Structural Health Monitoring (SHM) is a valuable tool for in-service assessment of structural condition. Despite a broad use in many engineering fields, SHM has seen limited application in space systems. This article explores specifics of SHM applied to space systems and satellites in particular. It is suggested that SHM may be considered for aiding rapid assembly of spacecraft components, monitoring system dynamics during launch, and model updating from an assessment of in-service variation of structural properties. The article presents a discussion of factors affecting realization of the SHM system for spacecraft and provides recommendations for the system configuration and its practical use. The SHM system design based on a network of piezoelectric active sensors is considered. System operation focuses on SHM of improperly tightened bolts, assessment of adhesive bonds, and embedded material characterization techniques. Synergistic use of the same hardware for acoustoelastic, non-linear acoustic, and material characterization methods is recommended, and further system integration options are proposed.

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Embedded ultrasonics has demonstrated considerable utility in structural health monitoring of aeronautical vehicle. This active sensing approach has been widely used to detect and monitor cracks, delaminations, and disbonds in a broad spectrum of metallic and composite structures. However, application of the embedded ultrasonics for active sensing of incipient damage before fracture has received limited attention. The aim of this study was to investigate the suitability of embedded ultrasonics and nonlinear acoustic signatures for monitoring pre-crack fatigue damage in aerospace structural material. A harmonic load was applied to structural specimens in order to induce fatigue damage accumulation and growth. Specimens of simple geometry were considered and piezoelectric active sensors were employed for generation and reception of elastic waves. The elastic wave signatures were analyzed in the frequency domain using nonlinear impedance and nonlinear resonance methods. A relationship between fatigue severity and linear as well as nonlinear acoustic signatures was investigated and considered in the damage classification procedure. Practical aspects of the active sensing of the fatigue damage before fracture were discussed and prospective avenues for future research were suggested.

Structural Health Monitoring (SHM) is a valuable tool for in-service assessment of structural condition. Despite a broad use in many engineering fields, SHM has seen limited application to space systems. The paper explores specifics of SHM applied to space systems and satellites in particular. It is suggested that SHM may be considered for aiding rapid assembly of satellite components, monitoring system dynamics during launch and assessing in-service variation of structural properties suitable for model updating. In this paper, we present a discussion of factors affecting realization of the SHM system for satellites and provide recommendations for the system configuration and its practical use. The SHM system design based on a network of piezoelectric active sensors is considered. Piezoelectric sensors were selected due to availability of both active and passive operation modes. The passive SHM mode may find applications related to spaceship launch process and on-orbit structural monitoring. It is anticipated that the active structural assessment may be exercised during satellite pre-launch qualification and possible on-orbit characterization. Hence, the present contribution focuses on SHM of improperly tightened bolts as one of major satellite integrity concerns and embedded material characterization techniques. The developed SHM method utilizes the acousto-elastic effect manifested through the elastic wave phase shift caused by stress-induced localized changes in the sound speed. Experiments aimed at improving fundamental understanding of this technique are discussed and applicability of the technique to realistic structures is investigated. The methodology for in-situ material characterization is tested on structural elements of simple geometry and extension to complex structural systems is suggested. Synergistic use of the same hardware for acoustoelastic and material characterization methods is recommended and further system integration options are proposed.

Dynamic measurements are widely used for structural condition assessment and damage detection. A wide range of studies are available on vibration-based detection and identification of fatigue cracks in simple and complex structures. This research explores the application of the electromechanical impedance method and nonlinear resonance measurements to high frequency detection of incipient fatigue damage in aluminum alloy specimens. The electromechanical impedance method relies on the coupling between the mechanical properties of a structure and the electrical properties of attached piezoelectric wafer active sensors (PWAS). This coupling allows structural properties to be inferred from the electrical impedance signature of the sensor. In this study, the electromechanical impedance method is utilized for assessment of material deterioration under cyclic fatigue loads. Aluminum specimens were subjected to increasing fatigue cycles at stress amplitudes below the yield point, and electromechanical impedance signatures were taken at discrete levels of fatigue damage. Linear and nonlinear features of the impedance signatures were compared for different damage conditions. The results show a downward frequency shift of impedance peaks with increasing fatigue load. This frequency shift is observed before visible crack development and fracture. Nonlinear resonance tests were applied to fatigued aluminum samples. PWAS were utilized for transmission and reception of elastic waves at increasing amplitude levels. Variations in structural dynamic characteristics were considered for different excitation conditions and increasing damage severity. This paper discusses damage detection capabilities of each method and provides perspectives for utilizing information on incipient damage for predicting structural performance under known operational loads.