Journal of Mechatronics and Artificial Intelligence in Engineering
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Simulation analysis and safety performance assessment of a novel am opening barrier for highway
Get PDFTo address the need for quick opening, easy mobility, and convenient maintenance of barrier in highway central medians, a novel Am rotatable open barrier has been designed. Based on guardrail safety performance evaluation standards, a finite element model of the vehicle-guardrail interaction is established for collision simulations to validate the adequacy of the new guardrail structure. In the meantime, full-scale vehicle crash tests are conducted to assess the safety performance of the proposed open guardrail. The results demonstrate that safety performance metrics, including vehicle post-collision acceleration, maximum dynamic inclination, maximum lateral dynamic deformation, and displacement extension values, meet standard requirements in both simulations and real-world validations. Additionally, the vehicle doesn’t penetrate, overturn, or ride over the barrier, and no rollover occurred. This indicates that the newly designed barrier not only fulfills the functions of quick opening and easy mobility but also provides excellent blocking and guiding capabilities, contributing to the enhanced safety and operational efficiency of highway service
The influence of robots on the spatial electric field measurement for zero value insulator recognition
Get PDFZero value insulators pose a threat to the safe and stable operation of transmission lines. By walking with tracked robots, the local electric field distribution of insulator strings can be quickly detected and measured, thereby identifying zero value pieces. To clarify the influence of robot architecture on the electric field measurement of insulator strings and propose a fast identification criterion for zero-value recognition, this paper establishes a true model of 220 kV insulator strings and an equivalent model of robots. The electric field distribution characteristics of the robot structure working on insulator strings were analyzed through finite element simulation, and the influence of factors such as robot material and size on local electric field distortion characteristics was studied, especially the local electric field variation laws under zero and non-zero values. The model's validity is confirmed through relevant simulations, ensuring its reliability for practical applications. Further detailed simulation analysis was conducted on the local electric field distortion characteristics of the robot architecture at different positions of the insulator string, and the electric field measurement characteristics of the zero value insulator were obtained. Based on the simulation results of the 220 kV insulator string, a criterion for measuring and identifying zero value insulators for 500 kV was proposed and applied to 500 kV. The research results reveal the influence of electric field detection and measurement robots on local electric field distortion of zero value insulators, which can provide technical support for intelligent operation and maintenance of external insulation in power transmission and distribution
Fuzzy dynamic self-tuning based linear active disturbance rejection control for PMSM speed control
Get PDFIn this paper, a novel control approach, namely fuzzy dynamic self-tuning-based linear active disturbance rejection control (FDS-LADRC), is proposed for the speed loop system of permanent magnet synchronous motors (PMSMs). Specifically, a control framework based on the linear active disturbance rejection control (LADRC) is presented. Fuzzy dynamic self-regulators are developed to enable simultaneous adaptive adjustments of both the controller and observer parameters. Additionally, the stability analysis is provided. A series of numerical simulations demonstrates that FDS-LADRC achieves superior adaptivity, transient performance, disturbance rejection capability, and anti-noise ability under various operating conditions. For instance, during no-load startup, compared with the traditional LADRC, nonlinear active disturbance rejection control (ADRC), a variant of FDS-LADRC named IT2FDS which utilizes interval type-2 fuzzy systems as fuzzy dynamic self-regulators, a state-of-the-art fractional-order ADRC with fuzzy self-tuning (FSFOADRC), and sliding mode control (SMC), FDS-LADRC reduces overshoot by 10.82 %, 13.55 %, 7.36 %, 5.53 %, and 3.94 %, respectively, and shortens settling time by 0.0132 s, 0.0076 s, 0.0139 s, 0.0009 s, and 0.0156 s, respectively. Finally, corresponding real-world experiments are conducted to validate the effectiveness and superiority of FDS-LADRC
Estimation of vehicle state based on maximum correntropy square-root cubature Kalman Filter
Get PDFState estimation of a vehicle is an important direction under the research branch of automotive dynamics, with the aim of determining state variables that reflect vehicle handling stability and other characteristics. In order to solve the problem of poor estimation accuracy caused by heavy tailed non Gaussian noise in traditional state estimation methods, a new filtering algorithm based on the Maximum Correlation Entropy criterion (MCC) and the Square-root Cubature Kalman Filter (MCSCKF) is proposed. On the basis of establishing a nonlinear 3-DOF vehicle model, the yaw rate and the side slip angle as well as the longitudinal velocity of the vehicle were estimated. And the effectiveness of the algorithm was verified through joint simulation with Carsim and Matlab/Simulink. The results show that the MCSCKF algorithm can adapt to complex working conditions and has better accuracy in vehicle state estimation than traditional state estimation algorithms. Meanwhile, the MCSCKF algorithm can effectively reduce the impact of heavy tail non Gaussian noise and improve the accuracy of vehicle state estimation
Coupling dynamics modeling and vibration characteristics analysis of TBM main drive system under complex tunnelling conditions
Get PDFIn order to ensure the reliable operation of TBM excavation process, it is particularly important to analyze the vibration characteristics in complex surrounding rock environments. The coupling dynamics model of the TBM main drive system proposed in this article considers the structural characteristics of distributed support and multi-source inputs, as well as nonlinear internal excitations such as bearing dynamic stiffness, gear meshing error, and tooth side clearance, which can more accurately calculate the dynamic characteristics of the main drive system. Based on the TBM scale test-bed, the modeling method and the vibration response of the main components were compared and verified. Based on the coupled dynamic model of the main driving system, the vibration characteristics of the driving system were analyzed under different excavation penetrations and different proportions of soft and hard surrounding rocks. The analysis results show that during the process of penetration from 5 mm to 6 mm, the average vibration increase speed is the highest, reaching 0.1493 g/mm. As the proportion of soft surrounding rock increases, the lateral unbalanced load and torque of the cutterhead significantly increase. Meanwhile, as the proportion of soft surrounding rock increases, the corresponding rate of load increase significantly increases. Within the range where the proportion of soft surrounding rock increases from 21 % to 35 %, its lateral overturning vibration RMS value increases by 13.08 %. Within the range where the proportion of soft surrounding rock increases from 35 % to 50 %, its lateral overturning vibration RMS value increases by 32.18 %. This can easily cause safety accidents such as the fracture of key load-bearing components of the system during the excavation process
Feature data analysis of dance movements by motion capture
Get PDFMotion capture technology has been applied in more and more fields, but the research in the field of dance is relatively rare. In order to combine motion capture technology with dance research, better understand the characteristics of dance movements, and provide support for their digital analysis, this paper mainly studied the application of a motion capture technology called Kinect in the analysis of dance movement feature data. The skeleton data of different dance movements was first collected based on Kinect v2, and then the collected data was analyzed using a spatio-temporal graph convolutional network (ST-GCN). On the basis of the original ST-GCN, the multi-branch structure was adopted to realize co-occurrence feature learning, and the bone length feature and direction feature were introduced to further enrich the feature data. Experiments were carried out on the NTU RGB+D and dance datasets. It was found that the improved ST-GCN had better performance than other current motion classification approaches on the NTU RGB+D. The top-1 accuracy for cross-subject (CS) and cross-view (CV) was 92.4 % and 96.7 %, respectively, and the average accuracy of different dance movements for the dance dataset was 96.035. The findings confirm the effectiveness of the proposed approach in the analysis of dance movement feature data, and it can be applied in the actual research of dance movements
Vibration characteristics testing and vibration reduction optimization design of four-wheel-drive micro-tiller handlebar assembly
Get PDFMicro-tillers are essential for agricultural operations in hilly and mountainous regions, yet their severe vibrations pose significant health risks to operators, including hand-arm vibration syndrome. This study presents an innovative vibration reduction solution through the installation of a damping spring isolator at the handle-frame connection point. Comprehensive vibration testing revealed that the vertical vibration under tillage conditions reached 2.15 m/s2 RMS, with spectral analysis identifying critical excitation frequencies at 39 Hz, 78 Hz, and 156 Hz. Constrained modal analysis demonstrated that the handle frame's third-order natural frequency of 41.02 Hz risked resonance with the engine’s 39 Hz excitation. The optimized isolator system, designed with a damping ratio of ξ= 0.2, successfully reduced this critical frequency to 34.87 Hz (15 % reduction), effectively avoiding resonance. Field validation showed significant vibration attenuation, with RMS values decreasing by 14.17 % (idle), 17.61 % (no-load), and 23.26 % (tillage), while achieving 19.3 % vibration energy absorption during operation. This research represents the first successful integration of isolation and damping mechanisms for micro-tiller handle frames, providing a cost-effective solution (< 1.5 % of machine cost) that significantly improves operator comfort and addresses long-standing ergonomic challenges in small-scale agricultural machinery. The solution's simple implementation without structural modifications makes it particularly suitable for widespread adoption in developing regions
Small sample fault diagnosis method based on dual convolutional kernel feature fusion and channel attention weighted temporal convolutional network (DCK-CAM-TCN)
Get PDFIn actual industrial environments, equipment failures often occur sporadically during operation, resulting in insufficient labeled data for training. To address the issues of difficult feature extraction and poor generalization caused by insufficient data in small-sample fault diagnosis, a small sample fault diagnosis method based on dual convolutional kernel feature fusion and channel attention weighted temporal convolutional network (DCK-CAM-TCN) is proposed. Firstly, dual convolution kernels are employed to extract signal features, with the large kernel capturing low-frequency components and the small kernel extracting additional features to enhance the network's expressiveness. Secondly, the channel attention mechanism adaptively adjusts the feature responses of each channel, enabling the network to focus on the most informative and relevant features while suppressing unimportant ones. Finally, the Temporal Convolutional Network (TCN) is utilized to capture dependency features within long time series, further improving the model's ability to process sequential data. Experimental results demonstrate that the DCK-CAM-TCN model significantly outperforms traditional Convolutional Neural Networks (CNNs) and other comparison models in small-sample scenarios. The results indicate the significant advantages of the DCK-CAM-TCN model in small-sample fault diagnosis
Innovative design of a gear belt transmission for technological machines
Get PDFThe article presents the types of belt transmission designs, as well as the advantages of their use in mechanical engineering. Belt drives create loads as a result of excessive vibrations due to a flexible element (belt). A new design of an innovative toothed belt drive is proposed, which contains two paired driving and driven gear pulleys with different diameters and two belts with teeth covering them, while the gear ratios of each pair of gears are equal to each other. The simulation demonstrates a 25-38 % reduction in velocity fluctuation compared to conventional drives, confirming the effectiveness of the proposed design
An analysis of the ultrasonic technology to stitch materials, and conceptualization and realization of a new sewing machine
Get PDFUltrasonic stitching is a thread-free and green technology for stitching fabrics, which uses the vibration energy of high frequency to transform it into heat at the joint to achieve local fusion. This paper provides the conceptual design and experimental validation of a roller-based ultrasonic sewing system for thermoplastic and composite textile. This work introduces a portable roller-type ultrasonic actuator coupled with a physics-based thermal model which allows the controlled and threadless joining of textiles, which is the main innovation of this paper. When operated at 27 kHz, 100 W and contact pressure of 5 MPa, the method gives maximum lap shear strengths of 86 N for polyester and 67 N for cotton + LDPE. The measured results define the process window and show the possibility of low-waste industrial utilization. Novelty: (I) a small size ultrasonic stitching unit based on the roller technology; (II) a closed-form thermal model for the relationship between energy input and joint strength; (III) validated process parameters towards a sustainable textile bonding application