Abstract: Phased array ultrasonic technology is one of the key research directions in the field of nondestructive testing in recent years and has made rapid development, among which defect recognition and classification based on ultrasonic phased array imaging is one of the research hotspots. This paper summarized the basic principles of ultrasonic phased array nondestructive testing and introduced representative defect recognition and classification algorithms, including support vector machines, artificial neural networks, genetic algorithms, neural evolutionary algorithms, and algorithms based on deep learning. Finally, it pointed out the challenges of existing defect recognition and classification algorithms and put forward the development direction of ultrasonic phased array defect recognition and classification.