OPTIC-BASED PATCH SENSOR FOR
STRUCTURAL HEALTH MONITORING IN
REINFORCED CONCRETE STRUCTURES

Olivier Plé, Yago de Souza Gomes, Mohamed Saidi, Anna Lushnikova, S.Y. Mohseni, Martin Richaud, Marie Allain, Didier Briand

► To cite this version:

Olivier Plé, Yago de Souza Gomes, Mohamed Saidi, Anna Lushnikova, S.Y. Mohseni, et al., OPTIC-BASED PATCH SENSOR FOR STRUCTURAL HEALTH MONITORING IN REINFORCED CONCRETE STRUCTURES. THE 2nd INTERNATIONAL SYMPOSIUM ON ADVANCED MATERIALS AND DESIGN FOR STRUCTURAL SAFETY AND SUSTAINABILITY, Feb 2025, Lyon, France. hal-04969438

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OPTIC-BASED PATCH SENSOR FOR
STRUCTURAL HEALTH MONITORING IN
REINFORCED CONCRETE STRUCTURES

O. Plé¹*, Y. De Souza¹, M. Saidi¹, A. Lushnikova¹, S.Y. Mohseni¹, M. Richaud²,
M. Allain³, D. Briand⁴

¹ Université Savoie Mont Blanc, LOCIE, CNRS UMR 5271, Le Bourget du Lac, France.
olivier.ple@univ-smb.fr

²Brochier technologies, 90 Rue Frédéric Fays, 69100, Villeurbanne, France.
martin.richaud@brochiertechnologies.com

³ Léon Grosse, 10 Boulevard de Russie, 73100 Aix-Les-Bains.
m.allain@leongrosse.fr

⁴ INOUiD, Pepinière de Valpré, 69130 Écully.
dbriand@inouid.com

**SUMMARY:** Nowadays accidents on bridges and buildings are regular and could intensify with climate change. In these conditions, it seems imperative to monitor civil engineering structures for accident prevention. In the majority of cases, problems occur because of damage to concrete. Cracks can appear under different conditions like mechanical disorder, the presence of water, and/or thermal expansions. This contribution is focused on the monitoring of cracks. For that, a consortium of 4 entities (Leon Grosse, Brochier Technologies, INOUid, and the laboratory LOCIE of the University Savoie Mont Blanc) has worked together through the SENTMI project. This work focuses on the development of a new sensor, based on the weaving of optical fiber developed by Brochier Technologies for reinforced concrete structures. This sensor can be embedded within superstructures or glued on the concrete's surface. Different from Bragg or Rayleigh fibers, this PMMA sensor's technology consists of a fabric featuring an optical fiber network that works with lateral light transmission. A displacement, like a crack that opens, implies a spread between a transmitting fiber and a receiving fiber, that induces a signal emission. The aims of this innovative sensor are numerous: detecting cracks, remotely tracking data over time, long-lasting during time and environment, sending alerts, low energy consumption, and less intrusive during set up and use. This sensor, when used in concrete structures, can detect opening cracks in the order of 0.01 mm in the laboratory with high precision, meeting regulatory standards of limit states (Eurocode2). It can accurately track crack evolution, including cyclic changes, by sensing both crack width increase and decrease. The procedure outlined in this paper includes a preliminary investigation into the influence of fiber diameter and density within the patch, as well as the attachment method to concrete surfaces, to select an optimal sensor configuration. Subsequently, the process of calibration is detailed, followed by numerous laboratory tests that were conducted on reinforced concrete samples of varying sizes. Comparisons and validations of optical fiber patch sensor measurements were performed using Digital Image Correlation. The concluding remarks of this paper may facilitate the consideration of deploying this new sensor both externally and internally within real reinforced concrete structures.

**KEY WORDS:** embedded sensors, structural health monitoring, optical fiber sensors, crack detection, sensing technologies, digital image correlation

# 1. INTRODUCTION

The monitoring of reinforced concrete structures is becoming more and more important. Fiber optic, piezoelectric, electrochemical, wireless and self-sensing technologies, and other numerous techniques for
structural health monitoring are currently used to enhance the reliability of concrete infrastructures and their operational lifespan [1]. Damages in concrete structures are often characterized by the presence of cracks. A commonly used diagnostic criterion is the crack width threshold to assess the risk associated with cracks in concrete structures. This threshold serves as an indicator of the severity of the crack and aids in determining the appropriate course of action. The specific crack width threshold varies depending on the type of structure and its intended purpose. Generally, Eurocode 2 considers a crack width threshold of approximately 0.2 mm acceptable for most structures [2]. Structural Health Monitoring (SHM) was defined by Villalba S, Casas J (2004) [3] as strategies for continuous or regular measurement and analysis of key structural and environmental parameters under operating conditions, for warning of abnormal states or accidents at early stages. Presently, there is a shift towards more intelligent surveillance methods characterized by remote monitoring in real-time, featuring automatic reports and alert systems, where deformation sensors play a crucial role [4]. Fiber optic-based sensors for deformation have emerged as a very interesting solution, transforming the field of structural health monitoring. Despite the existence of traditional and well established deformation sensors like strain gauges, linear variable differential transducer (LVTD), or vibrating wire strain gauges, fiber optic (FO) sensors offer several advantageous properties such as their lightweight and electromagnetic passiveness, and flexible installation. Among the technologies that are based on fiber optics, some can be highlighted, such as The Fabry-Pérot interferometer sensor [5] or the fiber Bragg grating sensor [6]. Another noteworthy technology is the distributed optical fiber sensor, commonly based on Rayleigh scattering or optical time-domain reflectometry (OTDR), which has the capability of continuously monitoring the entire length of the fiber, thus, for kilometers [7]. In this work, a new type of fiber optic-based sensor, that can be embedded in the concrete or attached to its surface, is presented, and its performance is analyzed. It consists of a textile where fibers are woven parallel to each other, intercalating fibers connected to a light source and fibers connected to a photosensitive dispositive that provides accurate Correlated Colour Temperature (CCT). The signal is then obtained by the rays that escape from the emitting fiber and entere a receiving fiber due to the intentional creation of surface irregularities. The detailed attributes of this 2D optical patch sensor are outlined in French Patent No. 3067806, officially registered under No. 1755382 [8]. Both the embedded and on-surface patch sensors will be discussed. The sensor is capable of accurately detecting opening cracks as small as 0.01 mm, within regulatory limits. It effectively tracks the progression of the crack by detecting both its widening and narrowing. An example of a real reinforced concrete structure is shown.

## 2. METHODS

### 2.1. Components description

#### 2.1.1 Light detector

The SENTMI (SENsor Textile Monitoring Infrastructures) project used a white LED OSLON SSL 150 "GW CSHPM1" (

**Figure 1-a)** and the AS7261 sensor from ams OSRAM, which is a chromatic white colour sensor that provides XYZ colour coordinates consistent with the CIE ("Commission Internationale de l'Éclairage") colour space as well as the Near Infra-Red (NIR) spectrum (
<figure><img src="image_1.png" /><figcaption>**Figure 1.** a) Sensor's LED; b) Chromatic White Color System; c) SENTMI fibre optic patch sensor</figcaption></figure>

### 2.1.2 Textile sensor

An elastane fabric incorporates PMMA-based optical fibres that are woven in a parallel configuration. In the active zone (Fig 1-c), a technique of damage is employed to create intentional flaws on the surface of the FO cladding and on the interface between the FO core and cladding. This allows the passage of light to adjacent fibres. There are two groups of optical fibers. Emitting fibers are the ones connected to the white LED, while the receiving fibers are the ones connected to the AS7261. Those two groups of fibers are arranged in an intercalated configuration [10]. The diameter of the fibres and the density of fibres are significant factors influencing the sensitivity of the textile sensor. The density is defined as the number of fibres per cm in the direction denoted as "a" in Fig 1-c.

## 2.2 Parameters of sensor configuration

The optimal configuration for the optical patch sensors was determined by examining a range of parameters, including fibre diameter, fibre density, fabric size, and light power. Fiber diameters ranging from 250 to 750 µm and densities between 7 and 26 optical fibres per cm were utilized for experimentation. Fabric of dimensions 30 × 30 mm², 50 × 50 mm², 50 × 150 mm², and 100 × 100 mm² were employed on different types of concrete samples. The findings from assessing the patch's effectiveness in detecting and measuring deformation are presented in this paper. The objective was to enhance the sensor configuration, aiming to improve sensitivity. The sensitivity is defined as the amount of displacement between the two edges of the sensor required to alter spectral coordinates by one unit. Considering these parameters, the initial configurations selected for further investigation were fibres with a diameter of 500 µm and a density of 18.5 fibres per cm (Fig 2).

<figure><img src="image_2.png" /><figcaption>**Figure 2.** Comparison of the displacement needed for varying light signal by one unit</figcaption></figure>
The dimensions were selected based on of their suitability for use in the testing and calibration process. Given the dimensions of the specimens and the clamps employed in the calibration cycles, the 30 × 30 mm² and 50 × 50 mm² patches were deemed appropriate.

## 2.3 Patch calibration

A calibration procedure was developed using digital image correlation as a means of comparison and validation. The calibration procedure is under the french patent number B256-B-69739 "Détecteur de déformation à base de fibres optiques, et procédé de calibration d'un tel détecteur" [10]. A series of patch configurations were subjected to uniaxial cycles tensile tests at a rate of 0.5 mm/min (Fig 3). The sensor demonstrated excellent reproducibility, producing identical light signal outputs when decreasing CCT during stretching and recovering it upon returning to its initial tension state. Therefore, the response is not strictly linear and an adjustment is required. The adopted calibration procedure, which is to be applied to all the patches, consists of performing one extended stretch of 8 mm and a return to the initial position, three times. This procedure is undertaken in order to derive the correlation equation through polynomial regression (Fig 3). The post-treatment of the patch signal includes considering the initial value of the light signal as the initial value.

<figure><img src="image_3.png" /><figcaption>Figure 3. a) Patch calibration; b) Equation of calibration</figcaption></figure>

## 2.4 Surface attachment method

The patches have been modified to include additional fabric borders surrounding the area where the glue is applied (Fig 4-a). This method was applied due to concerns about potential reinforcement effects on the crack and sliding movements resulting from the interaction of the glue with the patch in the fracture zone. The adhesive is applied at a distance from the active zone (Fig 4-a). However, due to the highly deformable nature of the tissue material, the non-active zone between the fibres and the adhesive zones (Fig 4-b) will absorb a portion of the overall deformation, resulting in an underestimation of the crack width.

For elastic materials, the ratio between the displacement ΔL and the initial length (L₁ + L₂) (Fig 4-b) is expressed as strain ε = ΔL/(L₁ + L₂). As the patch consists of two materials ΔL can be expressed in terms of strains and lengths as ΔL = ε₁.L₁ + ε₂.L₂ (Fig 4-b). If the modulus of elasticity are equivalent in the active zone and non-active zone ΔL₁ can be presented as ΔL₁ = ΔL. [L₁/(L₁ + L₂)]. The current gluing method employs an installation device, serving as a frame to ensure standardized patch application (Fig 4-c). The utilization of the device ensures a consistent pre-tension. This aspect is crucial to systematize the method and minimize the risk of errors.

<figure><img src="image_4.png" /></figure>
<caption>**Figure 4.** Gluing method: a) Principle; b) Displacement; c) Device</caption>

**2.5 Embedding method**

If the preceding technique is reserved for monitoring existing infrastructures, the patch can also be incorporated into new reinforced concrete structures during construction (Fig 5-a). An important difference between the operating principle of embedded patches and on-surface patches is that, when embedded, only cracks that occur in the active zone will be detected by the patch. The crack, as a discontinuity, occurring outside of the active zone will not result in the deformation of this zone. Moreover, this discontinuity results in the displacement of a limited number of fibres, one to the other, instead of a global strain throughout the active zone. In patches glued on the surface of the sample, the active zone is not bonded to the concrete. Consequently, any displacement between the two bonded zones results in a uniform displacement among the fibres. Conversely, in patches embedded within the concrete, the active zone adheres to the structure. Consequently, when a crack occurs, it induces localized deformation of the patch, resulting in localized displacement among a small number of fibres within the fracture zone.

<figure><img src="image_5.png" /><figcaption>**Figure 5.** a) Embedded method; b) Samples type 1 and 2; c) Samples type 3</figcaption></figure>

**2.6 Performance assessment method**

A crack in a material is a discontinuity caused by the failure of atomic bonds to withstand forces [11]. In concrete, crack opening is a complex mechanical process influenced by material characteristics, loading conditions, and environmental factors. Cracks evolve from microcracks into visible fissures. Initially, crack width is often microscopic and invisible to the naked eye, but it can expand as the load increases. The initial crack width varies based on factors such as the applied load, concrete's tensile strength, reinforcing elements, grain size, notches and defects, confinement arrangement, aspect ratio, and other geometric attributes [11,12]. The evaluation methodology encompasses several steps, including the fabrication of prismatic concrete samples of varying dimensions, the implementation of a calibration procedure, the attachment of the calibrated patch to the concrete sample, the mechanical testing of the sample to induce cracks, and an assessment of crack measurement accuracy through the use of Digital Image Correlation. This study utilized 40 samples measuring 10 cm × 10 cm × 40 cm (Fig 5-b), 8 samples measuring 15 cm × 15 cm × 60 cm (Fig 5-b), and 3 beams measuring 15 cm × 25 cm × 330 cm (Fig 5-c) respectively. The concrete is designed to meet the specifications of C30/37 for severe exposure classes according to NF EN 1992-1-1 [2] regulations. To induce cracks in the region of interest, notches with a height of 2 cm were created in the sample for specimen types 1 and 2 (Fig 5-b).

In this investigation, both Type 1 and Type 2 samples exhibited identical aspect ratios and notch sizes. However, type 2 samples were manufactured in two distinct configurations: with high-adhesion steel bars (reinforced) and without (non-reinforced). The reinforcement of type 2 specimens entailed the incorporation of two 8 mm diameter high-adhesion steel bars at the lower portion of the sample. Furthermore, three beams with no notches were reinforced (consisting of three 8 mm diameter high-adhesion steel bars at the lower section of the sample), with one of them additionally reinforced at the bottom surface with a layer of carbon-fibre-reinforced polymer (CFRP). CFRP, renowned for its
exceptional properties, including lightweight, high strength, and resistance to high temperatures, holds
significant promise for diverse applications across various fields, like structural repairs [13]. Following
calibration, the patches were attached to the surfaces of the specimens and subjected to a three-point
bending test, a methodology similar to that employed by Gkantou M. et al. (2019) and Cimellaro G. P. et
al. (2019) [14,15] in their investigation of crack detection in reinforced concrete structures. Specimens
of types 1 and 2 were positioned symmetrically between two parallel supports and subjected to bending
using a uniaxial displacement-controlled testing machine. The loading rate was 0.5 mm/min, and it was
applied specifically to the central region of the sample adjacent to the upright section of the notch. In
contrast, beams (type 3) underwent a stress-controlled three-point bending test at a rate of 0.05 kN/s.
These modes dictate how the test is conducted and how data is gathered. In a displacement-controlled
test, the testing machine applies a constant displacement rate to the specimen by moving the loading point
at a predetermined speed. The resulting data is a function of the applied displacement and the force
exerted. In a stress-controlled test, the testing machine is responsible for maintaining a specific force
level or load on the specimen. One disadvantage of a displacement-controlled test is that the device
controls the opening crack, which may not accurately reflect real-world conditions.

A 2D Digital Image Correlation (DIC) technique was applied to validate the performed calibration, utilising a NIKON D7000 camera with a 60 mm focal length. In mechanical testing, DIC can be applied through few different methods [16,17]. It is a non-destructive optical technique [18,19] that relies on a series of high-resolution images captured during deformation, at a specified frame rate. The process commences by applying a random speckle pattern on the specimen's surface, which serves as unique identification marker (Fig 5-a and Fig 5-c). As the material undergoes deformation, the camera captures images of the speckle pattern at various stages. The spatial shifts of pixels between the initial and deformed states are tracked by correlating their array of neighbouring pixels [20]. This technique allows for the computation of full-field displacement and strain maps, revealing localized deformations and strain distributions with high spatial resolution. DIC measurements can detect changes as small as a single pixel or even sub-pixel, in the order of 0.01 to 0.1 pixels. In ideal conditions, the accuracy of DIC displacement measurements can be in the range of 1 to 5 µm, or 0.01% of the field of view. Nevertheless, the precise physical length represented by this measurement will vary depending on factors such as the resolution of the camera and its distance from the surface being measured. Following the guidelines provided in the DIC Good Practices Guide by the International Digital Image Correlation Society (2017) [21], this study adopted a 2D-DIC approach. It is assumed that the sample maintains planar characteristics and a consistent stand-off distance throughout the testing process. To generate an appropriate speckle pattern for analysis, a white background colour was uniformly applied to the region of interest (ROI). Subsequently, black circular speckles were randomly superimposed on the white background in order to guarantee adequate contrast (Fig 5-a). In this study, a frame rate of 0.2 fps and an exposure time of 1/500 seconds were selected. The captured images have a resolution of 300 dpi and a size of 4928 × 3264 pixels. The images were subsequently processed using GOM Correlate 2018 software [22]. In this scenario, the Region Of Interest (ROI) corresponds to the surface area adjacent to the crack, and the height of the ROI is the height of the textile sensor. This height limitation dictates the extent to which the fiber optic textile can sense and respond to deformation. The dispositive will sense the overall deformation, which is the incremental distance from the left edge to the right edge of the textile. In bending tests, such as the three-point bending test, the crack width varies; it is wider at the bottom and narrower at the top, forming a triangular shape (Fig 6). The patch yields a single measurement representing the average crack width, as the variation in crack width relative to height is nearly linear. Consequently, the patch provides the crack width value for the mid-height.

<figure><img src="image_6.png" /></figure>
<caption>**Figure 6.** 2D-DIC at GOM Correlate 2018 Software: a) sample size 10×10×40 cm³; b) Reinforced beam</caption>

Python modeling environment was utilized to transform the export files from the sensor and DIC analysis into a graphical comparison. This post-processing includes reading both CSVcsv files (from the sensor and from DIC exports), fixing the initial absolute value of the light signal as zero, and applying the equation of calibration on the values of increment in light signal to obtain an output in millimeters, and plotting both lines in a single graphic.

# 3. RESULTS

## 3.1 Crack detection

The diverse characteristics of the samples result in distinct patterns of crack initiation and propagation. One notable distinction lies in the width of the crack upon its initial opening. This disparity in crack width is not only attributed to differences in sample characteristics but also to the inherent heterogeneity of concrete as a material. It is of great importance to examine such variations in crack width at the onset of opening, particularly given the crucial role of the sensor in detecting sudden crack openings or rapid crack developments, in addition to gradual and smooth crack propagation. It is observed that these sudden crack openings are observed predominantly present in specimens lacking reinforcement, which constitute the majority of samples utilized in this study (type 1). For samples of type 3, the crack progresses from a microscopic to a macroscopic manifestation. Measurements conducted via digital image correlation reveal that the type 3 samples exhibited an initial crack width of 3.5 µm, whereas the type 1 samples displayed an initial crack width of 1.078 mm. In consideration of the sensor's demonstrated sensitivity, when installed on the beam, the patch is capable of detecting a gradual increase in crack width from the onset. With a sensitivity of 0.004 mm/K for the patch affixed to the beam and a force rate of 0.05 kN/s, an average increment of 1 unit of light spectral coordinates occurs approximately every 14 seconds (Fig 7-a). Conversely, for specimen type 1, the patch registers crack opening as an almost instantaneous displacement of approximately 1 mm. In this instance, a sensitivity of 0.07 mm/K is obtained for the patch in use, resulting in an increment of 15 units of CCT within 1.09 seconds, which represents the sensor's acquisition time (Fig 7-b).

<figure><img src="image_7.png" /><figcaption>**Figure 7.** Crack detection: a) Type 3; b) Type 1</figcaption></figure>

## 3.2 Crack width evolution track

The light signal measurements collected over time by the patch, along with the crack width measurements at mid-height of the patch position, obtained via Digital Image Correlation, underwent processing using Python, allowing for the application of correlation equations. Enhancements in patch configurations have significantly improved the sensor's sensitivity. Through refinement of these configurations, a sensor sensitivity of 0.004 mm/K and an accuracy of 0.1% to 1% has been achieved, as shown in Fig 8. This figure presents graphs, where each of them corresponds to the result of one flexural test in a specimen,
comparing the sensor measurement (blue line) of crack width to the Digital Image Correlation corresponding measurement of crack width (red line). Measurements were conducted on samples of different types and sizes, as indicated in each image. Here, sensor sensitivity denotes the minimum increase in crack width (in mm) necessary to result in one unit change in CCT.

<figure><img src="image_8.png" /><figcaption>**Figure 8.** SENTMI sensor performance in following crack width</figcaption></figure>

Upon examination of the curves, it becomes evident that the patch signal closely mirrors the onset and advancement of the crack. The curves exhibit a high degree of alignment. Periodic abrupt increases occur sometimes (Fig 8-a) **erreur ! Source du renvoi introuvable**. due to material heterogeneity. The patch efficiently tracks both the gradual evolution and sudden spikes in crack width, demonstrating its capability to accurately capture these fluctuations and providing valuable insights into crack behaviour.

## 3.3 Cyclic test

It is crucial not only to monitor the evolution of crack openings, i.e., the increase in crack width, but also its converse, the decrease in crack width. The capacity of these sensors to measure displacements in both tension and compression modes is indispensable for a thorough understanding of structural integrity. For this test, a carbon-fiber-reinforced polymer (CFRP) layer was appropriately utilized to reinforce the bottom (tensile area) of the beam. Apart from its utility in repair applications, this beam has an advantage: due to the presence of the carbon layer, it could withstand higher loads across numerous load and unload cycles, facilitating cyclic testing. The elastic properties of CFRP enable the cracks to nearly close during unloading. The high strength of this material enables it to deform elastically under stress and revert to its original shape upon stress removal, given the applied loads [23]. In order to evaluate the beam reinforced with a layer of CFRP, a force-controlled three-point bending test was conducted. Initially, a pre-charge of 3.2 kN was established. From this point, the load progressively increased to 10 kN, then returned to 3.2 kN, repeating this cycle three times. Subsequently, three additional cycles were performed, with the load reaching 18 kN before reverting to 3.2 kN. Finally, three additional cycles were conducted, elevating the load to 26 kN before returning to 3.2 kN. The sensor exhibited reliable performance, accurately tracking the crack's progression during both opening and closing phases, although limited by the patch's sensitivity, set at 0.05 mm/K for this test.

## 3.4 Embedded patches

The capacity to function within the internal structure of concrete is a critical attribute for a displacement-measuring sensor. The embedded SENTMI patches demonstrated consistent performance comparable to their on-surface approach version, effectively monitoring the progression of cracks with a similar Mean Relative Error (MRE) that the best on-surface patches presented, ranging between 0.1% and 1%. Results are presented in Fig 9 on samples tested under two different configurations for density and diameter of optic fibres.

<figure><img src="image_9.png" /></figure>
<caption>**Figure 9.** *Results of crack width evolution for embedded patches*</caption>

**4. CONCLUSION**

This work presents the initial key discoveries of a new fibre optic-based sensor developed for structural health monitoring. The sensor patch, which can be embedded or affixed on a concrete structure surface, comprises a textile component containing two sets of optical fibres: one set linked to a light source (emitting fibres) and the other to a light sensor (receiving fibres). The deformation of the textile causes spectral coordinate variations, measured in correlated colour temperature, providing crucial data for structural assessment. Initially, the study concentrated on identifying configurations capable of achieving a sensitivity under the limits of recommended crack width limits, thus enabling the detection of minor displacement. Sensitivity is defined as the amount of displacement between the two edges of the sensor required to result in the variation of the spectral coordinates by one unit. Therefore, the most sensitive sensors present a lower amount of displacement needed for measurement variation. The parameters under analysis included the diameter of the optical fibres, the density of optical fibres per cm, and the dimensions of the fabric. It was observed that larger diameters and higher densities of optical fibres were associated with stronger light signals and enhanced sensor sensitivity. As a result, the optimal configuration was determined to be optical fibres with a diameter of 750 µm and a density of 11.5 fibres per cm. This density represents the maximum number of fibres of this diameter that can be accommodated within a width of 1 cm. The installation methods for textile sensors on concrete surfaces were investigated. The glue was applied 2.5 cm from the edge of the active zone. Once the optimal sensor configuration and its installation system has been identified, calibration was carried out. A series of stretching and releasing cycles was conducted to compute the equation of correlation via polynomial regression. The calibration was followed by the application of the textiles to concrete specimens of varying dimensions. These samples underwent a three-point bending test to induce cracking, after which the performance of the sensors was evaluated using digital image correlation. The mean relative error for the embedded and glued patches across all sample types was found to be between 0.1% and 1%. The diverse geometry and reinforcement of the specimens enabled the sensor to demonstrate its capacity to detect both gradual and abrupt crack initiations. The progression of the cracks, including both the opening and closing phases, was analyzed. The preliminary results are promising, with a sensitivity of up to 0.004 mm/K and a mean relative error for the embedded and glued patches across all sample types was found to be between 0.1% and 1%.

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