Displaying similar documents to “Machine fault diagnosis and condition prognosis using classification and regression trees and neuro-fuzzy inference system”

Residual generator fuzzy identification for automotive diesel engine fault diagnosis

Silvio Simani (2013)

International Journal of Applied Mathematics and Computer Science

Similarity:

Safety in dynamic processes is a concern of rising importance, especially if people would be endangered by serious system failure. Moreover, as the control devices which are now exploited to improve the overall performance of processes include both sophisticated control strategies and complex hardware (input-output sensors, actuators, components and processing units), there is an increased probability of faults. As a direct consequence of this, automatic supervision systems should be...

Data-driven models for fault detection using kernel PCA: A water distribution system case study

Adam Nowicki, Michał Grochowski, Kazimierz Duzinkiewicz (2012)

International Journal of Applied Mathematics and Computer Science

Similarity:

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...

Decomposition of the symptom observation matrix and grey forecasting in vibration condition monitoring of machines

Czesław Cempel (2008)

International Journal of Applied Mathematics and Computer Science

Similarity:

With the tools of modern metrology we can measure almost all variables in the phenomenon field of a working machine, and many of the measured quantities can be symptoms of machine conditions. On this basis, we can form a symptom observation matrix (SOM) intended for condition monitoring and wear trend (fault) identification. On the other hand, we know that contemporary complex machines may have many modes of failure, called faults. The paper presents a method of the extraction of the...

FDI(R) for satellites: How to deal with high availability and robustness in the space domain?

Xavier Olive (2012)

International Journal of Applied Mathematics and Computer Science

Similarity:

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...

Fault detection and isolation with robust principal component analysis

Yvon Tharrault, Gilles Mourot, José Ragot, Didier Maquin (2008)

International Journal of Applied Mathematics and Computer Science

Similarity:

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 is applied to remove the effect of outliers on the PCA model. In this paper, a fast two-step algorithm is proposed. First, the objective was to find an accurate estimate of the covariance...

Generalized reasoning about faults based on the diagnostic matrix

Michał Bartyś (2013)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper introduces a set of comprehensive general reasoning rules about single faults based on a diagnostic matrix. The reasoning scheme unifies inference about faults based on a conventional binary diagnostic matrix, a two- and three-valued fault isolation system as well as on their fuzzy counterparts. There are introduced and defined notions of alternative and dominant fault signatures, fuzzy fault signatures as well as a matrix of alternative signatures. This matrix is supposed...

Switching time estimation and active mode recognition using a data projection method

Assia Hakem, Vincent Cocquempot, Komi Midzodzi Pekpe (2016)

International Journal of Applied Mathematics and Computer Science

Similarity:

This paper proposes a data projection method (DPM) to detect a mode switching and recognize the current mode in a switching system. The main feature of this method is that the precise knowledge of the system model, i.e., the parameter values, is not needed. One direct application of this technique is fault detection and identification (FDI) when a fault produces a change in the system dynamics. Mode detection and recognition correspond to fault detection and identification, and switching...

An SFDI observer-based scheme for a general aviation aircraft

Marco Ariola, Massimiliano Mattei, Immacolata Notaro, Federico Corraro, Adolfo Sollazzo (2015)

International Journal of Applied Mathematics and Computer Science

Similarity:

The problem of detecting and isolating sensor faults (sensor fault detection and isolation-SFDI) on a general aviation aircraft, in the presence of external disturbances, is considered. The proposed approach consists of an extended Kalman observer applied to an augmented aircraft plant, where some integrators are added to the output variables subject to faults. The output of the integrators should be ideally zero in the absence of model uncertainties, external disturbances and sensor...