Gas turbine reliability estimation to reduce the risk of failure occurrence with a comparative study between the two-parameter Weibull distribution and a new modified Weibull distribution

Abstract

Responding to the needs of quality and robustness of analysis and management of degradation of equipment, to increase their life cycle and to expand these facilities to become more and more sophisticated and agronomic. This work proposes a contribution to increase the survival of a gas turbine, installed in a gascompression plant, with a comparative study between the two-parameter Weibull distribution. A new modified Weibull distribution was proposed also to reduce the risk of occurrence of failure in this rotating machine. A Statistical analysis and validation on the synthesis of turbine's reliability data and failures were considered, with a particular focus on the use of this data to increase the availability of this type of machine. So, developing a maintenance plan based on their reliability indices for scheduled inspections

ARMAX-based identification and diagnosis of vibration behavior of gas turbine bearings

“…Nadji Hadroug et al [21] studied the modeling of reliability and availability indices of a gas turbine using an adaptive neuro-fuzzy inference representation. Ahmed Zohair Djeddi et al [2] estimated the reliability of a gas turbine by minimizing the risk of failures and conducted a comparative study between usual reliability distributions. Ahmed Zohair Djeddi et al [3] improved the availability and maintainability of a gas turbine using long-term memory networks based on deep learning and exploiting failure data.…”