Oil Detection Fault Tree Analysis Based on Improved Expert’s Own Weight–Aggregate Fuzzy Number

Oil detection technology improves the reliability of machinery or equipment. The physical and chemical indicators fluid can reflect cause failure in various aspects, which prevent major accidents to greatest extent by setting up a fault tree. Owing lack data, it is difficult accurately obtain basic event probabilities, makes diagnose faults. expert evaluation method aggregated fuzzy numbers are used exact probability, where probability evaluated as subjective will expert. To improve probabilistic accuracy, weights improved combined assignment well reasonableness analysis. A tree diagnostic model constructed for qualitative quantitative analysis, taking ship engine oil viscosity high an example. According results, provide comprehensive analysis indicators. Experts’ own have large impact on with their weight changes leading change ranking. From discrimination, following Bland–Altman selected empowerment discrimination results 4.8% compared traditional method, 100% data consistency, proved that improvement was reliable effective. structure this diagnosis clear, quickly give reference value.