A damage identification method for a thin plate structure based on PVDF sensors and strain mode

Abstract

Damage identification methods for engineering structures based on vibration parameters have the advantages of easy detection and high precision; however, structural strain information is more sensitive to structural damage than displacement information. Traditional resistance strain sensors have low accuracy and poor stability when measuring structural strains. Therefore, this paper uses a highly sensitive polyvinylidene fluoride dynamic strain sensor to identify structural damage in a thin plate. The polyvinylidene fluoride sensor is used to obtain structural strain response information, and structural modal parameters are identified using operational modal identification methods based on the natural excitation technique and the eigensystem realization algorithm. This paper uses a damage index based on mode shape and flexibility. A new damage index based on the LU decomposition of the flexibility matrix is used to identify the damage of the thin plate structure. The effectiveness of the modal identification methods and the new damage index is validated via an elastic thin plate experiment. The results show that the modal identification method and the new damage index proposed in this paper can identify damage in a thin plate structure. Sensor comparison experiments also show that compared with a resistance strain sensor, the polyvinylidene fluoride sensor has higher damage sensitivity, better damage recognition and the ability to recognize farther from the sensor.

Keywords

Polyvinylidene fluoride sensor strain modes damage identification thin plate structure natural excitation technique eigensystem realization algorithm

Get full access to this article

View all access options for this article.

References

Zhao

Gao

Zhang

et al.

Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring. Smart Mater Struct 2007; 16: 1208–1217.

Fan

Qiao \P . Vibration-based damage identification methods: a review and comparative study. Struct Health Monit 2011; 10: 83–111.

Goyal

Pabla

. The vibration monitoring methods and signal processing techniques for structural health monitoring: a review. Arch Comput Methods Eng 2016; 23: 585–594.

Adewuyi

Serker

NHMK

. Assessment of Vibration-based damage identification methods using displacement and distributed strain measurements. Struct Health Monit 2009; 8: 443–461.

Tikka J, Hedman R and Siljander A. Strain gauge capabilities in crack detection. In: The 4th international workshop on structural health monitoring, Stanford, USA, 15–17 September 2003.

et al.

Damage identification research of reinforced concrete beam using strain response. J Residuals Sci Technol 2016; 13: 188.1–188.5.

Wang

Law

et al.

Covariance of dynamic strain responses for structural damage detection. Mech Syst Signal Process 2017; 95: 90–105.

Hong

Zhang

et al.

Application of FBG sensors for geotechnical health monitoring, a review of sensor design, implementation methods and packaging techniques. Sensor Actuat A-Phys 2016; 244: 184–197.

Wang

et al.

FBG-based real-time evaluation of transverse cracking in cross-ply laminates. Compos Struct 2016; 138: 151–160.

10.

Shakeel

Khan

Rahman

. Fabrication of cost effective and high sensitivity resistive strain sensor using DIW technique. Sensor Actuat A-Phys 2017; 258: 123–130.

11.

Cahill

Jackson

Mathewson

et al.

Polyvinylidene Fluoride (PVDF) material based energy harvesting from train and damaged bridge interaction. Key Eng Mater 2013; 569–570: 335–341.

12.

Hasni

Alavi

Jiao

et al.

A new approach for damage detection in asphalt concrete pavements using battery-free wireless sensors with non-constant injection rates. Measurement 2017; 110: 217–229.

13.

Dong

Lian

Wang

et al.

Structural vibration monitoring and operational modal analysis of offshore wind turbine structure. Ocean Eng 2018; 150: 280–297.

14.

Zhao

Noori

Altabey

et al.

Mode shape-based damage identification for a reinforced concrete beam using wavelet coefficient differences and multiresolution analysis. Struct Control Health 2017; 25: 1–41.

15.

Ciambella

Vestroni

. The use of modal curvatures for damage localization in beam-type structures. J Sound Vib 2015; 340: 126–137.

16.

Vo-Duy

Ho-Huu

Dang-Trung

et al.

A two-step approach for damage detection in laminated composite structures using modal strain energy method and an improved differential evolution algorithm. Compos Struct 2016; 147: 42–53.

17.

Sung

Koo

Jung

. Modal flexibility-based damage detection of cantilever beam-type structures using baseline modification. J Sound Vib 2014; 333: 4123–4138.

18.

Hosseinzadeh

Amiri

Razzaghi

SAS

et al.

Structural damage detection using sparse sensors installation by optimization procedure based on the modal flexibility matrix. J Sound Vib 2016; 381: 65–82.

19.

Bernagozzia

Venturab

Allahdadianb

et al.

Application of modal flexibility-based deflections for damage diagnosis of a steel frame structure. Procedia Eng 2017; 199: 2026–2033.

20.

Whalen

. The behavior of higher order mode shape derivatives in damaged beam-like structures. J Sound Vib 2008; 309: 426–464.

21.

Ganguli

Gouravaraju

. Damage detection in cantilever beams using spatial Fourier coefficients of augmented modes. Proc IMechE, Part C: J Mechanical Engineering Science 2016; 230: 3677–3690.

22.

Umesh

Ganguli

. Matrix crack detection in composite plate with spatially random material properties using fractal dimension. Comput Mater Con 2014; 41: 215–239.

23.

Reynders

Roeck

. Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis. Mech Syst Signal Process 2008; 22: 617–737.

24.

James

GHI

Carne

Lauffer

. The natural excitation technique (NExT) for modal parameter extraction from operating structures. J Analyt Exp Modal Anal 1995; 10: 260–277.

25.

Chang

Pakzad

. Modified natural excitation technique for stochastic modal identification. J Struct Eng 2013; 139: 1753–1762.

26.

Juang

Pappa

. An eigensystem realization algorithm for modal parameter identification and model reduction. J Guid Control Dyn 1985; 8: 620–627.

27.

Caicedo

. Practical guidelines for the natural excitation technique (Next) and the eigensystem realization algorithm (ERA) for modal identification using ambient vibration. Exp Techniques 2011; 35: 52–58.

28.

SLJ

. Noise issues of modal identification using eigensystem realization algorithm. Procedia Eng 2011; 14: 1681–1689.

29.

Kramer

Gugercin

. Tangential interpolation-based eigensystem realization algorithm for MIMO systems. Math Comput Model Dyn 2016; 22: 282–306.