Design of electronic circuit fault diagnosis based on artificial intelligence
by Yumei Tao
International Journal of Biometrics (IJBM), Vol. 14, No. 2, 2022

Abstract: In order to reduce the failure of electronic circuit components in large-scale circuit systems, it is necessary to design the fault diagnosis of electronic circuits to improve the steady-state working ability of electronic circuits. This paper proposes an electronic circuit fault diagnosis method based on artificial intelligence algorithm. The proposed method establishes the fault signal model of the circuit element, and then establishes the fault analysis model, and uses the data mining method to detect and analyse the fault characteristics. The signal detection method is used to analyse and discover the parameter state characteristics of the output of the electronic circuit, and the wavelet transform method is used to detect and identify the state. Experimental result shows that the proposed method has a good judgment function in circuit fault diagnosis.

Online publication date: Thu, 07-Apr-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email