Pipelines, as critical infrastructure in energy transmission, municipal facilities, industrial production, and specialized equipment, are essential to national economic security and social stability. This paper systematically reviews the domestic and international research status of pipeline in-line inspection (ILI) technologies, with a focus on four major technological systems: electromagnetic, acoustic, optical, and robotic technologies. The operational principles, application scenarios, advantages, and limitations of each technology are analyzed in detail. Although existing technologies have achieved significant progress in defect detection accuracy and environmental adaptability, they still face challenges including insufficient adaptability to complex environments, the inherent trade-off between detection accuracy and efficiency, and high equipment costs. Future research directions are identified as follows: intelligent algorithm optimization for multi-physics collaborative detection, miniaturized and integrated design of inspection devices, and scenario-specific development for specialized environments. Through technological innovation and multidisciplinary integration, pipeline ILI technologies are expected to progressively realize efficient, precise, and low-cost lifecycle safety monitoring of pipelines.

High-overload testing equipment is a key platform for evaluating mechanical performance under extreme conditions, requiring specialized functional design to meet stringent operational demands. The current design process faces numerous challenges, including overreliance on designers’ experience, incomplete requirement analysis, and insufficient automation, resulting in suboptimal solutions. To address these issues, in this study, we propose an integrated method based on axiomatic design (AD) and the Theory of Inventive Problem Solving (TRIZ). This method systematically decomposes technical specifications, maps requirements to a structural framework, and resolves design conflicts using inventive principles. The method employs a comprehensive evaluation framework combining the analytic hierarchy process (AHP) and quality function deployment (QFD) to quantitatively assess candidate designs. It facilitates the development of efficient, standardized high-load testing equipment solutions, enhancing design reliability and innovation capabilities.

Subsea pipelines are extensively utilized in transportation systems. Conducting regular and effective internal inspections of these pipelines to promptly identify internal defects and potential risks is of paramount importance to ensure safe operational practices. In response to the practical engineering requirements for the internal inspection of subsea pipelines, this paper presents the design of an inspection device capable of capturing point cloud data from pipelines with internal diameters of 100 mm and above and performing three-dimensional reconstruction through coding. This device clearly reveals internal pipeline defects and enables both qualitative and quantitative analyses. Upon designing the motion module, control system, and LiDAR-based detection module of the internal pipeline inspection device, the capacity to collect internal point cloud data and perform 3D reconstruction was achieved. An experimental prototype of the inspection device was manufactured and tested using a simulated pipeline constructed to replicate real-world conditions. An analysis of the inspection results demonstrates that the device can travel steadily inside the pipeline, and the collected point cloud data can be used for 3D reconstruction via coding, accurately and clearly displaying the internal 3D structure of the pipeline and its defects. This device provides a basis for the prediction of pipelines’ service lives.

Aiming at the problems of high complexity in source domain data, inaccessibility of target domain data, and unknown fault patterns in real-world industrial scenarios for mechanical fault diagnosis, this paper proposes a Feature Decomposition-based Source-Free Universal Domain Adaptation (FD-SFUniDA) framework for mechanical equipment fault diagnosis. First, the CBAM attention module is incorporated to enhance the ResNet-50 convolutional network for extracting feature information from source domain data. During the target domain adaptation phase, singular value decomposition is applied to the weights of the pre-trained model’s classification layer, orthogonally decoupling the feature space into a source-known subspace and a target-private subspace. Then, based on the magnitude of feature projections, a dynamic decision boundary is constructed and combined with an entropy threshold mechanism to accurately distinguish between known and unknown class samples. Furthermore, intra-class feature consistency is strengthened through neighborhood-expanded contrastive learning, and semantic weight calibration is employed to reconstruct the feature space, thereby suppressing the negative transfer effect. Finally, extensive experiments under multiple operating conditions on rolling bearing and reciprocating mechanism datasets demonstrate that the proposed method excels in addressing source-free fault diagnosis problems for mechanical equipment and shows promising potential for practical engineering applications in fault classification tasks.

Clearance-containing flexible oscillating mechanisms are widely used in aerospace systems, robotic manipulators, precision manufacturing systems, and intelligent machinery, where their nonlinear dynamic behavior directly affects motion accuracy, stability, and operational reliability. The combined effects of joint clearance, structural flexibility, contact–impact, and constraint nonlinearities can induce rigid–flexible coupled vibration, bifurcation, chaos, and nonsmooth responses. This review systematically summarizes recent advances in dynamic modeling, nonlinear dynamic analysis, vibration and chaos control, experimental validation, and engineering applications of such mechanisms. Particular attention is given to contact–impact models, rigid–flexible and clearance–flexibility coupled formulations, bifurcation and chaos analysis, active, passive, and semi-active control, Nonlinear Energy Sinks (NESs), hybrid control, and Digital Twin-enabled validation. Existing studies indicate that continuous contact force models and flexible multibody formulations remain widely adopted, while the bidirectional coupling between joint clearance and structural deformation is a primary source of complex nonlinear behavior. Hybrid active–passive control is receiving increasing attention, and NESs show strong potential for broadband vibration suppression. However, current research is still limited by insufficient multiphysics coupling, incomplete understanding of high-dimensional nonsmooth dynamics, underdeveloped motion-accuracy-oriented control frameworks, and limited long-term experimental validation. Future research should emphasize high-fidelity multiphysics modeling, data-driven dynamic prediction, intelligent vibration control, NES optimization, and Digital Twin-based online validation.

A compact autonomous recorder was developed for short-duration measurements in confined moving systems where event-time cabling is unavailable. The cylindrical platform combines pressure, high-range acceleration, and angular-velocity interfaces with channel-specific conditioning, FPGA/microcontroller control, SDRAM buffering, eMMC storage, internal power, and mechanical support. Its operating sequence covers baseline checks, circular buffering, threshold-initiated event capture, nonvolatile storage, and post-test retrieval. An eight-field map and count-to-unit equations describe the readout convention. Three-channel electrical checks captured 1 kHz inputs and gave voltage spans of 6–8 mV at a nominal 5 V input. The loading evaluation comprised one acceleration–angular-velocity event and one pressure–acceleration event. Both tests stored eight-field event records over 8 ms at a nominal sampling rate of 1 MS/s per recorded field. Using the count-to-unit conversions, axial acceleration exceeded 24,000 g in the first event and reached approximately 27,000 g in the second, which also recorded approximately 354 MPa pressure. Both records were retrieved after recovery, with post-event communication available. These results demonstrate autonomous recording and recovery for two paired sensing configurations within the same compact architecture. Full simultaneous pressure–acceleration–angular-velocity operation remains to be evaluated.