Application of machine learning with impedance based techniques for structural health monitoring of civil infrastructure
Increased attentiveness on the environmental and effects of aging, deterioration and extreme events on civil infrastructure has created the need for more advanced damage detection tools and structural health monitoring (SHM). Today, these tasks are performed by signal processing, visual inspecti...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Blue Eyes Intelligence Engineering and Sciences Publication
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/76243/1/76243_Application%20of%20Machine%20Learning%20with%20Impedance.pdf http://irep.iium.edu.my/76243/2/76243_Application%20of%20Machine%20Learning%20with%20Impedance_SCOPUS.pdf http://irep.iium.edu.my/76243/ https://www.ijitee.org/wp-content/uploads/papers/v8i6s4/F12370486S419.pdf |
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| Summary: | Increased attentiveness on the environmental and
effects of aging, deterioration and extreme events on civil
infrastructure has created the need for more advanced damage
detection tools and structural health monitoring (SHM). Today,
these tasks are performed by signal processing, visual inspection
techniques along with traditional well known impedance based
health monitoring EMI technique. New research areas have been
explored that improves damage detection at incipient stage and
when the damage is substantial. Addressing these issues at early
age prevents catastrophe situation for the safety of human lives.
To improve the existing damage detection newly developed
techniques in conjugation with EMI innovative new sensors,
signal processing and soft computing techniques are discussed in
details this paper. The advanced techniques (soft computing,
signal processing, visual based, embedded IOT) are employed as
a global method in prediction, to identify, locate, optimize, the
damage area and deterioration. The amount and severity,
multiple cracks on civil infrastructure like concrete and RC
structures (beams and bridges) using above techniques along
with EMI technique and use of PZT transducer.
In addition to survey advanced innovative signal processing,
machine learning techniques civil infrastructure connected to
IOT that can make infrastructure smart and increases its
efficiency that is aimed at socioeconomic, environmental and
sustainable development. |
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