The invention provides a method and device for analyzing electric field multivariate operating data. The method comprises steps of: standardizing each index data of the electric field multivariate operating data to generate a standardized item set of the index data; performing fuzzification on the standardized item set by using a normal distribution membership function to generate fuzzy sets and determining the membership grade value of each fuzzy set; determining a frequent 1 item set according to the membership grade value of each index data in each fuzzy set; identifying and computing a frequent item set by means of iteration according to the determined frequent 1 item set; generating an associated rule of the frequent item set by means of correlative steps of an Apriori algorithm, wherein the associated rule is a result of electric field multivariate data analysis. The provided improved fuzzy function associated rule mining algorithm is introduced into wind electric field multivariate operating data analysis. A Boolean type associated rule is converted into a value type associated rule by means of a divisional concept. The concept of a normal distribution membership function in fuzzy mathematics is introduced so that a boundary is reasonable and effective.