The increasing application of ultrasonic phased array technology for detecting defects in pipelines and plates highlights the importance of imaging algorithms for enhancing defect imaging quality. Building on the fully focused imaging (TFM) approach, the phase coherent imaging (PCI) algorithm is introduced in this study, which substantially improves the signal-to-noise ratio and lateral resolution of defect imaging by refining phase information processing and incorporating phase weighting. To further address challenges in defect classification accuracy and efficiency, a PCI-support vector machine (PCI-SVM) system is developed using the SVM algorithm. By optimizing the parameters and adjusting the model, the system automatically classifies pitting and crack defects with a classification accuracy of 94.6%. The experimental results demonstrate that the PCI-SVM system improves both defect detection accuracy and operational efficiency, offering a new and effective solution for industrial nondestructive testing. This study provides a theoretical foundation and practical guidance for advancing and optimizing ultrasonic phased array technology in real-world applications.