Abstract: A method of monitoring and/or controlling machining plans having time-dependent machining parameters includes measuring desired time-dependent machining parameters as a measured curve, generating time-independent numerical values from the measured machining parameters, and entering the time-independent numerical values into a classifier distinguishing between normal states of the machining plant and abnormal states of the machining plant. Training vectors regarded as abnormal can be filtered out from training vectors available by determining a distance of each training vector from every other training vector with a selected measure of distance for filtering of the abnormal training vectors, the training vectors having components made of time-independent numerical values, and the classifier can be trained with training vectors.

Abstract: In an apparatus and a method for detecting and assessing a spatially discrete dot pattern disposed in a multidimensional coordinate system, each dot in the pattern assumes at least two differentiatable status values. A measuring device records the coordinate values and status values of each dot of the multidimensional spatial dot pattern. A memory stores data that correspond to the recorded coordinate values and status values of each dot of the multidimensional spatial dot pattern. A computer into which the stored data are entered and in which a coordinate counter for each coordinate value of a coordinate axis is determined from the stored data, is associated with the memory. The value of the coordinate counter is formed from the number of detected dots of the coordinates that have a predetermined status value. A neural network is associated with the computer.