RESUMO
In the paper the authors present the procedure of measuring vibration and obtained data accruing in a bucket wheel excavator's operator cabin. Details of the selection and location of the measuring points are firstly given. In the following part, the example of for the bucket wheel excavator SchRs 1200, will be presented. This machine is in use at one of Poland's open cast mins. The operating conditions are briefly characterized in the descriptions of the measurement series. The measuring equipment is also presented. The recorded data are presented in two ways. The first of the presents time waveforms for each measuring channel. The second one presents Fast Fourier Transform (FFT) spectrums after filtering the measured signals. The obtained data is used to develop a vibrations control algorithm.
RESUMO
A novel approach toward neural networks modeling is presented in the paper. It is unique in the fact that allows nets' weights to change according to changes of some environmental factors even after completing the learning process. The models of context-dependent (cd) neuron, one- and multilayer feedforward net are presented, with basic learning algorithms and examples of functioning. The Vapnik-Chervonenkis (VC) dimension of a cd neuron is derived, as well as VC dimension of multilayer feedforward nets. Cd nets' properties are discussed and compared with the properties of traditional nets. Possibilities of applications to classification and control problems are also outlined and an example presented.
