A general purpose software for distance monitoring and diagnosis of electrical machines

This paper is mainly about the development of a virtual platform structure, on the design of the data-processing environment, the data standard, the design of the different acquisition and data processing systems, the database development for the management and the exchange of information. The main features are: user friendly interface, low maintenance source code, modularity to facilitate the integration of new computation and decision techniques, a standardized database for electrical machines monitoring and diagnosis to improve the knowledge of a large scientific community as well.

[1]  Pragasen Pillay,et al.  Motor current signature analysis , 1996, IAS '96. Conference Record of the 1996 IEEE Industry Applications Conference Thirty-First IAS Annual Meeting.

[2]  Gian Carlo Montanari,et al.  A new approach to the diagnosis of solid insulation systems based on PD signal inference , 2003 .

[3]  R. Teodorescu,et al.  Portable acquisition and identification tool for induction machine diagnosis , 1998 .

[4]  Alexander G. Parlos,et al.  Model-based incipient fault diagnosis - multi-step neuro-predictors and multiresolution signal processing , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[5]  C. Landi,et al.  Special measurement system for on-line fault diagnosis of induction motors , 1994, Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics.

[6]  A. Nandi,et al.  A comparison of artificial neural networks and other statistical methods for rotating machine condition classification , 1996 .

[7]  F. Filippetti,et al.  Quantitative evaluation of induction motor broken bars by means of electrical signature analysis , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[8]  Giovanni Franceschini,et al.  Development of expert system knowledge base to on-line diagnosis of rotor electrical faults of induction motors , 1992, Conference Record of the 1992 IEEE Industry Applications Society Annual Meeting.

[9]  Fiorenzo Filippetti,et al.  Recent developments of induction motor drives fault diagnosis using AI techniques , 2000, IEEE Trans. Ind. Electron..

[10]  L. Szentirmai,et al.  Computerised fault diagnosis of induction motor drives , 1995 .

[11]  R. Sasdelli,et al.  A low-cost dsp-based equipment for the detection of transients in power systems , 2003, Proceedings of the 20th IEEE Instrumentation Technology Conference (Cat. No.03CH37412).

[12]  G.-A. Capolino.  A comprehensive analysis of the current status in low voltage induction motor diagnosis , 2000 .

[13]  Alberto Bellini,et al.  Quantitative Evaluation of Induction Motor Broken Bars By Means of Electric Signals Signatures , 2001 .

[14]  G. B. Kliman,et al.  Noninvasive detection of broken rotor bars in operating induction motors , 1988 .

[15]  R. C. Kryter,et al.  Condition monitoring of machinery using motor current signature analysis , 1989 .