scholarly journals MULTI-SENSOR SIGNAL ACQUISITION AND DATA PROCESSING ANALYSIS OF COMBINE HARVESTER

2021 ◽  
pp. 335-344
Author(s):  
Li Wang ◽  
Shuo Li ◽  
Dianji Lv ◽  
Ghay Ekhlo
Keyword(s):  
Data Processing ◽  
Monitoring System ◽  
Intelligent Control ◽  
Large Scale ◽  
Electrical Equipment ◽  
Signal Acquisition ◽  
Test Bed ◽  
Environment Control ◽  
Combine Harvester ◽  
Combine Harvesters

In recent years, combine harvesters are increasingly developing in the direction of large-scale, technology, automation and intelligence, and more and more electrical equipment is installed on combine harvesters. The electrical system of combine harvester is prone to failure when it works in high temperature, high humidity, dusty and strong vibration environment. Parameters to be adjusted in the header system of combine harvester include header height, drum height, drum front and back position, cutting frequency and drum speed. Aiming at the inconvenience of debugging and testing the measurement and control system of combine harvester in the field operation environment, an intelligent control test bed of combine harvester was designed. The test bed can simulate various intelligent control algorithms of combine harvester in laboratory environment, control the forward speed of combine harvester according to data processing results, classify faults, and send and print stored data through serial communication. Experiments show that the system works stably and reliably, and can realize the integration of the monitoring system of combine harvester operation process. It can save costs and improve efficiency in the application of the monitoring system of combine harvester.

scholarly journals Welding station monitoring system using internet of thing (IOT)

2020 ◽  
Vol 18 (3) ◽  
pp. 1319
Author(s):  
Ernie Mazuin Mohd Yusof ◽  
Mohd Ismail Yusof ◽  
Rafidah Ali ◽  
Izzat Hilmi Harjimi ◽  
Qasidah Kamarul Bahrin
Keyword(s):  
Internet Of Things ◽  
Data Processing ◽  
Monitoring System ◽  
Large Scale ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
The Internet ◽  
Gas Industry ◽  
Welding Machine ◽  
Internet Of Thing

<span>In oil and gas industry, productivity is very important as the industry involves high cost and can be considered as a large-scale industry. Therefore, time and budget should be kept minimal to avoid loss to the oil and gas company. An example of lack of productivity in the industry is there are many complaints in the oil and gas industry that welders do not perform their job on time. Therefore, this project discussed about a system that can be used to monitor these welding stations. This system is important because it can help supervisors track the welding works from afar or anywhere using internet of things (IoT). To achieve that, a system must consist of hardware and software that are capable of connecting to the internet and monitor the welding works. In this project, the hardware chosen were Arduino Uno for data processing, ESP8266 to connect the microcontroller to the internet, voltage sensor to detect the voltage of the welding machine and a website to show the data taken. Other than that, this system was able to warn the welder of overvoltage of the welding machine. Thus, the system solved the problem of welders not performing their job on time. Supervisors were also able to monitor the job of welders to ensure maximum productivity. Based on the testing done on the system, the prototype was able to work as intended. The welding station monitoring system was able to detect welding usage, measure voltage values of welding and send the data to IoT for monitoring.</span>

scholarly journals Effects of fan volute structure on airflow characteristics in rice combine harvesters

2020 ◽  
Vol 18 (4) ◽  
pp. e0209
Author(s):  
Zhenwei Liang ◽  
Depeng Li ◽  
Jun Li ◽  
Kunpeng Tian
Keyword(s):  
High Yield ◽  
Test Bed ◽  
Airflow Velocity ◽  
Perforated Plates ◽  
Cleaning Performance ◽  
Rice Area ◽  
Combine Harvester ◽  
Combine Harvesters ◽  
Large Improvement ◽  
The Ideal

Aim of study: Selecting a proper fan for the rice combine harvesters to get a good cleaning performance when harvesting high yield rice. Area of study: Jiangsu Province, China.Material and methods: Three potential multi-duct fans were designed, and the computational fluid dynamics and hot wire anemometer technology were utilized to learn the airflow and pressure variation inside the fan with perforated plates at the outlet ducts as cleaning loads. Then, the fan with the best performance was selected and a multi-duct cleaning test-bed was developed. The variation of the corresponding airflow velocity in the cleaning system was analyzed and the ideal airflow velocity in different section of the sieve was clarified. Finally, a field experiment was carried out.Main results: For a rice combine harvester with a feed rate of 7 kg/s (material other than grain + grain), the requested airflow rates inside the cleaning shoe was about 3.0 m3/s. The ideal airflow velocity in different section of the cleaning shoe was 8-9 m/s at upper duct, 4-6 m/s at the middle section, and 3-4 m/s at the tail section; large improvement in cleaning performance was achieved with the designed fan.Research highlights: The airflow velocity decreased as the cleaning loads at the duct increased. The fan with the averaged airflow velocity ≥7 m/s at the upper duct under different cleaning loads, and the airflow velocity at the lowest duct ≥ 9 m/s, is favorable for forming a blowing airflow in the tail sieve and is good for grain stratification.

Scientific-methodological approach to the substantiation of the rational seasonal scenario of using combine harvesters by large-scale agricultural producers

2020 ◽  
pp. 205-217
Author(s):  
V. Skibchyk ◽  
V. Dnes ◽  
R. Kudrynetskyi ◽  
O. Krypuch
Keyword(s):  
Large Scale ◽  
System Analysis ◽  
Methodological Approach ◽  
Production Unit ◽  
Agricultural Producers ◽  
New Approach ◽  
Rational Use ◽  
Road Map ◽  
Analysis And Synthesis ◽  
Combine Harvesters

Аnnotation Purpose. To increase the efficiency of technological processes of grain harvesting by large-scale agricultural producers due to the rational use of combine harvesters available on the farm. Methods. In the course of the research the methods of system analysis and synthesis, induction and deduction, system-factor and system-event approaches, graphic method were used. Results. Characteristic events that occur during the harvesting of grain crops, both within a single production unit and the entire agricultural producer are identified. A method for predicting time intervals of use and downtime of combine harvesters of production units has been developed. The roadmap of substantiation the rational seasonal scenario of the use of grain harvesters of large-scale agricultural producers is developed, which allows estimating the efficiency of each of the scenarios of multivariate placement of grain harvesters on fields taking into account influence of natural production and agrometeorological factors on the efficiency of technological cultures. Conclusions 1. Known scientific and methodological approaches to optimization of machine used in agriculture do not take into account the risks of losses of crops due to late harvesting, as well as seasonal natural and agrometeorological conditions of each production unit of the farmer, which requires a new approach to the rational use of rational seasonal combines of large agricultural producers. 2. The developed new approach to the substantiation of the rational seasonal scenario of the use of combined harvesters of large-scale agricultural producers allows taking into account the costs of harvesting of grain and the cost of the lost crop because of the lateness of harvesting at optimum variants of attraction of additional free combine harvesters. provides more profit. 3. The practical application of the developed road map will allow large-scale agricultural producers to use combine harvesters more efficiently and reduce harvesting costs. Keywords: combine harvesters, use, production divisions, risk, seasonal scenario, large-scale agricultural producers.

Experimental Study on Wear Monitoring of Marine Diesel Engine’s Piston Ring by Magnetoresistive Sensor

2012 ◽  
Vol 424-425 ◽  
pp. 132-136
Author(s):  
Guo Jin Chen ◽  
Zhang Ming Peng ◽  
Jian Guo Yang ◽  
Qiao Ying Huang
Keyword(s):  
Diesel Engine ◽  
Large Scale ◽  
Piston Ring ◽  
Test Bed ◽  
Operating Modes ◽  
Magnetoresistive Sensor ◽  
Marine Diesel ◽  
Wear Monitoring ◽  
Oil Tanker ◽  
Test Result

On the diesel engine’s test bed, this paper has studied the parameters regarding the diesel engine’s rotational speed, the piston ring’s width and wearing capacity and so on, and their relation with the output signal of the magnetoresistive sensor under the reverse drawing of the diesel engine. The research discovered that the piston ring’s wear and the magnetoresistive sensor’s output have the corresponding relationship. And on the oil tanker with the 6RTA52U diesel engine, the influence of the diesel engine’s operating parameters and the load situations to the magnetoresistive sensor’s output is surveyed under four kinds of different operating modes. The test result and the research conclusion provide the technical foundation for the online Wear monitoring of the large-scale marine diesel engine’s piston ring.

scholarly journals Reliability of a Visual Recognition System for Detection of Johnsongrass(Sorghum halepense) in Corn

2011 ◽  
Vol 25 (4) ◽  
pp. 645-651 ◽  
Author(s):  
Dionisio Andújar ◽  
Ángela Ribeiro ◽  
Cesar Fernández-Quintanilla ◽  
José Dorado
Keyword(s):  
Large Scale ◽  
Visual Recognition ◽  
Visual Detection ◽  
Cropping Systems ◽  
Experimental Period ◽  
Recognition System ◽  
Infested Area ◽  
Net Returns ◽  
Cropping Season ◽  
Combine Harvester

The feasibility of visual detection of weeds for map-based patch spraying systems needs to be assessed for use in large-scale cropping systems. The main objective of this research was to evaluate the reliability and profitability of using maps of Johnsongrass patches constructed at harvest to predict spatial distribution of weeds during the next cropping season. Johnsongrass patches visually were assessed from the cabin of a combine harvester in three corn fields and were compared with maps obtained in the subsequent year prior to postemergence herbicide application. There was a good correlation (71% on average) between the position of Johnsongrass patches on the two maps (fall vs. spring). The highest correlation (82%) was obtained with relatively large infestations, whereas the lowest (58%) was obtained when the infested area was smaller. Although the relative positions of the patches remained almost unchanged from 1 yr to the next, the infested area increased in all fields during the 4-yr experimental period. According to our estimates, using a strategy based on spraying full rates of herbicides to patches recorded in the map generated in the previous fall resulted in higher net returns than spraying the whole field, either at full or half rate. This site-specific strategy resulted in an average 65% reduction in the volume of herbicide applied to control this weed.

Advanced monitoring techniques for a large‐scale data‐processing network

2008 ◽  
Vol 25 (5) ◽  
pp. 287-300 ◽  
Author(s):  
B. Martin ◽  
A. Al‐Shabibi ◽  
S.M. Batraneanu ◽  
Ciobotaru ◽  
G.L. Darlea ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Scale ◽  
Monitoring Techniques ◽  
Large Scale Data ◽  
Large Scale Data Processing ◽  
Processing Network ◽  
Scale Data
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