Operation Reliability Assessment Based on Running Condition Information for Large Machinery

Abstract

Listen

Translate article

Traditional reliability assessment methods predominantly based on probability and statistical theories need a large sample size to get the general, overall estimates for the identical units. However, the sample is often insufficient for large machinery, traditional reliability assessment methods became ineffective. More importantly, traditional reliability assessment cannot reflect the individuality of the running equipment. To overcome these deficiencies, a new approach based on running condition information to assess the operation reliability of large machinery is proposed. First, according to “short board effect”, the critical and weak component of the equipment is determined. Second, based on quantitative damage diagnosis, a mapping function called reliability membership function is built between equipment damage severity and a new reliability index which is defined as membership reliability. Third, quantitative damage diagnosis is employed to achieve the damage severity feature of the key component. Finally, by substituting the feature into the function, the value and change trend of the membership reliability is calculated and the equipment’s operation reliability assessment is gained. The application to the reliability assessment of the bearing for large machinery demonstrated the proposed method is reasonable and effective. Moreover, the proposed approach provides a new way to the operation reliability assessment for large machinery.