The problem of developing robust thresholds for fault detection is addressed. An inequality for the solution of a linear system with uncertain parameters is provided and is shown to be a valuable tool for developing dynamic threshold generators for fault detection. Such threshold generators are desirable for achieving robustness against model uncertainty in combination with sensitivity to small...

This paper deals with the application of state space neural network models to fault detection and accommodation of the boiler unit. The work describes two aspects. First one is the fault detection and in this paper to diagnose the fault the three methods are described and compared: simple and adaptive threshold and more robust method which is model error modelling. The second part of the paper ...

Quality control of textile products is an important stage in textile industries. To this end, the conventional method in fault detection is human inspection. In the present work, Wavelet transform was applied on images of simple circular knitted fabrics to diagnose five regular defects. The results showed that the method applied was accurate and fast in addition to being capable of determining ...

Fault detection and isolation (FDI) logic plays a crucial role in enhancing the safety and reliability, and reducing the operating cost of aircraft propulsion systems. However, it is a challenging problem achieving the FDI task with high reliability. For this purpose, various approaches have been proposed in the literature. In an on-line engine fault diagnoses, two tasks may use Kalman filter t...

Air data probes provide essential sensing capabilities to aircraft. The loss or corruption of air data measurements due to sensor faults jeopardizes an aircraft and its passengers. To address such faults, sensor hardware redundancy is typically combined with a voting system to detect and discard erroneous measurements. This approach relies on redundancy, which may lead to unacceptable increases...

In this thesis, model based fault detection, isolation, and estimation problem in several classes of nonlinear systems is studied using sliding mode and learning approaches. First, a fault diagnosis scheme using a bank of repetitive learning observers is presented. The diagnostic observers are established in a generalized observer scheme, and the observer inputs are repetitively updated using t...

Areas of Teaching Interest:  Analysis and Design of Control Systems  Discrete Time Control Systems  Intelligent Controls  Robust Nonlinear Controls Areas of Research Interest:  Robust and adaptive control of nonlinear systems  Homogeneous systems theory  Output feedback control  Observer design and fault detection  Intelligent control systems  Control of nonholonomic systems  Underac...

in this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. in one case, parameters of membership functions are selected in a conventional manner. in another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genet...