N-methylmorpholine oxide (NMMO) was synthesized by reacting N-methylmorpholine (NMM) with hydrogen peroxide (H?O?) in the presence of hexane under catalyst-free and atmospheric pressure conditions at 40~90°C, with simultaneous dehydration. The effects of H?O? dosage, hexane volume, and reaction temperature on the synthesis efficiency were systematically investigated. The optimized process parameters were determined as follows: molar ratio of n(NMM)∶n(H?O?) = 1.0:1.2, hexane volume of 60~70 mL, and reaction temperature of 75°C. Under these conditions, the conversion rate of NMM exceeded 98%, and the yield of NMMO reached over 93%.

To enhance the yield of pumpkin polysaccharides, this study employed an ultrasound-assisted extraction method and conducted single-factor experiments focusing on three variables: liquid-to-material ratio, ultrasonic power, and ultrasonic time. Based on the Box-Behnken design, both response surface methodology (RSM) and a genetic algorithm–backpropagation neural network (GA–BP neural network) model were applied to optimize the extraction process. The results showed that under the optimal conditions predicted by the GA–BP neural network and RSM, the relative errors between the actual and predicted yields were 0.75% and 0.96%, respectively, indicating that the GA–BP neural network exhibited superior predictive performance. The optimized extraction parameters were a liquid-to-material ratio of 31:1, ultrasonic power of 252 W, and extraction time of 10 minutes, under which the polysaccharide yield reached 25.17%. This study provides a valuable reference for the development and utilization of pumpkin resources.

To address the issue of suboptimal aquaculture outcomes and lower survival rates persistently caused by unreasonable environmental settings in traditional aquaculture methods, a biofloc technology-based aquaculture method is proposed. Based on the principles of biofloc technology application, it meticulously sets multiple key environmental factors for aquaculture, encompassing the size of the farming area, the specifications of circular trenches, and the placement of water push machines. Within this established environment, a series of preparatory work is conducted before juvenile stocking, including comprehensive disinfection of the farming environment, early-stage water fertilization, and the cultivation of aquatic plants. Juvenile stocking is carried out according to the optimal stocking time, followed by intensified post-stocking management focused on five critical aspects: feeding management, aquatic plant management, water quality management, disease prevention and control, and daily management, all aimed at ensuring environmental stability. Through this design, a biofloc technology-based aquaculture method is successfully established and applied in experimental tests. The results show that compared with traditional aquaculture methods, this method maintains a survival rate consistently above 95%, with an average survival rate as high as 97%, demonstrating significantly superior aquaculture performance.

Aiming at the problems of low manual sorting efficiency and slow detection speed and low recognition accuracy of existing machine vision recognition systems in the current process crop seed sorting， a seed target detection method based on improved YOLOv8n is proposed. First，in C2f，the lightweight network FasterNet is used replace Bottleneck， which reduces redundant calculations and memory access， and improves the network operation speed and capability. Second， the EMA attention mechanism is introduced， which uses parallel sub structure and cross-space information aggregation to focus better on multi-scale features，and improve the accuracy of seed recognition. Finally， the Wise-IOU-v3 loss function used，which reduces the impact of low-quality annotations and accelerates the convergence speed of the network. The experimental results show that compared with the standard YOLOv8 algorithm， the improved YOLOv8n algorithm has improved by 2.2%， 3.4%， 1.4%， and 4.4 in precision，recall，mAP(0.5)，and mAP(0.5:0.95)，and the FLOPs are reduced by 20.2%，and the number of parameters is reduced by 27.2%. The improved YOLOv8n shows significant advantages in the trade-off precision and speed， and it can provide more reliable technical support for agricultural automatic sorting equipment.

This paper establishes a PRO/II dynamic simulation model for the propylene distillation column based on actual operational data. It conducts a sensitivity analysis of single operational parameters and combinations of operational parameters, including operating pressure, feed temperature, and reflux ratio, to identify the key operational parameters affecting the yield and thermal energy consumption of the propylene column. A regression analysis method was employed to model the energy consumption of the column, and the significance tests of the regression equations confirm that the developed energy consumption model was accurate and reliable. This research lays a new theoretical foundation for the multi-objective energy-saving optimization of the propylene distillation column.

As a rich and renewable energy source, wave energy is not affected by seasons, time or climatic conditions, and has relatively stable energy output and high utilization potential. To capture and utilize more low-frequency energy in waves and improve power generation efficiency, a small float structure power generation device is proposed through the analysis and research of the characteristics of existing power generation devices, the energy characteristics of waves and the principle of piezoelectric effect. This device utilizes the vibration of the cantilever beam caused by the magnetic force between magnets, and uses springs and piezoelectric oscillators to increase the frequency, collecting and converting wave energy. Through simulation calculations, the influence curves of structural parameters on voltage and power generation capacity are obtained, and the relationship between the length of the cantilever beam, the natural frequency and the output voltage of the device is simulated and analyzed by Comsol, and the laws of the first-order natural frequency and output voltage of the system with the change of the length of the cantilever beam and external force are obtained. According to the characteristics of waves and simulation results, the system parameters are optimized to improve the power generation capacity of the small portable device, to meet the energy supply problems in remote areas such as the far sea and isolated islands. At the same time, this small magnetic cantilever vibration piezoelectric power generation device has a simple structure, small volume, and is easy to carry and use.

Manipulators are widely applied in aerospace, industrial manufacturing, and medical fields. Compared to rigid manipulators, Flexible manipulators offer greater flexibility. However, controlling flexible manipulators during motion is more challenging, and they exhibit larger elastic vibrations in their links. Addressing the difficulties of control and significant link vibrations inherent to flexible manipulators, this study focuses on Quanser’s rotary flexible link as the research object. A super-twisting global fast terminal sliding mode control algorithm is designed. This algorithm integrates super-twisting control with terminal sliding mode control, and employs an improved saturation function to mitigate chattering in the sliding mode control. Firstly, the dynamic model of the rotary flexible link is established using Lagrange's equations combined with the assumed mode method. Subsequently, a global fast tracking differentiator is designed to differentiate the system's reference input signal, and a global fast terminal sliding mode controller is developed for trajectory tracking. To enhance trajectory tracking accuracy and suppress elastic vibrations by the flexible link, the super-twisting algorithm is adopted to formulate the control law for the sliding mode switching control. Finally, the stability of the closed-loop system is proven using Lyapunov theory. Simulation experiments conducted on the Matlab platform demonstrate that the proposed super-twisting global fast terminal sliding mode control achieves higher tracking accuracy and induces smaller elastic vibrations in the link compared to other methods.

Aiming at the problem that the triple inverted pendulum only provides one driving force to the trolley, and the control objective is that all three pendulum rods can remain stable at the unstable equilibrium point and have a good ability to resist external interference, a robust controller is designed by adopting the smooth super-twisting sliding mode control strategy based on auxiliary feedback. Firstly, by combining the linear matrix inequality technique and using the method of constructing auxiliary feedback, the symmetric positive definite matrix in the sliding mode control law based on auxiliary feedback is solved, and then the design of the sliding mode surface is completed. Secondly, the buffeting problem existing in the sliding mode control algorithm itself is weakened, and in order to further ensure that the control rate is smooth, the smooth super-twisting sliding mode algorithm is introduced into the controller design framework. Finally, the stability of the closed-loop system is proved by the Lyapunov function. The simulation results show that this control strategy has a very good control effect on complex high-order unstable systems, achieving the control objective and having strong robustness.

In automotive phosphating processes, to address the abnormal crystallization caused by temperature gradients during the heating phase of phosphating solution, a temperature difference-PID coordinated control program was developed. This program integrates segmented temperature compensation and dynamic parameter adjustment to achieve precise thermal regulation. Application tests demonstrated that the optimized control system significantly reduced temperature fluctuations and effectively inhibited crystallization risks.

Aiming at the traditional PID control in the large inertia, pure delay resistance furnace temperature control system is prone to the problem of integral saturation, based on the principle of the original variable-speed integral PID algorithm, an improved variable-speed integral PID control strategy is proposed, which is based on the introduction of the absolute value of the ratio of the error to the set value as the basis of the segmentation, and at the same time combines with the cosine function to construct a nonlinear function, fimproved(x), from the adaptive Adjustment of integral term weight coefficients. The performance of the improved variable speed integral PID, the original variable speed integral PID and the ordinary PID algorithm in the temperature control system of the resistance furnace is simulated and compared under four different set values using Matlab software. The results show that the control based on the improved variable speed integral PID algorithm can significantly accelerate the system regulation speed, effectively reduce the overshooting amount, and improve the stability of the system, which is of certain reference significance for the temperature control of industrial heat treatment equipment.

Confronting the challenge of accurately extracting air compressor fault features from traditional MFCC spectrograms in high-noise environments, this paper proposes an air compressor fault identification method based on low-rank matrix recovery. The proposed approach utilizes low-rank background modeling to denoise MFCC spectrograms, effectively separating foreground features from noise. Subsequently, the MobileNetV2 model is employed for feature extraction, while Principal Component Analysis (PCA) is applied to achieve dimensionality reduction. Finally, the extracted fault features are clustered in an unsupervised manner using the K-means algorithm, enabling precise classification of air compressor fault states. Experimental results demonstrate that the proposed method not only significantly enhances recognition accuracy—for instance, ResNet18 achieved a 99.40% accuracy with substantially reduced training time—but also exhibits superior performance in clustering analysis by attaining higher CH and SC indices. These findings underscore the method’s robustness and advantage in noisy environments, offering a reliable and efficient solution for air compressor fault diagnosis and maintenance.

Based on the background of 3D metal printing technology, the digital characteristics of the vortex compressor in the design process can be better satisfied, and the error caused by the tool interference in the traditional processing process can be reduced. By comparing the deformation of the dynamic vortex disk produced by 3D metal printing technology and the casting technology under the condition of the same gas force, the deformation of the dynamic vortex disk of 3D metal printing is 0.07912mm, and the deformation of the cast dynamic vortex disk is 0.08123mm. Thus, the strength of 3D metal printing technology is better than the casting technology. Therefore, 3D metal printing technology provides a new way for the production of vortex compressors.

Power distribution of fuel cell hybrid vehicles should be reasonably controlled to ensure the power and economy performance, and give full play to the advantages of fuel cells and power batteries as well. AVL Cruise software is used to build a simulation model of fuel cell + power battery (FC +B) SUV hybrid energy storage system electric vehicles, and an improved finite state machine control strategy is proposed based on Matlab/Simulink software. Simulation with improved finite state machine control strategy under World Light Vehicle Test Cycle (WLTC) and New European Driving Cycle (New European Driving Cycle) have conducted, which compared with that of unimproved strategy. Results show that the improved finite state machine control strategy which with the power battery state of charge (SOC) in a reasonable range can reduce the consumption of hydrogen, thus improve the economy of vehicle.

Aiming at the problem of cutting force and surface integrity in cutting Ti6Al4V titanium alloy, the influence of cutting parameters on machining quality is revealed by orthogonal cutting test combined with multi-parameter dynamic analysis ( cutting speed, feed speed, cutting depth ). It is found that cutting force is positively correlated with feed speed and cutting depth, but negatively correlated with cutting speed. The surface roughness ( Ra / Rz ) is mainly dominated by the feed rate, and the Ra value can be reduced to less than 0.4μm by optimizing the parameters. The distribution of surface residual stress is consistent with the trend of cutting force, and high cutting speed can reduce surface defects. The research results provide a basis for parameter optimization for precision machining of titanium alloy parts in aerospace field, and have practical guiding significance for reducing processing energy consumption and improving surface quality.

Taking peanut kernels as the research object, this study explores visual hardware acquisition devices through experimental research, and ultimately proposes a method for identifying moldy peanut kernels based on binocular vision and the R component of color as the characteristic value. After the target image is captured by a binocular camera and input into the LabVIEW software processing system, the image undergoes preprocessing, grayscale histogram analysis, extraction and analysis of color characteristic values, classifier construction, and matching the extracted color characteristic values of the peanut kernel image with the classifier to complete the identification task. Finally, a moldy peanut kernel identification system is designed. Test results show that the accuracy rate of this method for identifying moldy peanut kernels reaches 95%, basically meeting the standard for moldy peanut kernel detection.