Vinylene carbonate was synthesized using vinyl chloride carbonate and sodium bicarbonate as raw materials by a molecular sieve circulating dehydration process. After optimizing the synthesis process conditions, the purity of vinylene carbonate reached up about 96% by the analysis method of gas chromatography，and its purity yield is 81.24%. Compared with traditional processes, this synthesis process has no by-products of triethylamine hydrochloride, no need for pressure filtration, and less solvent usage; The byproducts CO2, NaCl, and H2O can be removed through venting, sedimentation, and molecular sieve adsorption, respectively. Moreover, the external circulation adsorption dehydration process is not limited by the solvent boiling point, has fewer components in the crude reaction solution, high yield, easy separation, and low energy consumption.

In this paper, six 1,3,5-triarylpyrazoline compounds were synthesized under the catalysis of vitamin B1 by using substituted benzaldehyde and substituted acetophenone, with a yield of 75–93%. The method is convenient to operate and does not require acid, alkali and metal ions, vitamin B1 has good catalytic effect, non-toxic, green environmental protection can be commercially purchased. FT-IR, ¹H NMR, and HR-MS characterization were performed to determine the structure of the compound. The influence of the substituents on the fluorescence spectra of 1, 3, 5-triarylpyrazoline was studied by measuring the fluorescence spectra.

The electrolytic polishing solution was a mixture of perchloric acid and methanol at a ratio of 1:9 .The optimum process of the electrolytic polishing solution was determined by adjusting the voltage and polishing time. The microstructure of the sample surface after polishing with different combination parameters was observed under field emission electron microscope. The polished surface quality of electrolytic polishing samples used for EBSD（Electron Back-Scattering Diffraction）depends on the experimental parameters of electrolytic polishing. Under which the sample is used for EBSD test, and clear images of Kikuchi pattern and grain orientation are obtained. 

The intelligent plasma discharge system was designed and the plasma surface treatment of biaxiallyoriented polypropylene(BOPP)film was carried out with dielctric barrier glow discharge(DBGD)in high-purity air plasma.The surface contact angle was measured by the distilled water and Diiodomethane,andchanges of the chemical composition of BOPP were characterized by the Fourier infrared spectrometer.Theexperimental results showed that the gap for producing DBGD decreased with the increase of gas Pressure,thesolid surface energy of BOPP film treated by DBGD plasma was improved significantly.The surface liquidcontact angle decreases with the increase of treatment time and power density.The chemical reaction in BOPPsurface upon plasma treatment was characterized by the FT-IR measurement,new C—0 groups and C—Hbonds appeared in the treated BOPP films due to DBGD treatment.

A method based on an improved A* algorithm is proposed to address the issues of low safety and slow search speed in path planning for warehouse mobile robots. This method first performs an inflation operation on the obstacles in the map. Based on this, the search strategy and heuristic function of the traditional A* algorithm are improved. The algorithm utilizes a bidirectional search approach and introduces an exponentially weighted estimation cost. Experimental results demonstrate that compared to the traditional A* algorithm, the proposed algorithm can reduce search time by up to 18.59% in maps of different scales, significantly improving the search efficiency of warehouse mobile robots.

In this paper, a non-ideal distillation column for ethanol-water system is established, a steady-state model is built in Aspen Plus, a full-field control scheme is built after importing the steady-state model into Aspen Dynamics, and the dynamic response of the alcohol distillation process is investigated. Due to the traditional PID control scheme produces large fluctuations during perturbation, which ultimately leads to the problem of product purity degradation, the multivariate dynamic matrix predictive control algorithm (DMC) is added to the traditional control scheme of the dynamic model. The simulation results of the control system show that the Dynamic Matrix Predictive Control (DMC) based on the mechanism model can greatly reduce the production fluctuation and achieve a smooth operation process.

In order to accurately detect real-time changes in traffic signals, and traffic signals belong to small targets with high recognition difficulty, this paper proposes to use YOLOV5L to solve the problem of traffic signal recognition. This system can achieve recognition of traffic signals under target images and real-time monitoring. This system uses the Pytorch framework, which can provide high-precision real-time monitoring and recognition functions. Finally, experimental operations were conducted on a self-made traffic signal dataset, and the experimental results were obtained mAP@.50 Finally, it stabilized at 78.6%. The YOLOV5L model can basically meet the detection and recognition of traffic signals.

In the process of turning processing, tool wear is one of the most important factors affecting machining efficiency, before excessive damage to the work piece surface, it is necessary to identify and update the wear of the tool in time to achieve high-quality production and processing of the work piece. In this paper, a tool wear state recognition method based on deep learning is proposed, which records the turning tool images at different wear stages through a microscope, and uses the convolutional neural network to extract the different wear state features of the input images, and selects appropriate training parameters for the model to realize the state classification of cutting tool wear. Experiments show that the accuracy rate can reach 94.0% when classifying different wear states of turning tools, which can be used to identify tool wear states in the turning process at low cost.

As an important component of the steam turbine, blades often operate in complex environments with high workloads. Defects such as cracks can pose significant safety hazards to production. In order to detect early-stage cracks, the commonly used material 2Cr12NiMoWV stainless steel in steam turbines was chosen as the research object. A finite element simulation model of an eddy current testing system was established using COMSOL Multiphysics software. This aimed to investigate the impact of different types of defects on the probe coil detection results. The simulation results were validated through experimental equipment.  Furthermore, impedance signals at defect locations were analyzed, providing a theoretical basis and technical support for subsequent defect identification and classification.

Aiming at the problem of noise in UAV speed signal estimation, a filter algorithm based on strong tracking filter and Kalman filter is proposed to estimate unknown signal. When predicting the prior error covariance, the fading factor is introduced to reduce the influence of the past data on the filtering effect, and thus improve the response speed and accuracy of the filter. The speed signal estimated by the UAV autopilot is filtered. The results show that the signal response of strong tracking Kalman filter is faster, the overshoot is smaller and the precision is higher.

Aiming at the temperature control of xylene distillation tower top, the control method under the cooperative action of feedforward compensation and cascade PID was studied. The dynamic mathematical model was obtained by identifying the field data, and the feasibility of this scheme was verified by Matlab. A temperature control system for xylene distillation tower top based on SIEMENS S7-300 was designed. The test results show that the dynamic performance of the system is effectively improved and easy to be implemented, which provides a reference scheme for the system with large delay and multiple interference.

In this paper, a nonsingular fast terminal sliding mode control algorithm is designed to solve the problems of large chattering and low accuracy in the trajectory tracking of two-link flexible manipulator. Firstly, the dynamic equation of the two-link flexible manipulator is given according to Lagrange equation and energy conservation law. Then, a nonsingular fast terminal sliding mode controller based on the tracking error state equation is designed, in which the hyperbolic tangent function is used instead of the sign function to weaken the influence of chattering. The stability of the closed-loop system is demonstrated using Lyapunov theory. The simulation results show that the proposed control strategy has the advantages of high tracking accuracy and less chattering.

In the detection of small defects in the glass of mobile phone cover plates, an improved SSD model is proposed to address the issue of missed detection in traditional single shot multi-layer detector (SSD) models. This model uses ResNet50 as the backbone network, while incorporating dilation convolution and attention mechanism SeNet to improve the accuracy of small defect detection. Experimental comparisons were conducted on the defect dataset, and the results showed that the improved SSD model had higher detection accuracy and lower miss rate compared to traditional SSD models, which could meet the accuracy requirements of defect detection.

With the wide application of machine vision technology in the field of industrial measurement, industrial cameras have become a very important hardware device, and the accuracy of camera calibration will directly affect the measurement accuracy. Therefore, by building a machine vision experimental platform, using BDB-7 dot calibration plate as the experimental object, the image acquisition of the translated and rotated calibration plate is carried out, and the MechVision software is used to perform camera calibration experiments on the dot calibration plate and verify the measurement accuracy. The experimental results show that the average error of the center coordinate of the calibration plate under the robot coordinate system is within 0.003mm, which can be applied to the workpiece loading and unloading work field and meet its accuracy requirements.

The liquid sealing machine is a part of the automatic filling and sealing equipment, which can replace the manual sealing operation. It is developed for liquid food and beverage plastic bag packaging. The equipment adopts digital design, analysis and calculation, and finally through experimental test, the sealing effect is good. The equipment cost is low and the work is reliable. It mainly serves the self-employed and rural producers.

With the evolution of smart distribution grids, industrial parks are progressively advancing towards intelligence. Addressing the challenges in smart industrial parks where the response capability of demand-side users is underutilized, leading to suboptimal energy use and economic inefficiencies, an energy optimization strategy for smart industrial parks that considers user satisfaction is proposed. Firstly, the load characteristics of users within the park are extracted, and the responsive resources in the park are assessed based on users' electricity consumption behavior, which allows an analysis of the potential for demand response from industrial park users, as well as an evaluation of their willingness to respond. Secondly, the distributed photovoltaic resources and user-side demand response resources are introduced to establish an industrial parks' energy optimization model with the optimization objective of minimizing the sum of demand response cost, grid electricity purchasing cost, carbon emission cost, and equipment operation and maintenance costs. In addition, the non-dominated sorting genetic algorithm is employed to solve this model. Lastly, the effectiveness of the proposed approach is verified through a case study of an industrial park in a city in North China.