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By R. Husson

Details Processing is a key zone of analysis and improvement and the symposium awarded state of the art reviews on a number of the parts that are of relevance in computerized regulate: fault prognosis and process reliability. Papers additionally coated the position of specialist platforms and different wisdom dependent structures, that are wanted, to deal with the gigantic amounts of information generated by way of huge scale structures. This quantity could be thought of crucial analyzing for someone serious about this speedily constructing sector

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Extra info for Advanced Information Processing in Automatic Control (AIPAC '89)

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0032 (40) (41) T = ^ N Hereby following symbols are used grinding wheel p o s i t i o n in the contacting F 2D 1D [Kh/kg] Η None ,·£ T A (39) Normal cutting force equation Λ. Τ order. 17 shows the parameter estimates f o r normal conditions and changed conditions. The parameter estimates converge a f t e r 10 samples and show significant changes f o r the various operating conditions, see Table 4. Hence the changes of the estimated process c o e f f i c i e n t s can be used as symptoms o f faulty conditions f o r the grinding process.

25 RESULTS AND DISCUSSION The objectives of the simulations are to identify component bias failures and reconfigure the control system to accommodate them. The first task is to determine the effect of failures on the residual sequence of the Kaiman filter for the no failure hypothesis. This can be done by simulation of a normal test sequence on the SCOLE apparatus. g. the torque wheels of figure 4. Excitation is terminated after a prescribed level of sensor output has been achieved. Failures of the sensors are simulated by biasing the sensor output data.

These parameters are function of the structural state of the tool and independent to the experimental environment. Complex workpieces can also be treated. Feed (Fx) Ftrns ( F Y) Figure 7 : Sign Convention It is on the basis of this model that the following functions are performed given that on line parameter identification is the main chore of the perception level. ). These various steps are represented in Fig. 8 which gives some partial results of the procedure. Modeling of the wear process of cutting tools is now under investigation to open the possibility of prognosis and therefore solve the problem of predictive maintenance of tools.

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