scholarly journals An Experimental Test Bed for Developing High-Rate Structural Health Monitoring Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Bryan Joyce ◽  
Jacob Dodson ◽  
Simon Laflamme ◽  
Jonathan Hong
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Experimental Test ◽  
Sliding Mode ◽  
High Rate ◽  
Recursive Least Squares ◽  
Test Bed ◽  
Monitoring Methods ◽  
Structural Health ◽  
External Forces

Complex, high-rate dynamic structures, such as hypersonic air vehicles, space structures, and weapon systems, require structural health monitoring (SHM) methods that can detect and characterize damage or a change in the system’s configuration on the order of microseconds. While high-rate SHM methods are an area of current research, there are no benchmark experiments for validating these algorithms. This paper outlines the design of an experimental test bed with user-selectable parameters that can change rapidly during the system’s response to external forces. The test bed consists of a cantilever beam with electronically detachable added masses and roller constrains that move along the beam. Both controllable system changes can simulate system damage. Experimental results from the test bed are shown in both fixed and changing configurations. A sliding mode observer with a recursive least squares parameter estimator is demonstrated that can track the system’s states and changes in its first natural frequency.

Practical Considerations for Sliding Mode Observers for High-Rate Structural Health Monitoring

2018 ◽  
Author(s):  
Bryan Joyce ◽  
Jacob Dodson ◽  
Jonathan Hong ◽  
Simon Laflamme
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sliding Mode ◽  
State Parameter ◽  
High Rate ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Structural Health ◽  
Disturbance Estimation ◽  
Sliding Mode Observers

Structural health monitoring (SHM) of high-rate, mechanical systems in dynamically harsh environments presents many challenges over traditional SHM applications. Damage in these systems must be detected and quantified in tens to hundreds of microseconds in order to have sufficient time to react and mitigate damage. The computation speeds and robustness of sliding mode observers (SMOs) for state, parameter, and disturbance estimation for linear and nonlinear systems make them an attractive approach for real-time SHM of high-rate systems. This paper investigates a novel SMO combined with a recursive least squares parameter estimator to detect and track changing system parameters. The observer is simulated on a one degree-of-freedom system with time-varying model parameters to mimic damage. This paper focuses on practical considerations for SMOs for high-rate systems, such as the effects of measurement noise and sampling rates on the estimator’s accuracy and convergence speeds.

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.

Butterworth Filter Application for Structural Health Monitoring

2020 ◽  
pp. 733-748
Author(s):  
Ahmed Abdelgawad ◽  
Md Anam Mahmud ◽  
Kumar Yelamarthi
Keyword(s):  
Mathematical Model ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Guided Wave ◽  
Test Bed ◽  
Explicit Finite Element ◽  
Butterworth Filter ◽  
Structural Health ◽  
Aluminum Sheets ◽  
Set Up

Most of the existing Structural Health Monitoring (SHM) systems are vulnerable to environmental and operational damages. The majority of these systems cannot detect the size and location of the damage. Guided wave techniques are widely used to detect damage in structures due to its sensitivity to different changes in the structure. Finding a mathematical model for such system will help to implement a reliable and efficient low-cost SHM system. In this paper, a mathematical model is proposed to detect the size and location of damages in physical structures using the piezoelectric sensor. The proposed model combines both pitch-catch and pulse-echo techniques and has been verified throughout simulations using ABAQUS/ Explicit finite element software. For empirical verification, data was collected from an experimental set-up using an Aluminum sheets. Since the experimental data contains a lot of noises, a Butterworth filter was used to clean up the signal. The proposed mathematical model along with the Butterworth filter have been validated throughout real test bed.

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.

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