196,595 research outputs found
Data-Driven and Adaptive Automatic Approaches for Wind Turbine Fault Diagnosis
No full textSoftware premiato col terzo posto alla competizione internazionale sullo sviluppo delle migliori soluzioni software per la diagnosi dei guasti di turbine eoliche proposta dall’azienda danese kk-electronic e la MathWorks Inc. (USA). La premiazione ha avuto luogo durante il convegno modiale IFAC (Milano, 28 agosto – 2 settembre 2011) e la soluzione tecnica è descritta negli articoli:
o S. Simani, P. Castaldi, and A. Tilli, “Data–Driven Approach for Wind Turbine Actuator and Sensor Fault Detection and Isolation,” in Proceedings of the 18th IFAC World Congress (S. Bittanti, A. Cenedese, and S. Zampieri, eds.), vol. 18, (Università Cattolica del Sacro Cuore, Milan, Italy), pp. 8301–8306, International Federation of Automatic Control (IFAC), IFAC–PapersOnLine, August 28 – September 2, 2011. Special Session Invited Paper. DOI: 10.3182/20110828– 6–IT–1002.00447.
o S. Simani, P. Castaldi, and M. Bonfè, “Hybrid Model–Based Fault Detection of Wind Turbine sensors,” in Proceedings of the 18th IFAC World Congress (S. Bittanti, A. Cenedese, and S. Zampieri, eds.), vol. 18, (Università Cattolica del Sacro Cuore, Milan, Italy), pp. 7061–7066, International Federation of Automatic Control (IFAC), IFAC–PapersOnLine, August 28 – September 2, 2011. Special Session Invited Paper. DOI: 10.3182/20110828–6–IT–1002.01311
Concepts and methods in fault tolerant control with application to a wind turbine simulated system
No full textFaults in automated processes will often cause undesired reactions and shutdown of a controlled plant, and the consequences could be damage to technical parts of the plant, to personnel or the environment. Fault tolerant control combines diagnosis withcontrolmethods to handle faults in an intelligentway. The aim is to prevent that simple faults develop into serious failure and hence increase plant availability and reduce the risk of safety hazards. Fault-tolerant control merges several disciplines into a common framework to achieve these goals. The desired features are obtained through online fault diagnosis, automatic condition assessment and calculation of appropriate remedial actions to avoid certain consequences of a fault. The envelope of the possible remedial actions is very wide. Sometimes, simple re–tuning can suffice. In other cases,accommodation of the fault could be achieved by replacing a measurement from a faulty sensor by an estimate. In yet other situations, complex reconfiguration or online controller redesign is required. This chapter gives an overview of well–established and more recent tools to analyse and explore structure and other fundamental properties of an automated system such that any inherent redundancy in the controlled process can be fully utilised to maintain availability, even though faults may occur. On the other hand, the effectiveness of the analysed solutions has been verified when applied to a wind turbine system. In fact, wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high–fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of fault tolerant control solutions for wind turbine systems should consider these complexity aspects. On the other hand, these solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The second point of this chapter is thus to provide practical examples of the development of robust fault tolerant control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator represent the instruments for assessing the main aspects of the developed control methodologies
A study of fault diagnosis and recovery techniques for manufacturing systems
No full textThe paper describes a framework for the development of a diagnosismethodology for industrial manufacturing systems. The aim of the project is tosupport technicians that supervise the manufacturing plant to identify the causesof faults and failures on the machine and, in particular, to indicate a procedurefor the recovery of its working condition. The requirements described in the paperhave been defined giving particular care to the peculiarities of the applicationdomain, in order to allow the design of a powerful, but easy to use, diagnosticsystem for industrial technician
Data–Driven and Model–Based Fault Diagnosis of Wind Turbine Sensors
No full textIn order to improve reliability of wind turbines, it is important to detect faults in their
very early occurrence, and to handle them in an optimal way. This paper focuses on the pitch
sensors of the turbine blade system, as they are mainly used for wind turbine control, in order
to maximise the power production, and the efficiency of the whole process. On the other hand,
as the input–output behaviour of the system under diagnosis is nonlinear, this work suggests a
modelling scheme relying on piecewise affine models, whose parameters are identified through
the acquired input–output measurements affected by measurement uncertainty. Therefore, these
prototypes are exploited for generating suitable residual signals, which allow the detection
and the isolation of the considered sensor faults. This noise rejection scheme is used since the
wind turbine measurements are not very reliable, due to the uncertainty of wind speed acting
on the wind turbine, and to the turbulence around the rotor plane. A detailed benchmark
model simulating the wind turbine where realistic fault conditions can be considered shows the
effectiveness of both the identification and fault diagnosis techniques
Residual function design for linear multivariable systems
No full textClassical model–based fault detection schemes for linear multivariable systems require the definition of suitable residual functions. This paper shows the possibility of identifying residual generators even when the system model is unknown, by following a black–boxapproac h. The result is obtained by using canonical input–output polynomial forms which lead to characterise in a straightforward fashion the basis of the subspace described by all possible residual generators. The performance of the proposed identification method is tested by means of a Monte Carlo simulation
Reliable Real-Time Embedded Control for Offshore Wind Turbines
No full textReliable and sustainable control has begun to stimulate research and development in a wide range of industrial communities particularly for systems that demand a high degree of reliability and availability (sustainability) and at the same time characterised by expensive and/or safety critical maintenance work. For offshore wind farms a clear conflict exists between ensuring a high degree of availability and reducing costly maintenance times. Wind turbines have highly non-linear dynamics and a stochastic and uncontrollable driving force as input in the form of wind speed, presenting an interesting challenge for modern control methods. Suitable control methods can provide sustainable maximisation of energy conversion efficiency over wider than normally expected wind speeds, whilst also giving a degree of “tolerance” to certain faults, providing an important impact on maintenance scheduling, e.g. by capturing the effects of some turbine system faults before they become serious
Active fault tolerant control of nonlinear systems: The cart-pole example
No full textThis paper describes the design of fault diagnosis and active fault tolerant control schemes that can be developed for nonlinear systems. The methodology is based on a fault detection and diagnosis procedure relying on adaptive filters
designed via the nonlinear geometric approach, which allows obtaining the disturbance de-coupling property. The controller
reconfiguration exploits directly the on-line estimate of the fault signal. The classical model of an inverted pendulum
on a cart is considered as an application example, in order to highlight the complete design procedure, including the
mathematical aspects of the nonlinear disturbance de-coupling method based on the nonlinear differential geometry, as
well as the feasibility and efficiency of the proposed approach. Extensive simulations of the benchmark process and Monte
Carlo analysis are practical tools for assessing experimentally the robustness and stability properties of the developed fault
tolerant control scheme, in the presence of modelling and measurement errors. The fault tolerant control method is also compared with a different approach relying on sliding mode control, in order to evaluate benefits and drawbacks of both
techniques. This comparison highlights that the proposed design methodology can constitute a reliable and robust approach for application to real nonlinear processes
A study of fault diagnosis and recovery techniques for manufacturing systems
No full textThis chapter describes a framework for the development of a diagnosis methodology for industrial manufacturing systems. The aim of the project is to support technicians that supervise the manufacturing plant to identify the causes of faults and failures on the machine and, in particular, to indicate a procedure for the recovery of its working condition. The chapter presents a study as the first step of a design project whose objective is to realize a supervisory system with advanced features devoted to Faults Detection and Isolation (FDI) for the manufacturing industry, with an emphasis on its integration with Human-Machine Interfaces. The requirements described in the chapter are defined giving particular care to the peculiarities of the application domain to allow the design of a powerful, but easy to use for industrial technicians, diagnostic system. An example of a manufacturing machine quite common in the packaging industry is schematized in the chapter, which is analyzed to define the fault trees for the most critical failure modes. © 2007 Copyright © 2007 Elsevier Ltd All rights reserved
Active Fault Tolerant Control Scheme for a General Aviation Aircraft Model
No full textThis paper addresses the development of a novel active
fault tolerant control scheme. The methodology is based on a
fault detection and diagnosis procedure relying on adaptive filters
designed via the nonlinear geometric approach. The controller
reconfiguration exploits a further control loop, depending on the
on-line estimate of the fault signal. One of the advantages of this
strategy is that, for example, a structure of logic–based switching
controller is not required. The active fault tolerant control scheme
is therefore applied to a PA–30 aircraft simulator in several
flight conditions, in the presence of actuator faults, turbulence,
measurement noise, and modelling errors. The achieved results
in faulty conditions show the enhancement of the flying quality,
the asymptotic fault accommodation, and the control objective
recovery
Hybrid Model–Based Fault Detection of Wind Turbine Sensors
No full textIn order to improve reliability of wind turbines, it is important to detect faults in their
very early occurrence, and to handle them in an optimal way. This paper focuses on the pitch
sensors of the turbine blade system, as they are mainly used for wind turbine control, in order
to maximise the power production, and the efficiency of the whole process. On the other hand,
as the input–output behaviour of the system under diagnosis is nonlinear, this work suggests a
modelling scheme relying on piecewise affine models, whose parameters are identified through
the acquired input–output measurements affected by measurement uncertainty. Therefore, these
hybrid prototypes are exploited for generating suitable residual signals, which allow the detection
and the isolation of the considered sensor faults. This noise rejection scheme is used since the
wind turbine measurements are not very reliable, due to the uncertainty of wind speed acting
on the wind turbine, and to the turbulence around the rotor plane. A detailed benchmark
model simulating the wind turbine where realistic fault conditions can be considered shows the
effectiveness of both the identification and fault diagnosis techniques
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