A GA based optimized designation of detection sensor for broken steel stranded wire faults in ACSR

Steel stranded wire plays a supportive role for aluminum conductor steel-reinforced (ACSR), so that detection for broken strand of steel core is an important mean to insure safety operation of transmission lines. A detection sensor based on leakage magnetic flux (LMF) theory for broken strand of steel core in ACSR is developed by this paper, and the size of the detector is optimized by the modified niche adaptive genetic algorithm correspondingly. The detector can be carried by inspection robot to examine the conductors along overhead transmission lines. In the proposed detection scheme, the steel core in ACSR can be magnetized by 48H# Rb-Fe-B rare earth permanent magnet. Optimization design model is proposed, achieving minimal weight of detector is selected as the object function. Theoretical analysis and application results show that the proposed optimization method has a great ability of local searching and convergence rate, the design magnetization requirement is satisfied and the weight of detector is decreased, then the carrying capability of inspection robot is improved.