Condition-Based Maintenance (CBM) is gaining momentum in civil aviation, yet its widespread adoption remains constrained by economic and regulatory aspects (Verhagen et al. 2023; Meissner et al. 2025). In contrast, sectors like civil infrastructure, marine, and military aviation have successfully applied CBM for decades, leveraging active Structural Health Monitoring (SHM) systems to optimize maintenance and operations.

This paper examines the progress and potential of CBM in civil aviation, focusing on active monitoring of structural performance. CBM relies on availability of data, which active SHM systems can provide. While modern commercial aircraft generate extensive data for flight controls, navigation and systems, data specifically useful for structural health assessment is comparatively limited. Boeing is developing passive monitoring applications, prioritizing in-service crack detection, addressing common maintenance requests. CBM offers a comprehensive framework integrating these passive methods with active monitoring technologies, enhancing maintenance strategies.

As Boeing and the civil aviation industry move toward CBM frameworks, it is crucial to recognize that CBM is more than an economic tool. Beyond assisting fleet management, CBM is a predictive approach that enhances safety, anticipating structural issues before they become critical. Regulatory agencies are increasingly issuing guidelines defining requirements and scope for monitoring systems and data use. To gain certification, SHM and CBM systems must comply with these standards, and current development efforts focus on meeting them.

Passive monitoring provides discrete data points, such as during scheduled inspections, whereas active SHM offers real-time data. This continuous stream of data serves two main purposes: updating predictions and validating assumptions about structural performance. For example, active SHM can monitor aircraft utilization metrics like flight cycles and operating fuselage pressures, critical to assess fatigue life and damage progression of metal details.

Historically, commercial transport aircraft structure is designed based on various mission profiles such as short, medium or long flights. Durability requirements are used to design airframe structure to be crack-free up to a defined Design Service Objective (DSO), with defined reliability target and confidence level. Damage Tolerance (DT) analysis provides inspection intervals and methods based on the most critical mission profile. However, actual aircraft or fleet usage often deviates from these standard profiles. Active SHM enables user-specific mission profiles by monitoring real operational parameters, including fuselage pressure cycles, among others. This tailored data could refine predictions of fatigue and damage tolerance to provide operators relief from the baseline inspection programs.

Furthermore, SHM enables automation of feedback loops through Digital Twin models, which are essential for fully realizing CBM capabilities (Fig. 1). This paper discusses examples of potential active SHM/CBM applications, focusing on monitoring inputs like fuselage pressure and temperature, illustrating how these technologies can affect maintenance practices in civil aviation.

References:

Verhagen WJC, Santos BF, Freeman F, van Kessel P, Zarouchas D, Loutas T, Yeun RCK and Heiets I. 2023. Condition-Based Maintenance in Aviation: Challenges and Opportunities. Aerospace, 10(9).

Meissner R, Ali Pohya A, Weiss O, Piotrowski D & Wende G. 2025. Regulatory pathways to certifiable condition based maintenance solutions in aviation: A comprehensive review. Progress in Aerospace Sciences, 158.

Ice detection is critical for aircraft safety. The passive structural health monitoring (SHM) techniques offer a promising way to realize the real-time monitoring of the in-flight airplane. However, the passive identification of wavenumber for vibrating structures via the cross-correlation technique relies on the assumption of a diffuse wavefield, which makes the passive ice detection unreliable beyond the diffuse wavefield. To overcome this limitation, this study proposes a novel passive ice detection method based on a corrected finite difference scheme. This approach can estimate the ice thickness by identifying the local wavenumber using a small sensor array, free from the assumption of a diffuse wavefield.

The proposed approach is to identify the structural wavenumber based on the vibration equation of flexural plates, governed by Kirchhoff plate theory. The biharmonic operator in the governing partial differential equation (PDE) is discretized spatially via the finite difference scheme. A total of 13 uniformly spaced measurement points are employed to reconstruct the spatial derivatives in the governing PDE. To mitigate the discretization error derived from the PDE approximation, correction factors are introduced into the PDE. Finally, the wavenumber-frequency relationship (as referred to the dispersion curve) can be obtained by finding the roots of the corrected governing equation.

A thin plate with an ice layer accreted on its surface can be considered as a two-layer structure. The theoretical model of the dispersion curve for various ice thicknesses can be constructed by solving the equivalent material properties of the two-layer structure via the Ross–Kerwin–Ungar (RKU) mixture law. Based on the fact that the ice accretion on the thin-walled structure leads to the shift of the dispersion curve, the ice thickness can be estimated by minimizing the average distance between the estimated dispersion curve and the theoretical model.

According to the Shannon-Nyquist sampling theorem, the shortest wavelength that can be resolved without aliasing is twice the sensor spacing. Consequently, the maximum wavenumber that can be measured is defined as the Nyquist wavenumber. The minimum wavenumber is fundamentally limited by the array aperture, where the maximum resolvable wavelength is the aperture of the antenna array.

A passive experiment has been conducted on a 1mm-thick aluminum plate. 13 piezoelectric transducer (PZT) disks are bonded to the plate for measuring the structural vibration signals (i.e., dynamic strain), and the spacing between two adjacent sensors for the finite difference method is 0.01 m. Under varied ambient noise (i.e., flow-induced vibration generated by a household hairdryer and an air-jet, noise generated by a loudspeaker), this method is experimentally demonstrated to be robust, even for the arbitrary distribution of sources. Although the proposed method is limited to a narrower valid frequency range, due to its dependency on the spatial configuration of the sensor array, it can effectively detect ice conditions regardless of the source distribution. It is very accurate for thin ice, which is of more concern, because the early detection of airframe icing is essential in practice.

In the context of recent reusable launch vehicles (RLV) developments, SHM could help fast and economic revalidation of RLVs between launches, provided that the SHM sensors keep their functionality and reliability during harsh flight conditions and after repeating launches being exposed to such conditions. One of the targeted structures of this work are the metallic or composite cryogenic fuel tanks and fuel lines of the rocket. Thus, this paper focuses on cryogenic environment and cryogenic cycling that can affect both the immediate measurement and the long-term durability of the sensors.

In this study, bonded Piezoelectric and Fiber Bragg Gratings (FBG) sensors are studied for guided wave and acoustic measurement under such environment. FBG sensors under cryogenic conditions have been widely studied for both temperature and strain measurements but more rarely for acoustic or guided waves (GW) measurements. An FBG, as a fully passive sensor, presents some real safety advantages for the monitoring of structures in contact with highly flammable ergols where a potential electric spark is to be avoided.

The first part of this study is dedicated to assessing the durability of these sensors when integrated onto metallic or composite parts subjected to dozen of cryogenic cyclings. This is done by monitoring piezoelectric admittance spectras and FBG reflection spectra, which are sensitive to the degradation of the sensors or the bonding. Then the functionality of these sensors at cryogenic temperature is evaluated through some guided wave pitch catch measurements at temperatures varying between 293K (ambient) and 77K (liquid nitrogen immersion). Both the emitting performances of the piezoelectric transducer and the sensing capability of the receiving FBG are strongly influenced by temperature through intrinsic effect on the sensors properties and modified strain transfer between the sensors and the structure. For bonded FBG sensors, the cryogenic temperatures can lead to important spectrum distortion, which can directly affect the GW measurements as it uses the edge filtering approach and thus is directly linked to the spectrum slope. Therefore, an automated calibration step is implemented in the acquisition system to ensure reliable GW measurements with cryogenic temperature induced spectrum distortion.

Structural Health Monitoring (SHM) systems are now mature and are being widely considered for implementation on commercial aircraft. SHM systems can provide immense benefits for commercial aircraft including providing savings in planned maintenance, increasing aircraft flying time by minimizing aircraft downtime and streamlining operational logistics.

The pathway towards implementation will however need to address some key challenges including the availability of limited in-service data and the need to prove the viability of SHM systems compared to traditional inspection methods. The SHM system used to replace a conventional NDI method will need to demonstrate that the damage detection capability of the SHM system is equal to or better than that of the existing NDI method. In order to meet these requirements, it is imperative that the SHM system have the ability for robust and accurate damage detection in the aircraft flight environments.

The SMART Layer PZT based SHM system can help address the challenges associated with SHM system certification and implementation. The SMART Layers utilize PZT transducers that are now widely used for crack detection and structural health monitoring in aerospace applications. The PZT SHM system is based on traditional NDI-UT physics but utilizes a different wave propagation mode (Guided waves). SMART Layers are thin, flexible, optimally designed PZT sensor networks that are integrated with the structure for maximum energy transmission and easy integration. In addition, the SMART Layers are designed to

• be installed in hidden and hard to access locations on the aircraft potentially replacing Low or High Frequency Eddy Current (LFEC, HFEC) and enabling structural inspection without structural disassembly
• provide robust data in multi-environments for any type of application
• provide “area coverage” for crack detection irrespective of the crack orientation and location in the area of concern
• minimize false calls that can lead to unscheduled maintenance
• enable sensor placement such that the area can still be validated using traditional NDI methods if needed

In addition, the PZT SHM system has been tested over the years and can leverage historical data from previous aircraft installations precluding validation using alternate NDI methods.

This presentation will discuss the advantages of the PZT SHM system in “actively” providing structural inspection information using multiple diagnostic methods developed for the sensor networks. This paper will demonstrate that the SMART Layer PZT system inherently provides multiple, independent diagnostic methods that operate simultaneously within a single structurally integrated sensor network. Using the same PZT array, several physics-distinct approaches can be utilized including guided-wave interrogation, impedance methods, scattering-based time-of-flight analysis, and damage imaging to characterize crack initiation and growth at designated inspection areas. Each diagnostic method is governed by a different physical mechanism, providing orthogonal and cross-validating indicators of structural degradation.

These methods enable accurate detection of cracks in various flight environments. Historical and recently developed test data from multiple sources including coupon, flight tests and other non-commercial aircraft usage of the SHM system will be discussed to demonstrate a pathway towards the system certification while minimizing any false calls.