This paper deals with multiple soft fault diagnosis of nonlinear analog circuits comprising bipolar transistors characterized by the Ebers-Moll model. Resistances of the circuit and beta forward factor of a transistor are considered as potentially faulty parameters. The proposed diagnostic method exploits a strongly nonlinear set of algebraic type equations, which may possess multiple solutions, and is capable of finding different sets of the parameters values which meet the diagnostic test. The equations are written on the basis of node analysis and include DC voltages measured at accessible nodes, as well as some measured currents. The unknown variables are node voltages and the parameters which are considered as potentially faulty. The number of these parameters is larger than the number of the accessible nodes. To solve the set of equations the block relaxation method is used with different assignments of the variables to the blocks. Next, the solutions are corrected using the Newton-Raphson algorithm. As a result, one or more sets of the parameters values which satisfy the diagnostic test are obtained. The proposed approach is illustrated with a numerical example.
The paper deals with a multiple fault diagnosis of DC transistor circuits with limited accessible terminals for measurements. An algorithm for identifying faulty elements and evaluating their parameters is proposed. The method belongs to the category of simulation before test methods. The dictionary is generated on the basis of the families of characteristics expressing voltages at test nodes in terms of circuit parameters. To build the fault dictionary the n-dimensional surfaces are approximated by means of section-wise piecewise-linear functions (SPLF). The faulty parameters are identified using the patterns stored in the fault dictionary, the measured voltages at the test nodes and simple computations. The approach is described in detail for a double and triple fault diagnosis. Two numerical examples illustrate the proposed method.
The present article investigates the dynamic behavior of a fully assembled turbogenerator system influenced by misalignment. In the past, most of the researchers have neglected the foundation flexibility in the turbogenerator systems in their study, to overcome this modelling error a more realistic model of a turbogenerator system has been attempted by considering flexible shafts, flexible coupling, flexible bearings and flexible foundation. Equations of motion for fully assembled turbogenerator system including flexible foundations have been derived by using finite element method. The methodology developed based on least squares technique requires forced response information to quantify the bearing–coupling–foundation dynamic parameters of the system associated with different faults along with residual unbalances. The proposed methodology is tested for the various level of measurement noise and modelling error in the system parameters, i.e., 5% deviation in E (modulus of elasticity) and ρ (density), respectively, for robustness of the algorithm. In a practical sense, the condition analyzed in the present article relates to the identification of misalignment and other dynamic parameters viz. bearing and residual unbalance in a rotor integrated with flexible foundation.
This paper is devoted to multiple soft fault diagnosis of analog nonlinear circuits. A two-stage algorithm is offered enabling us to locate the faulty circuit components and evaluate their values, considering the component tolerances. At first a preliminary diagnostic procedure is performed, under the assumption that the non-faulty components have nominal values, leading to approximate and tentative results. Then, they are corrected, taking into account the fact that the non-faulty components can assume arbitrary values within their tolerance ranges. This stage of the algorithm is carried out using the linear programming method. As a result some ranges are obtained including possible values of the faulty components. The proposed approach is illustrated with two numerical examples.
In rotating machineries, misalignment is considered as the second most major cause of failure after unbalance. In this article, model-based multiple fault identification technique is presented to estimate speed-dependent coupling misalignment and bearing dynamic parameters in addition with speed independent residual unbalances. For brevity in analysis, a simple coupled rotor bearing system is considered and analytical approach is used to develop the identification algorithm. Equations of motion in generalized co-ordinates are derived with the help of Lagrange's equation and least squares fitting approach is used to estimate the speed-dependent fault parameters. Present identification algorithm requires independent sets of forced response data which are generated with the help of different sets of trial unbalances. To avoid/suppress the ill-conditioning of regression equation, independent sets of forced response data are obtained by rotating the rotor in clock-wise and counter clock-wise directions, alternatively. Robustness of algorithm is checked for different levels of measurement noise.