Damage integrity assessment for beams using structural health monitoring technique

2021 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Vanapalli Poornima ◽  
Venkat Lute
Author(s):  
Kyle Bassett ◽  
Rupp Carriveau ◽  
David S.-K. Ting

Structural health monitoring is a technique devised to monitor the structural conditions of a system in an attempt to take corrective measures before the system fails. A passive structural health monitoring technique is presented, which serves to leverage historic time series data in order to both detect and localize damage on a wind turbine blade aerodynamic model. First, vibration signals from the healthy system are recorded for various input conditions. The data is normalized and auto-regressive (AR) coefficients are determined in order to uniquely identify the normal behavior of the system for each input condition. This data is then stored in a healthy state database. When the structural condition of the system is unknown the vibration signals are acquired, normalized and identified by their AR coefficients. Damage is detected through the residual error which is calculated as the difference between the AR coefficients of the unknown and healthy structural conditions. This technique is tailored for wind turbines and the application of this approach is demonstrated in a wind tunnel using a small turbine blade held with four springs to create a dual degree-of-freedom system. The vibration signals from this system are characterized by free-stream speed. Damage is replicated through mass addition on each of the blades ends and is located by an increase in residual error from the accelerometer mounted closest to the damaged area. The outlined procedure and demonstration illustrate a single stage structural health monitoring technique that, when applied on a large scale, can avoid catastrophic turbine disasters and work to effectively reduce the maintenance costs and downtime of wind farm operations.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Xuefeng Zhao ◽  
Kwang Ri ◽  
Ruicong Han ◽  
Yan Yu ◽  
Mingchu Li ◽  
...  

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.


2021 ◽  
Author(s):  
◽  
Saurabh Singh

<p>Wireless sensor networks (WSNs) are designed for sensing phenomena and acquiring data. In structural health monitoring (SHM) of engineering structures, increasingly large number of sensor nodes are deployed to acquire data at the spatial density, needed for structural integrity assessment.  During catastrophic events like earthquake there is a surge in simultaneous production and transmission of data to a central server at remote location. The increased contention for the wireless channel increases the probability of packet collisions resulting in packet drops, multiple transmission attempts and consequent delays. It is also not uncommon to find certain nodes (e.g. closer to sink) having better success rate in transmission of data and thereby leading to biased data delivery. Many solutions to the problem exist and clustering is the most commonly used method among then, wherein sensor nodes are grouped together. While the existing clustering algorithms do solve the network contention problems, the problem of cluster bias induced due to the proximity to sink node still remains to be addressed. Moreover all the existing solutions are very much node centric.  This thesis presents a new perspective on cluster based WSNs designed to tackle Medium Access Control (MAC) layer congestion associated with burst packet generation in an unbiased manner, thereby making it more efficient for applications like SHM. In addition to solving the network bias problem, the proposed design also ensures faster transmission times, increased throughput and energy efficiency.</p>


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