Speed Operation Research Articles

麦茬地不同型式玉米播种机作业性能及产量对比试验研究

Mechanical seeding quality is a key factor affecting the yield of maize in stubble fields. To choose for high-performance seeders and determine the appropriate operating speed, comparative sowing tests were conducted using spoon-wheel seeders, lightweight and heavyweight finger-clip seeders, and air-suction seeders in six districts of Shandong Province. Three working speeds, low speed, medium speed and high speed, were set up to determine the qualified rate of plant spacing, the consistency of plants height and the yields under different working speeds. The results showed that the qualified plant spacing rate, plants height consistency, and yield of the spoon-wheel and lightweight finger-clip seeders were significantly affected by the operating speed, decreasing as the speed increased. At high speeds, the qualified plant spacing rates were less than 80%, and plants height consistency were less than 85%. Heavyweight finger-clip and air-suction seeders' qualified plant spacing rates, plants height consistency, and yields were not significant affected by the operating speed, remaining stable across different speeds and significantly higher than those of the spoon-wheel and lightweight finger-clip seeders. The differences in qualified plant spacing rates and plants height consistency were more significant at higher speeds, along with obvious yields increase advantage. The yields increase ranged from 3.50% to 7.84% at low speeds, 4.32% to 9.31% at medium speeds, and 7.64% to 11.65% at high speeds. This study provides a reference for the selection of high-performance planters for maize in stubble fields and the determination of suitable operating speeds.

自走式多功能开沟施肥机的设计与实验

In orchard management, trenching operations are labor-intensive and have low efficiency, and mechanization is of crucial importance for the development of the fruit industry in China. In view of the many deficiencies of the existing chain-type and disc-type trenching machinery, this paper designs a self-propelled multifunctional orchard trenching machine. Its core component, the double-disc trenching disc, is an innovative design. Compared with the traditional single-disc trenching disc, it effectively reduces the trenching power consumption while ensuring the trenching depth and width, and significantly improves the operation efficiency. The trenching machine is composed of a frame, a gearbox, a double-disc trenching disc, a trenching knife, a soil retaining plate, etc. Field tests show that the operation speed reaches 1.2 kilometers per hour, the trenching depth is 31.2 cm, the width is 30.5 cm, and the stability coefficient of the trenching depth is 97.2%. Its power consumption is in a relatively good parameter group. When the cutter roller speed is 400 r/min, the forward speed is 0.8 km/s, and the trenching depth is 0.3 m, the average power consumption value of the trenching component is measured to be approximately 7.63 kW, with an 11.18% reduction in power consumption compared with the current trenching machines. And it meets the requirements of orchard agronomy and industry standards. In terms of improving productivity, its high-efficiency operation performance can greatly shorten the trenching operation time in the orchard, enabling fruit growers to arrange production more reasonably and increase fruit output. In reducing labor costs, mechanization replaces manpower, reduces manpower input, reduces labor cost expenditures, and at the same time avoids the instability of manpower operations. For the sustainability of orchard operations, the precise and stable trenching operation helps to optimize the utilization of land resources, ensure the quality of orchard agronomy, maintain the long-term production capacity of the orchard, promote the sustainable development of the orchard, and inject new impetus into the mechanization process of the fruit industry.

Analysis of Causes on High False Rejection Rate of Dark Tipping Paper Connector of ZJ118 Cigarette Machine

ZJ118 cigarette making and tipping machine combination is widely promoted in the industry because of its fast speed of production and stable operation. However, with the development of process requirements and the diversification of cigarette types, when producing cigarettes using dark tipping paper, the false rejection rate of tipping paper joint detection system is higher than the normal level. Given this situation, taking Black Middle cigarettes of a tobacco company as an example, the engineer spent 3 months to analyze its causes according to the characteristics of the detection system through on-site statistical investigation progressively, and finally concluded that the problem lay in the mismatch between the transmittance of tipping paper and the detection system. Dark tipping paper due to its low light transmittance, caused high false rejection rate. This article elaborates this in detail.

Availability of five hydraulic damper models for dynamics simulation and application of two types of high-speed electrical multiple units

ABSTRACT To attenuate oscillations of railway passenger vehicles, hydraulic dampers are widely employed in suspension structures, for which high-speed electrical multiple units (EMUs) with excellent dynamics performance are critical. This study employs a vehicle-track coupling model to predict damper loads with an operation speed of 400 km/h. Five models characterizing hydraulic damper dynamics, namely the simplification model, Maxwell model, the new damper model presented by Ren, and two new damper models presented in this paper, are employed to study the availability of the damper models in simulating vehicle dynamics. Field-tested loads of the damping forces for the dampers of two types of EMUs are used to fulfill the investigation. It indicates that the damping velocity and unloading velocity of the damper is critical to the damping load and vehicle dynamics. The simplification model and Maxwell model have some deficiencies in the vehicle dynamics calculation, especially as the unloading velocity of the damper is much low.

Optimal Rotor Design for Reducing Electromagnetic Vibration in Traction Motors Based on Numerical Analysis

Interior permanent magnet synchronous motor (IPMSM) for traction applications have attracted significant attention due to their advantages of high torque and power density as well as a wide operating range. However, these motors suffer from high electromagnetic vibration noise due to their complex structure and structural rigidity. The main sources of this electromagnetic vibration noise are cogging torque, torque ripple, and radial force. To predict electromagnetic vibration noise, finite element analysis (FEA) with flux density analysis of the air gap is essential. This approach allows for the calculation of radial force that is the source of the vibration and enables the prediction of vibration in advance. The data obtained from these analyses provide important guidance for reducing vibration and noise in the design of electric motors. In this paper, the cogging torque and vibration at rated and maximum operating speed are analyzed, and an optimal cogging torque and vibration reduction model, with rotor taper and two-step skew structure, is proposed using the response surface method (RSM) to minimize them. The validity of the proposed model is demonstrated through formulations and FEA based entirely on numerical analysis and results. This study is expected to contribute to the design of more efficient and quieter electric motors by providing a solution to the electromagnetic vibration noise problem generated by IPMSM for traction applications with complex structures.

MnO2 nanoparticles enhance the activity of the Zr-MOF matrix electrochemical sensor for efficiently identifying ultra-trace tetracycline residues in food.

Anovel nanobiosensor was constructed by in situ locating nanometer MnO2 particles with controllable size and morphology in a Zr-MOF substrate to serve as an electrochemical probe. The synergistic effect of the two components, Zr-MOFs with high specific surface area and compatibility as a carrier for MnO2, resulted in improved electrochemical activity and excellent electrochemical identification performance for the MnO2@Zr-MOF/GCE biosensor. Under optimized experimental conditions and using CV and DPV technology, the biosensor showed a wide linear detection range (2-200μM), a low detection limit (2.577 × 10-8M), a recovery range (106.26-115.01%), and maximum relative standard deviation (5.155) for tetracycline(TC) identification. The recognition mechanism of the sensor was investigated adopting Laviron adsorption theory. The applicability of the sensor was verified through practical measurements. Overall, the MnO2 @Zr-MOF/GCE sensor possesses the advantages of fast analysis speed, high sensitivity, high selectivity, and simple operation, making it suitable for detecting trace amounts of TC in food.

Effect of Speed Linear Decrease on Internal Flow Characteristics and Pressure Pulsations of Variable-Speed Pump Turbine in Turbine Mode

Pumped storage units often deviate from the optimal operating conditions in the process of regulating new energy fluctuations. To effectively improve the performance of the units, the variable speed of the units is one of the more feasible means at present. This paper focuses on the part-load condition of turbine operation, with an emphasis on the internal flow characteristics and pressure pulsation characteristics of the pump turbine during the linear reduction of the rated speed. It is found that the streamlines in the runner become turbulent in the process of speed reduction, forming a vortex at the inlet of the runner, and the vortex scale gradually increases with the speed reduction. The vortex rope in the draft tube undergoes three types of changes during the speed reduction: helical eccentric vortex rope, vanishing vortex rope, and columnar vortex rope. Before the speed change, the low-frequency components with high amplitude exist in each flow-passing part, but gradually disappear with the speed reduction. Except for the runner, the frequency affected by rotor–stator interference of each flow-passing part increases with the decrease of speed, and the growth is most obvious in the vaneless region. The findings of this research can serve as a valuable reference for the variable speed operation of pumped storage units.

Design Optimization of a Marine Propeller Shaft for Enhanced Fatigue Life: An Integrated Computational Approach

This study investigates the design and potential failure modes of a marine propeller shaft using computational and analytical methods. The aim is to assess the structural integrity of the existing design and propose modifications for improved reliability and service life. Analytical calculations based on classification society rules determined acceptable shaft diameter ranges, considering torsional shear stress limits for SAE 1030 steel. A Campbell diagram analysis identified potential resonance issues at propeller blade excitation frequencies, leading to a recommended operating speed reduction for a safety margin. Support spacing was determined using both the Ship Vibration Design Guide and an empirical method, with the former yielding more conservative results. Finite element analysis, focusing on the keyway area, revealed stress concentrations approaching the material’s ultimate strength. A mesh sensitivity analysis ensured accurate stress predictions. A round-ended rectangular key geometry modification showed a significant stress reduction. Fatigue life analysis using the Goodman equation, incorporating various factors, predicted infinite life under different loading conditions, but varying safety factors highlighted the impact of these conditions. The FEA revealed that the original keyway design led to stress concentrations exceeding allowable limits, correlating with potential shaft failure. The proposed round-ended rectangular key geometry significantly reduced stress, mitigating the risk of fatigue crack initiation. This research contributes to the development of more reliable marine propulsion systems by demonstrating the efficacy of integrating analytical methods, finite element simulations, and fatigue life predictions in the design process.

Enhanced perpendicular magnetic anisotropy energy and Curie temperature in the CrOCl monolayer: strain effects

Abstract Magnetic monolayers offer a wide variety of applications in enhancing the functionalities of storage devices including higher thermal stability, lower power consumption, and higher operation speed, owing to their intrinsic long-range spin ordering. Herein, we study the biaxial ([110]) strain range of ± 5% influence on the formation energetics, electronic structure, and magnetic behaviour of the CrOCl monolayer (ML) based on the ab-initio calculations including spin–orbit coupling (SOC) effects. It is predicted that the system displays an insulating character having an energy band gap (E g ) of 2.05 eV with a ferromagnetic (FM) ground state in its unstrained state. The estimated partial spin magnetic moment on the Cr ion is +2.7 μ B /f.u. (per formula unit) with S = 1.5 and lies in a + 3 oxidation state with an electronic distribution of t 2 g 3 ↑ t 2 g 0 ↓ e g 0 ↑ e g 0 ↓ . Along with this, [001] (c-axis) is found to be the easy magnetic axis, which results in a magnetic anisotropy energy (MAE) of 0.2 meV having an MAE constant of 0.25 mJ m−2 and the computed Curie temperature (T c ) using Ising model is 157 K. Furthermore, the system shows the robustness of the FM insulating behavior against considered strains. However, a significant shift in the conduction band edge (CBE) position to lower energies is evident for tensile strains, which substantially reduces the E g up to 13%. The decrease in E g value is evidence of higher absorption in the visible range which makes it the best option for optoelectronics and photocatalysis. Simultaneously, our results revealed that strain enhances the MAE and T c up to 190% and 43%, respectively. Hence, optimized E g , MAE, and T c within a considerable strain range, make the CrOCl ML a potential candidate for its utilization in magnetic memory devices.

Development and Evaluation of a Helical Ribbon-Type Mixer for Mushroom Substrate

Manual substrate mixing for mushroom production such as rice straws, sawdust, and banana leaves is laborious and time-consuming. Substrates need to be thoroughly mixed to produce mushrooms of good quality. This study was done to design, fabricate, and evaluate the performance of a helical ribbon-type mixer. The performance of the ribbon-type mixer was evaluated in terms of the mixing capacity and mixing efficiency. Loading weight (5kg, 10kg, and 15kg) and operating speed (11-15rpm, 16-20rpm, and 21-25rpm) of the machine were used as the performance parameters. Analysis of Variance (ANOVA) for Factorial Experiment in Completely Randomized Design (CRD) was used to analyze the results while comparison among treatment means was tested at 5% level of significance using Duncan's Multiple Range Test (DMRT). Results revealed that the highest machine capacity of 226.67 kg/hr was attained at a loading weight of 15kg and an operating speed of 21-25rpm. Maximum mixing efficiency (95.27%) was achieved with the combination of 15 kg loading weight and an operating speed of 11-15 rpm. The initial investment in fabricating the substrate mixer for mushroom production was Php 21, 713. Operating the substrate mixer for mushroom production had a projected annual cost of Php 3,655.475. Break – even weight was 91,795.24 kg of substrates per year at a custom rate of Php 0.35 per kilogram.

Optimized design and magneto-thermal coupling simulation analysis of automotive permanent magnet synchronous motor

Abstract This paper presents an optimized design for automotive permanent magnet synchronous motors (PMSM) focusing on expanding their operational speed range and improving efficiency. The issues of high losses and low efficiency in standard built-in fractional-slot PMSMs, which impact the stable operation of vehicle motors, are identified and addressed., Three innovative rotor magnetic circuit structures are proposed utilizing electromagnetic theory and finite element analysis. These designs are simulated and analyzed to reduce overall motor losses to 59% of the original levels and to ensure thermal characteristics meet the demands of wide-speed automotive motors. The study establishes a three-dimensional transient temperature field simulation model to predict temperature rise and distribution across motor components. The optimized rotor structures enhance performance and serve as a reference for future thermal design in PMSMs.

The effect of icky shuffle training on 30 meter running speed in intensive development high school futsal players in Surabaya

Abstract Speed ​​is one of the fitness elements that might help in playing futsal. The ability to perform a task quickly or travel a long distance in the shortest time is called speed. This study aims to determine the potential impact of Icky shuffle training on 30 meter operating speed among futsal participants at Taruna Pembangunan Intensive High School Surabaya, as well as the efficacy of certain types of Icky shuffle training on increasing 30 meter running speed. running speed. This research uses quantitative research methods with a one-group pretest-posttest design. The following data results show these findings: comparison of pretest and posttest scores obtained from the 30 meter running test. The two-sided sig p value is 0.023, which is less than (<0.05), as can be observed. As a result, the 30 meter running speed of the Surabaya Taruna Pembangunan Intensive High School futsal players was affected by the unpleasant shuffle training. Keywords: Icky shuffle, sprint, futsal.

Interconnected expanded graphite/stearic acid networks for self‐lubricating PA6 composites with excellent heat dissipation performance

AbstractThe improvement in social production efficiency demands increasingly faster mechanical operation speeds. However, under high‐speed friction conditions, the frictional heat generated by nylon 6 (PA6) components is difficult to dissipate efficiently, leading to severe wear and subsequently threatening the safe operation of the equipment. In this work, interconnected expanded graphite/stearic acid (EG/SA) networks in PA6 composites were constructed to achieve fast frictional heat dissipation and self‐lubricating properties by a simple hot‐pressing method. The synergistic lubrication of EG and SA results in PA6 composites with a low coefficient of friction (COF) of 0.12, a 74.5% reduction compared to pure PA6. The low COF reduces the generation of frictional heat, while the conduction and absorption of frictional heat by the EG/SA network accelerates the dissipation of frictional heat, ultimately lowering the contact temperature from 106.9°C to 40.6°C. The specific wear rate of the PA6 composite is as low as 1.7 × 10−5 mm3 N−1 m−1, which is 90.1% lower than that of pure PA6. This study provides a new solution for the rapid dissipation of frictional heat in polymer composites under harsh operating conditions and broadens the application range of wear‐resistant polymer composites.Highlights Expanded graphite (EG) prevents stearic acid from leaking through adsorption. The interconnected EG network transfers frictional heat to stearic acid. The phase transition of stearic acid can absorb heat and promote lubrication. The low COF and high heat dissipation make PA6 composites highly wear‐resistant.

Application of Technology Artificial Intelligence in Claim Settlement at PT. Asuransi Allianz Life Syariah Medan Branch

This research aims to analyse the effectiveness of implementing artificial intelligence (AI) technology in accelerating the settlement process of Sharia insurance claims at PT Asuransi Allianz Life Syariah Medan Branch. The main focus of this research is to measure the impact of AI technology on customer satisfaction and the company's performance in handling Sharia insurance claims. Using qualitative research methods, data were collected through in-depth interviews with company representatives and analysis of the company's internal documents. The research results indicate that AI technology has significantly contributed to improving operational efficiency, speed, and accuracy in claim resolution. The implementation of AI enables more effective process automation, faster decision-making, and more accurate identification of potential fraud. Furthermore, the use of AI also supports the enhancement of compliance with Sharia principles, ensuring that all processes and decisions are in line with Sharia law. This research provides valuable insights for insurance companies looking to implement AI technology in their operations, particularly within the scope of Sharia insurance.

Research on Non-Intrusive Load Disaggregation Technology Based on VMD–Nyströmformer–BiTCN

Non-intrusive load disaggregation is a technique that monitors the total electrical load of an entire building or household. It uses a single power metering device to measure the total load. Then, it employs algorithms to break it down into the individual usage of different electrical devices. To address issues in load disaggregation models such as long training times, feature interference caused by the activation of other loads, and accuracy deficiencies caused by behavioral interference from users’ electricity usage habits, this paper proposes a VMD–Nyströmformer–BiTCN network architecture. The variational mode decomposition (VMD) filters the raw power data, reducing errors caused by noise and enhancing the accuracy of decomposing the load. A deep learning network utilizes a modified attention model, Nyströmformer, to reduce feature entanglement and accuracy degradation caused by habitual behavior interference during load disaggregation, while ensuring precise accuracy and improving network operational speed. The training network uses a bidirectional temporal convolutional network (BiTCN) and incorporates a residual network to expand the receptive field, allowing it to receive longer load sequence data and acquire more effective load information, thereby improving the disaggregation effectiveness for target appliances.

Semantic segmentation for weed detection in corn.

Reliable, fast, and accurate weed detection in farmland is crucial for precision weed management but remains challenging due to the diverse weed species present across different fields. While deep learning models for direct weed detection have been developed in previous studies, creating a training dataset that encompasses all possible weed species, ecotypes, and growth stages is practically unfeasible. This study proposes a novel approach to detect weeds by integrating semantic segmentation with image processing. The primary aim is to simplify the weed detection process by segmenting crop pixels and identifying all vegetation outside the crop mask as weeds. The proposed method employs a semantic segmentation model to generate a mask of corn (Zea mays L.) crops, identifying all green plant pixels outside the mask as weeds. This indirect segmentation approach reduces model complexity by avoiding the need for direct detection of diverse weed species. To enhance real-time performance, the semantic segmentation model was optimized through knowledge distillation, resulting in a faster, lighter-weight inference. Experimental results demonstrated that the DeepLabV3+ model, after applying knowledge distillation, achieved an average accuracy (aAcc) exceeding 99.5% and a mean intersection over union (mIoU) across all categories above 95.5%. Furthermore, the model's operating speed surpassed 34 frames per second (FPS). This study introduces a novel method that accurately segments crop pixels to form a mask, identifying vegetation outside this mask as weeds. By focusing on crop segmentation, the method avoids the complexity associated with diverse weed species, varying densities, and different growth stages. This approach offers a practical and efficient solution to facilitate the training of effective computer vision models for precision weed detection and control. © 2024 Society of Chemical Industry.

Enhanced YOLOv8 Ship Detection Empower Unmanned Surface Vehicles for Advanced Maritime Surveillance

The evolution of maritime surveillance is significantly marked by the incorporation of Artificial Intelligence and machine learning into Unmanned Surface Vehicles (USVs). This paper presents an AI approach for detecting and tracking unmanned surface vehicles, specifically leveraging an enhanced version of YOLOv8, fine-tuned for maritime surveillance needs. Deployed on the NVIDIA Jetson TX2 platform, the system features an innovative architecture and perception module optimized for real-time operations and energy efficiency. Demonstrating superior detection accuracy with a mean Average Precision (mAP) of 0.99 and achieving an operational speed of 17.99 FPS, all while maintaining energy consumption at just 5.61 joules. The remarkable balance between accuracy, processing speed, and energy efficiency underscores the potential of this system to significantly advance maritime safety, security, and environmental monitoring.

Transient flow field characteristics of scraper pump based on viscosity wall strategy

This study presents an innovative scraper pump design. The design utilizes the synchronized movement of the upper and lower scrapers of the rotor to adjust the cavity volumes on either side, facilitating efficient fluid transfer. Unlike previous studies, scraper pumps face the challenge of dynamic contact between the scraper and the rotor due to their unique structure. A viscous wall strategy was employed to address hydrodynamic challenges at the point of contact, significantly improving performance prediction accuracy. The experimental data verified the accuracy of the simulation model, and the mass flow rate deviation between the simulation results and the experimental results was maintained within 10% when the viscosity at the contact point was set to 40 times the original medium viscosity. In addition, the study examined the effect of different operating speeds and load pressures on the pump performance. The results indicated that the outlet flow rate decreased by 22% when the pressure was increased from 2 MPa to 10 MPa and increased by 88.24% when the speed was increased from 900 r/min to 2200 r/min. These quantitative analyses provided valuable insights into optimizing scraper pump design and offered clear guidance for improving hydraulic performance and operational efficiency.

Research on Advanced Imaging System Based on PZT Material and X-ray Tube

Along with the rapid development of social economy and the continuous improvement of people's living standards, medical and health care has taken on an important strategic position. As an important analysis and detection means, biosensing technology plays a key role in the field of healthcare. The piezoelectric biosensor is an innovative biosensor utilizing piezoelectric material for bioanalysis, which has excellent characteristics of good stability, fast detection speed, high accuracy and simple operation, and has important application value in the fields of biomedicine, health monitoring and disease prevention and control. Herein, we summarize the research progress of piezoelectric biosensors at home and abroad in recent years and introduce the working principle of piezoelectric biosensors based on the piezoelectric effect of quartz crystal microbalance as well as commonly used piezoelectric materials, including inorganic piezoelectric materials, organic piezoelectric materials, piezoelectric composites, and bio-piezoelectric materials. Furthermore, the applications of piezoelectric biosensors in human health monitoring and disease prevention and control, such as the monitoring of physiological signs such as heart rate and pulse, the detection of biomarkers and epidemic viruses such as neo-coronary pneumonia, are also introduced. Finally, the current problems faced by piezoelectric biosensors are summarized and their future development is prospected. We will also talk about the basic principle, type, detection technology, application and development trend of X-ray tubes are reviewed. X-ray tube is a kind of electronic device that can produce X-rays, which is widely used in medical, industrial, security and other fields. The basic principle is to obtain the internal structure and composition information of the sample by detecting the intensity and energy distribution after the X-ray passes through the sample by using the penetration and fluorescence effects of the X-ray.

A resonance-avoiding modal balancing method for multimodal balancing of high-speed flexible rotors

Abstract Conventional balancing methods for high-speed flexible rotors typically necessitate costly and potentially hazardous balancing tests conducted near their critical speeds. This paper first demonstrates the feasibility of achieving multi-mode balancing using measurements taken below the first critical speed, based on traditional modal balancing methods and rotor modal parameters. However, while theoretically viable, this approach is highly susceptible to measurement noise, complicating its practical implementation. To address this issue, we propose an innovative resonance-avoiding modal balancing (RAMB) method specifically designed for multi-mode balancing. In RAMB, balancing is performed mode by mode in a forward manner, effectively integrating the correction weights of lower modes into the balancing equation. This strategy eliminates the need to operate the rotor at unbalanced critical speeds, enhancing the effectiveness of multi-mode balancing while ensuring measurement safety. The effectiveness of both the conventional method and the RAMB approach is validated through numerical simulations and experimental tests as well. The results show that RAMB significantly enhances the vibration suppression over the entire operating speed range while avoiding resonance measurements and exhibits comparable robustness to noise, confirming the validity and superiority of the proposed balancing method