Component Connection Model Research Articles

A Classical Parameter Identification Method and a Modern Test Generation Algorithm

Many methods have been presented for the testing and diagnosis of analog circuits. Each of these methods has its advantages and disadvantages. In this paper we propose a novel sensitivity analysis algorithm for the classical parameter identification method and a continuous fault model for the modern test generation algorithm, and we compare the characteristics of these methods. At present, parameter identification based on the component connection model (CCM) cannot ensure that the diagnostic equation is optimal. The sensitivity analysis algorithm proposed in this paper can choose the optimal set of trees to construct an optimal CCM diagnostic equation, and enhance the diagnostic precision. But nowadays increasing attention is being paid to test generation algorithms. Most test generation algorithms use a single value in the fault model. But the single values cannot substitute for the actual faults that may occur, because the possible faulty values vary over a continuous range. To solve this problem, this paper presents a continuous fault model for the test generation algorithm which has a continuous range of parameters. The test generation algorithm with this model can improve the treatment of the tolerance problem, including the tolerances of both normal and faulty parameters, and enhance the fault coverage rate. The two methods can be applied in different situations.

Hierarchical fault diagnosis of analog integrated circuits

This paper introduces a hierarchical-fault-diagnosis algorithm as an aid to testing analog and mixed signal circuits. The diagnosis approach is based on that introduced by Wey and others and makes use of the self-test algorithm, and the component-connection model. The main extension to these techniques is the use of a hierarchical approach whereby blocks of circuitry are grouped together leading to a reduction in matrix size, so making even large scale circuits diagnosable. Other improvements from this approach include a novel test-point selection procedure and the fact that hard faults can also be diagnosed, provided they lie completely within a hierarchical block. The overall algorithm is described and the results from example circuits show good functionality of the diagnosis algorithm. Fault masking and sensitivity to the simulation/measurement resolution of test point values are examined and are highlighted as future activities to further improve the approach.

Parallel simulation of industrial power system transients by an inherent parallel algorithm

An inherent parallel algorithm for simulating industrial power system transient characteristics is implemented. This algorithm is based on the waveform relaxation method (WRM). The component connection model (CCM) is applied to assemble the individual power system component models into an integrated system representation, among which the generator stator and network transients are taken into account. Moreover, four different schemes of the relaxation Newton iteration method can be used to solve these separated component equation sets concurrently. To demonstrate the effectiveness of the proposed algorithm, the IEEE second benchmark model system No. 2 and a practical industrial cogeneration system are selected for numerical illustrations. The satisfactory speedups with different concurrent and vectorized numerical realizations on both the Alliant FX/80 and the Convex C3840 multi-processor systems are also provided. Results obtained from these simulations indicate that this combined algorithm is suitable for detailed industrial power system transient analysis and multiprocessor parallel processing.

An inherent parallel algorithm for analyzing power system transient characteristics on a multiprocessor system

This paper will present an inherent parallel algorithm for power system transient analysis with detailed generator stator and network transients taken into account. The component connection model (CCM) will be applied to the modeling and assembling of the power system components for developing an integrated system representation, in which the state equations of system components can be handled separately. The waveform relaxation method (WRM) will then be used to solve those separated component equation sets concurrently. This combined algorithm is thus suitable for parallel processing, and the remarkable speed-up effect of this algorithm by the concurrent and vectorized numerical realizations on an Alliant FX/80 multiprocessor system will be provided for illustration.

Implementation Of a constraint System For modelling And Reasoning With Physical Systems

This paper describes a framework, called a constraint system, for representing physical systems and for reasoning about them. Presently, the system is limited to physical devices with static states. The constraint system allows us to represent models of physical devices, where a device is represented as a component-connection model, and each component is modeled by a set of constraints. New derivations are done by a technique called constraint propagation, where an initial set of values are propagated through the constraint space, leading to the derivation new values. The system is built using an Assumption- based Truth Maintenance System (ATMS), and it is useful for a variety of tasks, such as model-based diagnosis, model-based prediction, model-based simulation, analysis, etc.

Extending component connection modeling for analyzing complex physical systems

The derivation of useful behaviors from component connection models of the physical structure of complex engineering systems is discussed. A component connection (CC) modeling scheme that compiles defined models to Qsim constraint representations for behavior generation is used. A number of issues arise in generating globally precise behaviors from a CC model when the behavioral models of the individual components are known. It is shown that the limitations of the current CC scheme can be addressed by incorporating global information in addition to the local connection specifications. This global information can be attributed to knowledge of teleology or intended functionality of the system being modeled.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Fault diagnosis under a limited-fault assumption and limited test-point availability

This paper describes a method of fault diagnosis for large interconnected circuits in which the number of faults is limited to, say,nf where it is possible thatnf exceeds the number of output measurements,no. The problem and its solution are formulated in the context of a frequency domain tableau based on the component connection model of a circuit/system. The paper describes Jacobian tests for diagnosability whennf≥no and states a full parameter diagnosability test as a corollary to the main theorem. An algorithm is developed for the identification of faulty parameters in this limited fault case. Finally, examples, including a 26-parameter video-amplifier circuit, illustrating the technique are given.

An algorithm to generate complete test sets for stuck-at faults in combinational logic circuits

A new algorithm to generate test sets for stuck-at faults in combinational logic circuits via fault simulation is presented. The algorithm is non-path-sensitizing, non-path-tracing and can be easily implemented on a computer. The stuck-at fault model in the algorithm is developed using the component connection model. The algorithm can be extended to sequential digital circuits. The software generates the complete set of test input vectors for each single stuck-at fault.

Model reduction of large-scale interconnected systems

The paper addresses model reduction of large-scale interconnected systems in the component connection model framework. It is shown that model reduction at the component level is equivalent to model reduction at the system level. A general procedure is presented to obtain a reduced-order model when (a) at least one of the components is exactly aggregable, and (b) none of the components are reducible. In the latter case, a reduced-order model is obtained by keeping the key state variables and compensating for the deleted ones using a numerical QL algorithm. An interconnected electric power system example is given to illustrate the proposed procedure.

Decentralization of large-scale systems: A new canonical form for linear multivariable systems

This note presents a new canonical form for linear multivariable systems. This canonical form casts and partitions the system to the so-called component connection model (CCM). The application of this canonical form to the problem of decentralized stabilization and estimation is discussed.

On the aggregation of interconnected systems

The paper presents a theorem showing that in the component connection model framework a large scale interconnected system is aggregable if and only if one of its components is aggregable.

Sensitivity calculations using the component connection model

Sensitivity calculations using the component connection model

Parallel system simulation

A relaxation algorithm composed of both a time-step parallel algorithm and a component-wise parallel algorithm is proposed for solving large-scale system simulation problems in parallel. The interconnected nature of the system, which is characterized by the component connection model, is fully exploited by this approach. A technique for finding an optimal number of the time steps is also described. Finally, this algorithm is illustrated via several examples in which the possible trade-offs between the speedup ratio, efficiency, and waiting time are analyzed.

Order Reduction of Singularly Perturbed Systems via Component Connection Models

This paper is concerned with the application of the Component Connection Model (CCM) to the reduction of a class of large Scale Systems, namely singularly perturbed systems.In this application, the reduction occurs on the component level which is assumed to be described by a set of singularly perturbed equations. Then the reduced composite system is formed using the assembly of the reduced order component models, respecting certain dynamical conditions.A relation between the Component Connection Model technique and singular perturbation techniques is established .To illustrate the utility of such a method we consider the application of the CCM to obtain a reduced order model of a ship boiler of 14th order.

Analog multifrequency fault diagnosis

This paper develops the multifrequency fault diagnosis problem in the context of a tableau approach based on the use of the Component Connection Model. This method avoids the computation of the composite system transfer function matrix. The resulting fault diagnosis equations have a regular structure with fixed polynomial order (often quadratic) which is exploited in the solution process. The development includes a test for diagnosability as well as a set of bounds on the number of test frequencies necessary to conduct a diagnosis. An iteration scheme to solve the fault diagnosis equations is proposed and is shown to be locally convergent. A sample diagnosis problem and solution concludes the paper.

The component connection model and structure preserving model order reduction

This paper uses the component connection model as a setting for model order reduction. The actual reduction occurs on the component level as opposed to the composite system level. A theorem with proof is given relating the component level reduction to the established singular perturbation method. Concepts of system structure preservation and nonstructure preservation are discussed using the framework of the component connection model. An example is presented where a single machine-infinite bus power system is reduced using the techniques presented in this paper.

Existence of state equation representation of linear large-scale dynamical systems

Linear time-invariant large-scale dynamical systems (LSDS's) are considered. A component-connection model is first proposed. Conditions under which an LSDS has a state equation representation are determined. A characterization of a class of dynamical systems, called unimodules, is established. A unimodule has the property that any given dynamical system can be realized by an interconnection of such unimodules.

Fault isolation with insufficient measurements

A technique is given for approximating the "most likely" values of the internal components of a system when insufficient measurements have made their exact determination impossible. It is limited to linear systems, all of whose measurements are made at a single frequency and whose connections can be represented by sets of linear algebraic equations. The technique is based on the Moore-Penrose generalized inverse of a linear approximation of the system function and is formulated in terms of the component-connection model of a largescale dynamical system.

Convergent systems

An equivalent relationship has been established between the problems of convergence or zero-input convergence of nonlinear systems and the problem of zero-input convergence of linear systems. A special feature is that the formulation of the problem and the analysis are done directly on a component-connection model instead of the usual input-output state model. As a consequence, the results obtained can be easily interpreted in terms of given practical systems.