Cluster Migration Distance for Performance Degradation Assessment of Water Pump Bearings

Abstract

Because the signal of water pump bearing is seriously disturbed by noise and the fault evolution is complex, it is difficult to describe the performance degradation trend of water pump bearing in a timely and accurate manner using the traditional performance degradation index (PDI). In this paper, a new Cluster Migration Distance (CMD) algorithm is proposed. The extraction of the indicator includes the following four steps: First, the relevant blind separation is used to extract the useful signal of the monitored bearing from the mixed signal; secondly, the impact component is further enhanced by wavelet packet analysis. Then, the redundancy of the original feature vectors is eliminated using our previously proposed KJADE (Kernel Joint Approximate Diagonalization of Eigen-matrices) method. Finally, the newly proposed CMD index is computed as PDI. By calculating the offset trajectory of the feature cluster centroid in the continuous running process of the bearing, CMD can aptly deal with the complex and variable features in the fault evolution process of the water pump bearing. The whole-life monitoring data of a 220 KW water pump system are processed. The results show that the proposed CMD index has better early-warning ability and monotonicity than the traditional kurtosis index.

Editorial for Special Issue: Machine Health Monitoring and Fault Diagnosis Techniques

“…The theme of this Special Issue focuses on machine health monitoring and fault diagnosis techniques, especially intelligent fault diagnosis. This Special Issue highlights 18 articles that can be divided into four categories: condition monitoring [ 1 , 2 , 3 , 4 ], degradation process prediction [ 5 , 6 , 7 , 8 ], intelligent diagnostic algorithms [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ], and sensor fault detection [ 16 , 17 , 18 ]. In addition to the traditional bearing vibration signals, the research objects include the electrode signals, blade vibration signals, diesel engine vibration signals, and bearing heat signals.…”

“…In [ 6 ], a new cluster migration distance (CMD) algorithm was proposed to address the problem in which traditional performance degradation indicators cannot accurately describe degradation trending on time. By calculating the offset trajectory of a feature cluster centroid in a continuous bearing running process, the CMD can appropriately handle the complex and variable features in the fault evolution process of a water pump bearing.…”