Fault diagnosis of pile machine based on improved artificial bee colony and K-means clustering algorithm

Aiming at the problem of pile machinery fault diagnosis, a fault diagnosis algorithm based on improved artificial bee colony and K-means clustering(IABC-K) is proposed. Firstly, the normalization method is used to preprocess the original fault data; Secondly, the artificial bee colony (ABC) algorithm is used to optimize the K-means clustering, which is affected by the initial clustering center, and cluster the characteristic parameters; Finally, the clustering and diagnosis results are analyzed. The results show that this method can effectively identify the fault type of pile driver and improve the efficiency of fault diagnosis of pile machinery.