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1
Content available remote

Fault location in EHV transmission lines using artificial neural networks

100%
Bouthiba T.
International Journal of Applied Mathematics and Computer Science
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2004
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tom 14
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nr 1
69-78
EN
This paper deals with the application of artificial neural networks (ANNs) to fault detection and location in extra high voltage (EHV) transmission lines for high speed protection using terminal line data. The proposed neural fault detector and locator were trained using various sets of data available from a selected power network model and simulating different fault scenarios (fault types, fault locations, fault resistances and fault inception angles) and different power system data (source capacities, source voltages, source angles, time constants of the sources). Three fault locators are proposed and a comparative study of the proposed fault locators is carried out in order to determine which ANN fault locator structure leads to the best performance. The results show that artificial neural networks offer the possibility to be used for on-line fault detection and location in transmission lines and give satisfactory results.
2
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Robust identification of parasitic feedback disturbances for linear lumped parameter systems

100%
Maksimov V., Pandolfi L.
International Journal of Applied Mathematics and Computer Science
|
2001
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tom 11
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nr 4
835-858
EN
We study the problem of identification of an input to a linear finite-dimensional system. We assume that the input has a feedback form, which is related to a problem often encountered in fault detection. The method we use is to embed the identification problem in a class of inverse problems of dynamics for controlled systems. Two algorithms for identification of a feedback matrix based on the method of feedback control with a model are constructed. These algorithms are stable with respect to noise-corrupted observations and computational errors.
3
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Actuator fault diagnosis for flat systems: A constraint satisfaction approach

100%
Seydou R., Raissi T., Zolghadri A., Efimov D.
International Journal of Applied Mathematics and Computer Science
|
2013
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tom 23
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nr 1
171-181
EN
This paper describes a robust set-membership-based Fault Detection and Isolation (FDI) technique for a particular class of nonlinear systems, the so-called flat systems. The proposed strategy consists in checking if the expected input value belongs to an estimated feasible set computed using the system model and the derivatives of the measured output vector. The output derivatives are computed using a numerical differentiator. The set-membership estimator design for the input vector takes into account the measurement noise thereby making the consistency test robust. The performances of the proposed strategy are illustrated through a three-tank system simulation affected by actuator faults.
4
Content available remote

Artificial intelligence methods in diagnostics of analog systems

100%
Bilski P., Wojciechowski J.
International Journal of Applied Mathematics and Computer Science
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2014
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tom 24
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nr 2
271-282
EN
The paper presents the state of the art and advancement of artificial intelligence methods in analog systems diagnostics. Firstly, the diagnostic domain is introduced and its problems explained. Then, computational intelligence approaches usable for fault detection and identification are reviewed. Particular groups of methods are presented in detail, explaining their usefulness and drawbacks. Examples, such as the induction motor or the electronic filter, are provided to show the applicability of the presented approaches for monitoring the state of analog objects from engineering domains. The discussion section reviews the presented approaches, their future prospects and problems to be solved.
5
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Sliding mode methods for fault detection and fault tolerant control with application to aerospace systems

100%
Edwards C., Alwi H., Tan C.
International Journal of Applied Mathematics and Computer Science
|
2012
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tom 22
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nr 1
109-124
EN
Sliding mode methods have been historically studied because of their strong robustness properties with regard to a certain class of uncertainty, achieved by employing nonlinear control/injection signals to force the system trajectories to attain in finite time a motion along a surface in the state-space. This paper will consider how these ideas can be exploited for fault detection (specifically fault signal estimation) and subsequently fault tolerant control. It will also describe applications of these ideas to aerospace systems, including piloted flight simulator results associated with the GARTEUR AG16 Action Group on Fault Tolerant Control. The results demonstrate a successful real-time implementation of the proposed fault tolerant control scheme on a motion flight simulator configured to represent the post-failure EL-AL aircraft.
6
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FDI(R) for satellites: How to deal with high availability and robustness in the space domain?

100%
Olive X.
International Journal of Applied Mathematics and Computer Science
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2012
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tom 22
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nr 1
99-107
EN
The European leader for satellite systems and at the forefront of orbital infrastructures, Thales Alenia Space, is a joint venture between Thales (67%) and Finmeccanica (33%) and forms with Telespazio a Space Alliance. Thales Alenia Space is a worldwide reference in telecoms, radar and optical Earth observation, defence and security, navigation and science. It has 11 industrial sites in 4 European countries (France, Italy, Spain and Belgium) with over 7200 employees worldwide. Satellite evolution and the wish to design more autonomous missions imply the enhancement of the satellite architecture and special attention paid to fault management (i.e., Fault Detection, Isolation and Recovery, or FDIR, in space). Nevertheless, the constraints on FDIR techniques and strategies remain the same as for standard missions: robustness, reactive detection, quick isolation/identification and validation. This paper gives an introduction to Fault Tolerance (FT) in the space domain and some principles for the coming FT architectures. The current context of FDIR is presented by describing the approach implemented on telecommunication satellites and, more precisely, on one of the most FDIR sensible subsystems: the AOCS (Attitude and Orbit Control System). Following the current state of FDIR in the space domain, some perspectives are given such as a centralized distributed FDIR strategy for the next generation of autonomous satellites as well as some research tracks and hybrid diagnosis.
7
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Data-driven models for fault detection using kernel PCA: A water distribution system case study

88%
Nowicki A., Grochowski M., Duzinkiewicz K.
International Journal of Applied Mathematics and Computer Science
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2012
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tom 22
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nr 4
939-949
EN
Kernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection. A systematic description of the system's framework is followed by evaluation of its performance. Simulations prove that the presented approach is both flexible and efficient.
8
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Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation

88%
Xu F., Puig V., Ocampo-Martinez C., Olaru S., Niculescu S.-I.
International Journal of Applied Mathematics and Computer Science
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2017
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tom 27
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nr 1
43-61
EN
In this paper, a fault-tolerant control (FTC) scheme is proposed for actuator faults, which is built upon tube-based model predictive control (MPC) as well as set-based fault detection and isolation (FDI). In the class of MPC techniques, tubebased MPC can effectively deal with system constraints and uncertainties with relatively low computational complexity compared with other robust MPC techniques such as min-max MPC. Set-based FDI, generally considering the worst case of uncertainties, can robustly detect and isolate actuator faults. In the proposed FTC scheme, fault detection (FD) is passive by using invariant sets, while fault isolation (FI) is active by means of MPC and tubes. The active FI method proposed in this paper is implemented by making use of the constraint-handling ability of MPC to manipulate the bounds of inputs. After the system has been detected to become faulty, the input-constraint set of the MPC controller is adjusted to actively excite the system for achieving FI guarantees on-line, where an active FI-oriented input set is designed off-line. In this way, the system can be excited in order to obtain more extra system-operating information for FI than passive FI approaches. Overall, the objective of this paper is to propose an actuator MPC scheme with as little as possible of FI conservatism and computational complexity by combining tube-based MPC and set theory within the framework of MPC, respectively. Finally, a case study is used to show the effectiveness of the proposed FTC scheme.
9
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Integrated design of observer based fault detection for a class of uncertain nonlinear systems

88%
Chen W., Khan A., Abid M., Ding S.
International Journal of Applied Mathematics and Computer Science
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2011
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tom 21
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nr 3
423-430
EN
Integrated design of observer based Fault Detection (FD) for a class of uncertain nonlinear systems with Lipschitz nonlinearities is studied. In the context of norm based residual evaluation, the residual generator and evaluator are designed together in an integrated form, and, based on it, a trade-off FD system is finally achieved in the sense that, for a given Fault Detection Rate (FDR), the False Alarm Rate (FAR) is minimized. A numerical example is given to illustrate the effectiveness of the proposed design method.
10
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Content available

Model-based techniques for virtual sensing of longitudinal flight parameters

88%
Hardier G., Seren C., Ezerzere P.
International Journal of Applied Mathematics and Computer Science
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2015
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tom 25
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nr 1
23-38
EN
Introduction of fly-by-wire and increasing levels of automation significantly improve the safety of civil aircraft, and result in advanced capabilities for detecting, protecting and optimizing A/C guidance and control. However, this higher complexity requires the availability of some key flight parameters to be extended. Hence, the monitoring and consolidation of those signals is a significant issue, usually achieved via many functionally redundant sensors to extend the way those parameters are measured. This solution penalizes the overall system performance in terms of weight, maintenance, and so on. Other alternatives rely on signal processing or model-based techniques that make a global use of all or part of the sensor data available, supplemented by a model-based simulation of the flight mechanics. That processing achieves real-time estimates of the critical parameters and yields dissimilar signals. Filtered and consolidated information is delivered in unfaulty conditions by estimating an extended state vector, including wind components, and can replace failed signals in degraded conditions. Accordingly, this paper describes two model-based approaches allowing the longitudinal flight parameters of a civil A/C to be estimated on-line. Results are displayed to evaluate the performances in different simulated and real flight conditions, including realistic external disturbances and modeling errors.
11
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Content available

Robust fault detection of singular LPV systems with multiple time-varying delays

88%
Hassanabadi A., Shafiee M., Puig V.
International Journal of Applied Mathematics and Computer Science
|
2016
|
tom 26
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nr 1
45-61
EN
In this paper, the robust fault detection problem for LPV singular delayed systems in the presence of disturbances and actuator faults is considered. For both disturbance decoupling and actuator fault detection, an unknown input observer (UIO) is proposed. The aim is to compute a residual signal which has minimum sensitivity to disturbances while having maximum sensitivity to faults. Robustness to unknown inputs is formulated in the sense of the H∞ -norm by means of the bounded real lemma (BRL) for LPV delayed systems. In order to formulate fault sensitivity conditions, a reference model which characterizes the ideal residual behavior in a faulty situation is considered. The residual error with respect to this reference model is computed. Then, the maximization of the residual fault effect is converted to minimization of its effect on the residual error and is addressed by using the BRL. The compromise between the unknown input effect and the fault effect on the residual is translated into a multi-objective optimization problem with some LMI constraints. In order to show the efficiency and applicability of the proposed method, a part of the Barcelona sewer system is considered.
12
Content available remote

Nonlinear model predictive control of a boiler unit: A fault tolerant control study

88%
Patan K., Korbicz J.
International Journal of Applied Mathematics and Computer Science
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2012
|
tom 22
|
nr 1
225-237
EN
This paper deals with a nonlinear model predictive control designed for a boiler unit. The predictive controller is realized by means of a recurrent neural network which acts as a one-step ahead predictor. Then, based on the neural predictor, the control law is derived solving an optimization problem. Fault tolerant properties of the proposed control system are also investigated. A set of eight faulty scenarios is prepared to verify the quality of the fault tolerant control. Based of different faulty situations, a fault compensation problem is also investigated. As the automatic control system can hide faults from being observed, the control system is equipped with a fault detection block. The fault detection module designed using the one-step ahead predictor and constant thresholds informs the user about any abnormal behaviour of the system even in the cases when faults are quickly and reliably compensated by the predictive controller.
13
Content available remote

Fault diagnosis and fault tolerant control using set-membership approaches: Application to real case studies

88%
Puig V.
International Journal of Applied Mathematics and Computer Science
|
2010
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tom 20
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nr 4
619-635
EN
This paper reviews the use of set-membership methods in fault diagnosis (FD) and fault tolerant control (FTC). Setmembership methods use a deterministic unknown-but-bounded description of noise and parametric uncertainty (interval models). These methods aims at checking the consistency between observed and predicted behaviour by using simple sets to approximate the exact set of possible behaviour (in the parameter or the state space). When an inconsistency is detected between the measured and predicted behaviours obtained using a faultless system model, a fault can be indicated. Otherwise, nothing can be stated. The same principle can be used to identify interval models for fault detection and to develop methods for fault tolerance evaluation. Finally, some real applications will be used to illustrate the usefulness and performance of set-membership methods for FD and FTC.
14
Content available remote

Configuring a sensor network for fault detection in distributed parameter systems

75%
Patan M., Uciński D.
International Journal of Applied Mathematics and Computer Science
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2008
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tom 18
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nr 4
513-524
EN
The problem of fault detection in distributed parameter systems (DPSs) is formulated as that of maximizing the power of a parametric hypothesis test which checks whether or not system parameters have nominal values. A computational scheme is provided for the design of a network of observation locations in a spatial domain that are supposed to be used while detecting changes in the underlying parameters of a distributed parameter system. The setting considered relates to a situation where from among a finite set of potential sensor locations only a subset can be selected because of the cost constraints. As a suitable performance measure, the Ds-optimality criterion defined on the Fisher information matrix for the estimated parameters is applied. Then, the solution of a resulting combinatorial problem is determined based on the branch-and-bound method. As its essential part, a relaxed problem is discussed in which the sensor locations are given a priori and the aim is to determine the associated weights, which quantify the contributions of individual gauged sites. The concavity and differentiability properties of the criterion are established and a gradient projection algorithm is proposed to perform the search for the optimal solution. The delineated approach is illustrated by a numerical example on a sensor network design for a two-dimensional convective diffusion process.
15
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Content available

A probabilistic method for certification of analytically redundant systems

75%
Hu B., Seiler P.
International Journal of Applied Mathematics and Computer Science
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2015
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tom 25
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nr 1
103-116
EN
Analytical fault detection algorithms have the potential to reduce the size, power and weight of safety-critical aerospace systems. Analytical redundancy has been successfully applied in many non-safety critical applications. However, acceptance for aerospace applications will require new methods to rigorously certify the impact of such algorithms on the overall system reliability. This paper presents a theoretical method to assess the probabilistic performance for an analytically redundant system. Specifically, a fault tolerant actuation system is considered. The system consists of dual-redundant actuators and an analytical fault detection algorithm to switch between the hardware components. The exact system failure rate per hour is computed using the law of total probability. This analysis requires knowledge of the failure rates for the hardware components. In addition, knowledge of specific probabilistic performance metrics for the fault detection logic is needed. Numerical examples are provided to demonstrate the proposed analysis method.
16
Content available remote

LPV design of fault-tolerant control for road vehicles

75%
Gáspár P., Szabó Z., Bokor J.
International Journal of Applied Mathematics and Computer Science
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2012
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tom 22
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nr 1
173-182
EN
The aim of the paper is to present a supervisory decentralized architecture for the design and development of reconfigurable and fault-tolerant control systems in road vehicles. The performance specifications are guaranteed by local controllers, while the coordination of these components is provided by a supervisor. Since the monitoring components and FDI filters provide the supervisor with information about the various vehicle maneuvers and the different fault operations, it is able to make decisions about necessary interventions into the vehicle motions and guarantee reconfigurable and fault-tolerant operation of the vehicle. The design of the proposed reconfigurable and fault-tolerant control is based on an LPV method that uses monitored scheduling variables during the operation of the vehicle.
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