Graph Based Signal-Behavior-Structure Mapping for State Maintenance of Equipment

doi:10.1007/s12204-017-1842-4

Abstract

Abstract: Equipment has dual nature: physical objects existing in nature, and artificial objects designed by human. The decision on the configuration and structural parameters of equipment is made by engineers based on technical-physical effects which control the behavioral parameters of the equipment. Sensors are mounted on the equipment to monitor the equipment state. Current methods for state monitoring and diagnosis mostly use mathematics and artificial intelligence technology to construct evaluation methods. This paper presents an integrated design and state maintenance method, in which graph and dual graph are used for recording design data and sensor arrangement and for mapping method from signals to substructures and connection pairs. An example of state maintenance of hydro power generating equipment is illustrated.

Key words: state maintenance| technical-physical effect| signal-behavior-structure mapping| graph

摘要： Equipment has dual nature: physical objects existing in nature, and artificial objects designed by human. The decision on the configuration and structural parameters of equipment is made by engineers based on technical-physical effects which control the behavioral parameters of the equipment. Sensors are mounted on the equipment to monitor the equipment state. Current methods for state monitoring and diagnosis mostly use mathematics and artificial intelligence technology to construct evaluation methods. This paper presents an integrated design and state maintenance method, in which graph and dual graph are used for recording design data and sensor arrangement and for mapping method from signals to substructures and connection pairs. An example of state maintenance of hydro power generating equipment is illustrated.

关键词: state maintenance| technical-physical effect| signal-behavior-structure mapping| graph

CLC Number:

X 913.4

ZHANG Wei1 (张伟), HOU Yuemin1,2* (侯悦民). Graph Based Signal-Behavior-Structure Mapping for State Maintenance of Equipment[J]. Journal of shanghai Jiaotong University (Science), 2017, 22(3): 349-354.

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