Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.

All-printed strain sensors: Building blocks of the aircraft structural health monitoring system

Abstract: Characterization of all-printed strain gages to assess their suitability for structural state monitoring of large structures is presented. Strain sensor response, transverse strain sensitivity and long-term reliability are key performance parameters of printed strain sensors on flexible substrates. These key performance parameters are evaluated for inkjet and screen printed strain sensors on polyethylene-terephthalate (PET) flexible substrates. More specifically, printing characteristics of commercially available inks, gage factor of serpentine strain sensors with transverse strain and temperature sensitivity, and sensor reliability under unidirectional tensile and fatigue loading is assessed. Maximum strain to which both inkjet and screen printable formulations can be reliably used for long-term repeatable measurements is recommended based on tensile and fatigue testing. Variation in gage factor is attributed to micro- and macro-scale fracture of printed traces under mechanical loading. Substrate, ink and printing process parameters are identified to further improve strain sensing characteristics of low-cost, large area strain mapping systems. Reliable, low-cost, and large-area strain mapping systems are sought for continuous or on-demand real-time diagnosis and prognosis of complex structural components.

Modeling of piezoelectric-based Lamb wave generation and sensing for structural health monitoring

Abstract: Among the various schemes being considered for Structural Health Monitoring (SHM), Lamb-wave testing has shown great promise. While Lamb-wave testing using hand-held transducers for Non Destructive Evaluation (NDE) is a well-established technology, Lamb-wave testing for SHM using surface-bonded/embedded piezos is a relatively new field. Little effort has been made towards a precise characterization of Lamb-wave excitation using piezos and often the various parameters involved are chosen without mathematical foundation. In this work, modeling of transient plane and circular-crested Lamb-wave generation and sensing using surface-bonded piezos in isotropic plates based on the 3-D linear elasticity equations is explored. Equations for the output voltage response of surface-bonded piezo-sensors in Lamb-wave fields are presented and optimization of the actuator/sensor geometry and materials is done based on those. Finally, numerical and experimental results to examine the validity of these models are discussed.

Structural health monitoring (SHM) of aerospace composites

Abstract: The chapter starts with a discussion of the structural health monitoring (SHM) techniques for aerospace composites. This is followed by a presentation of the major sensor classes used in SHM practice with focus on advanced sensors such as optical fiber Bragg gratings (FBG) and piezoelectric wafer active sensors (PWAS). Electrical sensing methods for composites SHM are also discussed. The chapter expands the discussion on several tracks such as passive sensing SHM, active sensing SHM, local-area sensing with the electromechanical impedance spectroscopy (EMIS), active sensing SHM with electrical methods, direct methods for impact damage detection. The chapter finishes with summary, conclusions, and suggestions for further work.

Internet of Things (IoT) Platform for Structure Health Monitoring

Abstract: Increase in the demand for reliable structural health information led to the development of Structural Health Monitoring (SHM). Prediction of upcoming accidents and estimation of useful life span of a structure are facilitated through SHM. While data sensing is the core of any SHM, tracking the data anytime anywhere is a prevailing challenge. With the advancement in information technology, the concept of Internet of Things (IoT) has made it possible to integrate SHM with Internet to track data anytime anywhere. In this paper, a SHM platform embedded with IoT is proposed to detect the size and location of damage in structures. The proposed platform consists of a Wi-Fi module, a Raspberry Pi, an Analog to Digital Converter (ADC), a Digital to Analog Converter (DAC), a buffer, and piezoelectric (PZT) sensors. The piezoelectric sensors are mounted as a pair in the structure. Data collected from the piezoelectric sensors will be used to detect the size and location of damage using a proposed mathematical model. Implemented on a Raspberry Pi, the proposed mathematical model will estimate the size and location of structural damage, if any, and upload the data to Internet. This data will be stored and can be checked remotely from any mobile device. The system has been validated using a real test bed in the lab.

Combination of a Time Reversal Process and a Consecutive Outlier Analysis for Baseline-free Damage Diagnosis

Abstract: A structural health monitoring system is developed for continuous online monitoring of delamination initiation and growth in composite structures. Structural health monitoring problems are often cast in the context of a statistical pattern recognition paradigm, in which a damage state of a structure is inferred by comparing test data with baseline data. However, subtle signal changes due to damage can often be masked by larger ambient variation of operational and environmental conditions of an in-service structure. Therefore, it is critical for the development of a robust monitoring system to minimize false-positive indications of damage caused by the undesired operational and environmental variation of the structure. The issue of minimizing damage misclassification has been addressed in this article by developing an instantaneous damage detection scheme that does not rely on past baseline data. The proposed instantaneous damage diagnosis is based on the concepts of time reversal acoustics and consecutive outlier analysis, and the proposed damage diagnosis has been tested for detecting delamination in composite plates.