A particle filter driven dynamic Gaussian mixture model approach for complex process monitoring and fault diagnosis

► A particle filter driven dynamic Gaussian mixture model is developed. ► Particle filtered Bayesian inference probability index for fault detection. ► Particle filtered Bayesian contribution decomposition for fault diagnosis. ► Superior capability in handling dynamic operating scenario changes in processes.