Dynamic CUSUM Chart With an Integrated Indicator for Bearing Condition Monitoring

The operation status of bearings plays a critical role in mechanical systems. Current models for condition monitoring of bearings tend to overlook the complex properties of the process, including its non-Gaussian, nonlinear, and dynamic characteristics. To address these issues, this article proposes a novel approach for condition monitoring based on a novel dynamic cumulative sum (CUSUM) chart with an integrated indicator. The integrated indicator accounts for the non-Gaussian, nonlinearity, and dynamic properties of the process by utilizing optimal components that are decomposed via independent component analysis (ICA) and its extended versions. The developed dynamic CUSUM chart can adapt to the variation of the process. The proposed condition monitoring strategy is validated using the simulation and experiment data of bearings. Results demonstrate that the proposed method yields a significant improvement in hit rates (HIT) and a reduction in false alarms compared to conventional methods.