A novel layered fuzzy Petri nets modelling and reasoning method for process equipment failure risk assessment

The continuous and stable operations of equipment are the crucial factor for the safety of process industries. Risk assessment has demonstrated its capabilities as a practical method to analyze and prevent process equipment failure. Since the status of equipment is mainly determined by its components and the coupling relationship is complex, a systematical and practicable method is needed to help risk assessment. Petri nets provide a graphical and mathematical representation for risk modelling and reasoning. With the complexity of equipment, there could be lots of diagnosis rules, which makes the network complicated and huge. In order to describe the coupling relationship clearly and make the computational process flexible, a layered Petri nets method is presented in this context to conduct complex rule-based risk analysis and assessment. Moreover, The fuzzy logic is introduced to represent expert knowledge in a semi-quantitative way. The method presented was applied for assessing the risk of reciprocating compressor failure, which is the supercharging equipment widely used in the natural gas transportation process.