Conditional Cross-Component Symmetry for Resilient Wireless Sensing and Health Monitoring of Homologous Paired Systems

Wireless sensing improves the flexibility of condition monitoring but introduces additional uncertainty from sensor faults, packet loss, and communication degradation, which can resemble genuine physical degradation. This study proposes a symmetry-aware framework for resilient monitoring of homologous paired technical systems, defined as pairs of functionally similar components operating under comparable conditions. The framework is based on conditional cross-component symmetry: paired components are not assumed to produce identical measurements, but their normalized multivariate states are expected to retain a statistically consistent healthy relationship once operating conditions and component-specific differences are accounted for. Departures from this relationship support discrimination between physical degradation and sensor- or communication-related anomalies, while the homologous component simultaneously serves as an external source of analytical redundancy for reconstructing unavailable measurements. A twin-engine aircraft configuration is used as a representative pre-deployment case study for prospective wireless engine-health monitoring. Because the real engines are not equipped with the full wireless sensing architecture investigated here, the quantitative evaluation uses a reproducible synthetic paired-engine environment grounded in real operating and maintenance context. Robustness is examined across independent data generations and under controlled nonlinear model-form mismatch. Within this synthetic setting, the results indicate that cross-component information complements conventional local analytical redundancy, particularly for exhaust gas temperature (EGT) reconstruction as local observability deteriorates, while its benefit decreases when the homologous-component information path itself degrades. The study therefore proposes extending symmetry from a diagnostic property to a potential information resource for resilient wireless sensing and provides a basis for subsequent validation with synchronized operational data.