399 / 2022-02-17 07:40:07

Impact load sparse recognition method based on MC penalty function

Rotating machinery;Impact load recognition model;Penalty function; Sparse decomposition

Machine condition monitoring and fault diagnosis

The rotor system is an important part of large-scale rotating machinery. Bearings, as a key component of the rotor system, play a vital role in the healthy operation of the rotor system. The bearings operate under harsh conditions such as high temperature, high pressure, and high speed. Complex and extremely prone to failure, especially when the bearing is affected by impact load, which seriously affects the remaining service life of the bearing. Therefore, the uneven bearing friction caused by the impact is one of the main factors for the premature failure of the bearing. Early identification Shock load and reasonable measures are extremely important to the safe operation of equipment. This paper proposes an impact load identification method based on the sparse decomposition of the Minimax Concave penalty function (Minimax Concave penalty function, MC). The method uses the MC penalty function to reconstruct the regularized sparse recognition model, and then uses the improved original dual interior point method to solve the problem. This model realizes the identification of vibration and shock loads. Relevant experimental verification is carried out, and the results show that the sparse decomposition result based on the MC penalty function is better than the L1 regularized sparse decomposition result, and the noise is well suppressed in the non-loaded area of the impact load. This method can be applied to the early fault diagnosis of the vibration signal of the gas turbine rotor.