The dual-motor coupling drive system (DCDS), which is widely used in electric vehicles, has attracted increasing attention due to its high transmission efficiency and economical fuel consumption. Current research has mainly focused on the control scheme of dual motors and has ignored the dynamic characteristics of the asymmetrical transmission structure. This paper presents an investigation of a dynamic model and an analysis method of the transmission process for the DCDS. The entire dynamic model of the DCDS was established by considering the planetary gear, differential bevel gear, and drive shaft with the transfer matrix method (TMM). Then, a detailed theoretical analysis was developed to study the influence of meshing stiffness and excitation source on the dynamic characteristics. Finally, the DCDS experimental platform was utilized to validate the effectiveness of the proposed dynamic model. For susceptibility to low-frequency vibrations, the first four natural frequencies and vibration modes of the DCDS were analyzed through the processing and analysis of acceleration signals. The experimental dynamic responses were generally consistent with the numerically computed results, which demonstrates the effectiveness of the proposed dynamic model with TMM. Furthermore, the proposed dynamic analysis method may be helpful for developing effective control algorithms to suppress vibrations and achieving highly smooth motions for electric vehicles.

The position synchronous control of multi-axis gantry-type feed stage is crucial in precision machine tools. Industrial position control which aims to widen the bandwidth and improve disturbance rejection of single axis is not enough to achieve precise synchronization in a dual-driving feed stage. The characteristics diversity, transmission-mechanism deformation, and mechanical coupling effect between dual axes will degrade the control accuracy. Hence, the novel two-degree-of-freedom (2-DOF) dynamic model-based terminal sliding mode control (TSMC) with disturbance and state observer is proposed in this paper for the synchronous control of a 2-DOF dual-driving feed stage. The 2-DOF dynamic model, based on Lagrange equation, is established along with the parameters identification method. The predictive natural frequencies and vibration modes frequencies by the proposed dynamic model are compared by a modal experiment. Then, the 2-DOF dynamic model-based TSMC is provided to satisfy the tracking and synchronization control. In order to reduce the chattering and to increase the robustness against the mechanical coupling, the disturbance and state observer is designed. Moreover, Lyapunov stability criterion is used to analyze the stability of the proposed control scheme. Finally, an industrial application of 2-DOF dual-driving feed stage is utilized to validate the effectiveness of the proposed control scheme. The proposed 2-DOF dynamic model-based TSMC with observer has been effectively demonstrated to improve synchronous performance and tracking accuracy.

The dynamic vibration of the gear coupling-rotor system (GCRS) caused by misalignment is an important factor of low frequency vibration and noise radiation of the naval marine. The axial misalignment of gear coupling is inevitable owing to mass eccentricity, and is unconstrained in axial direction at high-speed operation. Therefore, the dynamic model of GCRS is proposed, considering gear-coupling misalignment and contact force in this paper. The whole motion differential equation of GCRS is established based on the finite element method. Moreover, the numerical calculation method of meshing force, considering the uniform distribution load on contact surface, is presented, and the mathematical predictive time–frequency characteristics are analyzed by the Newmark stepwise integral approach. Finally, a reduced-scale application of the propulsion shaft system is utilized to validate the effectiveness of the proposed dynamic model. For the sensibility to low-frequency vibration, the natural frequencies and vibration modes of GCRS are analyzed through the processing and analysis of acceleration signal. The experimental dynamic response and main components of vibration are respectively consistent with mathematical results, which demonstrate the effectiveness of the proposed dynamic model of GCRS with misalignment. Furthermore, it also shows that the proposed finite element analysis and calculation method are suitable for complex shafting, providing a novel thought for dynamic analysis of the propeller–shaft–hull coupled system of marine.

Egg size is a crucial indicator for consumer evaluation and quality grading. The main goal of this study is to measure eggs’ major and minor axes based on deep learning and single-view metrology. In this paper, we designed an egg-carrying component to obtain the actual outline of eggs. The Segformer algorithm was used to segment egg images in small batches. This study proposes a single-view measurement method suitable for eggs. Experimental results verified that the Segformer could obtain high segmentation accuracy for egg images in small batches. The mean intersection over union of the segmentation model was 96.15%, and the mean pixel accuracy was 97.17%. The R-squared was 0.969 (for the long axis) and 0.926 (for the short axis), obtained through the egg single-view measurement method proposed in this paper.

As a traditional delicacy in China, preserved eggs inevitably experience instances of substandard quality during the production process. Chinese preserved egg production facilities can only rely on experienced workers to select the preserved eggs. However, the manual selection of preserved eggs presents challenges such as a low efficiency, subjective judgments, high costs, and hindered industrial production processes. In response to these challenges, this study procured the transmitted imagery of preserved eggs and refined the ConvNeXt network across four pivotal dimensions: the dimensionality reduction of model feature maps, the integration of multi-scale feature fusion (MSFF), the incorporation of a global attention mechanism (GAM) module, and the amalgamation of the cross-entropy loss function with focal loss. The resultant refined model, ConvNeXt_PEgg, attained proficiency in classifying and grading preserved eggs. Notably, the improved model achieved a classification accuracy of 92.6% across the five categories of preserved eggs, with a grading accuracy of 95.9% spanning three levels. Moreover, in contrast to its predecessor, the refined model witnessed a 24.5% reduction in the parameter volume, alongside a 3.2 percentage point augmentation in the classification accuracy and a 2.8 percentage point boost in the grading accuracy. Through meticulous comparative analysis, each enhancement exhibited varying degrees of performance elevation. Evidently, the refined model outshone a plethora of classical models, underscoring its efficacy in discerning the internal quality of preserved eggs. With its potential for real-world implementation, this technology portends to heighten the economic viability of manufacturing facilities.

The sterilization of liquid eggs plays a crucial role in the production of liquid egg products. Traditional pasteurization techniques can easily cause protein denaturation, while non-thermal sterilization techniques are often constrained by processing intensity and time. Improving the effectiveness of liquid egg sterilization while preserving the stability of its functional attributes poses a significant challenge. In response to this issue, a synergistic ultrasonic mild thermal sterilization system for liquid eggs is proposed, accompanied by the optimization of its process parameters. COMSOL is employed to simulate the acoustic field distribution of the ultrasonic–thermal system in the liquid egg medium. Verification is conducted through acoustic intensity measurements, and analysis is performed to obtain the optimal arrangement of ultrasonic transducers. Based on Modbus communication, an ultrasonic–thermal synergistic sterilization system is designed. Sterilization experiments are conducted with both 20 kHz + 28 kHz and 20 kHz + 40 kHz multifrequency ultrasound, compared with traditional 20 kHz single-frequency ultrasound. The results indicate that multifrequency ultrasound improves sterilization efficiency by approximately 15% compared to traditional single-source ultrasound. Utilizing multifrequency ultrasonic–thermal synergistic sterilization experiments, a three-factor, three-level response surface test is conducted with sterilization rate and foaming properties as evaluation criteria. The results indicate a strong correlation between ultrasonic frequency, processing time, heating temperature, and sterilization performance, with the impact magnitude being sterilization temperature > processing time > ultrasound frequency. Parameter optimization analysis is performed using a genetic algorithm, yielding sterilization conditions of 55 °C, 11 min and 30 s processing time, and 20 + 40 kHz ultrasonic frequency. The liquid egg sterilization rate is 99.32%, an average decimal reduction of 3.17 log values, and foaming properties are 42.79%.Through comparative analysis, it is determined that the sterilization rate of the ultrasonic–thermal synergistic sterilization system meets national standards, and functional properties such as foaming are superior to traditional pasteurization. This validates the proposed ultrasonic–thermal synergistic liquid egg sterilization control system as effective and feasible.