Deformation Transfer Characteristics of Vacuum Chamber Structures under Complex Loading Conditions

Gravitational waves, as predicted by Einstein's General Relativity, are spacetime disturbances that hold significant scientific value for exploring the evolution of compact celestial bodies and the structure of the early universe. Modern gravitational wave detectors utilize laser interferometry with micrometer-scale measurement techniques to monitor tiny displacements of freely suspended test masses. Space gravitational wave detection missions, such as the Laser Interferometer Space Antenna (LISA), require maintaining the stability of the inertial sensor core within an ultra-high vacuum (UHV) chamber to capture low-frequency gravitational wave signals. Due to the complex mechanical loads experienced by the bolted connections of the chamber, structural coupling generates gradient deformation leading to phase noise on the optical reference surface, thereby affecting the detection sensitivity of the gravitational wave signals. Hence, it is essential to measure the deformation in this region. Traditional intrusive detection methods compromise vacuum integrity, which this article addresses by proposing a non-contact inversion method based on the deformation transfer theory. By establishing a viscoelastic finite element model of the vacuum chamber and combining parametric load analysis, the deformation patterns of the bolted connection regions are revealed, enabling the construction of mathematical mappings between internal and external displacement fields. The results indicate that the deformation within the chamber generates linear gradient deformation in external components through mechanical coupling, with total displacements and vertical transfer rates of 31.5% and 26.7%, respectively, and an inversion error of less than 1%. This method effectively overcomes the technical limitations of traditional intrusive detection, achieving non-contact internal state inversion based on external displacements. It provides a theoretical basis for optimizing the stability and lifespan prediction of inertial sensors, making it applicable to the health monitoring of high-precision encapsulated sensors in the aerospace field.