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Damage identification of a belt conveyor support structure based on cross‐sectional vibration characteristics
Author(s) -
Rana Shohel,
Nagayama Tomonori,
Hisazumi Kazumasa,
Tominaga Tomonori
Publication year - 2019
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2349
Subject(s) - unavailability , identification (biology) , damages , vibration , reliability (semiconductor) , belt conveyor , structural engineering , computer science , reliability engineering , engineering , mechanical engineering , botany , physics , biology , power (physics) , quantum mechanics , political science , law
Summary Belt conveyors, widely used in various industries worldwide, are often exposed to corrosive environment. Decades after construction, many of the support structures of belt conveyors have severe degradation, which may cause structural failure and functional stop of associated industries. To ensure the safety and reliability, effective and efficient damage identification of belt conveyor support structures is essential. However, application of existing global vibration‐based damage identification techniques to these structures is difficult due to unavailability of baseline condition, the possible presence of multiple corroded members in a single structure, and the effect of nonstructural components that are occasionally updated. In this paper, a damage identification method of the main members of a belt conveyor support structure is proposed and validated through numerical and experimental studies. Cross‐sectional modes (CSMs), shown to exist on the main member numerically and experimentally, are utilized. Eigenvalue analysis of an FE model of the support structure reveals the characteristics of CSMs and localized CSMs (LCSMs). A damage identification method based on these modes is developed; the existence and location of the damage is evaluated from current state of the structure without the need for before–after comparison. By identifying the distinct LCSMs, multiple damages are also independently identified.