Detection System for Feeding Quantity of Mobile Straw Granulator Based on Power of Screw Conveyor

In order to improve the large-scale production efficiency of corn and realize the intellectualization and automation of corn seed metering technology, it is necessary to combine modern computer technology with intelligent algorithm to establish a feasible model suitable for corn seed metering device. In this paper, watershed algorithm and EDEM (EM Solutions EDEM) algorithm are used to establish an efficient corn particle recognition model. Watershed algorithm is used for image matching and recognition, EDEM algorithm is used for simulation and processing of corn particles. Twenty corn seeds were selected, and the proportion and volume fraction of seeds with different shapes were calculated by using the model. The parameters needed for simulation were calibrated to verify the reliability of corn sowing accuracy. Through the credibility evaluation of RTM (Resin Transfer Moulding) model in maize seed metering model, it can be seen that the model has credibility, and the variance test result P = 0.662 > 0.10 shows that the credibility of the model meets the requirements. The results show that the model can be applied to the large-scale production of corn seed metering device, greatly improve the production efficiency, has high reliability, and is worthy of practical application and promotion. In this paper, the model construction and Simulation of corn planter based on EDEM are deeply studied and analysed, and the related processes are improved, so as to comprehensively improve the work efficiency of corn planter and improve the quality of planter.

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Simulation Analysis and Construction of Maize Seeder Model Based on Edem (Em Solutions Edem)

Jia

Ghayekhloo

2021

INMATEH

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Analysis of Crankshaft Mechanism of Agricultural Engine Under the Application of Compound Supercharging Technology

Xu¹,

Mathkour

2021

INMATEH

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With the development of engine supercharging technology and the application of in-cylinder direct injection technology, engines with high power and torque have become a trend. Crankshaft, as one of the most important and expensive parts in tractor engine, plays the role of transforming linear motion into circular rotation. The damage and destruction of crankshaft will lead to the damage of other parts of the engine, which makes the engine unable to work normally, and its stability affects the reliability of the whole engine to a great extent. The main failure form of tractor engine crankshaft is bending fatigue failure, so alternating bending stress occurs in crankshaft, which may cause fatigue failure of crankshaft. Crankshaft is one of the important components of tractor engine, and its stress is complex, which is the key and difficult point of engine design. In this paper, the crankshaft of tractor engine is analysed and studied based on compound supercharging technology, so that the dynamic characteristics of the engine are deeply understood, the action law of dynamic working load is mastered, the response analysis and evaluation of the system are carried out, and the optimization method of crankshaft mechanism of agricultural tractor engine is found out.

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Intelligent Fault Monitoring System of New Energy Tractor Engine for Big Data

Qi¹

2021

INMATEH

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Tractor engine has complex working environment and many parts. In the process of use, with the increase of service mileage and working hours, parts will wear to a certain extent, resulting in some engine failures. Using modern fault diagnosis technology to know the working performance of tractor engine in time, and to judge whether each component is in or will be in any fault state, is of great importance and practical significance for the research of fault diagnosis technology theory and diagnosis system of tractor engine. Taking the engine of new energy tractor as the research object, the principle and monitoring method of engine intelligent fault diagnosis are introduced. Then, based on big data and neural network technology, the engine intelligent fault monitoring system of new energy tractor for big data is designed. The fault diagnosis system of tractor engine based on artificial intelligence and big data technology realizes the functions of database and signal analysis, which improves the real-time and accuracy of the system.

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Detection System for Feeding Quantity of Mobile Straw Granulator Based on Power of Screw Conveyor

Cited by 3 publications

References 11 publications

Simulation Analysis and Construction of Maize Seeder Model Based on Edem (Em Solutions Edem)

Simulation Analysis and Construction of Maize Seeder Model Based on Edem (Em Solutions Edem)

Analysis of Crankshaft Mechanism of Agricultural Engine Under the Application of Compound Supercharging Technology

Intelligent Fault Monitoring System of New Energy Tractor Engine for Big Data

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