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The rapid development of metal additive manufacturing (AM) technology has led to its widespread application across various industries, with quality control of AM components being a current focal point of research. To enable on-line defect detection during the metal AM process using laser ultrasonic technology, this paper proposes a defect detection method based on sparse scanning. By employing sparse scanning to collect data, the method significantly improves detection efficiency while accurately characterizing the position and morphology of defects. This study thoroughly investigates the interaction mechanisms between ultrasonic waves and defects. Ellipses are drawn based on the propagation paths of ultrasonic waves and scanning parameters, and the defect edges are characterized by the intersection points of adjacent ellipses and their corresponding tangent points. Five sets of experiments were designed to examine four typical types of defects, and multiple ultrasonic signals were collected using sparse scanning. For defects larger than 1 mm, the experimental results demonstrate that the proposed method can effectively output the position and edge morphology of the defects. Compared to the Synthetic Aperture Focusing Technique (SAFT) method, this method requires only 15.5% of the scanning data, achieves 31.92% of SAFT’s computational efficiency, and has a Mean Absolute Error (MAE) of 27%. For internal hole defect with a diameter of 0.4 mm, consistent results with the SAFT method were obtained using 32% of the data. These experiments validate that the proposed defect detection method based on sparse scanning is an efficient method suitable for on-line defect detection in additive manufacturing.

Sliding and spinning behaviors significantly affect the performance of rolling bearings, especially for dry-lubricated bearings, micro and macro sliding may lead to increased wear of the solid lubricating film. A unified rolling contact tribology analytical model is proposed for dry-lubricated angular contact ball bearings (ACBBs) considering the extreme conditions including high combined loads and rolling contact effects. A comprehensive solution framework is proposed to ensure the robustness of the model under different loading conditions. Equilibrium equations are solved to study the effects of friction coefficients, rotating speeds, and combined loads on the skidding and spinning characteristics of the ACBB. The results show that the rolling contact effects and combined loads significantly affect the skidding and spinning performance of the ACBB. Further analysis reveals that the skidding mechanism is related to the interaction between ball kinematical motion and traction forces. The developed analytical model is proved to more accurately predict the bearing kinematical and tribological behavior as it discards the raceway control hypothesis and considers the macro/micro-slipping, creepage, and self-spinning motions of the ball, which is validated using both the existing pure axial loading dry-lubricated ACBB model and the classical Jones—Harris model. The study would provide some guidance for the structure and lubrication design of dry-lubricated ACBBs.

Unbalance is an inevitable issue in rotating machineries due to the manufacturing tolerances, the assembly errors, the damage in rotating components, etc. The effects of unbalance on the nonlinear dynamics of cracked rotors are investigated in this paper. In order to overcome the assumption of weight dominance, 3D finite element models are employed to discretize the rotor and several contact pairs are defined on the cracked surfaces to simulate the intermittent breathing behavior of crack. Then, the complex free interface component mode synthesis method (CMS) is employed to reduce the model’s order and to increase the computational efficiency. Finally, the obtained models are used to study the effects of concentrated and distributed unbalances on the nonlinear dynamic response of cracked rotors. The results show that the unbalance can significantly affect the breathing mechanism of crack and consequently dramatically change the rotor’s dynamic behaviors. Moreover, the different levels and orientations of unbalance lead to obviously different results. Besides, the responses of rotors with two asymmetric distributed unbalance are similar to those of rotors with a single concentrated unbalance though the rotors are overall balanced.

Additive Manufacturing (AM) technology has gained widespread application across various industries due to its capability to directly produce products from computer-aided design models. Among AM techniques, the Electron Beam Selective Melting (EBSM) process has attracted significant attention, particularly in aerospace and automotive industries, owing to its high precision, speed, and excellent material properties. However, various defects, especially internal defects that inevitably arise during the manufacturing process, significantly limit the performance of EBSM parts. In this study, X-ray computed tomography (CT) was utilized to scan EBSM parts, and cross-sectional images were employed to train several state-of-the-art modern object detection models for evaluating their effectiveness in detecting internal defects. Sparse R-CNN demonstrated the best overall performance, while the YOLO series excelled in specific metrics. To further capitalize on the strengths of different detection models, a model ensemble approach, Selective Box Fusion (SBF) is proposed. This approach employs voting and weighted fusion of detection boxes to mitigate errors inherent in individual models. Experimental results show that the SBF ensemble method effectively integrates the advantages of multiple detection models, leading to improvements across various evaluation metrics compared to individual models and other ensemble methods.

Solid-lubricated rolling bearings are widely used in the aerospace field and are key components to support spacecraft rotors. During the start-up of the engine, the sharp acceleration may cause bearing skidding, resulting in damage of the solid lubricating film and a reduction in the remaining useful life of the bearing. However, the existing research on the tribo-dynamic responses of solid-lubricated ball bearings mostly relies on semi-empirical tribological models, which are limited in their ability to reveal the micro–macro sliding mechanisms of the ball–raceway contact interface. In this paper, a novel tribo-dynamic model for solid-lubricated angular contact ball bearings is developed by applying Kalker’s rolling contact theory to the Gupta dynamic model. The interpolation method is adopted to calculate contact parameters to improve the model’s efficiency. Using the proposed model, the dynamic response of the bearing in the acceleration process is studied, and the mechanism and influence characteristics of skidding, over-skidding, and creepage of the rolling element are analyzed. The results show that the main reason for skidding is that the traction force is not enough to overcome the resistance, and the gyroscopic effect is the main cause of over-skidding, which follows the principle of conservation of the angular momentum of the ball.

Surface angled cracks on critical components in high-speed machinery can lead to fractures under stress and pressure, posing a significant threat to the operational safety of equipment. To detect surface angled cracks on critical components, this paper proposes a “Quantitative Detection Method for Surface Angled Cracks Based on Full-field Scanning Data”. By analyzing different ultrasonic signals in the full-field scanning data from laser ultrasonics, the width, angle, and length of surface angled cracks can be determined. This study investigates the propagation behavior of ultrasonic waves and their interaction with surface angled cracks through theoretical calculations. The crack width is solved by analyzing the distribution of Rayleigh waves in the full-field scanning data. This paper also discusses the differences in ultrasonic wave propagation between near-field and far-field detection and identifies the critical point between these regions. Different computational methods are employed to calculate the inclination angle and the crack endpoint at various scan positions. Four sets of experiments were conducted to validate the proposed method, with results showing that the errors in determining the width, angle, and length of the surface angled cracks were all within 5%. This confirms the feasibility of the method for detecting surface angled cracks. The quantitative detection of surface angled cracks on critical components using this method allows for a comprehensive assessment of the component’s condition, aiding in the prediction of service life and the mitigation of operational risks. This method shows promising application potential in areas such as aircraft engine blade inspection and gear inspection.

The blind deconvolution methods (BDMs) is one of the most common methods for fault diagnosis of rolling bearings, and it is essential to maintain the safe and reliable operation of mechanical equipment. However, noise interference and the need for prior periods limit the scope of application of the BDMs. In this paper, a new minimum nonprobabilistic entropy deconvolution (MNPED) method is proposed. According to the correlation between fault impact and non-Gaussianity, the Gaussian membership function in fuzzy set theory is used to map the sample points to the membership degree of Gaussian distribution, and then the nonprobabilistic entropy (NPE) is formed to measure the impact characteristics of the signal. Then NPE is incorporated into the iterative process of solving the filter coefficient. Finally, the target signal and the optimal filter coefficient are selected based on the criterion of minimum NPE. MNPED is capable of adaptively extracting the periodic pulse of a signal without requiring prior knowledge of the period, even in the presence of strong noise interference. The effectiveness and robustness of the proposed approach are validated through simulation and experimental data.

To identify the major vibration and radiation noise, a source contribution quantitative estimation method is proposed based on underdetermined blind source separation. First, the single source points (SSPs) are identified by directly searching the identical normalized time-frequency vectors of mixed signals, which can improve the efficiency and accuracy in identifying SSPs. Then, the mixing matrix is obtained by hierarchical clustering, and source signals can also be recovered by the least square method. Second, the optimal combination coefficients between source signals and mixed signals can be calculated based on minimum redundant error energy. Therefore, mixed signals can be optimally linearly combined by source signals via the coefficients. Third, the energy elimination method is used to quantitatively estimate source contributions. Finally, the effectiveness of the proposed method is verified via numerical case studies and experiments with a cylindrical structure, and the results show that source signals can be effectively recovered, and source contributions can be quantitatively estimated by the proposed method.

The traction behavior in cryogenic solid-lubricated ball bearings (CSLBBs) used in liquid rocket engines (LREs) affects not only the dynamic response of the bearing but also the lubricity and wear characteristics of the solid lubrication coating. The traction coefficient between the ball and raceway depends on factors such as contact material, relative sliding velocity, and contact pressure. However, existing traction curve models for CSLBBs typically consider only one or two of these factors, limiting the accuracy and applicability of theoretical predictions. In this study, a novel traction model for CSLBBs is proposed, which incorporates the combined effects of contact material, relative sliding velocity, and contact pressure. Based on this model, a tribo-dynamic framework is developed to investigate the tribological and dynamic behavior of CSLBBs. The model is validated through both theoretical analysis and experimental data. Results show that the inclusion of solid lubricant effects significantly alters the relative sliding and frictional forces between the rolling elements and the raceway. These changes in turn influence the impact dynamics between the rolling elements and the cage, leading to notable variations in the bearing’s vibrational response. The findings may offer valuable insights for the wear resistance and vibration reduction design of CSLBBs.

Rolling contact fatigue is the main failure mechanism of tapered roller bearings. This study investigated the fatigue mechanism of rollers in a tapered roller bearing that failed in a run-to-failure test. Roller microstructure and crack morphology were investigated through scanning electron microscopy. A microhardness test was performed to investigate the strain hardening of the roller material induced by rolling contact fatigue. Results showed that microcavities and holes are important influential factors of crack initiation and propagation. Crack propagation angle affects crack morphology and propagation mode. Material strain hardening accelerates crack growth. Furthermore, roller misalignment causes uneven hardenability and severe damage to roller ends.