# Structural Health Monitoring (SHM) of Polymer-Matrix Composites (PMC) with the Insertion of Piezoelectric Transducers and a Data Fusion Approach

L Dolbachian, W Harizi, Z Aboura

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L Dolbachian, W Harizi, Z Aboura. Structural Health Monitoring (SHM) of Polymer-Matrix Composites (PMC) with the Insertion of Piezoelectric Transducers and a Data Fusion Approach. ECCM21 – 21st European Conference on Composite Materials, Jul 2024, Nantes (France), France. hal-04670929

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Submitted on 13 Aug 2024

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# STRUCTURAL HEALTH MONITORING (SHM) OF POLYMER-MATRIX COMPOSITES (PMC) WITH THE INSERTION OF PIEZOELECTRIC TRANSDUCERS AND A DATA FUSION APPROACH

L. Dolbachian¹, W. Harizi¹ and Z. Aboura¹

¹Université de Technologie de Compiègne, Roberval (Mechanics, Energy and Electricity)
Centre de Recherche Royallieu
CS 60319, 60203 Compiègne Cedex, France

**Keywords:** Polymer-Matrix Composites (PMC); Structural Health Monitoring (SHM); In-situ piezoelectric transducer; Self-heating test; Multi-acquisition procedure;

## Abstract

In this article, the results obtained from an experimental campaign, performed under self-heating four-point bending tests, on smart Polymer-Matrix Composite (PMC) are presented. The smart capabilities of these PMC specimens came from the insertion of in-situ piezoelectric transducers (PZT) within the material. These transducers were used both for evaluating the rapid fatigue limit and to monitor the health of the structure, known as Structural Health Monitoring (SHM). As the self-heating test can introduce damage in the material, it was possible to follow its evaluation through the Non-Destructive Testing (NDT) (Ultrasonic testing, Acoustic Emission, Capacitance measurement) methods used for SHM. In this study, the fatigue limit was evaluated from the capacitance measurements of the embedded transducers, and validated from the stabilized temperature measurements. So, this paper showed an original way of evaluating the fatigue limit and a multi-acquisition procedure for SHM, from in-situ piezoelectric transducers.

## 1. Introduction

In recent years, Polymer-Matrix Composite (PMC) materials have distinguished themselves from classic materials such as metals by their high mechanical properties relative to their low weight. This has led to an increase in their utilization across various domains and applications, including aeronautics, automotive, and sports. Consequently, there has been a surge in research on such materials, making it crucial to thoroughly understand their damage mechanisms and to develop methods for monitoring their health to ensure the integrity of their service life, known as Structural-Health Monitoring (SHM). Simultaneously, smart materials have also gained significant interest from the scientific community in recent years. Such materials can automatically respond to external stimuli or obtain relevant information. There exist different types of smart materials, including shape memory alloy, piezoelectric transducer, and optical fiber, that make possible the combination of smart materials with Structural Health Monitoring (SHM). In this study, Lead Zirconate Titanate (PZT) transducers were embedded within the PMC using the method developed by Tuloup [1–8] for the Liquid Resin Infusion (LRI) manufacturing process. This method is regularly used in our lab [9]. These transducers were used both in passive (Acoustic Emission (AE) and capacitance measurement) and active (Ultrasonic testing (US)) modes, in order to evaluate the health of the structure in real-time and the damage mechanisms evolution scenario, during the tests.

The self-heating four-point bending test consists of applying many cyclic loading blocks on the material with increasing levels in order to observe temperature stabilization during each loading phase. The stabilized temperature increases with the increase of the mechanical loadings. Plotting the stabilized temperatures versus the average or maximum loads illustrates two linear regimes, the intersection point between them can give an estimation of the fatigue limit of the studied material. Following the same reasoning, the capacitance variation and its stabilization during each mechanical block have also been used to evaluate the rapid fatigue limit estimation, this method was effectively used in the past during tensile tests of similar material [10].
For SHM purposes, AE, US and capacitance measurements were used to collect data before, during and after each cycle. The PMC was also inspected with external NDT techniques, such as external AE, thermocouples, strain gauges, laser, ... resulting in a test with a substantial amount of data. This instrumentation aims two goals: comparing and validating the internal methods (from the PZT) with the external ones; and collecting as much data as possible for the final step of this work, namely, a data fusion approach in order to automatize and to increase the robustness of the SHM task.

## 2. Smart PMC specimen

### 2.1. PMC manufacturing by Liquid Resin Infusion

A PMC plate was first made from LRI fabrication method and then cut in the desired shape (250x50 mm²) using a Computer Numerical Control machine (Charlyrobot). In order to test the validity of the smart specimen, several pristine specimens were also manufactured. The composition of the plate was :

* Fibers: 22 plies of glass fibers 2/2 twill fabric (Gazechim Composites: 0.2mm of thickness);

* Resin: Orthophtalic unsaturated polyester resin (pre-accelerated) Norester 822 for infusion (Nord Composites) with a degassing pressure of -0.4bar during 4min and an injection pressure or -0.8bar during the LRI;

* Harderner: 1% wt. of methyl ethyl ketone peroxide (MEKP) ketanox B180 (C.O.I.M s.p.a.);

### 2.2. Piezoelectric transducers and insertion

In this work, 9mm in diameter and 80µm in thickness PZT (Wealthland) were used and embedded within the PMC plate during the LRI. Such piezoceramic materials can be used both as actuators and sensors, thanks to their high piezoelectric properties (Figure 1).

<figure><img src="image_1.png" /><figcaption>**Figure 1.** PZT transducers.</figcaption></figure>

Three PZT transducers were integrated into the middle plane of the specimen:

* Two separated by 200mm distance with equal distance from the center of the specimen;

* One in the center of the plate;

As piezoceramic is known to be fragile, the localization into the middle plane was made in order to limit the risk of breaking a PZT. Indeed, during a bending test, the middle plane is the position through the thickness where the flexural stress will be the lowest (theoretically named as neutral fiber, where the positive and negative stress, due to the compression of the top and the tension of the bottom, join to be equal zero). This results in a full plate composed of specimens, either pristine or smart, embedding three PZT each (Figure 2).

<figure><img src="image_2.png" /><figcaption>**Figure 2.** Pristine and smart specimens, embedding PZT transducers.</figcaption></figure>
**3. Self-heating four-point bending test**

**3.1. Setup**

A servohydraulic testing system Landmark 370.10 (MTS) was used to perform these tests with a speed of 1mm/min during the loading and unloading phases, and a frequency of 5Hz during the fatigue cycling steps. The roller diameter was 10mm, the lower rollers were spaced 150mm apart and the upper rollers 50mm apart, following the L/3 four-point bending test procedure. The deflection of the specimen was measured from a laser and two longitudinal strain gauges were positioned on the upper and lower faces. In order to compare internal and external AE, two micro-80 AE sensors (Physical Acoustics Corporation) were positioned on the lower surface of the specimen (same position as the two embedded PZT). For the fatigue limit evaluation, three T-type thermocouples are used: one placed on the specimen, one on the lower roller and the third one on the upper roller, this gives the possibility to take into consideration the increase of the support temperature during the test. The capacitance of the transducers is measured during the test using an LCR Bridge HM8118 (Rohde & Schwarz). Finally, an AFG-3021 generator (Tektronix) and a DSO-X 2002A oscilloscope (Agilent Technologies) are used to generate and save the ultrasonic waves. The generated ultrasonic waves were modulated sinus, with 10Vpp amplitude and a varying frequency from 50 to 250kHz (Figure 3).

<figure><img src="image_3.png" /><figcaption>**Figure 3.** Setup and acquisition devices.</figcaption></figure>

**3.2. Procedure**

Preliminary, several specimens were tested under monotonic loading at 1mm/min, in order to obtain the mechanical behavior of the specimen to build the self-heating protocole. It results in a breaking of the specimen around 2350N ($F_{max}$) with a deflection of 13mm, and loss of linear slope starting around 1500N ($F_e$) and 8mm of deflection.

Based on these findings, we proceeded to conduct 8 cycles under the $F_e$ level, with each cycle experiencing an increase of 103N until failure. The fatigue ratio was set at 0.1, with a frequency of 5Hz for 5000 cycles. During each cycle, the specimen was loaded at a speed of 1mm/min until reaching the desired value, signaling the start of fatigue. Upon completion of the 5000 cycles, the specimen was unloaded back to 0N at the same loading speed. Subsequently, we allowed the specimen to return to its initial temperature before commencing the next cycle.

The procedure for the NDT multi-acquisition was :

* Before: US for the smart specimens (to get “healthy” data), several frequencies were tested: 50, 60, 100, 125, 150, and 200kHz (similar for every US of the test);

* During one cycle:

* Pristine specimens: thermocouples, AE (external), laser, gauges;

* Smart specimens: thermocouples, AE (internal and external), laser, gauges, capacitance (measured from the middle sensor);

* End of one cycle (before launching the following cycle):

* Pause the AE and perform the US measurements for the smart specimens;
# 4. Results and discussion

## 4.1. Rapid fatigue limit estimation

The stabilized temperature and capacitance showed a similar tendency over the cycles, a gradual and small increase of the stabilized value over the first cycles and a bigger increase for the last cycles (Figure 4). According to the classic self-heating tests with temperature measurement, this behavior can be divided into two distinct lines with different slopes, the intersection of these two lines will be the approximate fatigue limit.

<figure><img src="image_4.png" /><figcaption>**Figure 4.** Capacitance and temperature variations during the self-heating four-point bending test.</figcaption></figure>

## 4.2. Structural Health Monitoring

The comparison of the internal and external AE sensors shows a very similar trend, high amplitude and energy for the last two cycles (Figure 5). This shows that the PZT can be used as an efficient sensor for AE measurement.

<figure><img src="image_5.png" /><figcaption>**Figure 5.** Amplitude and Cumulative Absolute Energy (CAE) of the AE from the (a) external (micro-80) and the (b) internal (PZT) sensors.</figcaption></figure>

In the ultrasonic shots, many damage indicators can be used (the loss of the propagation velocity, the loss of US amplitude, ...), we can see on Figure 6 the loss of the maximum amplitude for the frequency of 125kHz. The signal slowly and gradually loses amplitude over the cycles.
<figure><img src="image_6.png" /><figcaption>**Figure 6.** Loss of the maximum amplitude of the US.</figcaption></figure>

As seen in the previous section, the capacitance variation followed the load/unload and cycling phases, several damage indicators could be extracted from this behavior: such as the slope measurement during the loading and unloading phases.

**5. Conclusions**

These preliminary results were obtained during a self-heating four-point bending test and they show promising possibilities. The in-situ PZTs showed efficiency in monitoring the health of the structure as well as obtaining useful information about the mechanical properties of the structure itself (fatigue limit). However, deeper analysis and data processing should still be done, such as damage indicator definition, and data fusion process development to improve the robustness of the SHM diagnostic. Once the procedure is mastered, it will be interesting and challenging to move towards more operational structures.

**References**

[1] Tuloup C, Harizi W, Aboura Z, Meyer Y. Integration of piezoelectric transducers (PZT and PVDF) within polymer-matrix composites for structural health monitoring applications: new success and challenges. *Int J Smart Nano Mater* 2020;11:343-69. https://doi.org/10.1080/19475411.2020.1830196.

[2] Harizi W, Tuloup C, Aboura Z. Evaluation of the crosslinking steps of an unsaturated polyester resin during the infusion process of polymer-matrix composites using embedded PZT transducer. *ESAFORM* 2021, *PoPuPS* (University of LiFge Library); 2021. https://doi.org/10.25518/esaform21.2693.

[3] Harizi W, Aboura Z, Meyer Y, Tuloup C. Structural Health Monitoring of smart Polymer-Matrix Composite during cyclic loading using an in-situ piezoelectric sensor. *ICCM22, Melbourne: 2019*.

[4] Tuloup C, Harizi W, Aboura Z, Meyer Y. Structural health monitoring of polymer-matrix composite using embedded piezoelectric ceramic transducers during several four-points bending tests. *Smart Mater Struct* 2020;29. https://doi.org/10.1088/1361-665X/abbc59.

[5] Tuloup C, Harizi W, Aboura Z, Meyer Y, Khellil K, Lachat R. On the manufacturing, integration, and wiring techniques of in situ piezoelectric devices for the manufacturing and structural health monitoring of polymer-matrix composites: A literature review. *J Intell Mater Syst Struct* 2019;30:2351-81. https://doi.org/10.1177/1045389X19861782.

[6] Tuloup C, Harizi W, Aboura Z, Meyer Y, Khellil K, Lachat R. On the use of in-situ piezoelectric sensors for the manufacturing and structural health monitoring of polymer-matrix composites: A literature review. *Compos Struct* 2019;215:127-49. https://doi.org/10.1016/J.COMPSTRUCT.2019.02.046.

[7] Tuloup C, Harizi W, Aboura Z, Meyer Y, Ade B, Khellil K. Detection of the key steps during Liquid Resin Infusion manufacturing of a polymer-matrix composite using an in-situ
piezoelectric sensor. Mater Today Commun 2020;24:101077.
https://doi.org/10.1016/J.MTCOMM.2020.101077

[8] Harizi W, Aboura Z, Meyer Y, Tuloup C. Real-time monitoring of the infusion process of a Polymer-Matrix Composite with an embedded piezoelectric transducer. ECCOMAS, 2019.

[9] Dolbachian L, Harizi W, Aboura Z. Structural Health Monitoring (SHM) Study of Polymer Matrix Composite (PMC) Materials Using Nonlinear Vibration Methods Based on Embedded Piezoelectric Transducers. Sensors 2023;23. https://doi.org/10.3390/s23073677.

[10] Najd J, Harizi W, Aboura Z, Zappino E, Carrera E. Rapid estimation of the fatigue limit of Smart Polymer-Matrix Composites (PMC) using the self-heating tests. Compos Struct 2022;282:115039. https://doi.org/10.1016/J.COMPSTRUCT.2021.115039.