2019Periodica Polytechnica Civil EngineeringOpen access

The Eigenfunction Method for Determining Displacement Time History in Structural Dynamic Analysis

Bo Li, Mahesh M. Pandey, Yang Lu, Kaoshan Dai

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Abstract

In condition monitoring of structures, acceleration time histories are usually recorded due to ease of instrumentation. In cases where the information about a displacement time history is required, the acceleration data needs to be integrated to obtain the velocity and then the velocity needs to be integrated to obtain the displacements. However, the numerical integration of the acceleration data usually introduces an unrealistic drift component to the velocity as well as displacement. This paper presents an eigenfunction method to derive velocity and displacement time histories from a given acceleration time history. The paper analyzes displacements in two case studies using the numerical integration as well as the proposed eigenfunction method. It is concluded that the eigenfunction method is a viable approach to derive the displacement information from the acceleration data.

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In condition monitoring of structures, acceleration time histories are usually recorded due to ease of instrumentation. In cases where the information about a displacement time history is required, the acceleration data needs to be integrated to obtain the velocity and then the velocity needs to be integrated to obtain the displacements. However, the numerical integration of the acceleration data usually introduces an unrealistic drift component to the velocity as well as displacement. This paper presents an eigenfunction method to derive velocity and displacement time histories from a given acceleration time history. The paper analyzes displacements in two case studies using the numerical integration as well as the proposed eigenfunction method. It is concluded that the eigenfunction method is a viable approach to derive the displacement information from the acceleration data.

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Available abstract

In condition monitoring of structures, acceleration time histories are usually recorded due to ease of instrumentation. In cases where the information about a displacement time history is required, the acceleration data needs to be integrated to obtain the velocity and then the velocity needs to be integrated to obtain the displacements. However, the numerical integration of the acceleration data usually introduces an unrealistic drift component to the velocity as well as displacement. This paper presents an eigenfunction method to derive velocity and displacement time histories from a given acceleration time history. The paper analyzes displacements in two case studies using the numerical integration as well as the proposed eigenfunction method. It is concluded that the eigenfunction method is a viable approach to derive the displacement information from the acceleration data.

Key concepts: Eigenfunction, Acceleration, Displacement (psychology), Instrumentation (computer programming), Numerical integration, Computer science, Mathematics, Mathematical analysis

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