structural health monitoring in industry;
applications;
economics of structural health monitoring;
system design;
performance validation;
data processing;
global monitoring;
local monitoring;
machine condition monitoring;
structural identification;
GUIDED-WAVE;
COMPLEX STRUCTURES;
ACOUSTIC-EMISSION;
DAMAGE;
IDENTIFICATION;
REFLECTION;
SENSORS;
BRIDGE;
PIPES;
ARRAY;
D O I:
10.1177/1475921717750047
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
There has been a large volume of research on structural health monitoring since the 1970s but this research effort has yielded relatively few routine industrial applications. Structural health monitoring can include applications on very different structures with very different requirements; this article splits the subject into four broad categories: rotating machine condition monitoring, global monitoring of large structures (structural identification), large area monitoring where the area covered is part of a larger structure, and local monitoring. The capabilities and potential applications of techniques in each category are discussed. Condition monitoring of rotating machine components is very different to the other categories since it is not strictly concerned with structural health. However, it is often linked with structural health monitoring and is a relatively mature field with many routine applications, so useful lessons can be read across to mainstream structural health monitoring where there are many fewer industrial applications. Reasons for the slow transfer from research to practical application of structural health monitoring include lack of attention to the business case for monitoring, insufficient attention to how the large data flows will be handled and the lack of performance validation on real structures in industrial environments. These issues are discussed and ways forward proposed; it is concluded that given better focused research and development considering the key factors identified here, structural health monitoring has the potential to follow the path of rotating machine condition monitoring and become a widely deployed technology.
机构:
Childrens Hosp Philadelphia, Philadelphia, PA 19104 USAChildrens Hosp Philadelphia, Philadelphia, PA 19104 USA
Deutsch, Ellen S.
Dong, Yue
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机构:
Mayo Clin, Med, Rochester, MN USAChildrens Hosp Philadelphia, Philadelphia, PA 19104 USA
Dong, Yue
Halamek, Louis P.
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机构:
Stanford Univ, Div Neonatal & Dev Med, Training & Assessment, Sch Med, Palo Alto, CA 94304 USA
Stanford Univ, Sch Med, Ctr Adv Pediat & Perinatal Educ, Palo Alto, CA 94304 USAChildrens Hosp Philadelphia, Philadelphia, PA 19104 USA
机构:
Duke Univ, Sch Med, Educ Technol, Durham, NC USA
Duke Univ, Sch Med, Human Simulat & Patient Safety Ctr, Durham, NC USAChildrens Hosp Philadelphia, Philadelphia, PA 19104 USA
Taekman, Jeffrey M.
Rice, John
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机构:
Soc Simulat Healthcare, Norfolk, VA USAChildrens Hosp Philadelphia, Philadelphia, PA 19104 USA