Time–Frequency Analysis Methods for Analyzing Jet Characteristics of dc Arc Plasma Torch

dc plasma jets are widely used in thermal spraying and materials processing due to their advantages of high temperature, low operating cost, and strong environmental adaptability. As the demand for product quality and process stability continues to increase, the stability of plasma jets has become an increasingly critical research topic. However, traditional approaches that evaluate jet characteristics using arc-voltage fluctuations or raw voltage signals, which are highly susceptible to noise in high voltage and strong electromagnetic environments, result in limited low assessment accuracy. For improving the assessment accuracy, based on a self-developed dc arc plasma generating system and jet characteristics monitoring system, a method of filtering the noise by finding the characteristic frequency with the fast Fourier transform (FFT) theory was proposed. By analyzing the time-frequency of the original signals of arc voltage, arc current, and gas flow rate based on the FFT theory, the characteristic frequency was determined, and the noise was filtered to purify the corresponding signals. With the purified signals, the jet stability could be evaluated more accurately. The research results show that the characteristic frequencies of the signals are always in 5–45- and 125–155-Hz bands. By analyzing the characteristics frequencies under various working conditions, the characteristic frequency could be predicted by using a polynomial fitting equation. This method enables rapid extraction of characteristic components and effective noise suppression, providing a robust tool for accurate diagnostics and stability assessment of plasma jets.