Research on Reliability Prediction Method of Compressor for Gas Transmission Pipeline Based on Machine Learning

Reliability calculation models based on machine learning can adaptively implement reliability analyses by combining computer technology and actual field data, improving efficiency and reducing costs. This paper analyses the failure data of S pipeline compressor sets, selects the characteristic variables of the prediction model, compares the prediction performance of the model under different combination algorithms, and finally implements the reliability calculation of the compressor by combining with the Monte Carlo method, and verifies the feasibility of the proposed method with an example. The study helps managers identify potential compressor failures and improve compressor and unit reliability promptly.