Heavy machinery allows for the efficient, precise, and safe management of large-scale
operations that are beyond the abilities of humans. Heavy machinery breakdowns or failures …

Monitoring bolt looseness in joint structures is vital for their safety and integrity. The
relationship between bolt looseness-sensitive acoustic emission (AE) feature selection and …

Machine learning techniques have progressively emerged as important and reliable tools
that, when combined with machine condition monitoring, can diagnose faults with even …

This article analyzes the commonly used non-destructive testing methods of bolted joints.
The contact method has high recognition accuracy for preload detection but is greatly …

Deep learning models such as convolutional neural networks (CNNs) encounter challenges,
including instability and overfitting, while predicting bolt looseness in data-scarce scenarios …

Bolt loosening assessment is crucial to identify early warnings of structural degradation and
prevent catastrophic events. This paper proposes an automatic bolt loosening assessment …

Looseness detection of complex multi-bolted flange joints has long been an important
problem to be focused on, especially for the scene of unknown multi-bolt loosening at the …

Ambient temperature effect on electro-mechanical admittance (EMA) signals always
imposes a threat to the accurate identification of concrete damages when using surface …

Existing machine learning (ML) models have limitations in classifying bolt looseness in data-
deficient scenarios. In this article, a novel audio-feature augmentation was established to …

This article detects the bolt looseness of a flanged joint based on the energy conversion
between multiple wave modes. The mode conversion introduced by the flange carries …