Structural Fault Diagnosis Based on Static and Dynamic Response Parameters

Abstract

Structural fault diagnosis is an important subject for ensuring the normal use of structures. More test data will help to improve the accuracy and reliability of structural fault diagnosis. Therefore, a structural fault detection algorithm based on static–dynamic mixed sensitivity analysis is proposed. The vibration parameters used were the vibration modes of some of the nodes in the structure measured by the vibration test system. The static response parameter used was the vertical displacement of the structure under the gravity load measured by the static test system. In particular, the gravity load and the structure were connected rigidly to form a new added-mass system. The vibration mode of the additional-mass system was measured again to obtain more equations for fault evaluation. Based on the static and dynamic measurement data, the failure coefficients of all components in the structure were calculated through the mixed sensitivity of the static displacement and vibration-mode shape. According to the calculated value of the failure coefficient, the failure state of all components in the structure could be finally evaluated. The main innovation of the proposed method was the use of the static load as a part of the new added-mass system to obtain more vibration parameters for the defect diagnosis. The implementation process and effect of this method were verified using a numerical truss structure and an experimental steel beam structure. Moreover, the defect diagnosis results of the proposed hybrid method were compared with those of a pure static algorithm and a pure dynamic algorithm to illustrate the advantages of the hybrid method. The research results showed that this method has the advantages of simple implementation and high diagnosis accuracy. Especially for symmetric structures, the proposed method can successfully avoid the possible missed diagnoses of the pure static algorithm and pure dynamic method. The algorithm provides a simple and feasible method for structural defect identification.