Intelligent Fault Diagnosis Algorithm for Mechanical and Electronic Systems Based on Structured Light Data

In the current era of rapid technological development, modern mechanical equipment systems continue to move towards automation and intelligence, which puts higher demands on the technical performance of various aspects of the system. Structured light 3D intelligent cameras have been widely used in many fields such as artificial intelligence (AI) and industrial inspection due to their significant advantages of fast imaging speed and high accuracy. Structured light measurement is the process of measuring from multiple angles using a structured light measurement system to achieve a complete representation of the object being measured. However, the stitching of measurement data from multiple perspectives can have an impact on the completeness of the expression of the measured object. This article innovatively proposes an intelligent fault diagnosis algorithm for mechanical and electronic systems that combines deep learning (DL) technology. The algorithm deeply explores the feature information in structured light data and utilizes the powerful pattern recognition ability of DL to achieve accurate diagnosis of mechanical and electronic system faults. The results show that the algorithm proposed in this paper can effectively improve the efficiency and accuracy of fault diagnosis, providing strong support for ensuring the stable operation of mechanical and electronic systems.