arXiv:2603.08288cs.CRcs.AI2026-03被引 1

用区块链实现飞机叶片检测全程可追溯,防篡改且自动触发检查。

A Blockchain-based Traceability System for AI-Driven Engine Blade Inspection

  • 基于区块链构建四角色协同系统,自动按飞行时长触发检测。
  • 100%完成100片叶片生命周期追踪,每分钟处理26次操作。
  • 支持AI模型版本溯源,适合航空监管与维护机构使用。

飞机发动机叶片维护依赖制造商、航空公司、维修机构和监管方共享的检测记录,但现有系统分散、难审计且易被篡改。本文提出BladeChain,首个集成多利益方认证、自动检测调度、AI模型溯源与加密证据绑定的区块链系统,实现全生命周期可审计追溯。基于四参与方(OEM、Airline、MRO、Regulator)的Hyperledger Fabric网络,系统以不可篡改的账本记录每个生命周期事件。链码驱动的状态机管理叶片状态流转,并在飞行小时、循环或日历阈值达标时自动触发检查,消除人工调度错误。检测数据离线存储于IPFS,通过SHA-256哈希关联链上记录,每条记录包含缺陷检测所用的AI模型名称与版本,使监管方可追溯检测结果及方法。检测模块可插拔,支持组织灵活更换或升级模型而不改动账本流程。原型评估显示,在100片叶片工作负载下实现100%生命周期完成,稳定吞吐量为每分钟26次操作。集中式SQL基线对比揭示共识开销,安全验证确认篡改检测时间仅需17~毫秒。

原文摘要 · Abstract (English)

Aircraft engine blade maintenance relies on inspection records shared across manufacturers, airlines, maintenance organizations, and regulators. Yet current systems are fragmented, difficult to audit, and vulnerable to tampering. This paper presents BladeChain, a blockchain-based system providing immutable traceability for blade inspections throughout the component life cycle. BladeChain is the first system to integrate multi-stakeholder endorsement, automated inspection scheduling, AI model provenance, and cryptographic evidence binding, delivering auditable maintenance traceability for aerospace deployments. Built on a four-stakeholder Hyperledger Fabric network (OEM, Airline, MRO, Regulator), BladeChain captures every life-cycle event in a tamper-evident ledger. A chaincode-enforced state machine governs blade status transitions and automatically triggers inspections when configurable flight hour, cycle, or calendar thresholds are exceeded, eliminating manual scheduling errors. Inspection artifacts are stored off-chain in IPFS and linked to on-chain records via SHA-256 hashes, with each inspection record capturing the AI model name and version used for defect detection. This enables regulators to audit both what defects were found and how they were found. The detection module is pluggable, allowing organizations to adopt or upgrade inspection models without modifying the ledger or workflows. We built a prototype and evaluated it on workloads of up to 100 blades, demonstrating 100% life cycle completion with consistent throughput of 26 operations per minute. A centralized SQL baseline quantifies the consensus overhead and highlights the security trade-off. Security validation confirms tamper detection within 17~ms through hash verification.

区块链航空检测AI溯源可审计

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