Improved System Based on ANFIS for Determining the Degree of Polymerization

Abstract

Transformer health assessment techniques, based on applicable standards, such as the dissolved gas analysis (DGA), through laboratory testing or online monitoring are used to analyze the symptoms of a failure which develops in transformers from an early stage. The DGA from a sample of dielectric liquid taken from the main tank generates information on the state of degradation of the active part. It was found that of all the furan derivatives which result from the degradation of insulation, 2-furfuraldehyde (2-FAL) is the only derivative which dissipates in large quantities in oil. Because of this, and due to its thermal stability as compared to other derivatives, 2-FAL is the best unit of measurement to determine and monitor the degree of polymerization (DP) of insulation. The poor accessibility of paper samples has led to difficulties in testing the ageing state of paper directly by measuring the tensile strength and the DP. It was developed methods to indirectly assess the ageing state of paper, by means of the chemical markers in oil which are associated with paper ageing. This article presents a method to determine the DP of solid insulation in transformers, which provides a faster and more accurate interpretation, as compared to the classical ones. The 2-FAL data resulting from the lab are recorded in a MySQL database, which is embedded in an intelligent system for diagnosis of DP (ISDDP) based on Adaptive Neuro-Fuzzy Inference System (ANFIS), generating at the output the report with the interpretation of the faults as word files. The automation of the DP diagnostic process will be achieved, allowing the operator to make timely decisions, to avoid any possible damages.

Control of PMSM Based on Switched Systems and Field-Oriented Control Strategy

“…Theorem 1. Given the system (15) and assuming that there is a positive definite matrix P so that the following relation is satisfied,…”

“…then the global asymptotic stability of the switched systems (15) is ensured for the switching signal σ and in addition the following inequality is fulfilled:…”

“…Different types of control systems can provide high performance, but variable costs of implementation in embedded systems have been developed and implemented in a particular manner depending on the applications and requirements of the PMSM control system. Thus, one can mention adaptive [9,10], predictive [11,12], and sliding mode control (SMC) [13,14], as well as neuro-fuzzy [15,16] and computational intelligence-based control systems [17,18].…”