With the development of intelligent buildings,the complexity of building electrical systems is increasing,and the fault types are diverse and the characteristics are not obvious,which brings great challenges to fault diagnosis.In this paper,we propose a method based on the combination of Variational Mode Decomposition(VMD)and a novel Multidimensional Dimensionless Index(MDI),and optimize the support vector machine(QGA-SVM)through quantum genetic algorithm to improve the accuracy and efficiency of fault diagnosis.Experimental results show that compared with traditional fault diagnosis methods,the proposed method has superior performance in feature extraction and classification accuracy,and the average test accuracy reaches 91.67％.
关键词
建筑电气系统/故障诊断/变分模态分解(VMD)/量子遗传算法(QGA)
Key words
Building electrical system/Fault diagnosis/Variational Mode Decomposition(VMD)/Quantum Genetic Algorithm(QGA)
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