The mechanical arm components generally have high working strength and are prone to various defects. If they are not found and handled in time, their working quality will be easily affected. Therefore, it is very necessary to detect the defects of mechanical arm components. Under this background, a defect detection method of mechanical arm components based on triangular laser is studied. In this study, the triangular laser method is used to scan the mechanical arm components to obtain the component image and carry out the graying and denoising processing. The corner feature of the image is extracted by USAN method and two texture features are extracted by gray level co-occurrence matrix. The feature parameters are normalized and fuzzed, and the defect type is determined by calculating the proximity degree to complete the defect detection of the mechanical arm components. The results show that under the application of the method, the under-segmentation rate is the smallest, which shows that the research is more effective for the defects of the mechanical arm components, and the detection accuracy of the method is higher.