Optimal Pressure Matching in Self-Excited Oscillation Cavities with Image Grayscale Analysis and Fast Fourier Transform

Industrial processes, including textile and paper manufacturing, generate substantial quantities of toxic dyes, such as methylene blue (MB), which pose severe environmental risks. Conventional wastewater treatment methods are frequently ineffective in removing these persistent pollutants and demand large volumes of chemicals. Hydrodynamic cavitation-based advanced oxidation presents an efficient, chemical-free alternative for dye degradation. This study explores cavitation dynamics and MB degradation in a self-excited oscillation cavity (SEOC) using simulated wastewater, and introduces a non-intrusive method called "resonant cavitation collapse", which combines high-speed image grayscale analysis with Fast Fourier Transform (FFT) to quantify cavitation intensity. A standardized procedure has been established to rapidly determine the optimal operating pressure for SEOCs, and was successfully used to predict the optimal pressure for another SEOC in a shorter time. In the first SEOC, when the pressure does not exceed 0.4 MPa, critical and partial cavitation occur, and a peak MB degradation efficiency of 44.44% is achieved at 0.3 MPa. When the pressure is above 0.5 MPa, super cavitation develops, and the maximum efficiency is reduced to 38.9%. These results indicate that the vapor volume fraction in SEOCs is not a reliable indicator of cavitation performance. The method proposed in this study provides a rapid and intuitive approach for matching the optimal operating pressure with a specific SEOC configuration, thus reducing the reliance on time- and resource-consuming trial-and-error experiments and facilitating more efficient and sustainable process optimization.