The percussion-based method has become a hot spot for bolt looseness monitoring due to its advantages of non-contact sensing, portability, and low cost. However, the features of bolt looseness in percussion methods lack phase information. In this paper, a percussion method based on the all-pole group delay function (APGDF) in the phase domain is proposed for the first time, and the bolt looseness is determined by a convolutional neural network (CNN). Under the four signal-to-noise ratio (SNR) levels (0, 2, 4 and 6dB), the accuracy of the proposed method is 90.25%, 92.75%, 93.5% and 94%. The experiment proves the percussion audio signal of the structural point away from the bolt can reflect the looseness of the bolt. The phase feature can represent the information of bolt looseness and has fast training speed and high recognition accuracy, which is suitable for detecting bolt looseness torque.
A method for calculating the static carrying curve of a double-row different-diameter ball slewing bearing was proposed. The relationship between the internal maximum rolling element load of each row and the combined external axial load and tilting moment load of the slewing bearing was established using the deformation compatibility and force equilibrium conditions. The rolling element load distribution range parameters of the main and auxiliary raceways of the double-row different-diameter ball slewing bearing were used as input invariables, and the corresponding external load combinations of the axial and tilting moment loads of the slewing bearing were obtained. These external load combinations were plotted in the coordinate system to obtain the static carrying curve of the slewing bearing. The obtained static carrying curve was compared with that calculated using the finite element method for verification. Finally, the influences of detailed design parameters such as the raceway groove radius coefficient, raceway contact angle, and rolling element diameter on the carrying capacity of the double-row different-diameter ball slewing bearing were analyzed based on the carrying curves. As the groove radius coefficient increases from 0.515 to 0.530, or the contact angle increases from 50° to 65°, the carrying capacity of the slewing bearing decreases. As the rolling element diameter increases from 0.90 times the initial diameter to 1.05 times the initial diameter, the carrying capacity of the slewing bearing increases.
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