A case study on health prediction of an industrial diesel motor using particle filtering

In various industrial applications such as transport, automotive, marine, diesel motors are widely used. However diagnosing faults and/or predicting its future health condition of such motor still remains widely open due to its complexity from both structural and functional points of view. The paper presents a study on health state prediction of such industrial diesel motor. A particle filter-based prognostic is developed and applied from real recorded data with different measurements. The recorded data are firstly pre-processed, and health indicator is then chosen before implementing the proposed approach. The use and advantages of the proposed approach are then highlighted through the obtained results.