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-ball joints are widely used in space structures, and their looseness may lead to major
safety accidents. The current bolt monitoring methods based on deep learning usually have …

Variational mode decomposition (VMD) gained popularity due to its excellent performance
in rolling bearing fault diagnosis. To obtain accurate diagnosis results depending on proper …

The fault diagnosis method of bearing-rotor system based on infrared thermography can
reflect the global fault information of the equipment, which is an advanced non-contact …

Structural health monitoring relies heavily on measurements. Entropy theory is emerging as
a critical quantitative analysis technique for interpreting measured data for both health …

Pipelines are susceptible to oil and gas leaks during long-distance transportation due to
factors such as damage from external forces and aging. However, existing pipeline leakage …

Accurate inspection of the steel fiber content is necessary to assure the designed
performance and required quality of steel fiber reinforced concrete (SFRC). This paper …

Aiming at the problems of noise interference and too many network parameters for power
quality disturbances'(PQDs') classification based on deep learning, the lightweight …

Impact modulation is a damage-sensitive, non-destructive testing method that combines
percussion with a high-frequency probing excitation signal to trigger modulation, which …