Study on Recognition Method of Ferrographic Debris Based on Neural Network

Abstract

A new method is proposed in which three images of the same field of view under different lighting conditions were analysed comprehensively. On the basis of pretreatment of debris digital image and extraction of characteristic parameter of debrises, the debrises were recognized by establishing the BP neural network model. The results showed that the recognition accuracy of debrises could reach 85.6% with this method.

Interrogative Sentences Recognition Based on the GRU Multiattentive Layer Model

“…Question answer system (QA) can better meet the user's retrieval need and can find out the answers the user needs faster, and is currently receiving a lot of attention [1]. QA systems generally consist of three main components: question understanding, information retrieval and answer extraction [2]. Question understanding, also known as sentence analysis, is a key step in a question and answer system, and its accuracy has a significant impact on how questions are answered.…”