The invention relates to a
rotary machine composite fault detection method and
system under a time-varying working condition, and belongs to the technical field of
rotary machine fault diagnosis. The method comprises the steps of collecting a non-stationary vibration
signal under a variable speed working condition, fusing a third-order Renyi entropy and
kinematics prior to construct an adaptive time-frequency enhancement model, and outputting weighted time-frequency distribution;
global optimization is carried out through a priori constraint
Viterbi algorithm, and an instantaneous frequency
ridge line is extracted under the condition of no rotating speed sensor; performing angular domain
resampling by taking the
ridge line as a phase reference, and converting a non-stationary
signal into an angular domain stationary
signal; constructing an extended difference mode
decomposition convex optimization model, and iteratively solving an optimal difference spectrum; and determining a
frequency spectrum segmentation threshold value based on self-
adaptive change point analysis, performing decoupling separation and
time domain reconstruction on the optimal difference spectrum, and completing composite fault diagnosis through feature comparison. The method does not need an external
tachometer, can adaptively extract and separate the composite fault features under the variable speed working condition, is high in diagnosis accuracy, and is good in
engineering application value.