Study of Fault Identification of Clearance in Cam Mechanism

Abstract

The clearance between the main roller and the cylinder cam has an important impact on the operational status of the bolt. In order to achieve the clearance and recoil of the cylinder cam mechanism, a bolt model was built and studied. The leading dynamic roller group and the dynamic bolt were analyzed. Positive stress and friction force change quickly on the high-speed leading roller group, influencing multiple aspects. When the main roller suddenly rotates or reverses in several short intervals, the assembling clearance and the massive friction force between the main roller and the cam curve slot are the main wear factors in theoretical analysis and test experiments. The leading roller group, the pure rolling criterion of the cylindrical cam mechanism of the automaton, is derived in this paper. Moreover, a new fault diagnosis method is developed, based on the Variational Box Dimension Kernel Fuzzy Mean Clustering Algorithm (VK) algorithm, which combines the variational mode decomposition and fractal box-counting dimension (VMD-FBCD) and the fuzzy clustering algorithms with a kernelized Mahalanobis distance (KMD-FC). With the simulation validation from 2810 samples, diagnosis using the VK algorithm is found to have a higher accuracy rate and slightly lower fallacy rate and to be faster than other diagnostic methods of similar studies. The results in terms of the recoil cylinder cam mechanism’s multi-body dynamic analysis and high-speed fault identification also have significance as a reference for solving similar problems.