A DSP-based diagnostic system for DC-DC converters using the shape of voltage across the magnetic components

Abstract

A new diagnostic method for the dc-dc converters is proposed in this paper. The shape of voltage across the magnetic component is used as the diagnostic criterion. The Fast Fourier Transform (FFT) is utilized to extract the features of the waveform and the neural network (NN) is applied to realize the state classification. The voltage sensor is needless because the required voltage signatures can be obtained easily by adding a winding in the magnetic component, or fixing a magnetic near field probe near the magnetic component. The diagnostic system is isolated from the power stage naturally; all the A/D conversion, FFT and NN are realized in a single DSP chip TMS320F2812; using the inner A/D channels of the DSP, up to sixteen dc-dc converters can be monitored synchronously. For the illustrative purpose, the diagnostic process of one A/D channel will be described in this paper and the phase shift full bridge (PSFB) converter is chosen as the diagnostic object. Based on the discussion, the proposed method can be easily extended to the other types of dc-dc converters.