Use of a Duffing chaotic oscillator with nonlinear stochastic resonance to retrieve faulty power equipment records

Abstract Fault detection becomes especially crucial for maintaining the dependability and safety of power equipment as power systems become more complicated. This work aims to increase the accuracy and efficiency of fault signal identification in power equipment by proposing a method based on nonlinear stochastic resonance and a Duffing chaotic oscillator to detect weak signals in power systems. First, this study develops a weak signal detection model based on the Duffing chaotic oscillator approach. By modifying the system parameters to put the signal in a critical condition, the model greatly increases the sensitivity of the signal to the tiny periodic sinusoidal waveforms. In the meantime, the stochastic resonance method’s high resistance to noise interference improves the dependability of signal identification. The experimental results demonstrate that the approach is more accurate and stable than the conventional method and can extract fault signal features when working with weak signals in high noise conditions. Ultimately, this paper’s research offers a fresh, efficient method for identifying power system faults.