Structural fault diagnosis is an important subject for ensuring the normal use of structures. More test data will help to improve accuracy and reliability structural diagnosis. Therefore, a detection algorithm based on static–dynamic mixed sensitivity analysis proposed. The vibration parameters used were modes some nodes in structure measured by system. static response parameter was vertical di...

the zagros fold-and-thrust belt is tectonically active and often has active faults with insensible and slow motions. determining the rate of movement and displacement in these faults requires very precise measurements. one of the measurement methods of fault movements is using geodetic and micro-geodetic studies. this research is focused on one of the active faults in the north of shiraz city, ...

The reliability of deep neural networks (DNN) against hardware errors is essential as DNNs are increasingly employed in safety-critical applications such automatic driving. Transient memory, radiation-induced soft error, may propagate through the inference computation, resulting unexpected output, which can adversely trigger catastrophic system failures. As a first step to tackle this problem, ...

Fault diagnosis of analogue circuits is essential for analogue and mixed-signal systems testing and maintenance. A new method is proposed in this paper for multiple fault diagnosis of linear analogue circuits in frequency domain. The Woodbury formula is applied to the modi9ed nodal equation to construct the fault diagnosis equation, which relates the limited measured circuit responses with the ...

An accurate autoregressive (AR) model can reflect the characteristics of a dynamic system based on which the fault feature of gear vibration signal can be extracted without constructing mathematical model and studying the fault mechanism of gear vibration system, which are experienced by the time-frequency analysis methods. However, AR model can only be applied to stationary signals, while the ...

Abstract—The Derivative-free nonlinear Kalman Filter is proposed for state estimation and fault diagnosis in distributed parameter systems and particularly in dynamical systems described by partial differential equations of the nonlinear wave type. At a first stage, a nonlinear filtering approach for estimating the dynamics of a 1D nonlinear wave equation, from measurements provided from a smal...

A method for finer fault isolation or localization in the model based fault detection and isolation (FDI) paradigm is developed using parallely computed bond graph models. Many of the existing model based FDI methods are based on the evaluation of model consistency expressed in terms of analytical redundancy relations (ARR). These evaluations lead to residuals, and a number of sensors are to be...