Neural Network Contour Error Predictor in CNC Control Systems

Paper presented as poster presentation at MMAR 2016 conference (Międzyzdroje,Poland, 29 Aug.-1 Sept. 2016)This article presents a method for predicting contour error using artificial neural networks. Contour error is defined as the minimum distance between actual position and reference toolpath and is commonly used to measure machining precision of Computerized Numerically Controlled (CNC) machine tools. Offline trained Nonlinear Autoregressive networks with exogenous inputs (NARX) are used to predict following error in each axis. These values and information about toolpath geometry obtained from the interpolator are then used to compute the contour error. The method used for effective off-line training of the dynamic recurrent NARX neural networks is presented. Tests are performed that verify the contour error prediction accuracy using a biaxial CNC machine in a real-time CNC control system. The presented neural network based contour error predictor was used in a predictive feedrate optimization algorithm with constrained contour error

Multifractal structure of turbulence in the magnetospheric cusp

Magnetospheric cusps are regions which are characterized by highly turbulent plasma. We have used Polar magnetic field data to study the structure of turbulence in the cusp region. The wavelet transform modulus maxima method (WTMM) has been applied to estimate the scaling exponent of the partition function and singularity spectra. Their features are similar to those found in the nonlinear multifractal systems. We have found that the scaling exponent does not allow one to conclude which intermittency model fits the experiment better. However, the singularity spectra reveal that different models can be ascribed to turbulence observed under various IMF conditions. For northward IMF conditions the turbulence is consistent with the multifractal <i>p</i>-model of fully developed fluid turbulence. For southward IMF experimental data agree with the model of non-fully developed Kolmogorov-like fluid turbulence

Breaking the Cycle of Pain In Diabetic Peripheral Neuropathy

An attitude of helplessness pervades both patients and health professionals when dealing with the problems of dia betic peripheral neuropathy. Those afflicted are often over whelmed by the pain and find themselves unable to fulfill the daily requirements of their diabetes regimen. The in consistencies in amounts and timing of meals, levels of ac tivity, and scheduling of insulin injections can result in hyperglycemia, a state that has been found to correlate strongly with the occurrence of nerve damage. Thus the pain perpetrates itself. For the health professional, having to confront this devastating pain without objective factors to assess and few scientific treatment measures to offer con tributes to a sense of inadequacy and ignorance. It is fre quently assumed that "nothing can be done." In reality, health professionals do have something to offer the person suffering from this condition. First, they can provide infor mation about the relationship between control and compli cations, and explain the need for the patient to change those behaviors that may be perpetuating the pain. Sec ond, and most importantly, health professionals can con vey support and confidence, without which many patients will be unable to make the changes in their behavior neces sary to resolve their pain.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68854/2/10.1177_014572178501100103.pd