Design and Application of Intelligent Diagnosis Model Based on Data Driven

In this paper, an intelligent diagnosis model is designed based on stress wave technology. The model includes two parts: primary diagnosis and advanced diagnosis. The primary diagnosis model mainly uses the K-Means algorithm to realize the function of automatic hierarchical warning. After the hierarchical warning is triggered, the advanced diagnostic model obtains multiple sets of spectrum data through systematic sampling, and uses the enumeration algorithm to select the most representative one from it to achieve automatic output of fault information and alarm functions. The intelligent diagnosis model is applied to the axial flow fan. The output of the model is the same as the analysis result of the professional, indicating that the model is well applied to the axial flow extension.