Combine Harvester Research Articles

Assembly Quality Inspection of Combine Harvester Based on Whale Algorithm Optimization LSSVM

In order to detect the assembly quality of the combine harvester accurately and effectively, a method for the assembly quality inspection of the combine harvester based on the improved whale algorithm (IWOA) to optimize the least square support vector machine is proposed. Aiming at the characteristics of whale optimization algorithm’s weak search ability and easy maturity, this paper introduces the cosine control factor and the sine time-varying adaptive weight to improve it and uses the benchmark function to verify the general adaptability of the algorithm. Combined with the local mean decomposition (LMD), the assembly quality inspection model of the combine harvester was established and applied to the Dongfanghong 4LZ-9A2 combine harvester for experimental verification. The experimental results show that the IWOA proposed in this paper has better optimization ability and adaptability. The average accuracy of the IWOA model proposed in this paper reaches 90.5%, which is 4% higher than that of the WOA model, and the standard deviation of the average accuracy is reduced by 0.15%, which indicates that the IWOA model has better stability.

Combine Harvester: Small Machine Solves Big Rice Harvesting Problem of Bangladesh

Bangladesh, a country with 87% of rural households that depend on agriculture and rice dominated diets (70%), engages the country’s food security. Therefore, there is strong advocacy for a mechanized paddy harvesting system for food security in South Asia, mainly Bangladesh. Some harvesting machinery is available; however, the precise roles of a combine harvester during this process are little. This study attempts to understand the consequences of combining harvesters for paddy harvesting and compare them with hand harvesting. For comparison of field performance of combine harvester with traditional harvesting, the experiment was conducted at Gazipur District, Bangladesh, in 2016. Results showed that the labor required for harvesting unit area 283, 15 and 9.87 man-h∙ha−1 for T1 (Sickle + Head carry + Beating + Kula), T2 (Reaper + Trolley carry + Close drum thresher + winnower), T3 (Combine harvester) system, respectively. Likewise, the harvesting costs were 1.84 (T2) and 2.5 (T1) times higher than the combine harvester (T3). Also, the postharvest loss can be saved 1.84%, to use combine harvester over manual harvesting of paddy. The above result revealed that the semi-mechanized and mechanized harvesting system is a time, labor and cost-saving system; however, the manual reaping system is concerned with more postharvest losses (3.09%). This study highlights the importance of combine harvester; however, further research is required in other places with large and mini-combine harvesters under diverse cropping areas and to test a combine harvester’s detailed potentiality.

Design and Experimental Study of a Spiral Auxiliary Feeding Device for Lodged Corn on a Combine Harvester

HighlightsThis study designed an auxiliary feeding device for lodged corn on a combine harvester.The mechanical characteristics of lodged corn stalks were studied as the basis of the design.The working parameters were optimized in an orthogonal experiment.Abstract. Lodging causes kernel and ear loss in mechanical harvesting of corn and threatens grain security. To address this issue, the mechanical bending properties and lifting forces of lodged corn stalks were explored in this study. The ears of lodged corn could be lifted to the normal harvesting height by applying an upward force to the stalks. Based on this conclusion, an auxiliary feeding device for lodged corn in a combine harvester was designed. An orthogonal optimization experiment was conducted to explore the effects of working parameters on the device performance. The results demonstrated that the sequence of the factors affecting kernel loss with the auxiliary feeding device was: harvesting direction, forward speed of the harvester, and rotating speed of the spiral stalk lifter. The optimal combination of harvester forward speed and rotating speed of the spiral stalk lifter was 0.5 m s-1 and 300 rpm, and the ratio of the peripheral speed to the speed of motion was 9.42. The optimal harvesting direction was opposite to the lodging direction of the stalks. This study provides a theoretical basis and design reference for low-loss harvesting of lodged corn. Keywords: Auxiliary feeding, Combine harvester, Corn, Harvest loss, Lodging, Orthogonal experiment.

An introspection into impact of combine harvester: A tale of sustainable livelihood security

Adoption of combine harvester (CH) for wheat cultivation is crucial for enhancing the competitiveness of wheat industry. A study has been conducted in Lower Shivalik Hills of India during 2016–2020 to elucidate the adoption level and its impact in livelihood security. Results revealed that due to variation in significant determinants of adoption, the extent of adoption was low (36.67%). A comparative analysis of socio-agro- economic impact of combine and manual harvesting method revealed thatCH required only 2.5 hours for harvesting 1 ha land whereas, manual harvesting required 7–8 hours. Value of B:C and Rate of Return for using CH was 1:1.55 and 155 per cent, respectively. To measure economic efficiency SUR model was adopted and found the variety HD-3059 had 14 quintal/ha more grain yield than other varieties.After a financial scaleout of CH based crop varieties to get clarity on its adoptability across the country for sustained livelihood security, appropriate strategies for promoting CH have been Penned down.

Optimization of a Low Loss Strategy for Combine Harvesters Based on Bayesian Network

In this study, the Bayesian network was used to optimize the harvesting strategy of the combine harvester for low loss rate. The range analysis and variance analysis of the orthogonal field experiments showed that the feed rate, concave clearance and threshing drum speed were main factors affecting the loss rate. Taken the main factors and loss rate as Bayesian network nodes, the optimal network structure was obtained through scoring search, in which the four scoring functions were respectively combined with hill-climbing method. An optimized harvesting strategy for low loss rate was inferred through the constructed network, and the strategy was implemented in field experiment. The results showed that the average loss rate was reduced by 0.8% compared to that normal harvesting strategy.

Numerical Simulation and Experiment of Cleaning Performance of Combine Harvester under the Action of Conical Fan

Numerical Simulation and Experiment of Cleaning Performance of Combine Harvester under the Action of Conical Fan

A New Model to Predict the Slippage Coefficient of Tracked Vehicles During Steering

Tracked vehicles during steering are always subjected to track slippage relative to the ground. Studies show that an excessive slippage coefficient reduces the steering ability of tracked vehicles and increases the risk of soil shear failure. Accordingly, fast and accurate tests of the slippage coefficient of tracked vehicles under different ground conditions can be effectively referenced to select track parameters and reach optimal operation. Aiming to resolve shortcomings of the conventional testing method in determining the slippage coefficient of tracked vehicles, a novel method is proposed in the present study. Then the trajectory of an arbitrary point on the tracked vehicle during steering was analyzed. Moreover, the time of vehicles steering around and the speed of track sprocket were measured, and the slippage coefficient of tracked vehicles steering on the specific ground condition was determined. Meanwhile, the slippage coefficient of the tracked combined harvester steering under different ground conditions was explored using the conventional method. The obtained results were compared quantitatively, and the accuracy of the established model was verified. The performed analyses demonstrate that the proposed method has a simple structure and can be effectively applied to various complicated working conditions. This method is expected to lay a theoretical basis to establish an online testing system for the slippage coefficient of tracked vehicles during steering.

Design and Performance Test of Rotary Grate Concave Threshing and Separating Unit of Head-Feeding Combine Harvester

HighlightsThis research was aimed at assessing the performance of a head-feeding combine harvester.The rotary grate concave threshing and separating unit were effective for improving and preventing the threshing cylinder from being jammed and improving working efficiency.More broken grains were obtained at a faster speed of concave grate.The speed of feeding chain was significant on the performance parameters that were evaluated.Abstract. It is easy for the threshing cylinder to get blocked in the head-feeding combine harvester with the fixed grate concave threshing and separating unit to affect the working efficiency when high yield rice is harvested. The rotary grate concave threshing and separating unit was designed to solve the above problem. The rotary grate concave surface revolved in the same direction along the cylinder arc of threshing drum. A test-bench of the rotary grate concave threshing and separating unit was developed. The rotational speeds of cylinder (RC), the speed of the concave grate (SG), and the speed of feeding chain (SF) were regarded as experimental factors, and the grain loss rate, broken grain rate, and impurities rate were selected as indices. Central composite design combined with response surface methodology and multi-objective optimization method were employed to conduct experiments and explore the interaction effects of factors on indices. The optimal operating parameters were nonlinearly optimized and determined to be RC of 547.6 rpm, SG of 0.93 m·s-1, and SF of 1.06 m·s-1. Under these conditions, the predicted values of the grain loss rate, broken grain rate, and impurities rate were 1.95%, 0.29%, and 0.58%, respectively. Verification experiments indicated that the observed values were in agreement with the predicted values. Results suggested that the rotary grate concave threshing and separating unit developed in this study were effective for preventing the threshing drum from being blocked, and there was a good potential for performance improvement of head-feeding combine harvester. Keywords: Central composite design, Cylinder speed, Feeding chain speed, Head-feeding combine harvester, Response surface methodology, Rotary grate concave, Threshing and separating unit.

Research on On-Line Monitoring System of Hydraulic Actuator of Combine Harvester

In view of the complicated hydraulic system, the many driving parts and the great load variation in the combine harvester, and on-line monitoring methods of hydraulic actuating parts such as cutting tables, conveyors and threshing drums were studied. By analyzing the working principle of the hydraulic system of the combine harvester, a mathematical model of the hydraulic system of the combine harvester was established; a simulation model for the fault diagnosis of the hydraulic system of the combine harvester was established based on AMESim. The load signal was introduced to simulate the feeding amount, and the simulation test was carried out. According to the simulation analysis results, the best position of each monitoring point was determined. The on-line monitoring system of the hydraulic actuators of the combine harvester was designed by using LabView, which can collect and display the working parameters of the main working parts of a combine harvester in real time, and alarm the user to faulty working conditions. The field experiment results show that the function and precision of the monitoring system completely meet the requirements of field operation condition monitoring of combine harvesters. The accuracy rate of the fault alarm is 96.5%, and the automatic diagnosis time of the fault alarm is less than 1 min and 18 s, which greatly improves the operation efficiency of the combine harvester.

Comparative Indicators of Grain Transportation When Unloading Combine Harvesters at the the Field Edge

Base don theresults of comparative experience in production conditions, the indicators of grain transportation by trucks were determined when unloading combine harvesters at the field edge.

Combine harvester assembly fault diagnosis based on optimized multi-scale reverse discrete entropy

An optimized multi-scale reverse discrete entropy (RDE, OMRDE) method for feature extraction is proposed to address the lack of effective feature extraction and detection methods for combine harvester assembly fault inspection. This method was used to extract the vibration signal features from the combine. A fault diagnostic method is designed to verify the efficiency of the associated methods. First, a comparative study of the RDE, multi-scale inverse DE (MRDE), and OMRDE methods was performed using simulated signals to verify the effectiveness of OMRDE. Second, the FSTPSO–VMD method was used to decompose the vibration signal of the combine assembly fault, and the OMRDE, MRDE, and fuzzy entropy were compared and analyzed. The actual feature extraction effect of the three entropy functions reached the highest classification accuracy (88.5%) after using OMRDE to extract features. Finally, a fusion feature set is constructed to further improve the classification accuracy, and the LSSVM classifier is optimized using FSTPSO. The analytical results show that the FSTPSO–LSSVM classifier constructed in this study adopts the fused feature with an accuracy of 93%, which is better than that of other common methods, and verifies the validity of the fault diagnostic model. Therefore, the performance of the OMRDE method proposed in this study is better than that of the MRDE. The proposed fault diagnostic model can accurately classify the fault detection of a combine harvester assembly.

The reasons for the loss of wheat from the harvest grown in the fields of Russia

A comparative analysis has been performed of statistical data on wheat losses in the fields from 2001 to 2019, using Russia as an example, which enables us to estimate the wheat losses from the crop grown accurately when harvested using combined harvesters. The analysis of the wheat losses from the grown crop in the fields was carried out in three directions based on the total sown areas, the average wheat yield, and the total harvested areas of the winter and spring wheat; according to the official data of the “Expert and Analytical Center for Agribusiness” and “Statistical Collections of Agriculture in Russia.” Analysis of wheat losses in the Russian Federation fields has been compared with the first and second directions. This analysis helps to identify the causes that affect the loss of wheat during the harvesting process by combined harvesters.

Bogie Axle Drive Solution for Combine Harvesters

A NEW AXLE DRIVE SYSTEM FOR AGRICULTURAL MACHINES ENSURES EQUAL DISTRIBUTION OF WEIGHT AND TRACTIVE EFFORT ON ALL FOUR TYRES

A Grain Yield Sensor for Yield Mapping with Local Rice Combine Harvester

Rice grain yield was estimated from a locally made Thai combine harvester using a specially developed sensing and monitoring system. The yield monitoring and sensing system, mounted on the rice combine harvester, collected and logged grain mass flow rate and moisture content, as well as pertinent information related to field, position and navigation. The developed system comprised a yield meter, GNSS receiver and a computer installed with customized software, which, when assembled on a local rice combine, mapped real-time rice yield along with grain moisture content. The performance of the developed system was evaluated at three neighboring (identically managed) rice fields. ArcGIS® software was used to create grain yield map with geographical information of the fields. The average grain yield values recorded were 3.63, 3.84 and 3.60 t ha−1, and grain moisture contents (w.b.) were 22.42%, 23.50% and 24.71% from the three fields, respectively. Overall average grain yield was 3.84 t ha−1 (CV = 63.68%) with 578.10 and 7761.58 kg ha−1 as the minimum and maximum values, respectively. The coefficients of variation in grain yield of the three fields were 57.44%, 63.68% and 60.41%, respectively. The system performance was evaluated at four different cutter bar heights (0.18, 0.25, 0.35 and 0.40 m) during the test. As expected, the tallest cutter bar height (0.40 m) offered the least error of 12.50% in yield estimation. The results confirmed that the developed grain yield sensor could be successfully used with the local rice combine harvester; hence, offers and ‘up-gradation’ potential in Thai agricultural mechanization.

Impact of Combine Harvester Technological Operations on Global Warming Potential

The agricultural machinery is making a considerable negative contribution to the acceleration of global warming. In this study, we analyzed the impact of combine harvesters (CHs) on the global warming potential (GWP) by evaluating the telematics data from 67 CHs operating in Lithuania and Latvia between 2016 and 2020. This study examined the use of their technological operations and the associated impacts on ambient air and performed field tests using the same CH model to determine the composition of exhaust gases and the impact of different technological operations on GWP. The data confirmed the release of significant GWP during indirect operation, and it was estimated that considerable lengths of time were spent in idle (~20%) and transport (~13%) modes. During these operations, over 13% of the total GWP (~27.4 t year−1 per CH), affected by emissions, was released. It was calculated that a GWP reduction exceeding 1 t year−1 per machine can be achieved by optimizing the idling and transport operations. The dual telematics/field test data approach facilitates a comprehensive assessment of both the impact of CH exhaust gases on GWP and the methods for reducing the negative impact on the environment.

Proper Technical Maintenance of Combine Harvester Rolling Bearings for Smooth and Continuous Performance for Grain Crop Agrotechnical Requirements

The threshing mechanism is the main component of the combine harvester on which the grain separation and cleaning qualitative work indicators depend. It is important to ensure that all threshing mechanism components, including the threshing drum bearings and all other bearings of the combine, are working properly and reliably. There are many places in the combine where it is not possible to measure bearing vibrations directly without dismounting them, since there is no suitable spot to mount a sensor. The paper investigates the threshing drum rolling bearing condition of combines, which are difficult to access, by using a vibration diagnostics technique utilizing a newly manufactured steel bracket. The vibration measurements and analysis were conducted by the Adash A4900 Vibrio M analyzer (Adash spol. s.r.o., Ostrava, Czech Republic). The vibration source measurement was based on the fast Fourier transform (FFT) spectrum analysis. Analysis of the experimental results showed that average squared velocity values (in the frequency interval of 10–1000 Hz), together with other measured vibration parameters, can be used for the combine threshing drum‘s bearing condition evaluation.

Optimization of Clamping and Conveying Device for Sunflower Oil Combine Harvester Header

To solve the problem of grain spatter during harvest by combine harvester headers, a new clamping and conveying device of the sunflower oil harvester header was designed. We investigated plant states during the conveying process. To optimize the parameters of the sunflower oil harvester header, a test bench was built to simulate sunflower plant harvest. The influence of the clamping gap, clamping speed ratio, and clamping length on conveying success rate was explored by a single-factor experiment. Based on this experiment, the secondary regression orthogonal rotation test was carried out. The optimal structural parameter combination was obtained as follows: the clamping gap was 20 mm, the clamping speed ratio was 1.3, and the clamping length was 345 mm. Under this combination parameter condition, the corresponding conveying success rate reached up to 85.16% and the minimum value of conveying grain loss rate was 1.57%. To verify the effect of parameter optimization, a verification test and a comparison test were performed. Results showed that the actual conveying success rate was 83.50% and the actual grain loss rate was 1.49%, which were close to the optimized parameter value. The comparison test showed that the conveying success rate of the flexible clamping and conveying device was 83.50% with a grain loss rate of 1.49%, and that of the rigid clamping and conveying device was 55% with a grain loss rate of 5.17%. This study provides a theoretical basis for the design of a low-loss sunflower oil combine harvester header.

Combine harvester improvement for selection and collection of high-quality soybeans

To obtain biologically valuable and high-quality soybeans it is necessary to improve the design of the two-phase threshing combine harvester which will have a gentle mode for threshing the most mature soybeans in the first threshing drum, make their high-quality cleaning directly in the combine harvester and collect them in a separate hopper. The first seed fraction of biologically valuable and high-quality soybeans is obtained by separating the threshed heap in the first threshing drum. It’s cleaned and collected in a separate hopper. The return is processed in the second threshing drum, and the second fraction of seeds is cleaned and collected in the second hopper of the combine. The straw that comes off the straw walker and enters the auger is divided into two parts, and when it leaves the auger on both sides, it is crushed and thrown out of the sides of the combine. At the same time, during the combine harvesting of soybeans, the chaff coming of the sieve boot and being the high-protein feed consisting of 90% of the bean flaps is collected in the chaff collector. By collecting the most valuable components of the soybean crop, i.e beans and chaff, and embedding the crushed plant stems on the small depth by disking or cultivation, the task of creating conditions for the growth and development of plants in the crop rotation with full mechanized technology of soybean harvesting is solved.

Combine Harvester Cooling Water Temperature Prediction Based on CDAE-LSTM Hybrid Model

Cooling water temperature of the combine harvester during operations can reflect the changes of its power consumption and even overloads caused by extreme workload. There is an existing problem when extracting water temperature information from harvesters: data redundancy and the loss of time series feature. To solve such problem, a Convolutional denoising autoencoder and Long-Short Term Memory Artificial Neural Network (CDAE-LSTM) hybrid model based on parameter migration is proposed to predict temperature trends. Firstly, the historical data of the combine harvester are taken into account to perform correlation analysis to verify the input rationality of the proposed model. Secondly, pre-training has been performed to determine the model’s initial migration parameters, along with the adoption of CDAE to denoise and reconstruct the input data. Finally, after the migration, the CNN-LSTM hybrid model was trained with a real dataset and was able to predict the cooling water temperature. The accuracy of the model has been verified by field test data gathered in June 2019. Results show that the root mean squared error (RMSE) of the model is 0.0817, and the mean absolute error (MAE) is 0.0989. Compared with the performance of LSTM on the prediction data, the RMSE improvement rate is 2.272 %, and the MAE improvement rate is 20.113 %. It is proven that the adoption of CDAE stabilizes the model, and the CDAE-LSTM hybrid model shows higher accuracy and lower uncertainty for time series prediction.

Harvest Losses of Wheat Crop

Harvest losses (10-30%) in wheat represent one of the major factors affecting grain yield. these losses may be during harvesting and/or threshing operations. Although combined harvester is gaining popularity, however, In most parts of Pakistan, the wheat crop is still manually harvested and then mechanically threshed. Therefore, the current study was conducted on Latif farm of Sindh Agriculture University, Tando Jam to evaluate the harvest losses during the manual harvesting and threshing operations in wheat. Three popular wheat varieties (SKD-1, TJ-83 & KIRAN-95) were selected for this study. The wheat crop was manually harvested and then harvest losses were estimated by harvest losses were estimated on the basis of collection and analysis of leftover / spilled earth heads in the freshly harvested field. Threshing losses were estimated by calculating the proportions of broken, unbroken grains and unthreshed ear heads. The study focused on harvesting and threshing operations and their impacts on crop production. The study depicted that harvesting operation was performed manually and threshing by tractor threshing charges were 05 and 10 percent of the crop production respectively while harvesting losses were high at the time of 16 percent due to over-drying and unskilled labors used in the field. Technological advancements in agriculture machinery led to reducing the harvesting and threshing losses and therefore, the study suggested that necessary steps of mechanized operation may be taken for minimizing the losses.