Abstract
Relay protection big data creates good conditions for the improvement of professional applications, and data integrity is an important aspect that reflects data quality. The association of relay protection big data is intense. This paper applies Apriori algorithm to mine data relevance and generate association rules. Based on this, the integrity of relay protection data is checked, and the incomplete data is predicted. Taking the relay protection defect data as an example, the paper explores the correlation among 251 items of the six dimensions of protection relay defect data such as type of protection, the severity of the defect, whether the protection is out of operation, the defect location, the cause of the defect, and the equipment manufacturer, completing the processing of incomplete data with great application results.