The detection of metal surface defects is crucial in the field of industrial production. However, in practical applications, challenges such as ambiguous defect directions, large scale differences, and strong background interference are often encountered. This paper proposes an improved multi-scale fine-grained object detection framework based on YOLOv11, referred to as “DA-YOLO.” Firstly, the 3D attention module (3DAM) was used to enhance the model’s ability to model spatial direction features and improve the model’s ability to perceive fine-grained structures. Secondly, a feature enhancement module (AMFEM) employing multi-scale convolution and a spatial-channel attention mechanism was constructed, significantly boosting the model’s recognition accuracy for multi-scale targets and blurry boundary defects. Furthermore, an intersection and union ratio Aware Joint Loss function (IoU-Aware joint loss, IAJ-Loss) was proposed and designed, which further enhanced the quality perception ability and stability of the model in complex detection scenarios. The experimental results show that the DA-YOLO model improved mAP@0.5 by 5.42% and 4.05% respectively on the GC10-DET and NEU-DET datasets compared to the baseline YOLOv11 model, demonstrating superior defect detection performance.

Laser Powder Bed Fusion (LPBF) and Laser Directed Energy Deposition (LDED) additive manufacturing technologies, as core techniques in high-end manufacturing, enable the production of complex parts and hold broad application prospects in aerospace, high-end equipment, and other fields. However, issues such as process parameter fluctuations and material property variations leading to defects have become stumbling blocks hindering the advancement of additive manufacturing toward mass production. In recent years, the rapid advancement of machine learning has shifted the research focus of LDED and LPBF from “process parameter optimization” to “AI-driven online quality control.” Integrating advanced sensing technologies has also become particularly crucial. This review outlines the progress and current status of intelligent monitoring research in LPBF and LDED additive manufacturing across five dimensions: process information sensing, internal/external defect assessment based on in-situ and ex-situ measurements, performance quality evaluation, process parameter optimization, and quality control. It highlights the challenges both technologies face in achieving mass production and outlines prospects.

Aiming at the problems of laser Simultaneous Localization and Mapping (SLAM), such as drift, low localization accuracy and map ghosting, which are prone to occur during localization and map construction in different structured environments, a tightly-coupled SLAM method of lidar and Inertial Measurement Unit (IMU) is proposed. Specifically, the initial position information provided by the IMU for the lidar is used to construct the joint error function of the IMU and the lidar, so as to achieve iterative position optimization. Following, the variety of the environmental structural information is determined, using a degradation detection method, based on the perturbation model, thus the selection of different methods for position estimation in different featured environments is achieved. Finally, when adequate number of structured features is obvious, the algorithm based online and surface feature matching, as proposed in LOAM, is used for motion estimation between neighboring frames. In the case of structural information lacking, the Iterative Closest Point (ICP) algorithm, containing distribution shape constraints, is introduced, to increase the constraints on the effective observation data, improving the stability and accuracy of the system, under the premise of ensuring that the system can run in real time. The results of extensive testing and validation in different scenarios, using open-source datasets, show that the proposed algorithm has higher accuracy and environmental adaptability, compared to other commonly used algorithms. In addition, real-vehicle tests, based on an autonomous self-driving car test platform, further demonstrate that the proposed method can be adapted to long-time drive and large-scale working environments, while it can operate steadily in real time.

We investigate the nonlinear passive control of vortex-induced vibrations of tubular telecommunication monopoles. The use of nonlinear energy sinks as an alternative to the commonly used tuned mass dampers for the control of vortex-induced vibrations is explored. The behaviors of the monopole coupled to a purely cubic nonlinear energy sink are analyzed using the complexification averaging method, while the linear dynamics of the system coupled with a tuned mass damper are studied through classical methods. The monopole is modeled as an Euler–Bernoulli beam, and the aerodynamic forces are represented by a simplified model from the literature, allowing the influence of wind speed and vortex shedding frequency to be considered. A design procedure for the nonlinear energy sink is proposed in order to estimate its optimal parameters. The validation of the developed analytical tools is carried out through numerical integration of the governing equations and also via simulations performed using the finite element method. Comparisons show that a nonlinear passive absorber can effectively control vortex-induced vibrations under certain conditions.

In this work, fatigue crack propagation tests were carried out at both macroscopic and microscopic scales. The propagation process was monitored using the digital image correlation (DIC) technique, which provided data on the fatigue crack growth rate and the unified constraint parameter A p (a parameter can represent both geometric constraint material constraint), and the correlation between the fatigue crack propagation rate and constraint was studied. Results demonstrate that a linear relationship between the fatigue crack propagation rate and the unified constraint parameter A p can be established for specimens at both scales, indicating a clear correlation between crack growth rate and structural constraint. Moreover, this correlation has been verified across different materials. In addition, based on the observed linear relationship, a new criterion for crack propagation was developed.

This article examines how the geometric parameters of bulldozer blades affect operational performance. The study compares standard moldboards with adaptive blades featuring articulated sections and flexible inserts. Key characteristics of both traditional and flexible-insert blades are described, along with the experimental methodology applied to assess their performance. The research highlights approaches to increasing efficiency and reducing bulldozer energy consumption. A notable improvement is achieved with blades that have a variable cutting angle or a flexible front surface. Such elements represent complex mechanical systems whose parameters can be optimized under different working conditions. The work emphasizes enhancing bulldozer equipment within traditional technological frameworks, which involve relatively low costs compared to full machine modernization. The study analyzes soil movement resistance along the blade and cutting resistance under changing curvature. A theoretical assessment is provided for flat blades with flexible front inserts, supported by experimental results identifying optimal parameters for variable-curvature and variable-angle blades. Tests on physical models further confirm these findings. This research was supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan under grant AP22684640 –“Development of an Articulated Bulldozer Blade Design with Multi-Level Geometric Adjustment.”

This paper studies the Job Shop Scheduling Problem (JSSP) with Unit Processing Times evolving in an uncertain environment. Our aim is to determine a set of solutions instead of a unique solution in order to manage unanticipated events. To achieve this, an approach integrating two techniques is presented to achieve sequential flexibility. In the first time, the decomposition of the initial problem into sub-problems is exploited for producing a dominant schedule. Then, based on the Group Sequence (GS) method, a set of schedules is constructed, allowing for sequential flexibility with an evaluation of performance. The present work also develops a new lower bound for the GS and compares it with an existing lower bound from the literature. Using benchmark data sets, computational studies demonstrate that the suggested lower bound significantly outperforms the established lower bound found in the literature. In addition, our approach succeeded in finding a set of solutions for all tested benchmarks within a reasonable amount of CPU time. Moreover, two interesting flexibility indicators are presented to evaluate the efficacy of our approach.

As the strategic position of the oceans in the political, military, and economic fields is increasing and the mankind’s use of ocean space is constantly being strengthened, underwater unmanned equipment is of vital importance and embraces a wide range of prospects for application, which plays a vital role in modern maritime military strategy, and is a key factor in ensuring that an advantage is gained in the field of underwater warfare in the new era. Underwater unmanned equipment can perform tasks such as environmental monitoring, target detection, anti-submarine, and anti-mine warfare, and can also be used as a weapon platform and a support platform, with the characteristics of strong concealment and low cost, and can be fitted with an optional payload according to the type of mission. As an essential part of underwater unmanned equipment, depth sensor is responsible for completing the deployment depth of the equipment in the seawater or sailing depth measurement, and the seawater pressure signal is converted into an electrical signal sent to the fuzzing device or control system and other electrical components for decoding and calculation, in order to control the sailing depth, thus completing the measurement of the automatic adaptation range in different depths, so as to ensure that the accuracy and the effectiveness of the target to be measured, which performs a crucial function in the process of equipment action. Meanwhile, for some underwater equipment, especially weaponry, the internal space is compact, the structure is complex, and the integration is high, making disassembly extremely difficult. Long-term use and storage, for sensors, cause time drift, which requires recalibrating. However, when sensors undergo time drift during long-term use or storage and require recalibration, they can only be removed and sent back to the manufacturer for maintenance during major overhauls. This process is time-consuming, and the secondary assembly after disassembly poses safety risks, significantly impacting the equipment’s performance. This paper introduces a CAN bus depth sensor with the capability of online calibration without disassembly, enabling the product to be quickly calibrated online without returning to the factory. This enhances the equipment’s supportability and ensures its long-term stable operation.

Dissimilar metal joints often fail due to the formation of brittle intermetallic phases at the interface. This study demonstrates a practical strategy to join titanium (Ti) and chromium (Cr) using laser surface alloying with molybdenum (Mo) as an intermediate layer. Single tracks and thin coatings of Cr and Mo were deposited on commercially pure Ti using a custom powder bed system that mimics key powder bed fusion parameters: laser power 150–450 W, scan speed 10 mm/s, beam diameter ∼ 254 µm, powder layer thickness 0.25 mm, and 50% overlap. Microstructure and composition were analysed by SEM-BSE/EDS and XRD, while hardness and Young’s modulus were measured by instrumented indentation. Cr-only deposits showed cracking near the fusion boundary, linked to brittle Ti-Cr intermetallics and residual stress. In contrast, Mo-only coatings were crack-free and promoted β -Ti stabilisation. A bilayer design (Ti/Mo+Cr) produced a continuous, crack-free modified zone. Mo acted as a compatibility layer, improving dilution and allowing the top Cr layer to form a Cr-Mo solid solution above metastable β -Ti. The Ti-Mo-Cr surface exhibited higher hardness than the substrate without the embrittlement seen in Ti-Cr alone. These findings show that a Mo interlayer can enable sound Ti-Cr joints in additive manufacturing.