Fan master control PLC fault diagnosis method and system based on digital twinning

By constructing a PLC source code graph and a timing graph attention network, combined with high-frequency timing data, the false alarm problem in the fault diagnosis of wind turbine main control PLC in the existing technology is solved, realizing efficient and accurate fault location and cause tracing, and improving the interpretability of diagnosis and operation and maintenance efficiency.

CN122411366APending Publication Date: 2026-07-17HUANENG RENEWABLES CORP LTD HEBEI BRANCH +2

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HUANENG RENEWABLES CORP LTD HEBEI BRANCH
Filing Date
2026-03-25
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies fail to effectively utilize the deterministic control logic and causal relationships within the PLC in wind turbine main control PLC fault diagnosis. This results in the diagnostic model generating numerous false alarms under varying operating conditions, lacking interpretability, and making it difficult to trace the underlying causes of the fault.

Method used

By constructing a control logic diagram based on PLC source code, combining high-frequency timing data, and using a timing diagram attention network for fault diagnosis, the deterministic control logic of the PLC and real-time data are integrated to perform residual calculation and anomaly scoring, thereby achieving fault location and cause tracing.

Benefits of technology

It improves the accuracy and interpretability of fault diagnosis, reduces the false alarm rate, provides actionable guidance for fault diagnosis, and improves operation and maintenance efficiency.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure CN122411366A_ABST
    Figure CN122411366A_ABST
Patent Text Reader

Abstract

本发明实施例提供了一种基于数字孪生的风机主控PLC故障诊断方法及系统,其通过深度融合PLC固有的确定性控制逻辑与实时高频运行数据,首先将PLC源代码解析并构建为控制逻辑图谱,以此作为数字孪生的基础;继而,结合数采系统采集的高频时序数据,运用基于时序图注意力网络的模型,对风机PLC的所有节点期望状态进行精准预测,进一步对预测状态与实际状态之间进行残差计算与异常评分,以实现对物理系统运行状态与内部逻辑关系的精确映射。通过这样的方式,极大地提升了诊断结果的准确性、可解释性和可操作性。
Need to check novelty before this filing date? Find Prior Art