Heterogeneous information fusion has long been a difficult problem due to the differences in the representation and feature of various physical information. Besides, the multisensor signals of large mechanical equipment,… Click to show full abstract
Heterogeneous information fusion has long been a difficult problem due to the differences in the representation and feature of various physical information. Besides, the multisensor signals of large mechanical equipment, such as aerospace engines, often change in a complicated way during the start-up stage and long-term operation, which makes the multisensor fusion-based health assessment research impending. To explore a suitable fusion method for multiphysical signals with different change rates and to monitor the health state of large mechanical equipment based on multisensor information, this article proposes a heterogeneous time-tracking fusion algorithm. First, the time-domain indexes and instantaneous frequencies of the fast-varying harmonic-like signals are obtained by employing index extraction and second-order synchrosqueezing transform, respectively, by which the overall and detailed characteristics of the signals are thus obtained. Second, after structuring a dynamic time-tracking function consisting of the hyperbolic tangent function and modified arctangent function, the time-dynamic confidence upper limit for fast-varying signals and the confidence interval for slow-varying signals are obtained creatively. Finally, the different varying-rate signals are fused into a dynamic normalized time-varying index representing the health state through the aforementioned functions. By applying the proposed method to the health evaluation for ignition start-up stage of gas generators and the long-term performance of the turbopump, its effectiveness and practicability in the aerospace engine health analysis have been validated.
               
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