In the equipment quality assessment of the power industry, it is necessary to combine the specific standards specified in the industry standard specification documents to accurately assess the quality of the equipment. Through the text differentiation model based on the retrieval reordering model, an automated, informative, and intelligent standard differentiation combing technology is established, which effectively solves the time-consuming and laborious problem of current equipment quality assessment, and improves the accuracy rate of text difference retrieval. This paper mainly focuses on the standard differentiation combing technology of automation, informationization and intelligence. Through the information retrieval model based on the retrieval reordering model, the text retrieval comparison for different standards in the same field is established, and the retrieval of differential content of different documents has different requirements for the same technology, and provides early warning. The innovation in the paper is to take advantage of the high accuracy of retrieval reordering, and to further improve the accuracy on the basis of retaining the recall candidate ability of the traditional difference retrieval recall model. The model is cross-validated on the real power industry technical standard documents to verify the effect of the proposed model. The results show that the model has good practicability and can be widely used in power equipment quality evaluation, supplier evaluation standard retrieval and other fields.