

In this work, we report on the significance of non-overlap channel architecture in nanoscale double gate (DG) FETs to improve performance of low-voltage analog and digital circuits. It is shown that the low-voltage operation of a cascoded Operational Transconductance Amplifier (OTA) and 6-T SRAM cell can be considerably enhanced using underlap gate-source/drain design. The present work provides new opportunities for realizing future low-voltage analog and digital circuits with underlap DG FETs.

In this paper, we propose a new time-domain performance bound analysis method for analog circuits considering process variations. The proposed method, called TIDBA, consists of several steps to compute the bound performances in time domain. First the performance bound in frequency domain is computed for a linearized analog circuits by an variational symbolic analysis method and the Kharitonov's functions. Then the time domain performance bound is computed via a new general-signal transient bound analysis method. The new algorithm can give transient lower bound and upper bound of the performance variations affected analog circuits accurately and reliably. Experimental results from two industry benchmark circuits show that TIDBA gives the correct bounds for the Monte Carlo analysis while it delivers one order of magnitude speedup over the Monte Carlo method.

Due to the lack of a feasible fault modeling method, soft fault diagnosis and tolerance are two challenging problems in analog circuit fault diagnosis. This paper proposes approaches to solve these two problems. First, a new fault modeling method and its theoretical proof are presented. In analog circuits, either the real part (“Ur”) or the imaginary part (“Ui”) of output voltage is the function of fault component parameter “ z,” viz., Ur=f1(z) and Ui=f2(z). By eliminating “ z,” equation F(Ur,Ui)=0 is achieved, where function “ F()” is independent from the value of “ z” and uniquely determined by the location of “ z” and the other fault free component in the circuit under test (CUT). Hence, the function “ F()” can be used as the fault model, which is applicable to both hard (open or short) and soft (parametric) faults. It is also applicable to either linear or nonlinear analog circuits. On a complex plane, the equation “ F(Ur, Ui)=0” represents a curve which is determined by the fault free output voltage and the shape of “ F().” Then, the parameter tolerance is taken into consideration. The tolerance influences the fault diagnosis by shifting the fault free output voltage and distorting the shape of “ F().” These influences can be mitigated in two ways: 1) The free output voltage is measured when an actual circuit is under steady state and free of fault, and 2) the minimal distance approach is used to find the fault component. The effectiveness of the proposed approaches is verified by both simulated and experimental results.

In this literature, a data pre-processing circuit designs and analyses for an infrared image seeker of a subsonic cruise missile are proposed.The flight speed of the missile is 250m/s.Therefore, automatic contrast control and automatic brightness control are usually needed to keep wanted contrast and brightness for best image properties in target recognition and tracking; especially for the missile at the terminal approaching phase to prevent signal saturation.Signal saturation implies target lost.The major parameters of imaging systems for contrast and brightness controls include average, maximum and minimum of gray level of the whole picture in the sampling interval.Therefore, the overall system is a complicated nonlinear sampled-data control system.It is difficult to describe, analyze and design the system.In this literature, the overall system is first decomposed into two linearized sampled-data control systems to get needed loop compensations, and verified by a special range-dependent testing signal to the overall system secondly.The controlled system is further verified by a thermal plate and real flight testing.Testing results give the proposed method can provide effective way to analyze and design the considered system. Minimal (MIN) Brightness Maximal (MAX) BrightnessD/A APC Control Signal(60Hz) CCD Focal Plane Array Pre-Processing Circuits AGC Control Circuit APC Control Circuit Amplifier Circuit A/D D/A AGC Control Signal(60Hz) Addressing for Desired Cell (256x256x60Hz) Micro-Processor MAX/ MIN/ AVG Digital Filters for APC Digital Filters for AGC