Reliability of crack quantification via acousto-ultrasound active-sensing structural health monitoring using surface-mounted PZT actuators/sensors

Abstract

This work presents the introduction and experimental investigation of an active-sensing acousto-ultrasound structural health monitoring approach for damage size quantification based on piezoelectric sensors/actuators mounted on multiple seemingly identical structural components. The objective of this work is to determine how reliable the damage diagnostics can be from one component to another similar (nominally identical) component using surface-mounted PZT (lead zirconate titanate) sensors/actuators, and also to evaluate how sensitive a sensor network configuration in terms of the number of sensors/actuators is with respect to its detection reliability. Extensive crack growth experiments on multiple identical coupons outfitted with the same sensor network configuration under cyclic loads were conducted to assess the damage quantification reliability from one coupon to another using the same diagnostic algorithm. The results of the study indicate that the crack size estimates obtained from the active-sensing structural health monitoring system can vary within the population of identical structural components (coupons), but the difference in quantifying damage among coupons decreases with the increase in the number of sensors and actuators used, that is, wave propagation paths. Furthermore, it is shown that the diagnostic results in terms of damage quantification converge with the increase in the number of sensors. The results of the study indicate that the diagnostic approach using a multi-path sensor network can reduce the damage quantification error from one component to another within a “hotspot” configuration (damage location is known or suspected a priori). Finally, the results of this study indicate that the more wave propagation paths used in the diagnostic active-sensing algorithm, the more reliable the damage quantification results are, provided that the same sensor network is used and installed at nominally identical locations for all coupons.

Keywords

Active-sensing structural health monitoring damage quantification reliability quantification ultrasound methods piezoelectric sensors hotspot monitoring

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References

Ihn

J-B

Chang

F-K

. Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: I. Diagnostics. Smart Mater Struct 2004; 13: 609–620.

Ihn

J-B

Chang

F-K

. Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: II. Validation using riveted joints and repair patches. Smart Mater Struct 2004; 13: 621–630.

Lonkar

Chang

F-K

. Modeling of piezo-induced ultrasonic wave propagation in composite structures using layered solid spectral element. Struct Health Monit 2014; 13: 50–67.

Sharif-Khodaei

Aliabadi

. Assessment of delay-and-sum algorithms for damage detection in aluminium and composite plates. Smart Mater Struct 2014; 23: 075007.

Flynn

Todd

Croxford

, et al. Enhanced detection through low-order stochastic modeling for guided-wave structural health monitoring. Struct Health Monit 2012; 11(2): 149–160.

Giurgiutiu

Soutis

. Guided wave methods for structural health monitoring. In: Blockley

Shyy

(eds) Encyclopedia of aerospace engineering. Hoboken, NJ: John Wiley & Sons, Ltd, 2010.

Kopsaftopoulos

Fassois

. A functional model based statistical time series method for vibration based damage detection, localization, and magnitude estimation. Mech Syst Signal Pr 2013; 39(1–2): 143–161.

Kopsaftopoulos

Fassois

. A vibration model residual-based sequential probability ratio test framework for structural health monitoring. Struct Health Monit 2010; 14(4): 359–381.

Rytter

. Vibration based inspection of civil engineering structures. PhD Thesis, Department of Building Technology and Structural Engineering, Aalborg University, Aalborg, 1993.

10.

Janapati

Kopsaftopoulos

, et al. Damage detection sensitivity characterization of acousto-ultrasound-based structural health monitoring techniques. Struct Health Monit 2016; 15(2): 143–161.

11.

Wilson

Chang

F-K

. Real time in-situ damage classification, quantification and diagnosis for composite structures. In: Proceedings of the 19th international congress on sound and vibration, Vilnius, 8–12 July 2012.

12.

Yadav

Banerjee

Kundu

. On sequencing the feature extraction techniques for online damage characterization. J Intel Mat Syst Str 2013; 24: 473–483.

13.

Yadav

Banerjee

Kundu

. Effective damage sensitive feature extraction methods for crack detection using flaw scattered ultrasonic wave field signal. In: Proceedings of the 8th international workshop on structural health monitoring. DEStech Publications Inc: Stanford, CA, 13–15 September 2011, vol. 1, pp. 167–174.

14.

MIL-HDBK-1823. Nondestructive evaluation (NDE) system reliability assessment. Arlington, VA: US Department of Defense, 1999.

15.

Matzkanin

Yolken

. Probability of detection (POD) for nondestructive evaluation (NDE). Austin, TX: Texas Research Institute, 2001.

16.

Wall

Burch

Lilley

. Review of models and simulators for NDT reliability (POD). Insight 2009; 51(11): 612–619.

17.

Giurgiutiu

Liu

. Development and testing of high-temperature piezoelectric wafer active sensors for extreme environments. Struct Health Monit 2010; 9: 513–525.

18.

Roy

Lonkar

Janapati

, et al. A novel physics-based temperature compensation model for structural health monitoring using ultrasonic guided waves. Struct Health Monit 2014; 13(3): 321–342.

19.

Janapati

Yadav

Kumar

, et al. Fatigue crack quantification approach based on multi-path unit-cell concept in sensor network. In: Proceedings of the 8th European workshop on structural health monitoring, Bilbao, 5–8 July 2016.

20.

Yadav

Chung

Kopsaftopoulos

, et al. Damage quantification of active sensing acousto-ultrasound-based SHM based on a multi-path unit-cell approach. In: Proceedings of the 11th international workshop on structural health monitoring. DEStech Publications Inc: Stanford, CA, 12–14 September 2017, pp. 3093–3103.

21.

Roy

Ladpli

Lonkar

, et al. Structural damage detection using ultrasonic guided waves under varying ambient temperature and loading environments. In: Proceedings of the 9th international workshop on structural health monitoring (IWSHM), Stanford, CA, 10–12 September 2013.

22.

Roy

Ladpli

Chang

F-K

. Load monitoring and compensation strategies for guided-waves based structural health monitoring using piezoelectric transducers. J Sound Vib 2015; 351: 206–220.

23.

Lin

Qing

Kumar

, et al. SMART Layer and SMART Suitcase for structural health monitoring applications. In: Proceedings of the smart structures and materials 2001: industrial and commercial applications of smart structures technologies, Newport Beach, CA, 4–8 March 2001, vol. 4332, pp. 98–107. Bellingham, WA: International Society for Optics and Photonics.