家电科技2025，Vol.1Issue(1)：48-52,5.DOI:10.19784/j.cnki.issn1672-0172.2025.01.007
基于双图注意力网络和区间预测的智能家电故障检测
Fault diagnosis of intelligent household appliances based on dual graph attention network and interval prediction
尚喆 1曹财广 1唐善玄 1刘明 1刘普1
作者信息
- 1. 广东美的制冷设备有限公司 广东 佛山 528000
- 折叠
摘要
Abstract
Although machine learning and artificial intelligence technologies have been applied to fault diagnosis in smart home appliances,they still face challenges such as data coupling between sensors,dynamic changes in data,and difficulty in obtaining fault data.To address the above issues,on intelligent famlt detection method for home appliances based on dual graph attention network and interval prediction is proposed.By simultaneously modeling the relationships between sensors and the dynamic patterns of data in time series,fault diagnosis can be performed through unsupervised learning,which does not require fault data for network training.This method achieved an accuracy of 92.3%in classifying normal and fault data on a real-world household air conditioning operation dataset.It maintained high accuracy even under noise interference,providing an effective and precise technical approach for enhancing fault diagnosis of smart home appliances.It is of great significance for promoting the development of smart home technology.关键词
故障检测/注意力网络/区间预测/智能家电/空调/传感器Key words
Fault diagnosis/Graph attention network/Interval prediction/Intelligent household appliances/Air conditioning/Sensor分类
动力与电气工程引用本文复制引用
尚喆,曹财广,唐善玄,刘明,刘普..基于双图注意力网络和区间预测的智能家电故障检测[J].家电科技,2025,1(1):48-52,5.
