Efficient Bayesian framework for multi-type sensor placement optimization based on posterior uncertainty minimization

Ce Huang

doi:10.1016/j.jsv.2026.120098

Efficient Bayesian framework for multi-type sensor placement optimization based on posterior uncertainty minimization

2026-09-02

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DOI：10.1016/j.jsv.2026.120098

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• Bayesian multi-type sensor placement driven by operational load statistics. • Load prior regularizes reconstruction when sensors are fewer than modes. • A dimensionless A-optimal posterior-trace criterion handles mixed sensor types. • Sequential floating selection with rank-one updates keeps the search efficient. • Low-budget robust response reconstruction with credible intervals.

Keywords:

Sensor placement optimization

Load prior

Bayesian inference

A-optimal design

Structural health monitoring

Uncertainty quantification

Efficient Bayesian framework for multi-type sensor placement optimization based on posterior uncertainty minimization

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