A Pump Fault Warning Algorithm Based on Improved PCA-KNN

In the industrial field, Water pumps are key equipment for fluid transportation in the industrial field, and the fault warning of water pumps is of great significance for ensuring the continuity and safety of production. This article proposes a pump fault warning method based on improved principal component analysis (PCA) and K-nearest neighbor (KNN) algorithm. Firstly, by improving PCA for dimensionality reduction of water pump operation data, the main features are effectively extracted to reduce data redundancy. Subsequently, the KNN algorithm was used to classify the reduced dimensional data for identifying fault states. The experimental results show that this method has significant advantages in both accuracy and response speed of fault detection, and can warn potential faults timely, reduce downtime and maintenance costs. The method presented in this article provides an effective approach for water pump fault warning and has promising application prospects.