Active Fault Diagnosis Research Articles

Active Fault Diagnosis for Nonlinear Systems with Probabilistic Uncertainties

Stringent requirements on safety and availability of high-performance systems necessitate reliable fault detection and isolation in the event of system failures. This paper investigates active fault diagnosis of nonlinear systems with probabilistic, time-invariant uncertainties of the parameters and initial conditions. A probabilistic model-based approach is presented for the design of auxiliary input signals enhancing fault diagnosability by separation of multiple nonlinear models pertaining to nominal and faulty system operations in the presence of the probabilistic uncertainties. To obtain a computationally tractable formulation, polynomial chaos expansions are used to propagate the probabilistic uncertainties through the system models. The input design problem is formulated in terms of a metric that characterizes the similarity of arbitrarily shaped distributions of the model outputs. An optimal input sequence is generated while considering hard input and state constraints. The simulation results for active diagnosis of multiple faults in a three-tank system indicate the capability of the presented approach to improve fault detectability and isolability under probabilistic uncertainties of the parameters and initial conditions.

Fault Tolerant Control for an Electric 4WD Vehicle's Path Tracking with Active Fault Diagnosis

This paper investigates the path tracking problem for an electric vehicle which has four electromechanical wheel systems under normal and faulty conditions. With considering wheel slip constraints and certain actuator faults, a passive fault-tolerant controller based on variable structure control is developed to maintain the system stability and guarantee the acceptable tracking performance. Then based on the designed controller, a simple active fault diagnosis approach is introduced for this typical over-actuated system to isolate and evaluate faults more precisely. With the diagnosed information, an accommodated fault tolerant controller is designed to maintain the tracking performance. Finally, simulations of traction engine multiple faults are conducted to illustrate the proposed method.

Certifying Robustness of Separating Inputs and Outputs in Active Fault Diagnosis for Uncertain Nonlinear Systems

To ensure safe operation of technical processes, faults have to be reliably detected and isolated to provide information for process maintenance, shutdown, or reconfiguration. Fault detection and isolation can be achieved by invalidation of fault candidates, i.e. models of the system in fault-free and faulty condition. In order to enhance the performance of fault detection and isolation, so-called active approaches use input signals with the objective that the resulting system outputs are consistent with at most one fault candidate. Guaranteeing or analyzing robustness of active fault diagnosis with respect to input, output, and process uncertainties and nonlinearities is challenging. This paper provides certificates of robustness of input sequences with respect to the aforementioned uncertainties and nonlinearities. The certificates enable the determination of input and output uncertainties for which unique fault diagnosis results can still be guaranteed. In addition, a method is presented to select a minimal number of outputs that still guarantee robust fault diagnosis, thus reducing the measurement setup and cost. The approach employs nonlinear mixed-integer feasibility problems and a relaxation framework and does not require the explicit computation of reachable sets. The approach is applicable to polynomial discrete-time systems and is demonstrated for a numerical example.

Active Diagnosis of Deterministic I/O Automata

A method for the active fault diagnosis of systems modeled by sets of deterministic input/output automata is presented, where each automaton describes the behavior of the system subject to a different fault. It is shown that the system is diagnosable if and only if there are no equivalent states in different automata. An active diagnostic algorithm is presented, which generates adequate input sequences for the system and evaluates the outputs of the system in order to identify the present fault. The applicability of the developed method is demonstrated by means of an example.

Fault diagnosis of a Wind Turbine Rotor using a Multi-blade Coordinate Framework

Fault diagnosis of a wind turbine rotor is considered. The faults considered are sensor faults and blades mounted with a pitch offset. A fault at a single blade will result in asymmetries in the rotor, which can be applied for fault diagnosis. The diagnosis is derived by using the multi-blade coordinate (MBC) transformation also known as the Coleman transformation together with active fault diagnosis (AFD). This transforms the setup from rotating to fixed frame coordinates. The rotor speed acts as the auxiliary input for the active diagnosis. The applied method take the varying rotor speed into account. Operation at different mean wind speeds is examined and it is discussed how to exploit the findings acquired by the investigation of the various faults.

Fault-Tolerant Control With Active Fault Diagnosis for Four-Wheel Independently Driven Electric Ground Vehicles

This paper presents a fault-tolerant control approach for four-wheel independently driven (4WID) electric vehicles. An adaptive control-based passive fault-tolerant controller is designed to ensure vehicle system stability and to track the desired vehicle motion when an in-wheel motor/motor driver fault happens. Due to the system actuation redundancy, it is challenging to isolate the faulty wheel and to accurately estimate the control gain of the faulty in-wheel motor/motor driver for 4WID electric vehicles. An active fault diagnosis (FD) approach is thus proposed to explicitly isolate and evaluate the fault. Based on the estimated control gain of the faulty wheel, the control efforts of all the wheels are redistributed to relieve the torque demand on the faulty wheel. Simulations using a high-fidelity CarSim full-vehicle model show the effectiveness of the proposed in-wheel motor/motor driver active fault diagnosis and fault-tolerant control approaches in various driving scenarios.

Performance improvement clarification for refrigeration system using active system monitoring

AbstractThis paper addresses the problem of determining whether a refrigeration plant has the possibility of delivering a better performance of the operation. The controllers are well-known but detailed knowledge about the underlying dynamics of the refrigeration plant is not available. Thus, the question is if it is possible to achieve a better performance by changing the controller parameter. An approach to active system monitoring, based on active fault diagnosis techniques, is employed in order to evaluate changes in the system performance under operation.

Active fault diagnosis by controller modification

Two active fault diagnosis methods for additive or parametric faults are proposed. Both methods are based on controller reconfiguration rather than on requiring an exogenous excitation signal, as it is otherwise common in active fault diagnosis. For the first method, it is assumed that the system considered is controlled by an observer-based controller. The method is then based on a number of alternate observers, each designed to be sensitive to one or more additive faults. Periodically, the observer part of the controller is changed into the sequence of fault sensitive observers. This is done in a way that guarantees the continuity of transition and global stability using a recent result on observer parameterization. An illustrative example inspired by a field study of a drag racing vehicle is given. For the second method, an active fault diagnosis method for parametric faults is proposed. The method periodically adds a term to the controller that for a short period of time renders the system unstable if a fault has occurred, which facilitates rapid fault detection. An illustrative example is given.

Active Fault Diagnosis - A Stochastic Approach

The focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow to obtain a fast change detection/isolation by considering the output or an error output from the system. It will be shown how it is possible to apply both the gain as well as the phase change of the output signal in the CUSUM tests. The method is demonstrated in an example.

Active Fault Diagnosis for Systems with Reduced Model Information.

A new approach for active fault diagnosis (AFD) in closed-loop systems is considered in this paper. This developed AFD approach is based on reduced model information. It is shown that it is possible to apply the AFD approach based on gain and phase information at a single frequency only. This means that simple models can be applied in the residual generation. The approach is demonstrated by an example.

Active Fault Diagnosis of Linear Hybrid Systems

A method for active fault diagnosis of linear discrete time hybrid systems is presented. The algorithm generates appropriate test signals that can be used for sanity check during system commissioning or later in the normal phase to detect faults which are impossible to detect by means of passive diagnosis methods because of regulatory actions of the controller. The algorithm is illustrated on a two tank benchmark example.

AN OBSERVER PARAMETERIZATION APPROACH TO ACTIVE FAULT DIAGNOSIS WITH APPLICATIONS TO A DRAG RACING VEHICLE

An active fault diagnosis method for additive, parametric or multiplicative faults is proposed. It is assumed that the system considered is controlled by an observer based controller. The method is then based on a number of alternate observers, each designed to be sensitive to one or more faults. Periodically, the observer part of the controller is changed into the sequence of fault sensitive observers. This is done in a way that guarantees continuity of transition and global stability using a recent result on observer parameterization. The proposed active fault diagnosis method distinguishes itself from the existing literature in terms of not relying on an exogenous excitation signal. An illustrative example based on a drag racing vehicle is given.

Active Fault Diagnosis Based on Stochastic Tests

Active Fault Diagnosis Based on Stochastic TestsThe focus of this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow us to obtain a fast change detection/isolation by considering the output or an error output from the system. The classical cumulative sum (CUSUM) test will be modified with respect to the AFD approach applied. The CUSUM method will be altered such that it will be able to detect a change in the signature from the auxiliary input signal in an (error) output signal. It will be shown how it is possible to apply both the gain and the phase change of the output signal in CUSUM tests. The method is demonstrated using an example.

Information Based Fault Diagnosis

Fault detection and isolation, (FDI) of parametric faults in dynamic systems will be considered in this paper. An active fault diagnosis (AFD) approach is applied. The fault diagnosis will be investigated with respect to different information levels from the external inputs to the systems. These inputs are disturbance inputs, reference inputs and auxiliary inputs. The diagnosis of the system is derived by an evaluation of the signature from the inputs in the residual outputs. The changes of the signatures form the external inputs are used for detection and isolation of the parametric faults.

A Setup for Active Fault Diagnosis

A setup for active fault diagnosis (AFD) of parametric faults in dynamic systems is formulated in this note. It is shown that it is possible to use the same setup for both open loop systems, closed-loop systems based on a nominal feedback controller as well as for closed-loop systems based on a reconfigured feedback controller. This will make the proposed AFD approach very useful in connection with fault tolerant control (FTC). The setup will make it possible to let the fault diagnosis part of the fault tolerant controller remain unchanged after a change in the feedback controller. The setup for AFD is based on the Youla-Jabr-Bongiorno-Kucera (YJBK) parameterization of all stabilizing feedback controllers and the dual YJBK parameterization. It is shown that the AFD is based directly on the dual YJBK transfer function matrix. This matrix will be named the fault signature matrix when it is used in connection with AFD

ACTIVE FAULT DIAGNOSIS IN CLOSED-LOOP UNCERTAIN SYSTEMS

Fault diagnosis of parametric faults in closed-loop uncertain systems by using an auxiliary input vector is considered in this paper, i.e. active fault diagnosis (AFD). The active fault diagnosis is based directly on the socalled fault signature matrix, related to the YJBK (Youla, Jabr, Bongiorno and Kucera) parameterization. Conditions are given for exact detection and isolation of parametric faults in closed-loop uncertain systems.

RAPPROCHEMENT BETWEEN ACTIVE FAULT DIAGNOSIS AND CHANGE DETECTION IN ARMAX SYSTEMS

The connection between AFD (Active Fault Diagnosis), ARMAX systems and RST controllers etc. are considered in this paper. It is shown that the applied setup in modern AFD for closed loop systems can be considered as a generalization of the setup used in connection with traditional methods for system identification and controller design in the polynomial setting.

FAULT TOLERANT CONTROL FOR UNCERTAIN SYSTEMS WITH PARAMETRIC FAULTS

A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera) parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation.

ACTIVE FAULT DIAGNOSIS BY TEMPORARY DESTABILIZATION

An active fault diagnosis method for parametric or multiplicative faults is proposed. The method periodically adds a term to the controller that for a short period of time renders the system unstable if a fault has occurred, which facilitates rapid fault detection. An illustrative example is given.

ACTIVE FAULT DIAGNOSIS IN CLOSED-LOOP SYSTEMS

Active fault diagnosis (AFD) of parametric faults is considered in connection with closed loop feedback systems. AFD involves auxiliary signals applied on the closed loop system. A fault signature matrix is introduced in connection with AFD and it is shown that if a limited number of faults can occur in the system, a fault separation in the fault signature matrix can be obtained. Then the single elements in the matrix only depend of a reduced number of parametric faults. This can directly be applied for fault isolation. If it is not possible to obtain this separation, it is shown how the fault signature matrix can be applied for a dynamical fault isolation, i.e. fault isolation based on the dynamic characteristic of the fault signature matrix as function of the different parametric faults.