For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health p...

Fault diagnosis is crucial for the operation of energy systems such as nuclear plants, and heavily relies on various types of sensors for temperature, pressure, concentration, etc. Due to the redundancy of sensors in each energy system, the sensor selection scheme can deeply influence the diagnostic efficiency. In this paper, a Boolean network (BN) with its linear representation is proposed for...

VAV system is a very complicated one in airconditionging systems, thus automatic control become the key of such a system. As necessary components in automatic control system, sensor has failure risk. It is so expensive that detect sensor fault by hardware redundancy in comfortable air-conditioning system. This paper presents an approach, Principal Component Analysis (PCA), to detect and identif...

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are pres...

This paper presents an novel approach for fault detection and diagnosis (FDD) of sensor as well as process faults for 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 using st...

Maintenance and diagnosis of complex systems are common activities in the industrial world. Technological advances have led to a continuously increasing complexity of industrial systems. This complexity, which is due to an increasing number of components reduces in turn the reliability of plants. Therefore, fault diagnosis is becoming a growing field of interest. But fault diagnosis relies on s...

In this paper, we present an energy-efficient on-line diagnosis algorithm for cluster-based wireless sensor networks. It employs local comparisons of sensed data and dissemination of the decision made by the comparison results. Cluster-heads act as checkers for their associated cluster members. Redundant sensor nodes, as far as sensing coverage is concerned, are partially utilized to tolerate m...

Based on the techniques of high gain observer and adaptive estimation, an algorithm is proposed in this paper for sensor fault estimation in nonlinear systems. It is essentially assumed that a high gain observer exists for the fault-free system. A high gain adaptive observer is then designed for sensor fault estimation. The convergence of the algorithm is established under a persistent excitati...

This paper presents a neural model for reliable and fault tolerant transmission in Wireless Sensor Networks based on Bi-directional Associative Memory. The proposed model is an attempt to enhance the performances of both the cooperative and non cooperative Automatic Repeat Request (ARQ) schemes in terms of reliability and fault tolerance. We have also demonstrated the performances of both the s...

A Distributed Sensor Network (DSN) consists of a set of sensors that are interconnected by a communication network. DSN is capable of acquiring and processing signals, communicating, and performing simple computational tasks. Such sensors can detect and collect data concerning any sign of node failure, earthquakes, floods and even a terrorist attack. Energy efficiency and fault-tolerance networ...