A New Inspection Method to Diagnose Winding Material and Capacity of Distribution Transformer based on Big Data

Abstract

This paper takes Zhejiang power corporation panoramic quality business chain as background, centering on the problem that distribution equipment is hard to be inspected accurately with routine inspection, proposes a new inspection technology, aiming to diagnose the quality problem of distribution equipment quickly, economically and accurately. This paper accumulates a large number of physical characteristic parameter and test data of more than one thousand distribution transformers from Zhejiang power corporation quality inspection center of distribution equipment, and analyzes the distribution of volume, weight, DC resistance, no-load loss, load loss and short-circuit impedance of distribution transformer in different capacity levels through the statistical method of big data, and finally makes a assessment process to diagnose winding material and capacity of distribution transformer. The specific assessment process is divided into three steps: 1) Determine the relevant core data for different inspection targets(winding material: volume, weight, DC resistance; capacity:no-load loss, load loss and short-circuit impedance); 2) Build associated database of core data and non-core data of distribution transformer; 3) Use the associated database for preliminary judgment, and other method to confirm one by one.