This study focuses on the intelligent early warning model for variable operating conditions of the primary helium circulator, aiming to solve the problem of equipment vibration changes caused by process parameters changes during the operation of the primary helium circulator, which cannot be accurately and timely warned based on fixed threshold alarm methods. Based on the analysis of the failure modes of the primary helium circulator, a suitable feature parameters space is established. Through process parameters such as rotational speed, vibration time domain, frequency domain, and other state characteristic parameters, a multi-parameter fusion variable-condition intelligent early warning model is established with process parameters such as rotational speed as the operating condition variables. The application of experimental data verifies that the model can effectively identify early fault characteristics of equipment and provide early warnings, avoiding false alarms caused by changes in operating conditions.