Enterprise AI Analysis

Real-World Application in Coal Mining: Enhanced Safety & Efficiency

Problem: Power supply lines for coal shearers in mining operations are subjected to extreme conditions, leading to frequent faults. Nonlinear loads, power electronic noise, and physical deformations of cables (coiling, winding) obscure faint transient fault signals, making traditional detection methods unreliable. This poses significant risks to operational continuity and worker safety.

Solution: The PIO-VMD-EDO method was rigorously validated on a sophisticated simulation model of a long-distance coal shearer power supply system, incorporating actual noise characteristics. Further, its effectiveness was confirmed on a physical cable fault location experimental platform.

Results: The method demonstrated superior performance, achieving a maximum relative error of less than 2.5%—significantly outperforming DWT, CWT, HHT, and EMD. Crucially, its accuracy remained robust across varying fault conditions, high noise interference, and diverse sampling rates. On the experimental platform, it enabled precise fault pinpointing.

Impact: This innovative approach delivers highly reliable and accurate fault location in coal mine power grids, directly translating to reduced downtime, improved operational safety, and more efficient maintenance. It is particularly well-suited for industrial environments characterized by complex nonlinear loads and extensive power electronic equipment.