Structural Analysis Extended with Active Fault Isolation - Methods and Algorithms

Gelso, Esteban R.; Blanke, Mogens

doi:10.3182/20090630-4-es-2003.00099

Cited by 5 publications

(6 citation statements)

References 16 publications

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“…The possibility of isolating a fault is evident for cases of single faults. Isolation if multiple faults should occur could be accomplished using active fault isolation techniques (Poulsen and Niemann, 2008), (Gelso and Blanke, 2009). The remedial action in case of an airspeed sensor system fault would be to avoid using airspeed in the avionics.…”

Section: Airspeed System Defectmentioning

confidence: 99%

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

Hansen

Blanke

Adrian³

2014

IFAC Proceedings Volumes

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Unmanned Aerial Vehicles (UAVs) need a large degree of tolerance towards faults.If not diagnosed and handled in time, many types of faults can have catastrophic consequences if they occur during flight. Prognosis of faults is also valuable and so is the ability to distinguish the severity of the different faults in terms of both consequences and the frequency with which they appear. In this paper flight data from a fleet of UAVs is analysed with respect to certain faults and their frequency of appearance. Data is taken from a group of UAV's of the same type but with small differences in weight and handling due to different types of payloads and engines used. Categories of critical faults, that could and have caused UAV crashes are analysed and requirements to diagnosis are formulated. Faults in air system sensors and in control surfaces are given special attention. In a stochastic framework, and based on a large number of data logged during flights, diagnostic methods are employed to diagnose faults and the performance of these fault detectors are evaluated against flight data. The paper demonstrates a significant potential for reducing the risk of unplanned loss of remotely piloted vehicles used by the Danish Navy for target practice.

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Section: Airspeed System Defectmentioning

confidence: 99%

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

Hansen

Blanke

Adrian³

2014

IFAC Proceedings Volumes

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“…Approaches to the combination of structural analysis and active diagnosis can be found in [7] and [8]. In these references, first, a structural analysis of the nominal system is used to identify residual generators that contain system inputs; second, it is verified that the transfer from inputs to residuals is affected differently by faults on different constraints.…”

Section: Input Generator Systemmentioning

confidence: 99%

Service diagnosis of dynamical systems based on local structural models

Ungermann

Lunze

Schwarzmann

2011

2011 19th Mediterranean Conference on Control &Amp; Automation (MED)

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The paper presents a new approach to the selection of tests used in service diagnosis of dynamical systems. It proposes a method to select input signals that steer the system into a particular operating region and to find the corresponding local residuals for evaluating the system's I/O behavior. The tests allow the isolation of faults that are generally not distinguishable, but become isolable under specific operation conditions. The method is based on the analysis of the structure graph, which represents the couplings among external and internal signals of the system and the possible faults. This graph changes if the system variables are restricted to different operating regions. Accordingly, the local structure of the system distinguishes from the global structure that holds for the unrestricted variables. By utilizing this difference, it is possible to determine tests that are sensitive to specific faults. The method is illustrated by its application to a throttle valve.

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“…The results of the analysis can hold lots of useful information for fault diagnosis design since it is revealed which components of the system that are monitorable and constraints usable for designing residuals based on analytic redundancy are identified. If the standard structural analysis shows that the system in question is not completely monitorable by a passive approach the analysis can be extended to investigate the input-output paths through the system that can be excited in an active fault diagnosis, where auxiliary test signals are applied to the inputs (Gelso and Blanke, 2009). …”

Section: Structural Analysis Of Refrigeration Systemmentioning

confidence: 99%

“…In (Gelso and Blanke, 2009) the following proposition about active fault isolation is stated: Active input to output structural isolation is possible if and only if both a structural condition and a quantitative condition are true. Structural condition: the known variables in the set of residuals associated with a group of nonstructurally isolable constraints include at least one control input.…”

Section: Extended Structural Analysismentioning

confidence: 99%

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Active sensor configuration validation for refrigeration systems

Hovgaard

Blanke

Niemann

et al. 2010

Proceedings of the 2010 American Control Conference

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SummaryThis master's thesis presents an approach to validation of the sensor configuration in control systems. Major faults in the commissioning phase of refrigeration systems are caused by defects related to sensors. With a number of similar sensors that differ only by spatial location and their use in the control system, fault-finding is not trivial and it often results in expensive delays. Validation and handling of faults in the sensor configuration are therefore essential to cut costs during commissioning. With passive faultdiagnosis methods falling short on this problem, this thesis describes an active diagnosis procedure to isolate sensor faults at the commissioning stage, before normal operation has started. Using statistical methods, residuals are evaluated versus multiple hypothesis models in a minimization process to uniquely identify the sensor configuration. The method as such is generic and is shown in the sequel to work convincingly on refrigeration systems with both nonlinear behaviors and significant mutual differences.The thesis includes sections concerning the target system with respect to building a dynamical model and analysis (both general and structural) of system properties and of the types of faults to be dealt with. Furthermore a complete solution strategy is presented in which a test signal is applied to one of the system inputs and to different system models resulting in residual signals for each of the faulty cases to be diagnosed. It is discussed how the dependency on accurate system models can be minimized by appropriate filtering of the residuals and a statistical detection method is applied, identifying the model best describing the system. Furthermore it is demonstrated how only very limited information of the system need to be contained in the models for the solution to be reliable. Thorough explanation of the utilized theory is given along with references to previous works in the area.Using both simulations and real data from commercial refrigeration systems validation of the method is offered. In the simulations it is illustrated how the proposed solution works as intended in the ideal cases with completely known system models and also how it is able to handle rather severe noise and model uncertainties when up to 25% variations are added randomly to both parameters and input of the model. Data collected in the refrigeration lab at Danfoss A/S reveals that parameter variations from one refrigeration system to another, depending on construction and dimensions, might exceed the amount of uncertainty that was successfully tested in the simulation environment. Hence, it is concluded that the solution is generic in the sense that it can be tuned to a certain class of systems for which it is very robust. With respect to measurement noise or low frequent disturbances e.g. the day/night or season changes the method is also proved to be very robust.In addition the work has resulted in a conference paper of the same title which has been submitted to the American Control Conference 2010...

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Structural Analysis Extended with Active Fault Isolation - Methods and Algorithms

Cited by 5 publications

References 16 publications

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

A Framework for Diagnosis of Critical Faults in Unmanned Aerial Vehicles

Service diagnosis of dynamical systems based on local structural models

Active sensor configuration validation for refrigeration systems

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