scholarly journals Progress of the COST Action TU1402 on the Quantification of the Value of Structural Health Monitoring

Author(s):  
SEBASTIAN THÖNS ◽  
MARIA PINA LIMONGELLI ◽  
ANA MANDIC IVANKOVIC ◽  
DIMITRI VAL ◽  
MARIOS CHRYSSANTHOPOULOS ◽  
...  
2006 ◽  
Vol 321-323 ◽  
pp. 140-145 ◽  
Author(s):  
In Pil Kang ◽  
Jong Won Lee ◽  
Gyeong Rak Choi ◽  
Joo Yung Jung ◽  
Sung Ho Hwang ◽  
...  

This paper introduces a new sensor design based on a carbon nanotube structural neuron for structural health monitoring applications. The carbon nanotube neuron is a thin and narrow polymer film sensor that is bonded or deposited onto a structure. The electrochemical impedance (resistance and capacitance) of the neuron changes due to deterioration of the structure where the neuron is located. A network of the long carbon nanotube neurons can form a structural neural system to provide large area coverage and an assurance of the operational health of a structure without the need for actuators and complex wave propagation analyses that are used with other SHM methods. The neural system can also reduce the cost of health monitoring by using biomimetic signal processing to minimize the number of channels of data acquisition needed to detect damage. The carbon nanotube neuron is lightweight and easily applied to the structural surface, and there is no stress concentration, no piezoelectrics, no amplifier, and no storage of high frequency waveforms. The carbon nanotube neuron is expected to find applications in detecting damage and corrosion in large complex structures including composite and metallic aircraft and rotorcraft, bridges, and almost any type of structure with almost no penalty to the structure.


Aerospace ◽  
2018 ◽  
Vol 5 (3) ◽  
pp. 87 ◽  
Author(s):  
Ting Dong ◽  
Nam Kim

Although structural health monitoring (SHM) technologies using sensors have dramatically been developed recently, their capability should be evaluated from the perspective of the maintenance industry. As a first step toward utilizing sensors, the objective of the paper is to investigate the possibility of using sensors for inspecting the entire fuselage during C-check. First, we reviewed various sensors for their detection range, detectable damage size, and installed weight, which revealed that the piezoelectric wafer active sensor (PWAS) is the most promising sensor for aircraft SHM. Second, we performed a case study of inspecting the fuselage of Boeing-737NG using PWAS. To maintain the same detecting capability of manual inspection in C-check, we estimated the total number of sensors required. It turned out that utilizing sensors can reduce the maintenance downtime and thus, maintenance cost. However, even with a very conservative estimate, the lifetime cost was significantly increased due to the weight of sensor systems. The cost due to the weight increase was an order of magnitude higher than the cost saved by using SHM. We found that a large number of sensors were required to detect damage at unknown locations, which was the main cause of the weight increase. We concluded that to make SHM cost-effective, it would be necessary either to improve the current sensor technologies so that a less number of sensors are used or to modify the aircraft design concept for SHM.


2019 ◽  
Vol 18 (3) ◽  
pp. 963-988 ◽  
Author(s):  
Wieslaw Ostachowicz ◽  
Rohan Soman ◽  
Pawel Malinowski

The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor placement offers an opportunity to reduce the cost of the SHM system without compromising on the quality of the monitoring approach. Several studies in the area of optimization of sensor placement for SHM applications have been undertaken but the approach has been rather application specific. This article is an attempt to present an unbiased state of the art of the work carried out in the area. The article is targeted towards researchers working in the field of structural health monitoring and optimization of sensor placement as well as practising engineers. This article reviews the work in the area of optimization of sensor placement. It first presents the definition of the optimization problem and then describes each step of the optimization. The current state of the art is then classified based on the techniques for which the optimization of sensor placement has been optimized. The article covers vibration-based monitoring, strain monitoring and elastic wave-based monitoring, as in the eyes of the authors these three techniques are most commonly used and accepted in the SHM community. The article later discusses the different optimization algorithms that have been applied in the literature. The article highlights the different pitfalls of the optimization algorithms and the countermeasures different researchers have proposed to overcome the known shortcomings. In the later section, the multi-objective optimization or the problem definition, keeping in mind the structural as well as executional demands, is discussed. A section has also been developed to showcase the use of optimization of sensor placement techniques’ data fusion–based systems.


Sign in / Sign up

Export Citation Format

Share Document