In the magnetic suspension bearing system, the protection bearing, as its key component, plays a role in supporting the safe operation of the drop rotor after the failure of the magnetic suspension bearing, to protect the whole system from damage. Based on a multi-body dynamics simulation, this paper studied the characteristics of the protection bearing, such as the speed fluctuation of the rotor and the bearing inner ring, and the contact force between the rotor and the protection bearing when the 5-DOF rotor fell on the protection bearing. By adjusting the friction coefficient, the initial speed of the rotor, and other parameters, the movement process of the rotor falling in the protection bearing was studied. By comparing the speed fluctuation and contact force of the rotor and the bearing inner race, the influencing factors and rules of the impact of the rotor falling on the protection bearing were analyzed and summarized.

The mechanical noise in the cabin of the ship is so large that the leakage of high-pressure fluid is not easily noticed. In view of this situation, a near-field acoustic holography for high-frequency weak sound source under low signal-to-noise ratio is proposed. The method uses the empirical mode decomposition method to add weights to the time-domain sampling signals of each array element, and then uses the plane equivalent source near-field acoustic holography combined with compressive sensing to find the holographic surface acoustic pressure distribution. The simulation and experiment show that this method has certain feasibility under low signal-to-noise ratio, and the results are better than the method based on Fourier transform and the traditional boundary element method. It is of positive significance to apply it to engineering practice.

Aiming at low efficiency of existing sliding bearing load balance calculation, a new method that based on neural network proportional-integral-derivative (PID) algorithm is proposed for the first time, in which a compound control algorithm combining neural network and PID algorithm is applied. In this new method, the load error is taken as the input of the system, and the eccentricity of the bearing is used as the input of the controller, and the output of the system is the oil film force of the bearing. Comparing with traditional method, calculation results show that: the number of iterations calculated by neural network PID algorithm is less than traditional one and has higher efficiency and stronger adaptability under different loads.

To accurately evaluate the load-bearing capacity of Cu-Ni alloy pipelines with double pitting corrosion defects, in this study, the influence of dual-defect morphological parameters on the ultimate load capacity was investigated through finite element simulation. On the basis of the ultimate load capacity model for single pit defects and simulation results, an assessment model was developed for Cu-Ni alloy pipelines containing double pitting defects, and its accuracy was validated through hydrostatic burst tests. The results indicate that the ultimate load capacity increases gradually with increasing interdefect center distance, asymptotically approaching the load-bearing capacity of a single-defect pipeline with an equivalent depth and diameter. The proposed model demonstrates excellent predictive performance, with a maximum error margin within 3%. During failure, Cu-Ni alloy pipelines with double pitting defects develop fine axial cracks at the defect sites while exhibiting significant overall bulging deformation. These findings can be effectively applied to predict the ultimate load capacity of Cu-Ni alloy pipelines with double pitting defects, providing substantial engineering value for an accurate assessment of the load-bearing capacity of pipelines with actual corrosion defects.

In order to improve the accuracy of the sparse regularization equivalent source acoustic holography algorithm, based on the analysis of the holographic algorithm theory, an optimized array arrangement is proposed. The sensing matrix constructed by the array parameters directly affects the accuracy of the acoustic imaging algorithm. By analyzing the influence of the sensing matrix on the imaging algorithm, the Restricted Isometry Constant (RIC) is chosen to evaluate the sensing matrix. Using genetic algorithm (GA), the RIC is taken as the fitness value, and the optimal pseudo-random array is selected and compared with the conventional array arrangement for acoustic imaging. Experiments show that the optimized pseudo-random array has better imaging effect under the same number of sensor measurements, and provides an optimization method for the design of acoustic array.

Selective laser melting (SLM) fabricated Ti6Al4V (TC4) has broad application potential, though its mechanical behavior is highly sensitive to processing conditions. However, the coupled response of Young’s modulus, Poisson’s ratio, and impact toughness to SLM process parameters remains insufficiently understood. In this study, laser ultrasonic testing (LUT), Charpy impact testing, fractographic observation, and defect statistical analysis were combined to systematically investigate the effects of laser power, scan speed, and hatch spacing on the mechanical behavior of SLM-fabricated TC4 samples. The results show that the three properties exhibit a similar non-monotonic dependence on process parameters, with an overall parabola-formed trend. The optimized process parameters for Young’s modulus, Poisson’s ratio, and impact toughness were identified as laser powers of 315, 348, and 336 W, scan speeds of 1230, 1277, and 1193 mm/s, and hatch spacings of 77, 82, and 87 μm respectively. The data fitting indicated that impact toughness is the most affected by changes in both laser power, scan speed, and hatch spacing. It was followed by Young’s modulus. And Poisson’s ratio received the least impact. The combined defect, fracture, and microstructural analysis further reveal that both excessively low and excessively high volumetric energy density increase porosity and defect size, as well as reduce the β phase volume fraction and area weighted mean value of the transformed-phase plates’ width, thereby degrading mechanical performance. These results establish a process–defect/microstructure–property relationship for SLM TC4 and provide useful guidance for the optimization of mechanical performance in additively manufactured titanium alloy components.