Review on energy harvesting for structural health monitoring in aeronautical applications

Progress in Aerospace Sciences ∎ (∎∎∎∎) ∎∎∎–∎∎∎

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Review on energy harvesting for structural health monitoring in aeronautical applications Minh Quyen Le a, Jean-Fabien Capsal a, Mickaël Lallart a, Yoann Hebrard b, Andre Van Der Ham c, Nicolas Reffe d, Lionel Geynet d, Pierre-Jean Cottinet a,n a

Laboratoire de Génie Electrique et Ferroélectricité (LGEF), INSA Lyon, 69621 Villeurbanne, France SKF-Aerospace, 22 rue Brillat SAVARIN Cedex 09 BP16235, 26958 Valence, France c SKF Engineering & Research Centre – Group Development Centre – SKF Business and Technology Park, Kelvinbaan 16, 3439 MT Nieuwegein, Netherlands d Oridao, Immeuble Jacques Cœur 5ème Etage 222 Place Ernest Granier, 34000 Montpellier, France b

art ic l e i nf o

a b s t r a c t

Article history: Received 7 June 2015 Received in revised form 11 October 2015 Accepted 15 October 2015

This paper reviews recent developments in energy harvesting technologies for structural health monitoring (SHM) in aeronautical applications. Aeronautical industries show a great deal of interest in obtaining technologies that can be used to monitor the health of machinery and structures. In particular, the need for self-sufficient monitoring of structures has been ever-increasing in recent years. Autonomous SHM systems typically include embedded sensors, and elements for data acquisition, wireless communication, and energy harvesting. Among all of these components, this paper focuses on energy harvesting technologies. Actually, low-power sensors and wireless communication components are used in newer SHM systems, and a number of researchers have recently investigated such techniques to extract energy from the local environment to power these stand-alone systems. The first part of the paper is dedicated to the different energy sources available in aeronautical applications, i.e., for airplanes and helicopters. The second part gives a presentation of the various devices developed for converting ambient energy into electric power. The last part is dedicated to a comparison of the different technologies and the future development of energy harvesting for aeronautical applications. & 2015 Elsevier Ltd. All rights reserved.

Keywords: Energy harvesting Aeronauticals Structure health monitoring Piezoelectric Thermoelectric

Contents 1. 2.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Energy sources in airplanes and helicopters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1. Mechanical sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2. Thermal sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.3. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Micro-generator based energy harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1. Mechanical energy harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.1. Electromagnetic conversion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 3.1.2. Piezoelectric conversion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.1.3. Electrostatic micro-generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1.4. Summary of mechanical energy harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.2. Thermal energy harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.1. Pyroelectric effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.2. Seebeck effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.2.3. Summary of thermal energy harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Corresponding author. E-mail address: [email protected] (P.-J. Cottinet).

http://dx.doi.org/10.1016/j.paerosci.2015.10.001 0376-0421/& 2015 Elsevier Ltd. All rights reserved.

Please cite this article as: M.Q. Le, et al., Review on energy harvesting for structural health monitoring in aeronautical applications, Progress in Aerospace Sciences (2015), http://dx.doi.org/10.1016/j.paerosci.2015.10.001i

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4. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

1. Introduction SHM for aerospace applications offers a truly viable solution for full-coverage continuous monitoring of aircraft (i.e., airplanes, helicopters) structures or security components (i.e., bearings, rods, etc.) [1]. In essence, it leads to optimized structures in critical areas, drastically alters maintenance regimes and minimizes downtime, whilst also improving reliability and safety. Furthermore, the implementation of an SHM system at the design stage results in an enhanced aircraft performance, lower fuel consumption, thus making it possible to reduce the weight and running costs of an aircraft [1]. To summarize, future applications for autonomous sensors in aeronauticals may be divided into following three groups [2–5]: 1. Maintenance support 2. Aircrew aid 3. Flight test instrumentation

All these application areas constitute a promising future market, but a number of challenges must still be resolved, as illustrated in the following sections.

2. Energy sources in airplanes and helicopters Modern aircraft comprise a multitude of energy sources that can be accessed with energy harvesting technologies: temperature differences, temperature changes, vibrations, strain, ambient light, pressure changes, electrostatic charges, etc. However, not all sources hold sufficient potential to provide enough power to a sensor system. The most critical parameter for comparing these technologies in the scope of aircraft applicability is their power-to-weight ratio (per flight cycle) [4]. Another important criterion is the reliability of these devices. Sources that seem most likely to meet the sector constraints are thermal and vibrational energies [2]. 2.1. Mechanical sources

Maintenance support aims at enhancing the effectiveness of all maintenance activities throughout the life of an aircraft. Actually, the maintenance of an aircraft is performed in a scheduled manner. For instance, in the company Airbus [3], three different checks, i.e., A, B, and C, are scheduled at fixed intervals, depending on the type of aircraft. A typical interval for an A check is about 300–700 flight hours, a B check is performed every five-six months, and a C check after 18 months at the latest. Whereas daily overnight inspection includes visual examinations of the aircraft, the checks mentioned above are accompanied by the dismantling of the cabin interior and the dismounting of fairings or the use of endoscopes to monitor inaccessible areas. Crack or damage detection is also performed, e.g., by using ultrasonic techniques, and all lubricants or other fluids are changed. Obviously, these checks require a lot of manpower and, in addition, the aircraft is grounded. A complete C check takes about five days depending on the aircraft [3]. It is therefore easy to understand that the benefit of a selfpowered system is twofold. First, it constitutes an efficient tool for improving maintenance activities, and second, it can be used as a transition from a programmed maintenance to a predictive one [2]. Hence, self-powered systems lead to an increased aircraft service life and thus reduced maintenance costs. Also, the efficiency can be improved by using autonomous sensors located at remote or inaccessible areas. In this case, measurements are easily carried out without dismantling any modules. Predictive maintenance can be performed with integrated self-sufficient network sensors aiming at collecting data to calculate the state of the monitored components [2]. An automatic aircrew aid system is useful to alleviate the workload and reduce the energy consumption. Harvesting body heat is just one example: instead of producing energy, it would simply collect energy from a passenger seat, and redirect it to power certain aircraft functions – such as the cabin lights, the passenger status monitoring, the security alarm. However, the weight of "aircraft equipment" is a key factor and must match the airline design and should not disturb the passengers. Another objective of self-powered systems is flight test instrumentation. This application field requires flexible sensors that considerably depend on the quantity and type of measurements [6,7].

Both internal and external sources of vibration exist in aircraft. The primary internal source is the propulsion system. In helicopters and propeller-driven aircraft, vibration is generated at very distinct frequencies associated with the rotor speed and blade passage frequency. The rotor speeds for helicopters can result in relatively low vibrations, usually less than 10 Hz. The blade passage frequencies related to three- and four-bladed helicopters can fall below 40 Hz. Other propeller-driven aircraft have higher rotor frequencies. For instance, the Navy E-2C Hawkeye has a rotor speed of 18.4 Hz [8]. With four blades, the passage frequency can lead to four times the rotor speed, i.e., 73.6 Hz [8]. Smith et al. measured the acceleration of 0.8 m/s2 at 73.6 Hz on a flight officer seat during E-2 Hawkeye operations [9]. All components experienced significant vibration from the main rotor and this dominated the low frequency spectrum depending on the positions in the aircraft. For example, components situated at or near the aircraft tail received principal harmonics of the tail rotor. On the other hand, components located adjacent to the engines and gearboxes obtained additional harmonics from the engine, shaft, and gearbox meshing frequencies. Dickson measured an acceleration of 3.5 g at 80 Hz in a gearbox of an AH-64A helicopter [8]. Currently, the majority of commercial airplanes use jet engines but even the latest advanced design and technology have not been able to counter the age-old challenge of noise and vibration. The vibration produced by the jet engine is typically included in the frequency bandwidth range between 20 Hz and 500 Hz, under a maximum acceleration of 3 g [10]. It is common practice to segregate the aircraft into regions and assume that the vibration amplitudes are similar for all equipment positioned in that region. The most commonly defined regions are: ● Fuselage – the vibration is dominated by harmonics of the blade passing frequency of the main rotor. ● Avionics bay – similar to the fuselage but vibration-isolated mounts are designed to reduce the rotor's vibration-induced vibration amplitudes. ● On or near the engines – additional sinusoidal harmonics induced through engine and gearbox harmonics and meshing frequencies.

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Fig. 1. Schematic localization of mechanical vibration in airplanes and helicopters.

Fig. 2. Typical localizations of thermal gradients in airplanes and helicopters.

● On or near the tail rotor – additional sinusoidal harmonics induced through tail rotor and gearbox harmonics. ● External stores and sponsons – additional aerodynamic loads induced by downwash from the main rotor and aerodynamics of the aircraft. In most cases, the vertical and lateral accelerations dominate the loading environment and the fore/aft axis is relatively benign. Air turbulence is the major external source of structure-borne vibration. Up to approximately 10,000 m, weather and thermal effects contribute to air turbulence. At altitudes above 10,000 m, wind shear between moving air masses can cause clear-air turbulence. At altitudes below 500 m, local heating and cooling between the air and ground can cause ground turbulence. Military aircraft and helicopters can be affected by ground turbulence since they can operate at these low altitudes. Ground effects can also generate vibration as a consequence of coupling between the downwash and blades [11]. Buffeting is the vibration of a vehicle as it interacts with separated flow regions, generating aerodynamic forces on the structure. These forces can excite various modes of vibration or resonances of the aircraft. Bad weather, thermal disturbances, and

clear-air turbulence can result in buffeting in commercial jet aircraft. Buffeting can occur at low frequencies and be transmitted to the occupant via the floor and seat of the aircraft. On rare occasions, buffeting in commercial aircraft can be great enough to affect its control. Significant buffeting can also occur during aerial combat maneuvers (ACMs) in high-performance military jet aircraft. The measurement of vibrations associated with the air turbulence is random, the measurements are complex and it is hence difficult to use these vibrations as an energy source [11]. Fig. 1 schematically illustrates the localization of vibration sources in airplanes and helicopters. In view of the data available in the literature, it is possible to assume that the vibration typically occurs in the range of 10–200 Hz with an average vibration amplitude of 1 g. 2.2. Thermal sources Since the advent of aviation more than 100 years ago, it has been demonstrated that thermal sources are always present in aircraft. For instance, several studies have characterized the thermal behavior of two planes: a North American X-15 [12] and a McDonnell XF-88 [13]. Experimental data have revealed that the

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voltage. Nonetheless, no further information regarding the power density is available [22]. Kinetron has proposed a micro-generator solution using EnOcean consortium [23]. Numerous miniaturized generators have been developed in [18,24,25]. However, their performance is limited, particularly by the:

Fig. 3. Apache pitch link energy harvester and sensor node.

maximum temperature at the engine outlet and at the air inlets were respectively about 600 °C and 476 °C, leading to a gradient of 120 °C at the wings structure [12]. Such measurements were carried out at relatively high speeds corresponding to most military applications. On the other hand, in the case of airliners such as the McDonnel XF-88, the empirical spatial gradient was found to be much smaller, i.e., between 10 °C and 20 °C [13]. It is noteworthy that the wings are not the only part of the aircraft where large gradients occur. As reported in [14], temperature variations of 20– 40 °C could be attained on the hydraulic system situated between the two walls of the fuselage. In the case of helicopters, a lot of research has been dedicated to the reduction of heat emission. Actually, due to their low altitude and relatively low-speed flight profiles, helicopters are subjected to serious threats from radio, infrared (IR), visual, and aural detection and tracking. Among these threats, infrared detection and tracking are regarded as more crucial for the survivability of helicopters [15]. Different research studies have demonstrated that it is possible to reach a thermal gradient of 20 °C near the gear box and rotor blade. Also, other investigations show the possibility of significant thermal changes in the cabin [16]. Fig. 2 summarizes various thermal gradients occurring on commercial airplanes and helicopters. 2.3. Summary The previous analysis allows us to confirm that vibrations and thermal gradients are potential sources for powering autonomous sensors in structural health monitoring applications.

3. Micro-generator based energy harvesting 3.1. Mechanical energy harvesting 3.1.1. Electromagnetic conversion Electromagnetic energy harvesters (also called induction energy harvesters) use the motion of a permanent magnet to induce a voltage across the terminals of a coil of wire. This voltage is used to energize an electric circuit [17]. Several electromagnetic generators have been investigated over the last few years [18–20]. In 2007, Beeby et al. developed a 0.15-cm3 micro-generator capable of delivering 46 mW on a 4-kΩ optimal load at 52 Hz under a 0.6-g acceleration [18]. Another experiment conducted by Lee et al. in 2003, i.e., a generator about the size of an AA battery, was able to produce 830 mW at a frequency of 110 Hz from a 150-mm excitation amplitude [20]. In 2007, perpetuum started to commercialize the electromagnetic generator PMG7 able to produce 5 mW from an excitation of 0.1 g at 50 Hz [21]. Ferro-solutions has examined a generator-based Faraday effect, operating at 21 Hz with a 3.3 V-regulated output

● Difficulty of micro-coil fabrication with satisfactory performance; ● Necessity of “exotic” materials like magnesium, titanium or carbon fiber for the fabrication of magnets (NeFB, CoPtP, etc.) with small sizes [26]; ● Realization of small distances between the coils and magnets. An example of electromagnetic energy harvesting from a vibration source was shown in [27–30] as part of the European WISE project for helicopter flight applications. The developed device generated an electrical power from ambient, low-frequency, mechanical vibrations of a helicopter during its flight operation, by use of a suitable electromagnetic generator. The design of this vibration power generator was the result of development cycles and the final generator could provide sufficient electrical energy for wireless sensors. The whole system was tuned up to 17 Hz and operated at a 0.1–1 g peak vibration level so that the output power reached 2–25 mW. For instance, under excitation levels of around 2 m/s2, the generator produced an electrical power output of 10 mW [27–30]. However, no information about the temperature performance has been provided by the authors [27–30]. MicroStrain recently developed adaptive energy harvesting electronics for wireless sensor networks. The company proposed several micro-generators, e.g., a Magneto-Inductive Vibration Energy Harvester (MVEH™) was designed to harvest relatively lowfrequency vibrational energy inherent in machines and structures. The MVEH™ provides a regulated 3.2 VDC output at
4 mW from input vibrations of 200-mg amplitude when tuned from 15 to 60 Hz. Factory tuning is accomplished by adjusting precision flexure elements, which resonate small coils around rare-earth magnets to create energy [31]. MicroStrain adapts the MVEH™ for specific applications. For instance, a continuous monitoring of the pitch link loads is employed to determine component lifetime of the Apache Helicopter, as illustrated in Fig. 3. Measuring the pitch link strain is particularly difficult with hard-wired sensors due to its remote location and highly dynamic motions. As a result, autonomous wireless sensors are ideal candidates for strain and load measurements in such applications [32]. A magneto-inductive harvester capable of mounting to the exterior of the pitch link, while still allowing clearance for inspection, maintenance and safety wiring has been designed. The harvester was coupled to a MicroStrain SG-Link (Strain Gauge) sensor node. The strain data was transmitted to a Wireless Sensor Data Aggregator (WSDA) using an adjustable power IEEE 802.15.4 radio in combination with an LXRS “lossless” communications protocol [33]. A pitch link harvester consists of two stacks of opposing magnets enclosed by a moving coil assembly. The vertical motion of the pitch link is primarily at one-per-rev frequency of 4.9 Hz. It is driven by the swashplate's cyclic input with typical amplitudes of the order of 30 mm peak–peak. Because of this large range of motion, it was deemed unnecessary to implement a highly resonant system. Instead, a pivot linkage system was implemented utilizing opposing magnets to slightly enhance the motion and provide end stops. Additional over-travel protection was provided with hardened stop buttons and spring plungers. The measurements showed a data transmission at 128 Hz for the typical mechanical excitation and a start-up in 25 s [33].

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Fig. 4. HV-60 spin harvester configuration.

MicroStrain proposes a specific architecture of micro-generators for controlling the UH-60 rotor head. Indeed, this part of the helicopter contains many components critical for flight. Thus, a high output energy harvester located on the rotor head capable of powering a number of wireless sensors was designed. The microgenerator takes advantage of the relative motion between the fixed and rotating sides of the swashplate. Permanent magnets were mounted on the fixed swashplate and power-generating pickup coils, whereas power-conditioning electronics were located on the rotating side (see Fig. 4). The relative motion between the magnets and coils made it possible to generate energy stored in the coils. It is noteworthy that the spin energy harvester's output was proportional to the square of the relative velocity and decreased exponentially with an increasing coil/magnet gap size. Matching the load impedance led to maximum energy conversion. The load impedance was determined to be
13 Ω for a spin harvester comprised of four coils. In a configuration of one magnet and four coils with a gap size of 5–18 mm, and at a relative velocity of 3 m/s, a continuous power output was achieved from 1.0 mW to 60 mW. At a higher velocity of 9 m/sec, the result was significantly enhanced, from 9.2 mW to 500 mW [32]. 3.1.2. Piezoelectric conversion When it comes to a piezoelectric effect based on vibration energy harvesting, two configurations have been reported. Either the piezoelectric element is directly bonded on the structure (Fig. 5(a)) and yields a direct image of the strain and stress within the host structure; or an intermediate mechanical system is used (b), allowing a simpler operation but requiring a fine-tuning of the resonance frequency so that it matches one of the modes of the host structure. In both configurations, the system operates in dynamic mode in order to dispose of a significant amount of mechanical energy [34]. In the case of direct coupling, the energy provided by an input force is first converted into mechanical energy through the host structure, then to electrostatic energy via the piezoelectric element. A main benefit of direct coupling involves its highly efficient energy harvesting over a large frequency range, especially for structures excited under a high variation of the mechanical bandwidth [17,35].

On the other hand, when using the indirect (seismic) coupling, an additional mechanical energy conversion is used, resulting in a reduced energy conversion as a part of the energy in the host structure is transferred to such an intermediate mechanical system. Nonetheless, this structure leads to an independent design of the host structure and therefore easier maintenance as well as optimization of the system performance. In order to render the micro-generator efficient, the following criteria need to be respected: ● A proper positioning of the piezo-element near maximum strain/stress locations (for direct coupling) or maximum acceleration areas (for indirect coupling) and adapting the additional structure to the host structure in the case of seismic coupling. ● The use of piezoelectric elements featuring high coupling coefficients and/or the use of artificial enhancement of the global coupling factor. ● Adapting the load seen by the piezoelectric element. Obviously, the interdependence of the conversion stages necessitates a global approach rather than an individual optimization. A typical example is the damping effect generated by the harvesting process [36]: as a significant part of the mechanical energy is converted into electricity, the decreased mechanical energy results in limited vibrations of the structure and thus less output electrical power. Generally, the structure optimization aims to achieve a great amount of energy at a large frequency range through a piezoelectric element, which can be obtained by using a proper geometry [37], a variable resonance frequency [38,39], or nonlinear structures [40–43]. Another commonly adopted solution is to use several cantilevers with different lengths [44], which however decreases the power density. CEDRAT technologies have developed a micro-generator based on the Amplified Piezoelectric Actuator technology. Its electromechanical converter, namely APA400M-MD, has been certified for aeronautical applications. The generator with a volume of 50  32  22 mm3 exhibits a large stroke of 400 mm and a stiffness of 0.1 N/mm. Based on such a structure, it is possible to harvest 50 mW under a 35-mm displacement and a 100-Hz frequency [43]. MicroStrain has recently developed a Piezoelectric Vibration

Fig. 5. Typical configuration for vibration energy harvesting using piezoelectric elements: (a) direct coupling and (b) indirect (seismic) coupling.

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Fig. 6. Structure of the self-powered SHM subsystems.

Harvester (PVEH™) tuned to resonate within a typical kHz-range gear tooth meshing frequency that is present in gearbox vibration spectra. The harvester utilized a multi-layer piezoelectric stack encased in a resonant frame with a proof mass attached. The frame was configured to amplify the forces generated by the vibrating proof mass, compressing the stack to generate electrical energy. The target resonant frequency was adjustable, within design limits, by altering the size of the proof mass. The PVEH™ provided a regulated 3.2VDC output at
30 mW from input vibrations of 1.5 g amplitude when tuned to 1000 Hz. The piezoelectric generator was tested on a helicopter gearbox, and results demonstrated that sufficient power was produced at all operational torque levels to collect and transmit the target acceleration data measured by the HS-Link node. The sensor node was configured to collect burst samples of acceleration data at 100 kHz, for durations of one second. This was repeated every ten minutes [32,33]. Regarding aerospace applications, Laboratory of Electrical Engineering – INSA Lyon (LGEF) has developed self-powered wireless systems for structural health monitoring of composites. The device analyzes the interaction of an acoustic wave (lamb wave) with the host structure [45]. It is composed of two self-powered components as depicted in Fig. 6. The Autonomous Wireless Transmitter (AWT), including the energy-harvesting and an Synchronized Switch Harvesting (SSH) module [45], and when the latter is sufficient, a microcontroller wakes up and applies a pulse voltage on an additional piezoelectric element, which therefore generates the Lamb wave. The AWT then sends an RF signal containing its identifier for time and space localization before entering into sleep mode for a given time period. The Autonomous Wireless Receiver (AWR), which also includes an SSHI system. The AWR features a RF listening module which wakes up the system when it senses an incoming RF communication from an AWT close by. Once woken up, the lamb wave signature is sensed, amplified, and its RMS value computed. This value is then compared to a reference value (obtained in the pristine case), allowing an estimation of the change in mechanical structure. The results are then sent by RF transmission together with an identifier. Once these operations are completed, the whole system enters into sleep mode. After a predefined time period, the RF listening module is enabled to detect a new inspection cycle. The energy consumption estimation for the AWT is 1.20 mJ and 1.68 mJ for the AWR. The system can operate as soon as the stress reaches 2 MPa, which is a realistic stress value in classical structures. Within the Clean Sky project, de Jong proposed to power health monitoring modules in blades [46] thanks to a piezoelectric stack installed inside the damper rod. Due to the well-defined peak force generated in the damper, the stack geometry required a very limited margin of safety. Typically, the stack geometry should be

chosen to prevent excessive voltage build-up as opposed to mechanical overload. Simulations demonstrated that up to 7.3 W of power could be harvested from a single lag damper during horizontal flight. Such energy is sufficient to supply countless measurement nodes in the blade. The authors argued that the system was expected to have minimal influence on the dynamic stability of the helicopter and the mechanics of the lag damper. In case the harvesting system failed, the safety of the aircraft would not be affected. KCF Technologies has developed a wireless load-sensing module integrated in elastomeric rod ends of an H-60 Helicopter [47]. These components consist of a piezoelectric stack for energy harvesting, a load sensor based on magnetostriction, data acquisition hardware, an RF transmitter, and the associated circuitry. Experimental testing demonstrated the system's ability to harvest energy at representative pitch link loading levels, continuously load sensor data at 100 Hz, and wirelessly transmit the data to a nearby location. A flash memory could also be embedded within the rod end to store critical parameters derived from pitch link loading history. Monthéard et al. demonstrated the possibility to power a wireless sensor node by only using an aeroacoustic energy harvesting device, meant to be installed on the outside skin of an aircraft [48]. Based on the aeroacoustic phenomenon, the proposed method consists of a membrane driven into vibration by acoustic waves that result from the interaction of the airflow with a particular geometry. The device can generate a power of 2 mW for an air flow speed of 0.5 Mach. Recently, Defense Science and Technology Organization (DSTO) has developed a biaxial approach for vibration energy harvesting [49,50]. Specifically, the approach increases the potential operational directionality from single-axis to 360° in a plane. Host vibrations cause a ball bearing to oscillate, producing magnetic flux to excite a transducer using Terfenol-D/piezo-ceramic laminate, resulting in the generation of harvestable electrical power. Under an RMS host acceleration of 0.061 g at 9.8 Hz, the measured peak load voltage reached 23.9 V across a 3.3-MΩ load resistor, yielding a maximum RMS load power of 121 mW. 3.1.3. Electrostatic micro-generator Another possibility to harvest power from vibration sources is through electrostatic devices. The basic design for electrostatic vibration energy harvesters is a capacitor, for which the capacitance varies as it vibrates. The device should be initially charged, either externally, like in the first working electrostatic generator designed by Gilbert and Balouchi [51], Torres and Rincon-Mora [52], or via the use of an electret, as reported by Peano [53]. Such an initial charge allows the transmission of work from outside to the system. Mitcheson et al. [54,55] compared the advantages and disadvantages of a resonant electromagnetic generator, a resonant

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electrostatic generator and a non-resonant electrostatic generator as a function of the stress. The results confirmed some interesting aspects of the resonant micro-generators under the stress excitation with a narrow spectrum. Indeed, the resultant response was obviously at a maximum when the resonant frequency of the generator corresponded to the center frequency of the applied stress. In this case, the resonant electrostatic system obtained a similar response with respect to the resonant electromagnetic generator. On the other hand, with large-bandwidth stress excitation or with excitation whose center frequency varied as a function of time, the non-resonant electrostatic generator exhibited the better performance. In 2008, Sanyo proposed a 23  42  6 mm3 architecture that issued 40 μW at a frequency of 2 Hz [56]. The development of an electrostatic micro-generator will certainly not advance without an improved expertize of the MEMS technologies aiming to solve several drawbacks of mechanical performance, thermal stability and structure guidance. Fig. 7. Power density function of frequency.

3.1.4. Summary of mechanical energy harvesting Current generators produce relatively low power (o1 mW) but are sufficientto supply some systems like low-consuming sensors. Each technology presented in the previous paragraphs has advantages and disadvantages. However, some trends related to the context of the study (i.e. aerospace application) may be issued. First an important point in the discussion of energy harvesters for aerospace application is what performance metrics, or figures of merit, are appropriate to compare different devices or design approaches. Power efficiency could be defined for a harvester as the ratio of electrical power out to mechanical power in, but while this would give some indication of the effectiveness of the transduction, it misses a key aspect namely, that the input mechanical power itself strongly depends on the device design. Various metrics other than efficiency have been proposed, including power density [57], normalized power density [18], and two proposed measures of effectiveness [54,58]. Power density is attractive because this measure is very important to the end user; however, it only provides a meaningful comparison for fixed vibration source characteristics, since attainable output is so dependent on these. Table 1 gives a summary of the important parameters, in order to compare the different technologies. Three parameters are introduced. Two concern the mechanical excitation (frequency, and amplitude of the vibration) and the last one the power density of the micro-generators. The power density remains in a range between 10 μW/cm3 and 200 μW/cm3 for a frequency bandwidth of 10–200 Hz. Fig. 7 plots the data presented in Table 1, in term of power density function of the frequency. The typical bandwidth of application for each technology has been added.

The piezoelectric and electrostatic generators are appropriate to the energy harvesting over a wide frequency range, which often corresponds to the case of aeronautical structures [17,59,60]. The electromagnetic generators are better suited to the macroscopic scale but are very selective in frequency. Table 2 lists a comparison of the three conversion principles. According to the user's socio-economic expectations, the current trend is not necessarily a miniaturization at all costs but rather to achieve a fully autonomous system capable of operating over a wide frequency range together with a dedicated and effective electronics management module. For the aeronautical area, the constraints in terms of temperature involve numerous challenges either for conversion materials (e.g., the Curie temperature of ferromagnetic/ferroelectric materials [61] or the holding temperature of electric charge of an electret) or for mechanical structures of the converter with the dilatation phenomena [62]. For instance, the maximum temperature of a commercially available electret is around 110 °C [63] while that of some piezoelectric materials can reach 1000 °C [61] as can the temperature of ferromagnetic alloys [64,65]. Another equally important requirement for a self-powered system is the possibility of a maintenance-free operation of the wireless monitoring system. In the most extreme case, this may be the complete life of an aircraft component, i.e., over ten years before substitution during a D check. Regarding the above analysis, it appears that micro-generators based on piezoelectric or electromagnetic effects seem to be

Table 1 Comparison of power density for different technologies. Type

Frequency (Hz)

Amplitude (lm)

Power density (lW/cm3)

References

Electromagnetic Electromagnetic Electromagnetic Electromagnetic Piezoelectric Piezoelectric Piezoelectric Piezoelectric Electrostatic Electrostatic Electrostatic Electrostatic

60 107 64 99 85 100 150 40 10 20 50 6

200 210 100 2.54 7.9 184 11 36 1000 1130 90 9000

100 1.5 8.06 27 90 82 45 145 15 4 56 2.42

[76] [77] [78] [79] [80] [81] [82] [82] [83] [84] [85] [86]

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Table 2 Comparison of three conversion technologies. Electromagnetic

Electrostatic

Advantages

þ High output current þ Robustness þ Long lifetime proven

þ þ þ þ

Disadvantages

- Lowoutput voltage, problem ofelectronicmanagement - Bulky - Requirement of precision machining - Insufficient knowledge on temperature resistance - Low efficiency in low frequencies and small sizes - Problem of electromagnetic compatibility

- Needs a polarization source. - Complex power circuit management - Mechanical guiding - Low capacitor (sensible to parasitic capacitor) - No information about time life - Insufficient knowledge on temperature resistance

excellent candidates for energy harvesting from vibrational sources. Actually, these two technologies perfectly complement each other. In other words, the piezoelectric generator is suitable for high vibration frequencies whereas the electromagnetic one is appropriate for low frequencies (o 100 Hz). As a result, a combination of both technologies makes it possible to achieve a full bandwidth-range micro-generator. The mechanical vibration source is not the only one available on an aircraft. The following paragraphs will thus introduce another solution based on thermal generators. 3.2. Thermal energy harvesting Temperature variations can be an alternative solution for selfsustaining sensors as they are present in aerospace applications. The principle is based on a conversion into electrical energy from heat flow moving between two points at different temperatures. Several physical functionalities have been developed to ensure such a transduction: – Pyroelectric effect – Seebeck effect 3.2.1. Pyroelectric effect The pyroelectric effect is the property of some dielectric materials with polar point symmetry which shows a spontaneous electrical polarization as a function of temperature. A temperature change in time determines a corresponding variation in the induced charge. The pyroelectric energy harvesting consists in extracting energy of time-variable heat through the thermal capacitance of the active material. The optimization of the input energy lies in the trade-off in the heat capacitance value, as energy should enter easily (low heat capacitance value and high thermal conductivity), and in the amount of available energy (high heat capacitance value). Over the past ten years, pyroelectric thermal-to-electrical energy harvesters, such as the system of Hunter et al. [66], have been proposed. The approach uses a resonantly driven pyroelectric capacitive bimorph cantilever structure, i.e., a pyroelectric/metal bilayer. The bimorph permanently contacts with a surface whose temperature susceptibly changes as a function of time. When the temperature of the surface increases, the beam bends downwards due to the difference of the thermal dilatation coefficient between the metal layer and the pyroelectric layer. Afterward, the metal side of the beam touches the cold surface of the heat sink, resulting in: (1) the apparition of a heat flux circulating from the hot to the cold surface, producing a thermal-to-electric conversion thanks to the pyroelectric material, (2) cooling of the metal layer

Very high output voltage Harvesting on low frequencies Simple implementation and integration Coupling coefficient easy to adjust

Piezoelectric þ þ þ þ þ

High output voltage High electric capacitor Simple use Robustness Large T° range

- Theconversion propertiesof themicro-generatorareintimatelyrelatedto those of the piezoelectric element.

after the contact, allowing the bilayered system to return to its initial position. When the contact with the cold surface is interrupted, the temperature of the metal layer tends to increase and the process is reproduced again. Sebald et al. [67] and Lallart [17] have also proposed solutions for energy conversion using pyroelectric elements. Despite the enormous enthusiasm of the scientific community when it comes to pyroelectric materials, no industrial generator has appeared. The major barrier to mass commercialization of this technology is poor knowledge of the material, a low conversion efficiency and high production costs. At the moment, most commercial thermal harvesters are based on the Seebeck effect. 3.2.2. Seebeck effect Thermoelectricity is the conversion of heat into electricity (Seebeck effect), or inversely, of electricity into heating or refrigeration (Peltier effect). The use of the Seebeck effect could make it possible to save heat that would otherwise be lost. A good thermoelectric generator (TEG) must have a high Seebeck coefficient to produce the required voltage, a high electrical conductivity to reduce thermal noise, and a low thermal conductivity to reduce thermal losses [68]. Energy generated by the TEG can be used thanks to thermopiles. Thermopiles are composed of several thermocouples, usually connected electrically in series and thermally in parallel [69]. The working principle is the following. Thermal gradients in the environment are directly converted to electrical energy through the Seebeck effect. In fact, temperature changes between opposite segments of a conducting material result in heat flow and consequently charge flow since mobile, high-energy carriers diffuse from high to low concentration regions. Thermopiles consisting of n- and p-type materials electrically joined at the high-temperature junction are therefore constructed, allowing heat flow to carry the dominant charge carriers of each material to the low temperature end, establishing a voltage difference across the base electrodes in the process [68]. The generated voltage and power increase with the temperature gradient. Basically, a solid-to-air miniature harvester is used and consists of a thermoelectric device positioned between an aluminum interface plate and small, heat sink to maintain the thermal gradient. This allows to improve the thermal gradient as well as the Seebeck coefficient. Paget et al. proposed a sensor node architecture that can simultaneously control three strain gauges. According to the Seebeck effect, a temperature gradient of about 30–50 °C is necessary to generate sufficient energy for the measurements to be selfsufficient [70,71]. Such a gradient can be easily found in the aircraft environment, e.g., by exploiting the difference between the outer shell and the lining of the aircraft.

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Fig. 8. Working principal of the thermo-generator in an airplane structure. Figure adapted from [71].

Within the AMETYST project, the approach of a quasi-static temperature difference in aircraft has been investigated [72]. Fig. 8 shows the general deployment of a mimic using the static temperature gradient in aircraft. Temperature measurements during the test flight of an aircraft have been performed, e.g.,  20 °C at the outer shell and þ20 °C at the inner shell. Micropelt proposed to commercialize this device with a series of high-tech thin-film TEGs including the MPG-D751 [73]. Static energy harvesting is a very interesting method in cases when both “hot” and “cold” sides are available, leading to a Seebeck element. However, this approach is not valid for all relevant locations of autonomous sensors in aeronautical applications. Actually, the aircraft flight envelope offers another specific physical phenomenon which is the temporal change in temperature, e.g., during takeoff and landing. These temperature variations can go from an ambient temperature on the ground to  55 °C at cruising altitude. To take advantage of such a specific feature of the airplanes, a thermoelectric device must be associated with a thermal mass on one side of the device which prevents simultaneously getting the same temperature on the other side. In order to increase the thermal constants of the phase change, additional materials may be used. For instance, water will freeze when the temperature is below 0 °C. The thermal storage device described by Elefsiniotis et al. consists of two concentric cylinders, containing different phase change materials (PCMs) [74]. During the phase changes, they release or absorb energy equal to their respective latent heats. The choice of a PCM is critical as it defines the operating temperature range of the device. The concept of

having two different PCMs increases the operational temperature range of the device substantially. The material used for the cylinders is PMMA due to its low thermal conductivity and low density. The bottoms of the cylinders are made of copper, which has a high thermal conductivity. Hence, most of the heat flux goes through the copper via the TEGs to the fuselage and vice versa. The proposed thermoelectric harvester has shown great potential with regard to performance. Independent of the investigated temperature ranges, the minimum harvested energy was more than 39.74 J and could under optimum conditions be as high as 69.73 J. This amount of energy is sufficient to power a wireless sensor [72]. 3.2.3. Summary of thermal energy harvesting The thermal power generation technology uses heat as a power source, eliminating the need to use traditional wired power sources or replaceable batteries. When paired with wireless transmitters, the thermal solution can provide a source of power for years of maintenance-free operation. In aeronauticals, the use of thermal-source devices on the outer surface of aircraft could power distributed devices like sensors, and suppress the need for some of the wires currently used to feed them, leading to a reduction in aircraft weight, and therefore a lower fuel consumption. As in the case of a micro-mechanical generator, energy harvesting based on heat variation results in relatively low power but is sufficient for the self-powering of some sensor nodes. The previous state of the art has demonstrated the existence of two

Table 3 Comparison of different thermal conversion technologies. Pyroelectric

Thermoelectric

Advantages

þ High output voltage þ Possibility to harvest on quick change of temperature as a function of time

þ Technological maturity þ Large range of material þ Commercially available circuit dedicated to energy harvesting þ Robustness

Disadvantages

- The conversion properties of the micro-generator are intimately related to the one of the pyroelectric element. - Insufficient knowledge on temperature resistance - Difficulty of harvesting on spatial gradients, needs a spatial-to-temporal conversion using thermal machine

- Low efficiency
10% - Bulky, requires heat sinks to keep the spatial gradient. - Difficulty of harvesting on temporal fluctuations of temperature

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thermal harvesting technologies, i.e., pyroelectricity corresponding to a temporal temperature gradient and thermoelectricity corresponding to a spatial temperature gradient. Table 3 presents the advantages and disadvantages inherent to each technology. As observed, thermoelectricity based on the Seebeck effect shows advantages over pyroelectricity in terms of robustness, simplicity, and technological maturity. The pyroelectric element, however, with such interesting characteristics as a high output voltage and the possibility to harvest on quick temperature change, is an excellent alternative to the thermoelectric component [75]. Before achieving that, many drawbacks of the pyroelectric process need to be overcome, which is surely feasible in the near future thanks to considerable advances of the MEMS technology.

4. Conclusion Energy harvesting systems are an important technological tool for the introduction of wireless autonomous sensors in aeronautical applications. Indeed, for devices supplied by batteries, the weight becomes too important, once the power consumption of the circuit and the self-discharge of the battery are extrapolated to the total lifetime. This paper gives an overview of the different solutions currently developed for autonomous wireless sensors, showing promise for future applications of energy harvesting in aeronauticals. Despite several energy sources available in airplanes and helicopters, engineers and scientists have to face numerous challenges when trying to achieve reliable devices able to capture sufficient energy to perform any useful work. Among the existing sources, energy harvesting based on vibrational and thermal effects has been chosen as the subject for this review, thanks to their better reliability and performance compared to others. In the case of vibrational energy, the production of microgenerators using either electromagnetic or piezoelectric conversion elements seems the most promising. Both conversion principles are complementary although the electromagnetic one is more effective in the low frequency range ( o100 Hz). For thermal energy harvesting, the system operation is based on the principle of the Seebeck effect. Such technologies are investigated because of their robustness and resistance to environmental stresses, i.e., mechanical and thermal. Nonetheless, a number of challenges must be solved before achieving efficient wireless autonomous sensors for real aeronautical applications, such as long-lasting selfsufficient operation of sensors, selection of wireless protocols, etc.

Acknowledgments This work has received financial support from SKF within the framework of the “EPICE” project.

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