The invention discloses a cost-sensitive support vector machine locomotive wheel detecting system and a detecting method thereof. The system comprises a data preprocessing module, a cost-sensitive support vector machine training module, a parameter optimizing module, an optimal cost-sensitive support vector machine classifying module, a determining module and a wheel state output module. The detecting method comprises eight steps totally. The parameter optimizing step is an adaptive mutation particle swarm optimization algorithm and has advantages of high robustness, global searching characteristic, etc. A space which continuously reduces in iteration is enlarged, and searching is performed in a larger space. Furthermore high population diversity is kept. Additionally, a possibility of finding out an optimal value by the algorithm is improved.