Fast Range Query of Fault Equipment Location Based on Breadth and Depth Ratio of the Binary Tree Model

The requirement for detecting faulty equipment is widespread in the industry. In today's big data era, using big data features to detect equipment is facing new opportunities and challenges. In order to improve the efficiency of faulty equipment detection, we found the characteristics of the binary tree that are suitable for manufacturing processes of the current status. In practice, this paper establishes a binary tree model for the manufacturing process. Then, in order to analyze and study the breadth traversal process and depth traversal process of bad nodes in binary tree, this paper proposes a location method of breadth and depth ratio. Finally, the location range of the faulty equipment (bad node) is quickly found due to the influence of breadth and depth ratio. The experimental results show the difference between the existing mechanisms of detection and position. In terms of accuracy and efficiency, both methods of deep traversal and breadth traversal have their own advantages in different devices and processes. To compare with the two methods, the detection method of breadth and depth ratio in this paper has the characteristics of higher efficiency, feasibility and accuracy.