Method for solving the nonlinear inverse problem in gas face seal diagnosis based on surrogate models

Abstract

Physical models carry quantitative and explainable expert knowledge. However, they have not been introduced into gas face seal diagnosis tasks because of the unacceptable computational cost of inferring the input fault parameters for the observed output or solving the inverse problem of the physical model. The presented work develops a surrogate-model-assisted method for solving the nonlinear inverse problem in limited physical model evaluations. The method prepares a small initial database on sites generated with a Latin hypercube design and then performs an iterative routine that benefits from the rapidity of the surrogate models and the reliability of the physical model. The method is validated on simulated and experimental cases. Results demonstrate that the method can effectively identify the parameters that induce the abnormal signal output with limited physical model evaluations. The presented work provides a quantitative, explainable, and feasible approach for identifying the cause of gas face seal contact. It is also applicable to mechanical devices that face similar difficulties.

Graphical abstract

Keywords

surrogate model / gas face seal / fault diagnosis / nonlinear dynamics / tribology

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Acknowledgements

This work was supported by the National Key R&D Program of China (Grant No. 2020YFB2010000) and the National Natural Science Foundation of China (Grant No. U1737209). None of the funding bodies influenced the study at any stage.

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