Mining machinery and equipment used in modern mining are equipped with sensors and measurement systems at the stage of their production. Measuring devices are most often components of a control system or a machine performance monitoring system. In the case of headers, the primary task of these systems is to ensure safe operation and to monitor its correctness. It is customary to collect information in very large databases and analyze it when a failure occurs. Data mining methods allow for analysis to be made during the operation of machinery and mining equipment, thanks to which it is possible to determine not only their technical condition but also the causes of any changes that have occurred. The purpose of this work is to present a method for discovering missing information based on other available parameters, which facilitates the subsequent analysis of machine performance. The primary data used in this paper are the currents flowing through the windings of four header motors. In the method, the original reconstruction of the data layout was performed using the R language function, and then the analysis of the operating states of the header was performed based on these data. Based on the rules used and determined in the analysis, the percentage structure of machine operation states was obtained, which allows for additional reporting and verification of parts of the process.