Adaptive Faults Diagnosis and Reasoning Method Based on MFM

Multilevel Flow Modeling (MFM) is an abstract hierarchical model of the complex process industrial system based on the system goal
and the functional subject to achieve the goal. In a specific MFM model, there are two different modes of influence between function
and objectives. In the first mode, the failure of a component or function will immediately lead to the failure of the final objective, while the second mode is the opposite. Namely, the importance of sub-goals and components to the overall or specific goals is not same. In this paper, we purposed an adaptive fault diagnosis and reasoning method combining MFM and improved Analytic Hierarchy Process (AHP) . Firstly, the MFM model is established, which already has the function of preliminary fault diagnosis according to the signal and process parameters. Secondly, the improved AHP algorithm is introduced to calculate the weights of components and functions under typical failures. Finally, the importance of components and functions are sorted, and the MFM modeling method expands the ability of quantitative analysis, which is of great significance for assisting faults diagnosis and risk management. To better illustrate the structure and execution process of the proposed method, a case study on a lubrication system of a plunger pump is analyzed and displayed, which verifies the feasibility of this method for fault diagnosis and quantitative evaluation.