Bonding Integrity Study between Steel Pipeline andComposite Wraps Using Structural Health Monitoring Technique

Author(s):  
Mahadi Abd Murad ◽  
Simon Richard Frost ◽  
Feargal Peter Brennan
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.


2013 ◽  
Vol 281 ◽  
pp. 593-596
Author(s):  
Woong Ki Park ◽  
Hyun Uk Kim ◽  
Chang Gil Lee ◽  
Seung Hee Park

In recent years, numerous mega-sized and complex civil infrastructures are being constructed all over the world. Therefore, more precise construction and maintenance technologies are required for these complicated construction projects. So a variety of sensors-based structural health monitoring (SHM) techniques have been studied, but these techniques could not manage the sensors efficiently access the database obtained from the sensors. Recently, Quick response (QR) code and AR-based data access technologies have been developed. In this paper, an AR-based concrete curing strength monitoring technique for sensor management and efficient access of the measured data is introduced. It is confirmed that the AR-based concrete curing strength monitoring technique is useful for construction process. In addition, it is concluded that both efficient sensor location recognition and data visualization at anytime, anywhere, and any smart PC devices are promising.


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