Automated system for monitoring and predicting the state of photoelectronic separators complex for processing agricultural raw materials

The paper proposes an automated procedure for assessing the actual state of photoelectronic separators in real time. Random process outliers over tolerance zones are proposed as the main controlled parameter. In contrast to traditional methods, several threshold levels are used to provide the flexibility of control and forecasting. Measurement of the amplitude and duration of the outliers of random processes over the tolerance zones helps to collect statistical samples, which become the basis for statistical models in the form of distribution law. The automated system makes it possible to identify the distribution law by classical methods if the samples are of sufficient statistical volume.