Detection of FM transmitter device malfunctions with artificial neural networks

This study is about detecting FM transmitter device malfunctions using artificial neural networks, which are highly popular today. Artificial neural networks are the modeling process of biological neural networks with mathematical formulas, which emerged in the 1940s. This method, used in many areas, provides safe results in solving complex problems. In this study conducted with Artificial Neural Networks (ANN), which has both advantages and disadvantages, the parameters of an FM transmitter, which is an electronic device, were used. The data set was tested with ANN models included in the MATLAB program and the method that gave the best results was found. We are looking for the answer to the question of whether it is a method that can be used to detect electronic device malfunctions. The FM transmitter consists of two parts. These; Exciter and Amplifier. As Exciter; A device named AFM-30, produced by İDİL electronic company, was used. In this study, the detection of malfunctions that occurred and may occur in the Exciter unit was carried out using Artificial neural network models. In the artificial neural network architecture, it is possible to produce 3 output data, encoded using the binary number system, in response to 12 input data. In this thesis, what an amplifier is is mentioned, but details are not given because it is off-topic. In today's world, where different methods and techniques are being tried to be found, considering the development of technology in addition to primitive methods, we can say that malfunctions can be detected with ANN, which is another method.