The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A robust incipient faults diagnosis proposal for a class of nonlinear system with unknown input disturbances is presented in this paper. First, the uncertain nonlinear system is transformed into two subsystems and one of them is free from disturbances. Then for the subsystem free from disturbances, an adaptive observer is constructed to reconstruct incipient faults and a sliding mode observer is constructed...
Wireless Sensor Networks (WSN) have attracted considerable research effort in the community during the past couple of years. One of the most challenging issues so far is the extension of network lifetime with regards to small battery capacity and self-sustained operation. Endeavors to save energy have been made on various frontiers, ranging from hardware improvements over medium access and routing...
Fault diagnosis and protection is the key of safe running of power net. At present, the main studies of fault diagnosis and protection of power net (FDPPN) concentrate on the establishment and simulation of idiographic model, but there is not universal model. There is distinct limit between discrete character and continuous character in FDPPN, so that the paper extended HPN model to propose Hybrid...
The paper deals with the problem of fault detection and isolation in machining centers, which are the basis of FMSpsila. The problem is of paramount importance since an effective diagnostic system can lead to a significant increase in the autonomy of an automated system. The paper considers a special case study: an hydraulic circuit which blocks and unblocks the pallet on the rotary table in a machining...
Fault monitoring plays an important role for safety and reliability of industrial systems. We present a novel on-line monitoring technique for automated manufacturing systems employing the first order hybrid Petri nets formalism, i.e., Petri nets making use of first order fluid approximation. The proposed fault analysis approach belongs to the class of event based methodologies, so that the state...
In this paper, an anomaly detection structure, in which different types of anomaly detection routines can be applied, is proposed. Bearing fault modes and their effects on the bearing vibration are discussed. Based on this, a feature extraction method is developed to overcome the limitation of time domain features. Experimental data from bearings under different operating conditions are used to verify...
In multivariate statistic process control (MSPC), the projection methods, in particular, the principal component analysis (PCA) proved their efficiencies to the problems of fault diagnosis. In this paper, we explained the use of this tool and its major interest. A projected observation in the PCA space has a score distance (SD) in the principal component subspace and an orthogonal distance (OD) or...
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance matrix of the data is very sensitive to outliers in the training data set. Usually robust principal component analysis was applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm...
The purpose of this article is to present a method for industrial process diagnosis with Bayesian network. The interest of the proposed method is to combine a discriminant analysis and a distance rejection in a bayesian network in order to detect new types of fault. The performances of this method are evaluated on the data of a benchmark example: the Tennessee Eastman Process. Three kinds of fault...
In this paper, a fault tolerant control (FTC) system based on data driven fault detection (FDI) is presented. The behaviour of the system with proactive and reactive FTC strategies is studied in the presence of faults in an online product quality analyser with a simulated dearomatisation process operated under model predictive control (MPC). The performance of the system is validated onsite at the...
This paper presents a benchmark study on fault diagnosis of electrohydraulic servoactuators (EHSA). EHSA are considered to be affected by faults and disturbances. The linear mathematical model of the EHSA is given. Two different design methods for fault diagnosis are studied. The first method considers the strategy of parity space design, and observer-based implementation, in which a perfect disturbance...
This paper presents a diagnosis system for detecting tramway rollers defects. First, the continuous wavelet transform is applied on vibration signals measured by specific accelerometers. Then, the Singular Values Decomposition (SVD) is applied on the time-scale representations to extract a set of singular values as classification features. The resulting multi-class classification problem is decomposed...
The paper investigates the development of a new type of recurrent wavelet neural network and its application to fault detection and isolation (FDI) of a dynamic process. Hybrid learning based on c-means fuzzy clustering algorithm and the steepest-descent method, is used to train the proposed neural network. The experimental case study concerns the sensor and actuator fault diagnosis of a sub-system...
This paper addresses fault detection and isolation (FDI) problem using a sliding mode fuzzy observer on the basis of a uncertain Takagi-Sugeno (T-S) fuzzy model. First, a robust fuzzy observer with respect to the uncertainties is designed. The convergence of the fuzzy observer is performed by the search of suitable Lyapunov matrices. It is shown how to synthesis observers using a set of linear matrix...
The main goal of this paper consists in the development of a new actuator fault-tolerant control dedicated to nonlinear systems. Based on the assumption that the nonlinear system is described by a finite number of interpolated linear time invariant models, the proposed method makes possible the faults compensation for the whole operating range through an extended interacting multiple model. Its principle...
In this paper, a new active FTC strategy is proposed. First, it is developed in the context of linear systems and then it is extended to Takagi-Sugeno fuzzy systems. The key contribution of the proposed approach is an integrated FTC design procedure of the fault identification and fault-tolerant control schemes. Fault identification is based on the use of an observer. While, the FTC controller is...
In this paper Fisher's discriminant analysis (FDA) is used for detecting and diagnosing faults in a real plant. FDA provides an optimal lower dimensional representation in terms of discriminating between classes of data, where, in this context of fault diagnosis, each class corresponds to data collected during a specific, known fault. A discriminant function is applied to detect and diagnose faults...
The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other...
In this paper, a diagnosis system using unknown input observers in order to detect, isolate and estimate faulty control surface positions for a small UAV, is presented. As this aircraft is equipped with redundant actuators, flap and aileron positions are not input observable and an active diagnosis process has to be implemented.
We develop a multi-decision framework for decentralized diagnosis of discrete event systems (DES), where each diagnoser issues a tuple of diagnoses instead of a single diagnosis. We use the multi-decision framework to generalize existing methods for decentralized diagnosis. We study the diagnosis of the occurrence of fault as well as the diagnosis of the absence of fault. We show that the multi-decision...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.