Kalman Filter Based Fault Detection Research Articles

Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction Systems in High-Speed Trains

Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction Systems in High-Speed Trains

Residual-Based Fault Detection and Exclusion With Enhanced Localization Integrity

In this paper, we give an integrity framework for vehicle localization in urban environments based on fusion of GPS and dead reckoning. To guarantee localization integrity, a novel Kalman filter-based fault detection and exclusion method is presented to reject faulty measurements via a chi-square test with iterative residuals. For a tight upper-bound for position error, we introduce a protection level calculation method with minimum detectable bias and the integrity budget allocation among all failure modes have been improved to enhance the accuracy of positioning. The algorithm provides integrity assessment and reliable estimations of vehicle position information in an iterative manner. Numerical simulations and experiments show that the proposed method can effectively deal with and recover from abrupt faults with a low rate of false alarm and a tight integrity risk bound.

Switching Fault-Tolerant Control for DFIG-Based Wind Turbines With Rotor and Stator Current Sensor Faults

This paper presents a switching fault-tolerant control (SFTC) strategy for a doubly-fed induction generator-based wind turbine (DFIG-WT) subject to rotor and stator current sensor faults. A novel stator-current-loop vector control scheme is proposed for the regulation of DFIG-WT without involving rotor currents, and it is compared with the conventional rotor-current-loop vector control scheme on closed-loop stability, tracking performance, and robustness against model uncertainties and external disturbances through theoretical analysis. The SFTC strategy switches between the rotor and stator current vector controllers via a switching logic based on Kalman filter-based fault detection and isolation (FDI) scheme. The proposed SFTC strategy is able to provide superb transient and steady-state performance, strong robustness to parameter uncertainties, and high fault-tolerance capability under rotor and stator current sensor faults. Simulation studies verify the control performance of the SFTC strategy.

Adaptive Extended Kalman Filter Based Fault Detection and Isolation for a Lithium-Ion Battery Pack

Abstract To monitor the battery system, a well-designed battery management system with a set of current and voltage sensors is demanded to properly track the battery properties. It is imperative to design a reliable and robust diagnostic scheme in case of the employed sensors faults occurred. This paper presents a model-based fault diagnosis scheme to detect and isolate the faults of the current and voltage sensors applied in the series battery pack based on an adaptive extended kalman filter, and the robustness of the proposed diagnostic strategy is ensured. The diagnostic scheme is validated in the Matlab/Simulink, and the simulation results show the effectiveness of the proposed strategy in detecting and isolating various fault scenarios using the real-world driving cycles.

Kalman filter based fault detection for two-dimensional systems

Fault detection and isolation for two-dimensional (2-D) systems represent a great challenge in both theoretical development and applications. Use of Kalman filters in fault detection has been well developed for one-dimensional (1-D) system. In this paper, a fault detection algorithm is developed for 2-D systems described by the Fornasini & Marchesini (F–M) model. Based on the state estimate from a recursive 2-D Kalman filter, a residual is generated. From the model of residual over a 2-D evaluation window, the residual is explicitly related to faults within the evaluation window. Using generalized likelihood ratio (GLR), residual evaluation is carried out and compared with a calculated threshold value for fault detection. Simulation results indicate that faults can be detected effectively using the proposed method.

Detection and Isolation of Leakage and Valve Faults in Hydraulic Systems in Varying Loading Conditions, Part 2: Fault Detection and Isolation Scheme

AbstractLeakages and valve faults are among the most common faults in hydraulic systems. This paper studies the real-time detection and isolation of certain leakage and valve faults based on the results obtained in part one. In the first part, the mathematical model of a hydraulic test bed was analysed with Global Sensitivity Analysis to facilitate a systematic and verified approach to model-based condition monitoring. In this paper, an Unscented Kalman Filter-based Fault Detection and Isolation scheme for leakage and valve faults of a generic servo valve-controlled hydraulic cylinder is devised. Compared to existing literature, the leakage and valve faults are decoupled from cylinder static and dynamic loading which makes the results generic and applicable to any servo valve-controlled hydraulic cylinder. Moreover, a more comprehensive set of fault patterns for the detection and isolation of leakages and valve faults with experimental and simulation results are presented. We show that detecting an extern...

SPC and Kalman filter-based fault detection and diagnosis for an air-cooled chiller

Buildings worldwide account for nearly 40% of global energy consumption. The biggest energy consumer in buildings is the heating, ventilation and air conditioning (HVAC) systems. In HVAC systems, chillers account for a major portion of the energy consumption. Maintaining chillers in good conditions through early fault detection and diagnosis is thus a critical issue.

Detection and Isolation of Leakage and Valve Faults in Hydraulic Systems in Varying Loading Conditions, Part 1: Global Sensitivity Analysis

Model-based condition monitoring methods are widely used in condition monitoring. They usually rely on ad hoc approaches to verify the system model and then best practices are reported to detect the given set of faults. This first part of a two-piece paper introduces a generic Global Sensitivity Analysis-based approach that can be applied systematically to verify the model parameter sensitivities used for the model-based fault detection. The case study is a generic servo valve-controlled hydraulic cylinder with unknown loading condition which is then systematically analyzed with Global Sensitivity Analysis. The method shows valuable insight into systematic model verification and resulting fault detection in terms of showing the dominant sensitivity of the nominal flow rate and nominal pressure difference, and the exact sensitivities of 0-1 dm3/min external and internal leakages on cylinder chamber pressures and velocity. In the second paper, an Unscented Kalman Filter-based Fault Detection and Isolation scheme for leakage and valve faults of a generic servo valve-controlled hydraulic cylinder is devised and fault patterns are presented.

Comparison of two model based residual generation schemes for the purpose of fault detection and isolation applied to a pneumatic actuation system

This paper discusses research carried-out on the development and validation (on a real plant) of a parity-equation and Kalman filter based fault detection and isolation (FDI) system for a pneumatic actuator. The parity and Kalman filter equations are formulated and used to generate residuals that, in turn, are analysed to determine whether faults are present in the system. Details of the design process are given and the experimental results are compared. The results demonstrate that both approaches can successfully detect and isolate faults associated with the sensors, actuators (servo-valves and piping) and the pneumatic cylinder itself. The work is part of a BAE SYSTEMS sponsored project to demonstrate advanced control and diagnosis concepts on an industrial application.

A simple method for automotive switching-type solenoid valve stuck fault detection

This paper proposes a method for the diagnosis of faults in switching-type solenoid valves widely used in automotives, specifically the case in which the valve plunger is sticking during operations. This kind of fault is frequently encountered in electro-hydraulic systems of in-use vehicles and is difficult to detect because the solenoid valves are generally inside the system. A Kalman filter-based fault detection algorithm is derived. Experimental results showed that, using only the measured voltage across and current through the coil of the solenoid, the designed algorithm predicted the plunger motion and diagnosed the stuck fault accurately.

Active fault tolerant control with actuation reconfiguration

This paper presents an integrated approach to fault detection, isolation, and fault tolerant control (FTC). In the proposed approach a constrained Kalman filter based fault detection and isolation (FDI) method (Larson et al., 2002) is modified to reduce its computation load and then applied to detect and isolate a faulty actuator or sensor. Explicit algorithms are derived to estimate the effectiveness factor of a detected faulty actuator or sensor. Furthermore, a design concept of actuation reconfiguration is proposed and implemented in the derived control scheme to restrain the workload of a faulty actuator while recovering the prefault system performance. Simulation results on an aircraft dynamic model have demonstrated the effectiveness of the proposed method.