In-Situ Estimation of Bolt Clamping Force by Utilization of Its Effects on Flexural Vibration Propagation

Abstract

After a bolt assembling process, non-destructive identification of the clamping force is important to minimize unexpected failure of the assembled joint structures. For in-situ inspection for every parts, a detachable device which allows generation and detection of vibration propagation was proposed in this study. Tone burst excitation was transmitted through the bolted-joint structure. The vibration propagation characteristics depended on the clamping force. With an increase in the clamping force, the surface vibration propagation speed increased. The vibration magnitude decreased due to increasing constraint. A band-pass filter was used to remove noise component. The filtered vibration propagation responses were used in convolutional long short-term memory (CLSTM) training. The performance of CLSTM model was verified through comparison with actual clamping force. With minimal physical influence on the assembled parts, the clamping force of bolted-joint was measured using the surface vibration propagation characteristics.

Keywords

• Flexural vibration
• clamping force
• deep learning