To address the challenges of fault location in mining cables caused by short lengths and multi-level radial structure

a fault section location method for coal mine power grid lines based on deviation-guided global search rules is proposed. First

a mathematical model incorporating switch functions and deviation is established based on the grid topology to describe the fault status of mining cable sections. Subsequently

an adaptive ant colony optimization algorithm is introduced to identify suspicious paths

reducing the search space dimension and enhancing fault section location efficiency. Thus

the deviation-based search rules are applied to achieve accurate fault section identification in coal mine power grid lines. Simulation tests are conducted on typical dual-source power supply network topologies in coal mines finally. The results demonstrate that accurate fault section location can be achieved for both single-source and dual-source radial networks under single-point and multi-point faults. Furthermore

the proposed method is compared with particle swarm optimization

genetic algorithms

conventional ant colony optimization

improved ant colony optimization

and immune binary particle swarm optimization in terms of accuracy. The results demonstrate that the proposed method achieves the highest accuracy and exhibits superior stability among all six methods.