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Data validation: a case study for a feed-drive monitoring

Habbadi, Abdallah and Desforges, Xavier and Noyes, Daniel Data validation: a case study for a feed-drive monitoring. (1999) In: SDEMPED'99, The IEEE international Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, 1 September 1999 - 3 September 1999 (Gijon, Spain).

(Document in English)

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The monitoring of machine-tools implicated in the metal cutting process is the subject of increasing developments because of requests on control, reliability, availability of machine-tools and on work-piece quality. The use of computers contributes to a better machine and process monitoring by enabling the implementation of complex algorithms for control, monitoring, … The improvement of monitoring of the main machine-tools devices, the feed-drives and the spindles that drive the cutting process, can be realised by estimating their fault sensitive physical parameters from their continuous-time model. We have chosen to use a continuous-time ARX model. We particularly focus on slow time varying phenomena. This estimation should run while there is no machining process to avoid false detection of faults on the machine due to the cutting process. High speed motions, that occur at least for each tool exchange, are exploited. Some functional constraints require the use of an off-line estimation method, we have chosen an ordinary least squares method. Estimating the physical parameters is insufficient to obtain an efficient monitoring. A measurement analysis and validation are necessary as the validation of the estimated physical parameters. An approach of the measurement and physical parameter estimation validation for a NC machine-tool feed-drive is proposed.

Item Type:Conference or Workshop Item (Paper)
HAL Id:hal-04039618
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Laboratory name:
Deposited On:21 Sep 2010 13:30

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