Coupling-Seam Diagnostics: Reading Where a Multi-Domain System Begins to Fail

Most diagnostic tools read a complex system one domain at a time: its mechanics, its thermals, its power budget, each in isolation. Yet many catastrophic failures do not originate inside a single domain. They originate at the seam between domains, where load in one domain silently raises load in another until a chain forms. This paper presents a diagnostic method that takes the cross-domain coupling structure of a system as its only input and returns a map of where the system is strong, where it is weak, and which coupling is the dominant failure path. The method is demonstrated first on a model of a bipedal walking robot, and then validated on a real multi-domain dataset: the UCI Condition Monitoring of Hydraulic Systems data, from which a five-domain coupling matrix is estimated empirically. On that real matrix, the method recovers a physically sensible coupling structure with no prior knowledge, and a targeted intervention guided by the dominant eigenvector improves the stability margin substantially more than a uniform one. The contribution is not a new stability criterion, nor new spectral mathematics, but the application of established eigenvector-guided intervention methods to an empirically estimated cross-domain coupling matrix, framed as a reading of the seam between domains. Version 2 adds a validation of the method on real multi-domain condition-monitoring data, an explicit positioning relative to the established spectral-intervention literature, and a stated regime of validity. The original method and worked example are unchanged.