Earticle

초록

영어

Compressive sensing (CS) is a novel framework which exploits both the sparsity and the intra-correlation of the signal in structural health monitoring (SHM) based on wireless sensor networks (WSNs). It contains sparse signal representation, the measurement matrix selection and the reconstruction algorithm. The SHM signal is recovered by M measurements following the restricted isometry constant (RIC). However, the signal should be denoised before reconstruction. This paper discusses two wavelet noise reduction methods, soft threshold and hard threshold method, and verifies the performance of different methods for SHM signal reconstruction. Experimental results show that wavelet hard threshold method has much better effect on SHM sparse signal reconstruction than soft threshold method. Meanwhile, we can get a more accurate corresponding relation of RIC that is M≥CK*log(N / K).

목차

Abstract
 1. Introduction
 2. Compressive Sensing Theory
 3. Noise Reduction in CS
  3.1 Wavelet threshold noise reduction
 4. Simulation and Performance Evaluation
  4.1 The evaluation standards for CS applications in SHM
  4.2 The soft and hard threshold selection in CS
 5. Conclusions and the Future Works
 Acknowledgments
 References

키워드

저자

• Sai Ji [ Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, The Aeronautic Key Laboratory for Smart Materials and Structures, Nanjing University of Aeronautics and Astronautics, 29# Yu Dao Street, Nanjing, China, 210016 ]
• Liping Huang [ Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, 219# Ningliu Road, Nanjing, China, 210044 ]
• Jin Wang [ Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, 219# Ningliu Road, Nanjing, China, 210044 ]
• Jinwei Wang [ Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, 219# Ningliu Road, Nanjing, China, 210044 ]
• Jian Shen [ Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, 219# Ningliu Road, Nanjing, China, 210044 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605