In order to ensure the quality and service life of mechanical parts, it is necessary to complete the machining defect identification of mechanical parts. Therefore, a method of machining defect identification of mechanical parts based on laser scanning imaging is proposed. The image acquisition module mainly takes laser scanning imaging system as the core to complete the imaging of mechanical parts. The difference algorithm and resolution generation adversarial network model are used to reconstruct the acquired images. The kernel principal component analysis method was used to extract the characteristic values of machining defect fringes in laser images, and the extracted results were input into support vector machine to identify machining defects of mechanical parts. The test results show that the method has the highest recognition accuracy of 97%, the lowest recognition error of 1%, and the fastest recognition efficiency of 3s. It can effectively deal with noise points in images, improve image clarity, and realize machining defect recognition of mechanical parts.