An expert-based method for the risk analysis of functional failures in the fracturing system of unconventional natural gas

This paper proposes an expert-based method to analyze functional failure risk in the fracturing system of unconventional natural gas. The newly proposed Fuzzy-FFIP method integrates functional failure identification and propagation (FFIP) with fuzzy logic. Fuzzy-FFIP is sufficient for dealing with the complexity and correlation of functional failures and the lack of failure data, as well as capturing the fuzziness of functional states of a critical component and entire system. From a configuration-behavior-function aspect, FFIP is a common framework used to represent system-wide logical relationships and study functional failure propagation paths. This framework is an expert system where knowledge base and inference engine are based on behavioral rules (BRs) and functional failure logic (FFL), respectively. Using FFL as a support, fuzzy logic is specifically applied to analyze the fuzzification and defuzzification of functional states – operating, degraded, and lost. The proposed method can clearly provide functional failure modes, effectively reveal failure propagation paths, and quantitatively assess functional failure risk levels in the fracturing system. To illustrate its validity, an on-site pump lubricant subsystem of fracturing unit is selected as a test case. Results show that Fuzzy-FFIP is more detailed and accurate, and contributes to system safety during the whole fracturing period.