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基于改进SSD算法的结构表观裂缝病害检测

刘永胜 熊吉光 游志杰 吴勋杰 翟天正

华东交通大学学报2023,Vol.40Issue(6):1-7,7.
华东交通大学学报2023,Vol.40Issue(6):1-7,7.

基于改进SSD算法的结构表观裂缝病害检测

Structural Apparent Crack Disease Detection Based on Improved SSD Algorithm

刘永胜 1熊吉光 2游志杰 2吴勋杰 2翟天正2

作者信息

  • 1. 华东交通大学土木建筑学院,江西南昌 330013||安徽理工大学深部煤矿采动响应与灾害防控国家重点实验室,安徽淮南 232001
  • 2. 华东交通大学土木建筑学院,江西南昌 330013
  • 折叠

摘要

Abstract

The original backbone of the SSD network was replaced with a lightweight MobileNetV2 network.At the same time,the channel attention mechanism SENet structure was introduced to apply different weights to dif-ferent channels of the feature map,making it more conducive to detection.Using the crack data in three different environments to fuse,a new data set was built so that the network can better learn crack objects in different en-vironments,further improving the network's recognition ability and speeding up the network's reasoning speed.The anchor in the original SSD network were set according to the general data set,and the data type concerned in the detection of structural surface cracks was relatively single.The K-means algorithm was used to cluster the anchor suitable for the crack data set,which speeded up the convergence of the model and was more efficient than the original one.The model had higher accuracy.Finally,the accuracy of the improved algorithm is 3.6%higher than that of the previous one,and the detection speed is as much as 2 times that of the previous one,which is enough to meet real-time detection,the algorithm can provide a faster and more accurate detection method for the detection of structural apparent cracks in practical engineering.

关键词

目标检测/表观病害/裂缝识别/SSD算法/注意力机制

Key words

target detection/apparent disease/crack identification/SSD algorithm/attention mechanism

分类

建筑与水利

引用本文复制引用

刘永胜,熊吉光,游志杰,吴勋杰,翟天正..基于改进SSD算法的结构表观裂缝病害检测[J].华东交通大学学报,2023,40(6):1-7,7.

基金项目

国家自然科学基金项目(51664014) (51664014)

江西省研究生创新专项资金项目(2022-S510) (2022-S510)

华东交通大学学报

OACSTPCD

1005-0523

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