Slurry pumps constitute critical equipment in mining and metallurgical industries, where impeller wear critically compromises operational efficiency and safety. To overcome the inadequacies in early fault detection and significant noise susceptibility in complex operating environments, this study proposes a novel diagnostic method integrating Theil-entropy-impact energy fusion with linear frequency modulation optimization. First, a fused Theil entropy-impact energy feature index is constructed, capturing impeller wear-induced cyclostationary patterns and transient impacts through frequency-domain synergy. Second, an optimized spectral estimation method based on the Chirp Z-Transform is designed, enabling high-precision fault frequency extraction with a limited number of sampling points. Finally, the effectiveness and accuracy of the proposed method were validated via simulated and industrial data, supplemented by a performance comparison of vibration and acoustic emission approaches. The proposed method provides a reference for monitoring the early wear state of slurry pump impellers.
Hou et al. (Sun,) studied this question.