Neural network-based L1-norm optimisation approach for fault diagnosis of nonlinear circuits with tolerance

The paper deals with fault isolation in nonlinear analogue circuits with tolerance under an insufficient number of independent voltage measurements. The L1-norm optimisation problem for different scenarios of nonlinear fault diagnosis is formulated with a new fast method being presented. How to solve the L1-norm optimisation problem is discussed and a new neural network-based approach for solving the nonlinear constrained L1-norm optimisation problem is proposed and utilised in locating the most likely faulty elements in nonlinear circuits. The validity of the proposed method is verified and simulation examples are presented.