The groove of ultra-narrow gap welding is narrow and deep, so it is difficult to evaluate the welding quality directly through vision. To solve the above problems, this paper proposed an ultra-narrow gap welding quality evaluation model based on chaotic multistrategy disturbed sparrow search algorithm ( CMDSSA) to optimize support vector machine ( SVM). Firstly, the sparrow search algorithm ( SSA) is improved, and the Logistic-Tent chaotic mapping and multi-disturbance strategy are introduced to improve the optimization performance of the sparrow search algorithm. Then, the superiority of CMDSSA algorithm is verified by comparing with SSA, CSSOA, PSO, GA and WOA algorithms. Finally, CMDSSA was used to optimize the penalty factor C and the kernel parameter g of SVM, and a CMDSSA-SVM quality evaluation model was constructed to evaluate the welding quality. The results show that the evaluation accuracy of CMDSSA-SVM is 97. 541%, which verifies the high accuracy and feasibility of the proposed method for ultranarrow gap welding quality evaluation.