scholarly journals Autocorrelation Analysis in Time and Frequency Domains for Passive Structural Diagnostics

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Satoru Goto ◽  
Yoshinori Takahashi ◽  
Mikio Tohyama
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Frequency Estimation ◽  
Scale Model ◽  
Monitoring Methods ◽  
Autocorrelation Functions ◽  
Modal Frequency ◽  
Structural Health ◽  
Frequency Domains ◽  
Time And Frequency Domains

In this paper, modal frequency estimation by using autocorrelation functions in both the time and frequency domains for structural diagnostics is discussed. With popular structural health monitoring methods for periodic inspections such as with the “hammering test,” hearing is very useful for distinguishing differences between structural conditions. Hearing detects pitch and tone, and it is known that the auditory process is related to wave periodicity calculated from autocorrelation functions. Consequently, on the basis of the hammering test, modal frequencies can be estimated by autocorrelation, the same as hearing. In this paper, modal frequencies were estimated by using autocorrelation for constant structural health monitoring under a nonstationary noise condition. First, fundamental modal frequencies were estimated by using the autocorrelation of the time domain which was inspired by pitch detection of hearing. Second, higher modal frequency compositions were also analyzed by using autocorrelation in the frequency domain as with tones discrimination. From the results by conducting scale-model experiments under unknown nonstationary noise conditions, periods of fundamental modal frequency were derived by using periods histogram of autocorrelation functions. In addition, higher modal frequency estimation under nonstationary noises was also discussed.

scholarly journals A New Damage Index for Structural Health Monitoring: A Comparison of Time and Frequency Domains

2021 ◽  
Vol 179 ◽  
pp. 930-935
Author(s):  
Fergyanto E. Gunawan ◽  
Tran Huu Nhan ◽  
Muhammad Asrol ◽  
Yasuhiro Kanto ◽  
Insannul Kamil ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Index ◽  
Structural Health ◽  
Frequency Domains ◽  
Time And Frequency Domains

Review of piezoelectric impedance based structural health monitoring: Physics-based and data-driven methods

2021 ◽  
pp. 136943322110384
Author(s):  
Xingyu Fan ◽  
Jun Li ◽  
Hong Hao
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Low Frequency ◽  
Data Driven ◽  
Mode Shapes ◽  
Monitoring Methods ◽  
Destructive Testing ◽  
Electromechanical Impedance ◽  
Structural Health

Vibration based structural health monitoring methods are usually dependent on the first several orders of modal information, such as natural frequencies, mode shapes and the related derived features. These information are usually in a low frequency range. These global vibration characteristics may not be sufficiently sensitive to minor structural damage. The alternative non-destructive testing method using piezoelectric transducers, called as electromechanical impedance (EMI) technique, has been developed for more than two decades. Numerous studies on the EMI based structural health monitoring have been carried out based on representing impedance signatures in frequency domain by statistical indicators, which can be used for damage detection. On the other hand, damage quantification and localization remain a great challenge for EMI based methods. Physics-based EMI methods have been developed for quantifying the structural damage, by using the impedance responses and an accurate numerical model. This article provides a comprehensive review of the exciting researches and sorts out these approaches into two categories: data-driven based and physics-based EMI techniques. The merits and limitations of these methods are discussed. In addition, practical issues and research gaps for EMI based structural health monitoring methods are summarized.

scholarly journals Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 826 ◽  
Author(s):  
Christoph Kralovec ◽  
Martin Schagerl
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Composite Structures ◽  
Joint Damage ◽  
Ultrasonic Waves ◽  
Physical Models ◽  
Monitoring Methods ◽  
Structural Health ◽  
Different Levels

Structural health monitoring (SHM) is the continuous on-board monitoring of a structure’s condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the state-of-the-art damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strain-based or conductivity-based methods and with additional sensors for environmental entities might yield a robust multi-sensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multi-sensor SHM approach is presented.

scholarly journals Experimental Research on Quick Structural Health Monitoring Technique for Bridges Using Smartphone

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Xuefeng Zhao ◽  
Kwang Ri ◽  
Ruicong Han ◽  
Yan Yu ◽  
Mingchu Li ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Extreme Event ◽  
Force Measurement ◽  
Low Cost ◽  
Practical Significance ◽  
Scale Model ◽  
Structural Health ◽  
Bridge Health Monitoring ◽  
Monitoring Technique

In the recent years, with the development and popularization of smartphone, the utilization of smartphone in the Structural Health Monitoring (SHM) has attracted increasing attention owing to its unique feature. Since bridges are of great importance to society and economy, bridge health monitoring has very practical significance during its service life. Furthermore, rapid damage assessment of bridge after an extreme event such as earthquake is very important in the recovery work. Smartphone-based bridge health monitoring and postevent damage evaluation have advantages over the conventional monitoring techniques, such as low cost, ease of installation, and convenience. Therefore, this study investigates the implementation feasibility of the quick bridge health monitoring technique using smartphone. A novel vision-based cable force measurement method using smartphone camera is proposed, and, then, its feasibility and practicality is initially validated through cable model test. An experiment regarding multiple parameters monitoring of one bridge scale model is carried out. Parameters, such as acceleration, displacement, and angle, are monitored using smartphone. The experiment results show that there is a good agreement between the reference sensor and smartphone measurements in both time and frequency domains.

Structural Health Monitoring on Real Scale Model of a Masonry Triumphal Arch

2007 ◽  
pp. 279-284
Author(s):  
Giovanni Damonte ◽  
Stefano Podestà ◽  
Giuseppe Riotto ◽  
Sergio Lagomarsino ◽  
Georges Magonette ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Scale Model ◽  
Structural Health ◽  
Real Scale
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