The invention discloses a parallelized method for defective text classification of power equipment. The parallelized method includes the steps of adding a field lexicon to a user dictionary, preprocessing defect cases, and performing word segmentation and removing stop words; using a crawler algorithm to collect text corpora of power grid fault cases, using word2vec of Spark for training and obtaining word vector representations in the field; performing vectorized representation on the acquired defect cases and word vectors, expressing the defect cases in text, and forming a matrix; inputtingthe matrix into an SVM multi-classifier, conduct training and classification, and obtaining classification results.