A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred senso...

a new fault tolerant controller (ftc) has been presented in this research by integrating a fault detection and diagnosis (fdd) mechanism in a nonlinear model predictive controller framework. the proposed fdd utilizes a multi-sensor data fusion (msdf) methodology to enhance its reliability and estimation accuracy. an augmented state-vector model is developed to incorporate the occurred sensor fa...

Fault detection and diagnosis (FDD) are very important for engineering systems in industrial applications. One of the most popular approaches is model-based fault detection. Recently, many techniques have been proposed in the FDD area. However, there are still very few reported applications or real-time implementations of the schemes. This paper presents online sensor FDD based on the model-bas...

Because of the complexity and diversification of today’s HVAC systems, Fault Detection and Diagnosis (FDD) systems have become necessary to reduce maintenance cost and to provide building energy efficiency, but with a minimum of engineering cost. Based on a generic method of generating Fault Detection (FD) systems from Building Information Models (BIM), we now propose an extension of the underl...

The need for fault detection and diagnosis (FDD) is becoming increasingly important for industrial processes as the complexity of processes increases. A state space model of a counterflow heat exchanger is used as a case study to illustrate the usefulness of energy-based FDD. Energy is regarded as a unifying parameter to uniquely describe the state of the heat exchanger under fault conditions o...

The railway assets studied in this project, are those widely distributed pieces of equipment that are critical to the dependable operation of the railway system. A failed asset is likely to cause significant delay to rail services, and may even place the system into an unsafe state. A generic fault detection and diagnosis (FDD) solution for a number of railway assets of different types is there...

Models of faulty components or processes may either be used on-line as part of a fault detection and diagnosis (FDD) system or may be used in simulations to train or test FDD procedures. Some faults may be modelled by choosing suitable values of the parameters of fault free models, whereas other faults require specific extensions to fault free models. An example of the modelling of various faul...

A rule-based, system-level fault detection and diagnostic (FDD) method for HVAC systems was developed. It functions as an interface between multiple, equipment-specific FDD tools and a human operator. The method resolves and prioritizes conflicting fault reports from equipment-specific FDD tools, performs FDD at the system level, and presents an integrated view of an HVAC system’s fault status ...

Simultaneous state and parameter estimation based actuator fault detection and diagnosis (FDD) for single-rotor unmanned helicopters (UHs) is investigated in this paper. A literature review of actuator FDD for UHs is given firstly. Based on actuator healthy coefficients (AHCs), which are introduced to represent actuator faults, a combined dynamic model is established with the augmented state co...

Fault detection and diagnosis (FDD) is a critical approach to ensure safe and efficient operation of manufacturing and chemical processing plants. Multivariate statistical process monitoring (MSPM) has received considerable attention for FDD since it does not require a mechanistic process model. The diagnosis of the source or cause of the detected process fault in MSPM largely relies on contrib...