电力设备质量检测方法、装置、计算机设备及存储介质
By constructing a federated learning model based on a tree structure of workshop production, and using process data of power equipment parts for quality inspection, the problem of power equipment production data security is solved, and efficient quality inspection and privacy protection are achieved.
CN115438387BActive Publication Date: 2026-07-17湖南红普创新科技发展有限公司 +3
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 湖南红普创新科技发展有限公司
- Filing Date
- 2022-09-06
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
In the process of power equipment production, existing technologies cannot effectively protect the security of production data, leading to potential data leaks and economic losses.
Method used
By acquiring component process data of power equipment parts, using a pre-set database to obtain standard production data, a federated learning model based on a tree structure of workshop production is constructed. Through federated learning, quality inspection results are obtained without disclosing production data of process steps.
Benefits of technology
This enables the safety and accuracy of power equipment quality testing without disclosing production data, thus improving the privacy protection of production data.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN115438387B_ABST
Abstract
本申请公开了一种电力设备质量检测方法、装置、计算机设备及存储介质，应用于质量检测技术领域，用于提高电力设备在质量检测阶段的数据安全性。本申请提供的方法包括：获取电力设备在生产过程中每个零件的零件工序数据；针对每个所述零件，从预设数据库获取所述零件的标准生产数据，根据所述标准生产数据与所述零件工序数据的差值，得到所述零件的零件生产信息；获取工序环节信息与车间信息，并基于所述工序环节信息与所述车间信息构建车间生产树形结构；基于所述车间生产树形结构，构建联邦学习模型，并将所述零件生产信息输入所述联邦学习模型，得到质量检测结果。
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