While modern control methods were becoming widespread, in addition to demanded repeatability and accuracy specifications, reliability and detection and isolation of probable faults have become an obligation for automatic control systems. In the early 70’s, first studies were appeared on this subject. While the first studies on fault detection and isolation (FDI) were implemented for supervisory...

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC s...

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC s...

Sensor fault detection, isolation (FDI) and accommodation has been investigated along with detection of unknown faults for an automotive engine. Radial basis function (RBF) neural networks are used for fault diagnosis. The RBF network is trained off line with K-means and batch least squares (BLS) algorithms. No fault and fault data are simulated in Matlab for four different sensors e.g. throttl...

This paper presents an integrated approach for fault detection and isolation (FDI) of sensor as well as process faults in Electro-Hydraulic Actuators (EHA) using a bank of residual generators, each of which employs an Extended Kalman Filter (EKF)-based parameter estimator. In traditional sensor fault detection schemes, actual sensor measurements are compared with measurements reconstructed usin...

Fault detection and isolation (FDI) has become a useful strategy for determining fault appearance and on-line reconfiguration. However, unknown scenarios during on-line performance are still an open field for research. Different methods, such as knowledge-based techniques or analytical redundancy, have been followed. Nevertheless, both methods present inherent drawbacks for isolation. The prese...

Abstract: This paper describes a fault detection and isolation (FDI) scheme performed on the benchmark problem of a ship propulsion system. The model used for the ship propulsion system is nonlinear, for which two types of additive sensor faults, an additive incipient fault, and a multiplicative parametric fault are simulated. The estimation of the fault severity is accomplished by using an ada...

We present a novel approach for model-based FDI of abrupt faults in process components of continuous dynamic systems. Abrupt faults refer to parameter value changes that occur much faster than the nominal process dynamics, and component faults refer to faults that correspond to physical parameters in the bond graph model of a system. These faults cause transients in system behavior. We analyze ...

In this paper fault detection and isolation schemes using an extended Luenberger observer for non-linear systems and linear fault sensitive filters are presented. The idea is to implement both approaches on the same plant, achieve on-line fault detection and show some practical issues related to on-line fault detection implementation on a real laboratory plant, where for evaluation of residuals...

The TRANSCEND system for fault detection and isolation in continuous systems uses qualitative reasoning methods to analyze transients caused by abrupt faults. Qualitative transient analysis avoids some of the computational difficulties associated with numerical schemes, but they lack discriminating power. This paper presents the formal basis for qualitative transient analysis, and then establis...