T/XJBX 0144-2025 Intelligent inspection system for mechanical and electrical special equipment fault early warning and maintenance adaptation application guide

Scope

Electromechanical special equipment is characterized by high load capacity, frequent operation, long service life, and complex working scenarios. Equipment failures often occur suddenly and have a chain-reaction effect, which may lead to personal injuries, property losses, and social impacts. With the continuous increase in the number of equipment in service, the rising proportion of outdated equipment, and higher regulatory requirements for inspection and testing quality and efficiency, the traditional management approach dominated by manual experience and periodic planned inspections has obvious shortcomings in early failure identification, hazard trend judgment, inspection resource optimization, and precise adaptation of maintenance strategies. At the same time, the maturity of technologies such as sensing and IoT, edge computing, automated non-destructive testing, industrial Internet, and artificial intelligence provides a practical foundation for building an intelligent inspection system of "state perception - failure warning - inspection decision - maintenance adaptation - closed-loop verification". The intelligent inspection system for electromechanical special equipment typically involves cross-disciplinary and multi-stakeholder collaboration: it involves not only information technology fundamentals such as sensors, acquisition terminals, communication networks, and platform systems, but also professional knowledge in equipment structure, component mechanisms, failure modes, inspection methods, risk assessment, and maintenance processes; it serves both the operation and maintenance management of user units and needs to be integrated with the inspection decisions, inspection reports, and evidence chain management of inspection agencies, while meeting regulatory requirements for data authenticity, traceability, and security. In engineering applications, the lack of unified failure warning grading rules, model verification requirements, and maintenance adapt

Development Information

Related Standards