Paper · 2025

A self-powered vibration sensor for real-time vibration monitoring and aeroelastic instability detection in tiltrotor aircraft transition

A published study on a self-powered sensing approach for real-time vibration monitoring and aeroelastic-instability detection during tiltrotor transition.

Chengxiao Li; Yonggang Yang · AIP Advances 15, 095314 (2025)

DOI: 10.1063/5.0288836

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ABSTRACT

© 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). https://doi.org/10.1063/5.0288836

I. INTRODUCTION Flight safety remains a central concern in the aviation industry, essential for safeguarding the operational integrity of passengers, crew, and aircraft systems.1,2 Sensors play a pivotal role by continuously monitoring flight conditions, environmental variations, and structural responses, providing real-time and accurate feedback to the flight control system.3,4 The accuracy of sensing data is directly linked to whether the aircraft remains within a stable flight envelope, helping preempt hazards and failures. Thus, the reliability of aircraft operations is closely tied to the performance of onboard sensing systems. Common sensor technologies—such as accelerometer,5 fiber Bragg grating (FBG) sensor,6 piezoelectric transducer,7 and strain gauge8 —have been widely used for structural and aerodynamic monitoring. However, these systems often face limitations, including high power consumption, complex wiring, limited spatial resolution, and susceptibility to electromagnetic interference.9,10 Their rigid structure and integration challenges further hinder their

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

use in distributed sensing across lightweight and complex surfaces, especially in dynamic flight environments. Among modern aircraft, tiltrotor platforms have gained prominence due to their dual capability for vertical takeoff and high-speed cruise. Yet, the transition between these modes presents a particularly demanding phase, involving strong coupling among propulsion, aerodynamics, and attitude control.11,12 During this stage, the aircraft encounters significant disturbances and modal interactions that can trigger flutter, buffeting, and resonance.13 In extreme cases, this can lead to instability, structural fatigue, or flight control failure. For example, rotor downwash interacting with the wing during tilt can disrupt airflow attachment, inducing local excitation or flow separation and amplifying structural vibrations.14,15 Without timely detection and regulation, such instabilities pose serious threats to flight safety. Therefore, there is an urgent need for high-sensitivity, fast-response, and easily deployable sensing strategies to detect and suppress aeroelastic vibrations during tiltrotor transition, enabling proactive state awareness and risk control.

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Flight safety in a tiltrotor aircraft is highly sensitive to vibration-induced instabilities during transition between vertical and horizontal flight modes. However, conventional vibration monitoring systems often suffer from high power consumption, complex integration, and limited spatial resolution. Here, a flexible, self-powered oil-absorbing cloth-based triboelectric nanogenerator (OAC-TENG) is developed for realtime vibration sensing and energy harvesting in dynamic aerospace environments. The device is constructed using a porous oil-absorbing cloth and a PTFE film as triboelectric layers, laminated on Kapton substrates with aluminum electrodes via a scalable hot-pressing process. Owing to the large effective contact area and strong charge separation, the OAC-TENG delivers high output performance, with a peak opencircuit voltage (VOC ) of 137.6 V, short-circuit current (ISC ) of 44.7 μA, and maximum power output of 0.43 mW. The device also exhibits excellent durability, humidity tolerance, and energy storage capability, successfully powering LED arrays and charging capacitors. Furthermore, the OAC-TENG enables high-resolution sensing of vibration amplitude and frequency and is demonstrated on a tiltrotor model for monitoring transition-induced aeroelastic disturbances. This work highlights the potential of OAC-TENGs as multifunctional, self-powered platforms for intelligent structural health monitoring and vibration suppression in next-generation aerospace systems.

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

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of capturing both amplitude- and frequency-dependent mechanical responses. When integrated onto a tiltrotor model undergoing simulated transition-induced vibrations, the sensor generates stable voltage and current signals that reflect structural oscillation characteristics in real time. These findings demonstrate the OACTENG’s feasibility for deployment in distributed structural monitoring networks for future intelligent flight systems, offering new pathways for aeroelastic instability detection, self-powered sensing, and closed-loop vibration suppression in tiltrotor aircrafts. II. EXPERIMENTS A. Materials A 30 μm-thick PTFE film, sourced from Taixing Aixin Technology New Materials Co., Ltd. (China), was utilized as the negative triboelectric layer. The positive triboelectric material was prepared using a 100 μm-thick oil-absorbing cloth (OAC) obtained from a local small commodity market in China. Flexible Kapton substrates were constructed by bonding ultrathin double-sided adhesive tape (Chengdu Deyi Adhesive Products Co., Ltd., China). For the electrode layer, a 50 μm-thick high-purity (99.9%) aluminum foil from Hejian Jinrui Thermal Insulation Materials Co., Ltd. (China) was employed. The complete multilayer assembly was fabricated using a hot-pressing process to promote strong interfacial adhesion and enhance the efficiency of triboelectric charge transfer. The OAC used in this work is a commercially available nonwoven fabric composed primarily of PP and PET fibers. Both PP and PET are located toward the tribopositive end of the triboelectric series and thus readily donate electrons when in contact with highly electronegative materials such as PTFE. The OAC possesses a high-porosity (∼85%) fiber network with diameters of approximately 5–15 μm, providing abundant micro-asperities and an enlarged effective contact area for triboelectric charge generation. B. The preparation process of the OAC-TENG device Figure 1(a) shows the conceptual framework for employing the proposed OAC-TENG in vibration monitoring of a tiltrotor aircraft during transition flight. The transition phase, characterized by the rotation of the nacelles from vertical to horizontal orientation, introduces complex aeroelastic disturbances including flutter, buffeting, mode shape variation, and resonance. These instabilities can compromise flight stability and structural integrity. The self-powered OAC-TENG sensor is designed to capture characteristic mechanical signatures of such vibrations, providing a potential solution for real-time monitoring and intelligent suppression. Figure 1(b) illustrates the fabrication process of the positive triboelectric layer. A Kapton substrate is first adhered with an aluminum electrode, followed by the lamination of a 100 μm-thick oil-absorbing cloth. The entire structure is hot-pressed to improve interfacial adhesion and ensure robust charge transfer. The porous and flexible nature of the oil-absorbing cloth enhances surface contact and charge generation under cyclic mechanical excitation. Figure 1(c) describes the preparation of the negative triboelectric layer. A similar process is used, with a PTFE film replacing the oil-absorbing cloth. PTFE’s high electronegativity and smooth surface provide complementary triboelectric properties, forming an effective pair with the oil-absorbing layer. Figure 1(d) presents the schematic structure of the assembled OAC-TENG device. The two triboelectric

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As an emerging self-powered energy harvesting and sensing platform, the triboelectric nanogenerator (TENG) has demonstrated substantial potential in recent years across a wide range of applications, including intelligent sensing, structural health monitoring, and the Internet of Things (IoTs).16–51 Its working principle is based on the coupling of contact electrification and electrostatic induction, where measurable electrical signals are generated through the repeated contact and separation between dissimilar materials.52,53 This mechanism enables energy conversion and signal acquisition without the need for external power sources. Compared to conventional sensors, TENGs offer several advantages, such as simple structure, lightweight form factor, low fabrication cost, and high responsiveness.54,55 Moreover, they can be tailored to various operational modes—such as contactseparation, lateral sliding, single-electrode, and freestanding triboelectric configurations—making them adaptable to diverse and complex application environments.27,56 Owing to their excellent integrability and high sensitivity, TENGs have been widely employed in various sensing systems, including pressure sensors, tactile recognition devices, displacement monitors, environmental sensors, and motion detectors for human biomechanics.27,57–59 In particular, TENG-based vibration sensing has received increasing attention, as these devices can effectively convert subtle structural or environmental vibrations into high signal-to-noise ratio electrical outputs. They are capable of real-time monitoring of lowfrequency, broadband, and even aperiodic vibrations. For instance, TENGs have been successfully applied to bridges, dams, and highrise buildings for vibration detection and structural health assessment, enabling the capture of dynamic responses under wind loads, seismic events, or operational excitations.60,61 In addition, TENGs have shown significant promise in smart transportation, machinery fault diagnostics, and wearable electronics.62,63 Building on this foundation, the integration of TENG technology into aircraft vibration monitoring systems—particularly during high-dynamic, disturbance-prone transition phases—holds significant research and practical value.64–67 Its self-powered nature, lightweight design, and suitability for distributed deployment allow for accurate capture of localized vibration signals in critical structural regions. This enables new strategies for flight state awareness, aeroelastic disturbance warning, and closed-loop control, ultimately contributing to the development of safer and more intelligent aerospace monitoring architectures. Here, an oil-absorbing cloth-based triboelectric nanogenerator (OAC-TENG) is developed as a lightweight, self-powered sensing system for real-time aeroelastic vibration monitoring in tiltrotor aircraft during transition flight. In this design, a porous oil-absorbing cloth functions as the positive triboelectric layer, paired with a PTFE film as the negative counterpart. The fabricated OAC-TENG demonstrates high output performance under a range of mechanical excitations, including a peak open-circuit voltage (VOC ) of ∼137.6 V and a short-circuit current (ISC ) of ∼44.7 μA. It achieves a maximum instantaneous output power of 0.43 mW at an optimal load resistance of ∼2 MΩ, highlighting its capability to harvest low-frequency mechanical energy and power small-scale electronic components. More importantly, the device exhibits reliable environmental tolerance, long-term output stability, and effective capacitor charging performance, enabling successful demonstrations such as powering commercial LED arrays. Beyond energy harvesting, the OAC-TENG serves as a high-sensitivity vibration sensor capable

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layers are positioned face-to-face with aligned electrodes, and the output signal is connected to an external load. Under vibrationinduced contact–separation or sliding motion, triboelectric charges are generated and transferred, enabling self-powered sensing. The lightweight, flexible multilayer architecture is particularly suitable for integration into aircraft surfaces or joints where vibration signatures are strongest. C. Characterization and measurements Figure 1(e) displays the physical appearance and flexibility of the oil-absorbing cloth used as the positive triboelectric material. The material exhibits a nonwoven, fibrous texture with excellent mechanical compliance, enabling it to conform easily to curved or irregular surfaces. Such flexibility is critical for ensuring intimate contact with the counter surface under dynamic mechanical excitation, thereby enhancing triboelectric output performance. Figure 1(f) shows the two primary triboelectric layers after integration with the Kapton substrates and aluminum electrodes. The PTFE film (left) and the oil-absorbing cloth (right) are both firmly adhered to their respective substrates via a hot-pressing process. This modular assembly allows each triboelectric component to be independently characterized and later paired in a face-to-face configuration. Figure 1(g) presents the final OAC-TENG device, where the PTFE and oil-absorbing layers are combined into a stacked configuration with a defined contact area. The compact design (∼1 × 1 cm2 ) and lightweight structure enable the device to be easily deployed onto structural elements of the tiltrotor aircraft without adding significant weight or complexity. Figure 1(h)

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

provides SEM images of the oil-absorbing cloth surface at low and high magnifications. The microstructure reveals a randomly oriented fibrous network with microscale gaps and surface roughness. This porous morphology increases the effective contact area during operation and promotes charge trapping, both of which are beneficial for enhancing triboelectric performance and sensing resolution. The randomly oriented microfibers create a rough and porous surface, which increases the real contact area and promotes efficient charge trapping. This structural feature, together with the inherent tribopositive nature of PP/PET fibers, underlies the effective electron transfer to the PTFE layer during contact–separation cycles. The electrical performance of the OAC-TENG—specifically VOC , ISC , and QSC —was comprehensively characterized using a highprecision electrometer (Keithley 6514). To ensure consistent and controlled mechanical stimulation, a programmable vibration platform was utilized to impose periodic contact–separation motions with tunable frequency and force parameters. III. RESULTS AND DISCUSSION A. Working principle of the OAC-TENG device Figure 2(a) illustrates the working principle of the OAC-TENG based on the vertical contact–separation mode. The device comprises a top triboelectric layer (oil-absorbing cloth) and a bottom triboelectric layer (PTFE film), each attached to a Kapton substrate with an intermediate aluminum electrode. Upon contact between the two triboelectric materials, due to the difference in their electron affinity, electrons are transferred from the oil-absorbing cloth

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FIG. 1. Design, fabrication, and structural characterization of the OAC-TENG for vibration monitoring in a tiltrotor aircraft. (a) Conceptual illustration of vibration sensing in a tiltrotor aircraft during transition flight. [(b) and (c)] Fabrication processes of the positive (oil-absorbing cloth) and negative (PTFE film) triboelectric layers. (d) Schematic diagram of the assembled OAC-TENG device. (e) Photographs showing the oil-absorbing cloth used as the positive friction layer. (f) Prepared triboelectric layers: PTFEbased (left) and oil-absorbing-cloth-based (right) components adhered to Kapton substrates with electrodes. (g) Assembled OAC-TENG device integrating both triboelectric layers in a compact, flexible configuration. (h) SEM images of the oil-absorbing cloth at low (left) and high (right) magnifications.

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to the PTFE surface, resulting in opposite charges accumulating on each surface (Step 1). When an external mechanical force separates the two layers (Step 2), a potential difference is generated between the electrodes owing to the separation of triboelectric charges. This potential drives electron flow through the external circuit from one electrode to the other, generating a transient current. As separation increases, the potential also increases, until a maximum is reached. In Step 3, when the device is fully separated, the electrostatic equilibrium is established. Upon release of the mechanical force, the layers return to contact (Step 4), causing the electrostatic field to collapse and electrons to flow back in the opposite direction, producing a reverse current. This bidirectional current forms an alternating output under repeated mechanical excitation. Throughout this process, the device converts mechanical vibration into electrical energy through the periodic formation and neutralization of triboelectric charges. The use of a flexible and porous oil-absorbing cloth ensures enhanced contact area, while the PTFE film contributes strong electronegativity, together enabling high output performance and reliability under dynamic loading conditions. B. Electrical performance and load matching characteristics of the OAC-TENG device Figures 2(b)–2(d) presents the electrical output performance of the OAC-TENG under periodic contact–separation motion at a frequency of 3 Hz and a pressing force of ∼50N. VOC reaches a peak value of ∼137.6 V [Fig. 2(b)], demonstrating the device’s strong charge-separation capability. Correspondingly, ISC achieves a peak

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

of ∼44.7 μA [Fig. 2(c)], and QSC accumulates up to ∼93.7 nC per cycle [Fig. 2(d)], indicating efficient charge transfer and robust triboelectric coupling between the oil-absorbing cloth and PTFE layers. Figure 2(e) depicts the equivalent circuit used for output measurements. The OAC-TENG is connected in series with an external variable resistor and a voltmeter, allowing systematic analysis of output voltage and current under different electrical load conditions. Figure 2(f) shows the dependency of output voltage and current on external resistance ranging from 0.1 to 100 MΩ. As resistance increases, the output voltage rises steadily from ∼3.1 V to over 62 V, while the current exhibits a decreasing trend from ∼31 to ∼0.62 μA, consistent with Ohm’s law behavior in a high-impedance generator. Figure 2(g) illustrates the corresponding power output calculated using formula P=I2 R. The instantaneous power reaches a maximum of ∼0.43 mW at an optimal load resistance of ∼2 MΩ. This peak highlights the importance of resistance matching to maximize energy extraction from the TENG system. Together, these results confirm that the OAC-TENG exhibits high voltage and current outputs, along with considerable power density, making it suitable for self-powered vibration sensing and energy harvesting applications in aerospace structures. C. Effect of frequency, force, and displacement on the electrical output characteristics of the OAC-TENG device Figures 3(a)–3(c) investigates the influence of mechanical excitation frequency on the electrical output of the OAC-TENG. As the frequency increases from 2 to 5 Hz, ISC shows a distinct

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FIG. 2. Working mechanism and electrical performance of the OAC-TENG. (a) Schematic illustration of the contact–separation working mechanism of the OAC-TENG. [(b)–(d)] Measured electrical output signals under periodic mechanical stimulation: (b) VOC with a peak of ∼137.6 V; (c) ISC reaching ∼44.7 μA; and (d) QSC of ∼93.7 nC. (e) Equivalent circuit configuration used for load-dependent measurements. (f) Output voltage and current as functions of external load resistance (0.1–100 MΩ). (g) Corresponding output power calculated as P = I2 R.

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rising trend [Fig. 3(b)], while VOC [Fig. 3(a)] and Qsc [Fig. 3(c)] remain relatively constant. The increase in Isc can be attributed to the reduced duration of each contact–separation cycle at higher frequencies, which results in faster charge transfer rates and thus higher instantaneous current. However, since the triboelectric charge density and the maximum electrostatic potential difference between the two layers are determined primarily by the material properties and contact area—both of which remain unchanged—VOC and Qsc exhibit negligible variation. This behavior suggests that while frequency modulates the output rate (current), it does not significantly alter the total amount of triboelectric charge generated per cycle or the maximum voltage. Figures 3(d)–3(f) demonstrates the effect of varying applied force on output performance. With increasing force, all three electrical parameters—VOC [Fig. 3(d)], ISC [Fig. 3(e)], and Qsc [Fig. 3(f)]—exhibit a clear increasing trend. This enhancement is due to improved interfacial contact under larger pressure, which promotes more efficient charge generation and reduces contact resistance. The stronger compression also leads to greater surface deformation and intimacy between the triboelectric layers, resulting in higher triboelectric charge density and better signal output. This force-dependent behavior confirms the device’s sensitivity to mechanical loading conditions. The output voltage increases monotonically with increasing applied force in the range of 5N–50N, indicating a positive correlation throughout the tested range. From

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

5N to 30N, the voltage rises moderately from ∼60–80 V, which can be attributed to gradual growth of the real contact area under elastic deformation of the OAC fibers. Beyond ∼30N, the microfibrous network undergoes more significant compression, markedly increasing contact intimacy and the number of effective charge-transfer sites, leading to a sharper voltage rise up to 137.6 V at 50 N. This two-stage growth reflects the mechanical transition of the porous structure from elastic to more compacted states, thereby enhancing triboelectric charge generation efficiency. Figures 3(g)–3(i) evaluates the effect of vertical displacement amplitude on the device’s output characteristics. As the separation distance increases from 1 to 5 mm, VOC [Fig. 3(g)], ISC [Fig. 3(h)], and Qsc [Fig. 3(i)] all show a gradual rise. This is attributed to the larger electrostatic potential difference generated during the increased separation, which drives a stronger charge flow and enhances the overall energy conversion efficiency. In addition, the larger displacement allows for more complete charge recombination during contact and separation cycles. Hence, the OAC-TENG exhibits distinct and tunable output behavior under varying external conditions. Frequency predominantly affects Isc , while force and displacement influence all output metrics—Voc , Isc , and Qsc . These results highlight the sensor’s robustness and adaptability for monitoring complex vibrational environments such as those encountered during tiltrotor aircraft transition maneuvers.

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FIG. 3. Dependence of the electrical output performance of OAC-TENG on excitation frequency, applied force, and displacement. [(a)–(c)] VOC , ISC , and QSC of the OACTENG under different excitation frequencies (2–5 Hz). [(d)–(f)] Influence of varying applied force (5–30 N) on VOC , ISC , and QSC . [(g)–(i)] Electrical outputs of the device under different vertical displacements (1–5 mm).

D. Humidity tolerance and energy harvesting capabilities of the OAC-TENG device Figures 4(a)–4(c) illustrates the electrical response of the OACTENG under varying relative humidity (RH) levels, ranging from 20% to 80%. As RH increases, VOC [Fig. 4(a)], ISC [Fig. 4(b)], and QSC [Fig. 4(c)] all gradually decrease. This trend can be attributed to the detrimental effect of moisture adsorption on the triboelectric surfaces, which impairs charge retention and suppresses surface potential differences. The reduction in surface charge density under humid conditions confirms that ambient humidity is a critical factor influencing the output of triboelectric devices. Figure 4(d) evaluates the long-term output stability of the OAC-TENG under continuous mechanical cycling. QSC remains highly stable over a prolonged operation period of 1600 s (more than 25 min), with no visible degradation in signal amplitude. The inset graphs at different time intervals (0–4, 800–804, and 1500–1504 s) show consistent waveform profiles, indicating excellent mechanical durability and electrical repeatability. This long-term reliability is crucial for practical sensing and energy harvesting in dynamic environments. In addition to stable output under varying humidity levels (20%–80% RH) and during 1600 s of continuous operation, the chemical inertness, hydrophobicity, and solvent resistance of PP/PET fibers have been widely reported in aerospace-related materials. These

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characteristics ensure the OAC maintains mechanical integrity and electrical functionality over prolonged use, even under temperature and humidity fluctuations encountered in aerospace environments. Figure 4(e) shows the schematic circuit used for energy storage and voltage measurement. The OAC-TENG is connected to a full-wave bridge rectifier, followed by a capacitor, to convert the alternating triboelectric signal into a unidirectional voltage suitable for storage and powering electronics. Figure 4(f) presents the charging behavior of capacitors with different capacitances (10, 20, and 30 μF) when charged by the OAC-TENG. As expected, smaller capacitance results in faster voltage buildup due to lower charge storage requirements. This highlights the tunability of the output for different storage or load applications. Figure 4(g) further demonstrates the effect of mechanical excitation frequency (3–7 Hz) on capacitor charging performance. Higher frequencies lead to faster voltage accumulation across the same capacitor, owing to the increased number of effective charge cycles per unit time. This confirms the frequency-responsive nature of the OAC-TENG and its efficiency in rapid energy delivery. Figure 4(h) demonstrates a practical application scenario, where the OAC-TENG device is used to power a commercial LED array. After energy accumulation through the rectifier-capacitor circuit, the device successfully lights up a 100+ pixel green LED matrix, visually confirming the ability of the OAC-TENG to convert mechanical motion into usable electrical energy. The inset image provides a

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FIG. 4. Environmental stability, energy storage capability, and practical application of the OAC-TENG. [(a)–(c)] VOC , ISC , and QSC of the OAC-TENG under varying relative humidity levels (20%–80%). (d) Long-term charge stability of the OAC-TENG over 1600 s of continuous operation. (e) Schematic of the energy storage circuit for converting AC output into stored DC energy. (f) Capacitor charging curves using the OAC-TENG for different capacitances (10, 20, 30 μF). (g) Charging performance under different excitation frequencies (3, 5, 7 Hz). (h) Demonstration of OAC-TENG powering a commercial LED array after energy storage.

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

close-up view of the illuminated array. Collectively, these results verify the OAC-TENG’s strong environmental adaptability, longterm output stability, energy storage capability, and practical potential for powering small-scale electronic devices. Such characteristics make it highly suitable for self-powered vibration monitoring and signal feedback applications in aerospace and other intelligent structural systems. E. Real-time sensing of transition-induced vibrations in tiltrotor aircraft via the OAC-TENG device Figure 5 illustrates the experimental demonstration of the OAC-TENG as a self-powered vibration sensor designed for monitoring and potentially suppressing aeroelastic instabilities—such as flutter, buffeting, and resonance—during the transition phase of tiltrotor aircraft. The transition process, characterized by nacelle rotation and mode switching from vertical take-off to horizontal

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cruise, presents a highly unsteady aeroelastic environment where dynamic pressure fluctuations, structural coupling, and mode shape interactions may trigger flight-critical vibrations. To address this challenge, a distributed, power-independent sensing system capable of detecting real-time vibration characteristics is crucial for enabling feedback-based control strategies. The working principle and experimental setup of the system are outlined in Fig. 5(a). A programmable signal generator is used to drive a modal exciter that delivers controlled sinusoidal vibrations to a tiltrotor model, simulating operational vibrational conditions during transition. The OAC-TENG sensor is directly integrated onto the aircraft model, functioning as a triboelectric-based transducer that converts mechanical oscillations into measurable electrical signals—voltage, current, and charge. These signals provide direct insight into vibration amplitude, frequency, and waveform characteristics, which are essential indicators of aeroelastic phenomena. Photographs of the experimental platform are shown in

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FIG. 5. Self-powered vibration sensing performance of OAC-TENG during tiltrotor aircraft transition. (a) Schematic diagram of the experimental system for simulating tiltrotor vibrations and acquiring sensing signals from the OAC-TENG. (b) Photographs of the test setup showing a tiltrotor aircraft model mounted on a modal vibrator. The VOC (c), ISC (d), and QSC (e) output of the OAC-TENG device under sinusoidal excitation, confirming stable and repeatable signal generation. [(f) and (g)] Output voltage and charge at varying vibration amplitudes from 1 to 9 mm. [(h)–(k)] Voltage outputs of the OAC-TENG under different vibration frequencies (2–5 Hz).

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

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of the OAC-TENG. Higher vibration amplitudes increase the real contact area and relative sliding between the triboelectric layers, thereby enhancing charge generation. In contrast, elevated humidity accelerates surface charge dissipation, resulting in reduced output levels. To reliably attribute signal variations to either factor, several strategies can be implemented: (i) baseline calibration under known vibration and humidity conditions prior to deployment; (ii) integration of a miniature humidity sensor adjacent to the OAC-TENG to provide real-time environmental data for algorithmic compensation; (iii) multi-parameter signal analysis, in which amplitude changes affect both magnitude and waveform shape, whereas humidity variations primarily cause a baseline shift without altering frequency content; and (iv) application of hydrophobic surface coatings or encapsulation to suppress humidity sensitivity. These measures can enhance signal reliability and robustness in varying operational environments. IV. CONCLUSIONS In this work, a lightweight and flexible oil-absorbing clothbased triboelectric nanogenerator (OAC-TENG) was developed as a self-powered sensing platform for real-time vibration monitoring in a tiltrotor aircraft during transition flight. The device integrates a porous oil-absorbing cloth and a PTFE film as triboelectric layers, forming a multilayer structure with high mechanical compliance and interfacial charge transfer efficiency. The OAC-TENG device exhibits outstanding electrical performance, achieving a peak VOC of 137.6 V, a ISC of 44.7 μA, and a maximum power output of 0.43 mW. It also demonstrates excellent durability, environmental adaptability, and effective energy storage capabilities, successfully powering commercial LEDs and charging capacitors. Importantly, the OAC-TENG device enables sensitive detection of both vibration amplitude and frequency under simulated transition conditions. When deployed on a tiltrotor aircraft model, it accurately captures aeroelastic responses such as flutter and buffeting, offering a feasible approach for distributed sensing without external power. These findings underscore the potential of OAC-TENGs for integration into intelligent aerospace structures, where real-time vibration sensing and energy harvesting are essential for flight safety, structural health monitoring, and active vibration suppression. This work paves the way for advancing self-powered sensing technologies in next-generation flight platforms with high dynamic complexity.

AUTHOR DECLARATIONS Conflict of Interest The authors have no conflicts to disclose. Author Contributions Chengxiao Li: Conceptualization (lead); Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (lead); Project administration (lead); Resources (lead); Software (lead); Supervision (lead); Validation (lead); Visualization (lead); Writing – original draft (lead); Writing – review & editing (lead). Yonggang Yang: Conceptualization (equal); Data curation (equal); Funding acquisition (equal); Investigation (equal); Project

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Fig. 5(b), where the tiltrotor is mounted vertically on a shaker system, and the OAC-TENG is attached to a representative structural location on the airframe. This setup mimics a realistic transition scenario in which structural parts—such as nacelle mounts, fuselage interfaces, or wing joints—are subjected to complex vibrations. By situating the sensor in these zones, localized vibration information can be harvested without any external power requirement. This is particularly advantageous for tiltrotor aircrafts, where weight constraints, spatial distribution, and high vibration risk demand robust, low-power sensing solutions. Figures 5(c)–5(e) present typical electrical output signals generated by the OAC-TENG during vibrational excitation. VOC [Fig. 5(c)] exhibits distinct, periodic peaks corresponding to the contact–separation cycles between the triboelectric layers. ISC [Fig. 5(d)] and QSC [Fig. 5(e)] follow similar periodic patterns, confirming stable signal output under dynamic loading. These results validate the sensor’s functionality under realistic conditions, demonstrating its ability to consistently transduce mechanical input into electrical output with clear temporal resolution. Such high-fidelity response enables direct mapping of vibration signatures, making it possible to identify early warning signs of aeroelastic instability, including sudden amplitude growth, asymmetric oscillation, or frequency shifts. As the excitation amplitude is increased from 1 to 9 mm, both the voltage [Fig. 5(f)] and charge output [Fig. 5(g)] exhibit a pronounced monotonic increase. This correlation reveals that the output magnitude is strongly dependent on the contact force and displacement between the triboelectric interfaces, allowing the OAC-TENG to quantitatively resolve vibration severity. Such amplitude-resolved sensing is particularly useful for detecting localized modal amplifications—commonly observed in flutter onset conditions—where small structural deformations can escalate rapidly under resonance conditions. Figures 5(h)–5(k) further explore the frequency response of the OAC-TENG by exposing it to vibrational frequencies ranging from 2 to 5 Hz. As the frequency increases, the output waveforms maintain consistent amplitude while the waveform density increases proportionally, indicating the sensor’s capability to track frequency changes accurately. Frequency-resolved sensing is especially relevant in tiltrotor systems, where different aerodynamic modes interact during transition. The ability to distinguish between stable oscillation and highfrequency buffeting offers valuable data for adaptive flight control and real-time health monitoring. Taken together, these results establish the OAC-TENG as a viable tool for integrated vibration monitoring in tiltrotor aircraft. Its capacity to extract both amplitude and frequency information from dynamic mechanical inputs, without relying on external power, makes it uniquely suited for deployment in structurally critical areas prone to aeroelastic excitation. When paired with onboard control systems, the voltage or current signals generated by the OAC-TENG device can serve as feedback inputs for active vibration suppression mechanisms—such as rotor speed modulation, tilt angle adjustment, or structural damping activation. Furthermore, the device’s lightweight, flexible, and scalable design allows it to conform to complex geometries, supporting multi-point monitoring architectures across the aircraft structure. The implementation of OAC-TENG arrays could, therefore, contribute to a new class of intelligent tiltrotor systems capable of autonomously sensing and responding to hazardous vibration states during the most vulnerable phase of flight. In practical applications, both vibration amplitude and ambient humidity influence the electrical output

administration (equal); Resources (equal); Validation (equal); Visualization (equal); Writing – original draft (equal); Writing – review & editing (equal). DATA AVAILABILITY The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

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K. Xia and Z. Xu, “Applying a triboelectric nanogenerator by using facial mask for flexible touch sensor,” Sens. Actuators, A 331, 112710 (2021). 23 J. Luo, W. Gao, and Z. L. Wang, “The triboelectric nanogenerator as an innovative technology toward intelligent sports,” Adv. Mater. 33(17), 2004178 (2021). 24 R. Walden, C. Kumar, D. M. Mulvihill, and S. C. Pillai, “Opportunities and challenges in triboelectric nanogenerator (TENG) based sustainable energy generation technologies: A mini-review,” Chem. Eng. J. Adv. 9, 100237 (2022). 25 K. Xia, M. Yu, Y. Luo, and Y. Ding, “All-foam intrinsic triboelectric static and dynamic pressure sensor with a standardized DC/AC measurement method for industrial robots,” Nano Energy 139, 110953 (2025). 26 D. Choi, Y. Lee, Z. H. Lin et al., “Recent advances in triboelectric nanogenerators: From technological progress to commercial applications,” ACS Nano 17(12), 11087–11219 (2023). 27 B. Xie, Y. Guo, Y. Chen et al., “Advances in graphene-based electrode for triboelectric nanogenerator,” Nano-Micro Lett. 17(1), 17 (2025). 28 Y. Zou, J. Xu, K. Chen, and J. Chen, “Advances in nanostructures for highperformance triboelectric nanogenerators,” Adv. Mater. Technol. 6(3), 2000916 (2021). 29 K. Xia, Y. Hao, P. Luo et al., “A faraday cage-inspired triboelectric nanogenerator enabled by alloy powder architecture for self-powered ocean sensing,” Energy Environ. Mater. 8, e70040 (2025). 30 X. Fu, X. Pan, Y. Liu et al., “Non-contact triboelectric nanogenerator,” Adv. Funct. Mater. 33(52), 2306749 (2023). 31 H. Zhang, D. Zhang, Z. Wang et al., “Ultrastretchable, self-healing conductive hydrogel-based triboelectric nanogenerators for human–computer interaction,” ACS Appl. Mater. Interfaces 15(4), 5128–5138 (2023). 32 J. Fu, K. Xia, and Z. Xu, “A triboelectric nanogenerator based on human fingernail to harvest and sense body energy,” Microelectron. Eng. 232, 111408 (2020). 33 K. Xia, Z. Xu, Z. Zhu et al., “Cost-effective copper–nickel-based triboelectric nanogenerator for corrosion-resistant and high-output self-powered wearable electronic systems,” Nanomaterials 9(5), 700 (2019). 34 Y. Yu, Q. Gao, X. Zhang et al., “Contact-sliding-separation mode triboelectric nanogenerator,” Energy Environ. Sci. 16(9), 3932–3941 (2023). 35 C. Li, R. Luo, Y. Bai et al., “Molecular doped biodegradable triboelectric nanogenerator with optimal output performance,” Adv. Funct. Mater. 34(29), 2400277 (2024). 36 Y. Zhou, M. Shen, X. Cui et al., “Triboelectric nanogenerator based self-powered sensor for artificial intelligence,” Nano Energy 84, 105887 (2021). 37 K. Xia and M. Yu, “Highly robust and efficient metal-free water cup solid–liquid triboelectric nanogenerator for water wave energy harvesting and ethanol detection,” Chem. Eng. J. 503, 157938 (2025). 38 Y. Yu, H. Li, X. Zhang et al., “Substantially boosting performance of triboelectric nanogenerators via a triboelectrification enhancement effect,” Joule 8(6), 1855–1868 (2024). 39 K. Xia, Z. Xu, Y. Hong, and L. Wang, “A free-floating structure triboelectric nanogenerator based on natural wool ball for offshore wind turbine environmental monitoring,” Mater. Today Sustainability 24, 100467 (2023). 40 Z. Shao, J. Chen, Q. Xie, and L. Mi, “Functional metal/covalent organic framework materials for triboelectric nanogenerator,” Coord. Chem. Rev. 486, 215118 (2023). 41 L. Zhang, H. Cai, L. Xu et al., “Macro-superlubric triboelectric nanogenerator based on tribovoltaic effect,” Matter 5(5), 1532–1546 (2022). 42 G. M. Rani, C. M. Wu, K. G. Motora et al., “Acoustic-electric conversion and triboelectric properties of nature-driven CF-CNT based triboelectric nanogenerator for mechanical and sound energy harvesting,” Nano Energy 108, 108211 (2023). 43 K. Xia, J. Fu, and Z. Xu, “Multiple-frequency high-output triboelectric nanogenerator based on a water balloon for all-weather water wave energy harvesting,” Adv. Energy Mater. 10(28), 2000426 (2020). 44 W. Akram, Q. Chen, G. Xia, and J. Fang, “A review of single electrode triboelectric nanogenerators,” Nano Energy 106, 108043 (2023). 45 W. T. Guo, Y. Lei, X. H. Zhao et al., “Printed-scalable microstructure BaTiO3 /ecoflex nanocomposite for high-performance triboelectric nanogenera-

13 October 2025 09:45:26

1 Y. Wu, B. Wei, L. Xie et al., “Flight safety oriented ice shape modulation using distributed plasma actuator units,” Chin. J. Aeronaut. 34(10), 1–5 (2021). 2 C. Walko and B. Schuchardt, “Increasing helicopter flight safety in maritime operations with a head-mounted display,” CEAS Aeronaut. J. 12, 29–41 (2021). 3 S. Vladov, L. Scislo, V. Sokurenko et al., “Neural network signal integration from thermogas-dynamic parameter sensors for helicopters turboshaft engines at flight operation conditions,” Sensors 24(13), 4246 (2024). 4 S. Sun, G. Cioffi, C. De Visser, and D. Scaramuzza, “Autonomous quadrotor flight despite rotor failure with onboard vision sensors: Frames vs. Events,” IEEE Rob. Autom. Lett. 6(2), 580–587 (2021). 5 W. Jiang, R. C. Chang, S. Zhang, and S. Zang, “Structural health monitoring and flight safety warning for aging transport aircraft,” J. Aerosp. Eng. 36(5), 04023059 (2023). 6 G. Hegde, S. Asokan, and G. Hegde, “Fiber Bragg grating sensors for aerospace applications: A review,” ISSS J. Micro Smart Syst. 11(1), 257–275 (2022). 7 Z. Tong, H. Hu, Z. Wu et al., “An ultrasonic proximity sensing skin for robot safety control by using piezoelectric micromachined ultrasonic transducers (PMUTs),” IEEE Sens. J. 22(18), 17351–17361 (2022). 8 H. Kwon, Y. Park, C. Shin et al., “In-flight strain monitoring of aircraft tail boom structure using a fiber Bragg grating sensor based health and usage monitoring system,” Int. J. Aeronaut. Space Sci. 22(3), 567–577 (2021). 9 Z. Zhu, H. Zhang, K. Xia, and Z. Xu, “Pencil-on-paper strain sensor for flexible vertical interconnection,” Microsyst. Technol. 24, 3499–3502 (2018). 10 K. Xia, Z. Zhu, H. Zhang et al., “Cost-effective triboelectric nanogenerator based on teflon tape and conductive copper foil tape,” Microelectron. Eng. 199, 114–117 (2018). 11 X. Yu, X. Zhou, Y. Zhang et al., “Safety control design with flight envelope protection and reference command generation,” IEEE Trans. Aerosp. Electron. Syst. 58(6), 5835–5848 (2022). 12 X. Zhou, X. Yu, K. Guo et al., “Safety flight control design of a quadrotor UAV with capability analysis,” IEEE Trans. Cybern. 53(3), 1738–1751 (2023). 13 Q. Zou, R. Huang, X. Mu et al., “Body-freedom flutter analysis and flight test for a flying-wing aircraft testbed,” Mech. Syst. Signal Process. 221, 111717 (2024). 14 H. Yan, Y. Xu, Q. Liu et al., “Data-driven joint noise reduction strategy for flutter boundary prediction,” Eur. Phys. J. Spec. Top. 234, 619–636 (2025). 15 Q. Zou, R. Huang, H. Hu, and H. Liu, “Studying body-freedom flutter mechanism via a rigid-elastic aeroelastic model of reduced-order,” Aerosp. Sci. Technol. 161, 110155 (2025). 16 T. Cheng, J. Shao, and Z. L. Wang, “Triboelectric nanogenerators,” Nat. Rev. Methods Primers 3(1), 39 (2023). 17 S. A. Lone, K. C. Lim, K. Kaswan et al., “Recent advancements for improving the performance of triboelectric nanogenerator devices,” Nano Energy 99, 107318 (2022). 18 K. Xia and Z. Xu, “Double-piezoelectric-layer-enhanced triboelectric nanogenerator for bio-mechanical energy harvesting and hot airflow monitoring,” Smart Mater. Struct. 29(9), 095016 (2020). 19 S. Bairagi, C. Kumar, C. Kumar et al., “Wearable nanocomposite textile-based piezoelectric and triboelectric nanogenerators: Progress and perspectives,” Nano Energy 118, 108962 (2023). 20 R. Liu, K. Xia, T. Yu et al., “Multifunctional smart fabrics with integration of self-cleaning, energy harvesting, and thermal management properties,” ACS Nano 18(45), 31085–31097 (2024). 21 Z. Zhao, L. Zhou, S. Li et al., “Selection rules of triboelectric materials for directcurrent triboelectric nanogenerator,” Nat. Commun. 12(1), 4686 (2021).

AIP Advances 15, 095314 (2025); doi: 10.1063/5.0288836 © Author(s) 2025

pubs.aip.org/aip/adv

57

F. Salemi, F. Karimzadeh, M. H. Abbasi et al., “Recent progress in self-powered graphene-based triboelectric nanogenerators,” Int. J. Precis. Eng. Manuf.-Green Technol. 12, 749–779 (2025). 58 C. Ma, A. Matin Nazar, A. H. Moradi et al., “Advanced triboelectric nanogenerator sensing technologies for high-efficiency cardiovascular monitoring,” Energy Technol. 13(5), 2401863 (2025). 59 D. Tao, P. Su, A. Chen et al., “Electro-spun nanofibers-based triboelectric nanogenerators in wearable electronics: Status and perspectives,” npj Flexible Electron. 9(1), 4 (2025). 60 W. Dong, Z. Gao, Z. Duan et al., “Sliding-mode cement-based triboelectric nanogenerators in intelligent infrastructure for a new energy harvesting paradigm,” Mater. Today Energy 52, 101943 (2025). 61 M. R. Ritu, R. Mitra et al., “Flexible high temperature stable hydrogel based triboelectric nanogenerator for structural health monitoring and deep learning augmented human motion classification,” Small 21, 2502739 (2025). 62 Z. Zhou, Z. Xu, L. N. Y. Cao et al., “Triboelectricity based self-powered digital displacement sensor for aircraft flight actuation,” Adv. Funct. Mater. 34(8), 2311839 (2024). 63 H. Sheng, L. N. Y. Cao, Y. Shang et al., “Conformal self-powered high signal-tonoise ratio biomimetic in-situ aircraft surface turbulence mapping system,” Nano Energy 136, 110694 (2025). 64 W. Zhang, L. Deng, X. Lü et al., “Advanced handwriting identification: Triboelectric sensor array integrating with deep learning toward high information security,” InfoMat 7, e70002 (2025). 65 B. Zhu, H. Wu, H. Wang et al., “Spherical 3D fractal structured dualmode triboelectric nanogenerator for multidirectional low-frequency wave energy harvesting,” Nano Energy 124, 109446 (2024). 66 W. Zhang, M. Liu, X. Lü et al., “Triboelectric sensor-empowered intelligent mouse combined with machine learning technology strides toward a computer security system,” Nano Energy 126, 109666 (2024). 67 S. Chen, Y. Tang, M. Liu et al., “From single- to multi-channel systems: Advancing handwriting forgery detection with triboelectric nanogenerator arrays,” Nano Energy 139, 110925 (2025).

13 October 2025 09:45:26

tors and self-powered human-machine interaction,” Nano Energy 131, 110324 (2024). 46 K. Xia, C. Du, Z. Zhu et al., “Sliding-mode triboelectric nanogenerator based on paper and as a self-powered velocity and force sensor,” Appl. Mater. Today 13, 190–197 (2018). 47 R. Cao, Y. Liu, H. Li et al., “Advances in high-temperature operatable triboelectric nanogenerator,” SusMat 4(3), e196 (2024). 48 H. Meng, J. Zhang, R. Zhu et al., “Elevating outputs of droplet triboelectric nanogenerator through strategic surface molecular engineering,” ACS Energy Lett. 9(6), 2670–2676 (2024). 49 K. Xia, D. Wu, J. Fu, and Z. Xu, “A pulse controllable voltage source based on triboelectric nanogenerator,” Nano Energy 77, 105112 (2020). 50 X. Cao, Y. Xiong, J. Sun et al., “Multidiscipline applications of triboelectric nanogenerators for the intelligent era of internet of things,” Nano-Micro Lett. 15(1), 14 (2023). 51 H. Zhang, D. Zhang, R. Mao et al., “MoS2 -based charge trapping layer enabled triboelectric nanogenerator with assistance of CNN-GRU model for intelligent perception,” Nano Energy 127, 109753 (2024). 52 Y. Cheng, K. Li, S. Gong et al., “Fully self-powered pipeline leakage detection and localization enabled by triboelectric nanogenerator,” Nano Energy 142, 111280 (2025). 53 W. Chen, J. Kang, J. Zhang et al., “An information display and encrypted transmission system based on a triboelectric nanogenerator and a cholesteric liquid crystal,” Nano Energy 134, 110594 (2025). 54 K. Xia, Z. Zhu, H. Zhang et al., “Milk-based triboelectric nanogenerator on paper for harvesting energy from human body motion,” Nano Energy 56, 400–410 (2019). 55 K. Xia, D. Wu, J. Fu et al., “A high-output triboelectric nanogenerator based on nickel–copper bimetallic hydroxide nanowrinkles for self-powered wearable electronics,” J. Mater. Chem. A 8(48), 25995–26003 (2020). 56 E. Su, S. Xu, Z. Wang et al., “Buoyancy-gravity optimized triboelectric nanogenerators via conductive 3D printing for robust wave energy harvesting,” Mater. Sci. Eng.: R: Rep. 164, 100953 (2025).

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