To solve the problem of multi-fault blind source separation (BSS) in the case that the observed signals are under-determined, a novel approach for single channel blind source separation (SCBSS) based on the improved tensor-based singular spectrum analysis (TSSA) is proposed. As the most natural representation of high-dimensional data, tensor can preserve the intrinsic structure of the data to the maximum extent. Thus, TSSA method can be employed to extract the multi-fault features from the measured single-channel vibration signal. However, SCBSS based on TSSA still has some limitations, mainly including unsatisfactory convergence of TSSA in many cases and the number of source signals is hard to accurately estimate. Therefore, the improved TSSA algorithm based on canonical decomposition and parallel factors (CANDECOMP/PARAFAC) weighted optimization, namely CP-WOPT, is proposed in this paper. CP-WOPT algorithm is applied to process the factor matrix using a first-order optimization approach instead of the original least square method in TSSA, so as to improve the convergence of this algorithm. In order to accurately estimate the number of the source signals in BSS, EMD-SVD-BIC (empirical mode decomposition—singular value decomposition—Bayesian information criterion) method, instead of the SVD in the conventional TSSA, is introduced. To validate the proposed method, we applied it to the analysis of the numerical simulation signal and the multi-fault rolling bearing signals.

A bridge crane is often used in a complex environment and is often subject to the interference of all loads. Some uncertain factors often have an inevitable impact on its swing. So the force situation of the bridge crane during a working cycle is analyzed, and a three-dimensional dynamic mathematical model of the bridge crane is built. Through the simulation analysis of the model under the action of a driving force and wind load, the change law of the swing angle of the bridge crane is studied. Then, the fuzzy control theory is used to determine the control parameter in the anti-sway control process. The position, swing angle deviation, and deviation rate of the bridge crane are taken as the input, and the parameter correction is obtained after the fuzzification by using the center of gravity method. The anti-sway fuzzy control system of the bridge crane is designed and simulated. The research results show that the swing model of the crane is reasonable and the fuzzy PID anti-sway controller can not only improve the adaptability of the control system, but also overcome the large overshoot, quickly restrain the swing, and effectively realize the anti-sway function of the bridge crane.

The bridge crane is often used in a complex environment, often subject to interference of all loads. Some uncertainties factors often have an inevitable impact on its swing. So the force situation of the bridge crane during a working cycle is analyzed, and a three-dimensional dynamic mathematical model of the bridge crane is built. Through the simulation analysis of the model under the action of driving force and wind load, the change law of the swing angle of the bridge crane is studied. Then, the fuzzy control theory is used to determine the control parameter in the anti sway control process. The position, swing angle deviation and deviation rate of the bridge crane are taken as the input, and the parameter correction is obtained after the fuzzification by using the center of gravity method, the anti sway fuzzy control system of the bridge crane is designed and simulated. The research results show that the fuzzy PID anti sway controller can not only improve the adaptability of the control system, but also overcome the large overshoot, quickly restrain the swing, and effectively realize the anti sway function of the bridge crane.

The mechanical properties of large 2219 Al–Cu alloy rings need to be further improved with the diameter of the launch vehicle being more than 10 m. In this study, the effects of cold rolling (CR) and cold compression on microstructure evolution and the comprehensive mechanical properties of such rings were compared. The evolution of dislocation characteristics, grain structure, second phase, and the mechanical properties of the T8-aged samples were examined. Results show that compared with CR, because of deformation characteristics, cold compression deformation induces less increase in dislocation densities; however, the increase in dislocation densities on the core was higher than at other positions, resulting in a more uniform grain structure and elongation in the axial and radial direction. The cold compression deformation contributes to the uniform dissolution of the secondary phase, resulting in denser precipitates, and thus improved strength. Brittle fractures occur in fewer CR samples because of the longer moving distance of the Al matrix. In summary, both CR and cold compression can improve the mechanical properties. However, the cold-compressed sample exhibits more uniform microstructure and higher comprehensive mechanical properties (the radial elongation increased from 7.1 to 11.2%; the in-plane anisotropy decreased from 36.6 to 8.9%), without any brittle fractures, because of more uniform metal flow.

This study provides a review of recent advances in percussion-based bolt looseness monitoring. Beginning with the engineering mechanism of the tap-induced vibro-acoustic response in bolted joints, this study traces the technical evolution of the field across three progressive levels: basic signal preprocessing, discriminative feature extraction, and intelligent diagnosis modeling. Subsequently, a multi-dimensional comparative analysis of typical monitoring methods is conducted, and targeted combined detection schemes tailored to different engineering scenarios are synthesized. Furthermore, the main constraints impeding engineering application are elucidated, and prospective research directions oriented to complex engineering conditions are outlined. This review is intended to provide a systematic technical roadmap and theoretical framework for the further development and engineering deployment of intelligent percussion-based bolt looseness monitoring technology.