Frequency warping compressive sensing for structural monitoring of aircraft wing

Perelli, Alessandro; Harput, Sevan; Marchi, Luca De; Freear, Steven

doi:10.1109/icdsp.2013.6622668

Cited by 7 publications

(5 citation statements)

References 17 publications

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“…For instance, in the aerospace industry, the use of ultrasonic sensors is very common. Zhao et al [ 138 ], Meyendorf et al [ 139 ], and Perelli et al [ 140 ] introduced novel low-cost monitoring systems based on ultrasound technology for aircraft´s health monitoring applications. In the oil industry, in order to track the health of the pipelines, Wan et al [ 141 ] and Barshinger et al [ 142 ] developed low-cost wireless ultrasound-based monitoring devices.…”

Section: Resultsmentioning

confidence: 99%

Low-Cost Technologies Used in Corrosion Monitoring

Komary

Komarizadehasl

Tošić

et al. 2023

Sensors

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Globally, corrosion is the costliest cause of the deterioration of metallic and concrete structures, leading to significant financial losses and unexpected loss of life. Therefore, corrosion monitoring is vital to the assessment of structures’ residual performance and for the identification of pathologies in early stages for the predictive maintenance of facilities. However, the high price tag on available corrosion monitoring systems leads to their exclusive use for structural health monitoring applications, especially for atmospheric corrosion detection in civil structures. In this paper a systematic literature review is provided on the state-of-the-art electrochemical methods and physical methods used so far for corrosion monitoring compatible with low-cost sensors and data acquisition devices for metallic and concrete structures. In addition, special attention is paid to the use of these devices for corrosion monitoring and detection for in situ applications in different industries. This analysis demonstrates the possible applications of low-cost sensors in the corrosion monitoring sector. In addition, this study provides scholars with preferred techniques and the most common microcontrollers, such as Arduino, to overcome the corrosion monitoring difficulties in the construction industry.

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Section: Resultsmentioning

confidence: 99%

Low-Cost Technologies Used in Corrosion Monitoring

Komary

Komarizadehasl

Tošić

et al. 2023

Sensors

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“…CS is also used to compress wave-like signals such as guided waves [85], ultrasonic phased array [96], lamb waves [97,98], and acoustic emissions (AEs) [99][100][101]. Such applications have been used for defect detection, crack and corrosion monitoring in aircraft wings [101], and delamination detection in composite plates [102].…”

Section: Compressive Sensingmentioning

confidence: 99%

High-dimensional data analytics in structural health monitoring and non-destructive evaluation: a review paper

Momeni

Ebrahimkhanlou

2022

Smart Mater. Struct.

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This paper aims to review high-dimensional data analytic methods for structural health monitoring (SHM) and non-destructive evaluation (NDE) applications. High dimensional data is a type of data in which the number of features for each observation is much larger than the number of all observations. High dimensional data may violate assumptions of the classic methods for statistical modeling and data analysis. Then, classic statistical modeling will no longer be applicable. High dimensional data analytics (HDDA) methods were developed to overcome this challenge and analyze these types of data. In the field of SHM/NDE, there are several sources of high-dimensionality. Examples include a large number of data points in continuous waves/signals or high-resolution images/videos. HDDA methods are used as a dimension reduction tool to preprocess data for further analysis, or they are directly implemented for damage detection and localization. This paper reviews six HDDA methods as well as existing and potential applications in SHM/NDE. Particularly, this paper discusses the vast range of implemented SHM/NDE applications from crack detection to data missing data imputation. Furthermore, experimental and simulated datasets have been used to show the application of HDDA methods as hands on examples. It is shown that the potential of HDDA for SHM/NDE studies is significantly more than the existing studies in the literature, and these methods can be used as a powerful tool that provides vast opportunities in SHM/NDE.

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“…De Marchi (2012, 2013) constructed a sparse basis of the wing bending wavelet and the frequency transform for ultrasonic guided wave of the composite material, and the damage signals were simulated and analyzed for the damage detection and location, and the effectiveness of CS was illustrated in SHM [11][12][13][14][15]. De Marchi et al (2017,2018) adopted CS to reduce the number of points measured, and the scanning time of the measuring instrument, to speed up the imaging speed of damage, and to compare various sparse bases [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Compressive sampling system based on random demodulation for active and passive structural health monitoring

Liang¹,

Han²,

Cai³

et al. 2022

Smart Mater. Struct.

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Structural health monitoring (SHM) is a revolutionary and innovative technique for determining structural integrity. It has broad application prospects in industrial equipment and infrastructure such as aircrafts, bridges and buildings. SHM system is used to monitor and diagnose the damages of these large structures, and it requires to install large sensor networks in or on large structures such as aircraft wings and airframes. The large number of sensors results in a very large amount of data for excited and received signals, especially for ultrasonic guided wave-based SHM with high frequency signals. According to the traditional Nyquist sampling theorem, the sampling rate is at least 2 times higher than the highest frequency of the received signal. The high sampling rate and the large amount of data pose a serious challenge on the signal acquisition, transmission, storage, and processing equipment, especially in the case that the signal needs to be transmitted to the base station for processing in real time. Therefore, how to compress and sample signals obtained by large sensor networks to improve monitoring efficiency and reduce costs is a research hotspot in current SHM. This paper adopts compressive sensing (CS) theory which has appeared in recent years to solve the big data and high frequency acquirement problem of SHM. The random demodulation system is chosen to realize CS, and the corresponding hardware and software systems are designed, which are achieved to compress and sample signal and reduce the sampling rate and the amount of data at the same time. The active and passive SHM signals based on piezoelectric sensor networks are compressed and sampled, and the new method are compared with the traditional Nyquist sampling in the experiment. The results show the effectiveness of the proposed method.

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Frequency warping compressive sensing for structural monitoring of aircraft wing

Cited by 7 publications

References 17 publications

Low-Cost Technologies Used in Corrosion Monitoring

Low-Cost Technologies Used in Corrosion Monitoring

High-dimensional data analytics in structural health monitoring and non-destructive evaluation: a review paper

Compressive sampling system based on random demodulation for active and passive structural health monitoring

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