Integration of Piezoresistive Sensors into AM Structural Components: Evaluation of Sensor Properties and Its Impact on Component Mechanical Performance

Additive manufacturing (AM) technology has experienced significant growth in recent years, opening new prospects across various sectors, from biomedicine to aerospace. Among these, the Fused Filament Fabrication (FFF) additive manufacturing technology, which deposits material layer by layer, enables the integration of piezoelectric material during the printing process, thereby allowing for the creation of sensors within thermoplastic components. Such sensors have the potential to monitor and detect various internal physical parameters within the component at locations inaccessible to traditional sensors. In this field, scientific research is continuously advancing, primarily aimed at developing sensors with high performance. In this context, the objective of this study is to assess the measurement properties, both static and dynamic, of sensors produced using this technology and to evaluate the influence on the static and dynamic behavior of the component caused by the incorporation of these sensors within the component itself.


Introduction
Additive Manufacturing technology, with its capability to produce objects of complex geometries, has opened new frontiers in design.One of these frontiers is the ability to integrate sensors during the component production process [1] [2].By depositing material layer by layer [3], it allows for precise control over the manufacturing process and the creation of each individual layer.Moreover, it offers the advantage of incorporating different material layers at specific points within the structure, enhancing its functionality and potential applications.
This perspective finds applications in diverse fields [4], starting from the biomedical domain, where highly sensitive sensors have been studied for integration into wearable devices to monitor movement [5], all the way to environments like aviation [6] and aerospace [7].It can also have relevance in everyday life, such as the ability to incorporate small Internet of Things (IoT) sensors into the Gravity Separation Spirals (GSS), enabling remote monitoring of operational conditions, prediction of failures, and utilization of collected data for production optimization [8].
As of today, the significant advancement in 3D printing technology has made it possible to have multiple extruders on the same machine, which can print different materials.This capability 1306 (2024) 012021 IOP Publishing doi:10.1088/1757-899X/1306/1/012021 2 allows for the simultaneous production of both the component and the integrated sensor in a single printing process.This not only enables designers to determine sensor placement in advance during the design phase but also facilitates their introduction into positions that are not normally accessible through external sensors.
The emerging frontier of embedded sensors for measuring parameters such as temperature and deformation, which can be used in algorithms for damage calculation and remaining component life, marks a turning point in structural monitoring [9] and early fault detection [10], especially in dynamic environments [11].
Structural monitoring is indeed a fundamental component in the realm of dynamic design, ensuring the safety and longevity of structures while reducing maintenance costs and risks to public safety.These measures are especially critical in civil or aerospace contexts where they are used for transporting people.However, they are also of paramount importance in situations where human lives are not directly at stake, such as in the aerospace industry.In such cases, mission failures can result in significant economic losses and safety concerns due to space debris.
The development of printed sensors directly during the printing process has become possible thanks to the advancement of new materials, such as Conductive PLA, that is a thermoplastic material primarily composed of polylactic acid (common PLA) filament with the introduction of conductive particles within it to make it electrically conductive.Commonly used conductive materials include graphite powder, carbon black (CB) powder, carbon fibers (CF), or carbon nanotubes (CNT) [12].The conductive particles are evenly distributed within the filament during the production phase, and the material's conductivity properties can vary depending on the quantity and dispersion of these particles [13].The resulting filament is, in essence, a piezoresistive material, meaning that its resistance changes proportionally to the deformation applied to the object.
In the literature, there are already studies on sensors created using this type of material that have led to the development of printed sensors for measuring deformations with the classical form of a strain gauge, assessing their functionality [14], the effects of certain printing parameters [15], and conducting studies on the impact of their integration within components and their reproducibility in a static environment [16].
Given the potential of this application, studies have also been conducted on sensors with temperature compensation [17] and on possible applications in high-temperature environments [18].
Indeed, the development of a printed sensor in Additive Manufacturing requires a comprehensive characterization of the material, both from a mechanical and electrical perspective [19].This characterization is essential to ensure the functionality of the sensors.
The purpose of this work is to dynamically characterize a printed sensor of any shape using conductive PLA.The goal is to measure the deformation of a component subjected to dynamic loads, essentially creating a printed "strain gauge."This will be achieved by evaluating its linearity, repeatability, and assessing the range of usability before it is integrated into a structural component.

Dynamic Characterization
The environment in which the printed sensor operates is primarily subjected to dynamic loads and vibrations; therefore, the sensor must be capable of differential measurements.For these reasons, a dynamic characterization of the sensor has been conducted.
Dynamic characterization is very similar to static characterization, with the difference that the inputs vary over time.However, the quantities being defined are essentially the same, and they are used to assess the sensor's performance and make comparisons with other measuring instruments to determine the most suitable one.
The investigated characteristics are as follows: • Linearity: the sensor's ability to provide responses that follow a linear trend with increasing inputs.• Repeatability: it indicates the sensor's ability to provide the same result for the same input.Typically, repeatability is quantified by evaluating the maximum standard deviation of responses for the same input.• Usable Range: it represents the frequency range within which the sensor can accurately measure.This is used to define the measurement linearity range and the upper and lower limits To determine these characteristics, a rectangular test specimen measuring 150 mm x 25 mm x 5 mm was created, printed in Red PLA.Within this specimen, a rectangular sensor measuring 10 mm x 5 mm x 1 mm, was fabricated using conductive PLA, as depicted in the Figure 1.
The chosen printing parameters were optimized for PLA printing [8] [20] and for conductive PLA, the parameters recommended in the datasheet were used [21].The printing directions selected were ± 45°for the red PLA and 90°for the conductive PLA, so that the deposited filament was parallel to the longer dimension of the test specimen.To perform the dynamic characterization, an electrodynamic shaker was used for linearity and repeatability tests, and an instrumented hammer was used to analyze the frequency range within which the sensor can measure.

Dynamic analysis: Linearity and Repeatability tests
The dynamic tests were conducted using an electrodynamic shaker, which allows for the imposition of defined displacements, providing control over the test.One end of the test specimen was kept fixed, as depicted in the diagram in Figure 1a, while the other end was connected to the shaker.
Since the study pertains to dynamic measurements, the test specimen was excited using a sinusoidal signal with constant amplitude and frequency.Consequently, the test specimen underwent a dynamic flexural test.
In Figure 1b, the operating diagram of the test and the data acquisition system is shown.The shaker is controlled through a data acquisition system (LMS), which utilizes an accelerometer positioned at the base for closed-loop operation.Additionally, the same data acquisition system, not only manages the shaker, but also captures the signal output from the sensor.At both ends of the sensor, tracks have been placed, from which two copper wires extend and are connected in parallel to a resistor, resulting in a total output resistance of 120 Ω from the sensor.Before the signal is sent to the strain gauge, it is routed through a Wheatstone bridge quarter-bridge system, which compensates for the signal and outputs the voltage value.This voltage value is recorded by the LMS data acquisition system.
The voltage value obtained is proportional to the deformation caused by the imposed displacement.However, the recorded signal is still in Volt, while the output from the accelerometer, which records the input signal, is in m/s 2 .Therefore, a direct comparison in terms of amplitude is not possible, only in terms of phase.This is not a problem because, in this initial investigation, the goal is to determine the sensor's response time.Upon overlaying the output signals, it becomes evident that the two signals are in phase.This indicates that the sensor is capable of measuring the deformation variation at the moment it is applied The procedure was repeated while keeping the frequency of the applied load constant and varying the amplitude value of the sine wave up to a maximum of 3 mm.This effectively covers a double range of displacement since the sine function is by definition an even function.The same procedure was also repeated for different frequency values, keeping them constant and varying the amplitude.The tests were conducted multiple times to assess the linearity and repeatability of the measurement.
The output signals from the sensor were analyzed in the time domain by averaging the maxima within the acquisition period.This process resulted in obtaining a voltage value for each different amplitude and frequency value.
The voltage values were plotted as a function of the imposed displacement for each analyzed frequency, and the results are shown in Figure 2. The graphs obtained for each frequency, as a function of various displacements, were linear and consistent across repetitions, indicating that the sensor exhibits linear behavior.In Equation 1, the law governing the strain gauges is presented.
Where e 0 and E represent the output voltage value and the voltage applied to the strain gauge, respectively, ∆R is the change in resistance of the strain gauge, and R is the initial resistance value.The voltage value e 0 is necessary to obtain information about the measurement being conducted, but a conversion factor is required to convert the voltage value from volts to strain in µstrain.This conversion factor is represented by the gauge factor K s .
The obtained curves were then related to the deformation caused by the imposed displacement value in the region where the sensor was printed.Deformation was calculated manually, taking into account all the factors that contribute to it.
Once the graph was converted into a Strain-Resistance curve, with displacement values converted to strain and voltage values using Equation 1 to obtain the resistance change ∆R/R, a linear regression was performed on this data.
The slope of the line obtained represents the gauge factor K s , and the values for the three curves are listed in Table 1.

Dynamic analysis: Frequency range
The analysis of the frequency range in which the sensor can operate was determined using an instrumented hammer, which allows for excitation of the structure up to 3000 Hz.The same test specimen used previously was employed for this test, with one end fixed and the other end left free, resembling a cantilever configuration.
To facilitate a comparison, an accelerometer was placed at the free end of the test specimen to monitor the natural frequencies of the structure.The data acquisition system remained the same as used previously, with the difference being the management of the input.
The tests were repeated 10 times, with an average of 5 hammer strikes for each test.The frequency response functions, shown in Figure 3, revealed good repeatability in the sensor's response, with the curves appearing nearly superimposed.
A direct comparison between the frequency response functions of the two instruments is not possible because they have different units of measurement, with the accelerometer using g/N and the strain gauge using Volt/N.However, to assess the quality of the measurement and the operating range, it is sufficient to analyze the peaks in the responses corresponding to the system's vibration modes Table 2 contains the values of frequencies detected by the sensor and the accelerometer, along with the error between the two measurements.
As evident from the obtained results, the sensor can capture the natural frequencies of the system with an error of less than 2% compared to a calibrated accelerometer.Furthermore, these results demonstrate that the printed sensor is capable of detecting the system's response up to at least 2000 Hz.

Conclusion
In this study, the methodology for creating an integrated sensor using Additive Manufacturing for structural monitoring and stress analysis was verified.Through the dynamic characterization process, it was possible to assess the linearity and repeatability of the measurements.Using the collected measurements, a regression line was calculated for the measurement points, allowing for the determination of the sensor's gauge factor.This gauge factor enables the conversion of measurements expressed in Volt to the actual deformation measurement.Furthermore, through a control system implemented with an accelerometer, frequency range in which the printed sensor can make measurements was assessed and found to be at least up to 2000 Hz.This work marks the beginning of a study on the creation of sensors integrated into the same 3D printing process as the component to be monitored.The next steps will involve investigating variations in printing parameters to optimize sensor performance and the miniaturization of the sensor's data acquisition system.

Figure 1 .
Figure 1.a) Experimental Setup for Dynamic Analysis Using a Shaker b) Block Diagram of the Data Acquisition System

Figure 2 .
Figure 2. Results of Dynamic Analysis: Voltage Values Acquired as a Function of Displacement

Figure 3 .
Figure 3. Experimental Frequency Response Functions for the Test with the Instrumented Hammer

Table 1 .
Values of the gage factor for three different frequencies