Fuzzy logic methodology to study the behavior of energy transformation processes based on statistics T² and Q

In the processes of energy transformation, to carry out an adequate follow-up of the process parameters represent an opportunity to propose strategies to improve the processes' performance. For this reason, it is essential to analyze the behavior of process variables under the quantitative and qualitative optics supported by the experts. Thus, this work proposes a methodology of fuzzy Mandani type logic that allows the analysis of energy transformation processes (such as internal combustion engines) based on T² and Q statistics, as a way to identify whether the operation limits are kept within the normal or exceed the limits, achieving to identify the anomaly in the process. In the initial stage, MATLAB implements two diffuse systems; the first system aims to determine the impact variables have on the generation of an anomaly, without identifying the type of defect. In the second stage, it's defined as a function of the number guests, the kind of monster that occurs in the observations made from the transition range in the operation of the system analyzed, until the last measurement obtained. In the third stage, the statistics T², Q, and its limits are determined from the operating variables of the selected system. Finally, the previously calculated statistics are graphically processed in the diffuse systems. The results obtained in this work show that the analysis of processes or phenomena based on qualitative observations, the methodology implemented, is a useful tool for decision making in the industrial sector.