Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters

This research proposes an artificial neural network(ANN)-based repair and maintenance(R&M)cost estimation model for agricultural machinery.The proposed ANN model can achieve high estimation accuracy with small data requirement.In the study,the proposed ANN model is implemented to estimate the R&M costs using a sample of locally-made rice combine harvesters.The model inputs are geographical regions,harvest area,and curve fitting coefficients related to historical cost data;and the ANN output is the estimated R&M cost.Multilayer feed-forward is adopted as the processing algorithm and Levenberg-Marquardt backpropagation learning as the training algorithm.The R&M costs are estimated using the ANN-based model,and results are compared with those of conventional mathematical estimation model.The results reveal that the percentage error between the conventional and ANN-based estimation models is below 1%,indicating the proposed ANN model’s high predictive accuracy.The proposed ANN-based model is useful for setting the service rates of agricultural machinery,given the significance of R&M cost in profitability.The novelty of this research lies in the use of curve-fitting coefficients in the ANN-based estimation model to improve estimation accuracy.Besides,the proposed ANN model could be further developed into web-based applications using a programming language to enable ease of use and greater user accessibility.Moreover,with minor modifications,the ANN estimation model is also applicable to other geographical areas and tractors or combine harvesters of different countries of origin.

Assessment of BRRI Whole Feed Combine Harvester (Model BRRI WCH2021) for Mechanized Rice Harvesting in Bangladesh

Agricultural mechanization plays a pivotal role in the transition from subsistence to commercial agriculture, with a particular focus on labour-intensive activities like harvesting. This study assesses the operational characteristics of the BRRI Whole Feed Combine Harvester (Model BRRI WCH2021) at the field level. Developed under the SFMRA project, the harvester’s technical performance and loss assessment were conducted during the Boro 2022 and Aman 2022 seasons in farmer fields in Bangladesh’s Rangpur region. The field efficiency of the harvester was determined to be 62.5% and 57.9% in the Boro and Aman seasons, respectively. Fuel consumption rates were recorded at 2.77 l/ha and 2.31 l/ha for the Boro and Aman seasons. The total harvesting losses, encompassing cutter bar, shatter, cylinder, and separation loss, averaged 0.56% and 0.48% in the Boro and Aman seasons, respectively. Mechanized harvesting with the BRRI Whole Feed Combine Harvester significantly reduced paddy losses by 5.81% compared to manual methods. The field evaluation results indicate the combine harvester’s satisfactory performance, highlighting its potential to alleviate labour demands during peak harvesting. The development of the BRRI WCH offers a sustainable solution for rice harvesting mechanization among progressive farmers. It paves the way for the broader adoption of advanced agricultural technology in Bangladesh.

Development of uncut crop edge detection system based on laser rangefinder for combine harvesters

The objective of this research was to develop an uncut crop edge detection system for a combine harvester.A laser rangefinder(LF)was selected as a primary sensor,combined with a pan-tilt unit(PTU)and an inertial measurement unit(IMU).Three-dimensional field information can be obtained when the PTU rotates the laser rangefinder in the vertical plane.A field profile was modeled by analyzing range data.Otsu’s method was used to detect the crop edge position on each scanning profile,and the least squares method was applied to fit the uncut crop edge.Fundamental performance of the system was first evaluated under laboratory conditions.Then,validation experiments were conducted under both static and dynamic conditions in a wheat field during harvesting season.To verify the error of the detection system,the real position of the edge was measured by GPS for accuracy evaluation.The results showed an average lateral error of±12 cm,with a Root-Mean-Square Error(RMSE)of 3.01 cm for the static test,and an average lateral error of±25 cm,with an RMSE of 10.15 cm for the dynamic test.The proposed laser rangefinder-based uncut crop edge detection system exhibited a satisfactory performance for edge detection under different conditions in the field,and can provide reliable information for further study.

Real-time grain breakage sensing for rice combine harvesters using machine vision technology

Breakage rate is one of the most important indicators to evaluate the harvesting performance of a combine harvester.It is affected by operating parameters of a combine such as feeding rate,the peripheral speed of the threshing cylinder and concave clearance,and shows complex non-linear law.Real-time acquisition of the breakage rate is an effective way to find the correlation of them.In addition,real-time monitoring of the breakage rate can help the driver optimize and adjust the operating parameters of a combine harvester to avoid the breakage rate exceeding the standard.In this study,a real-time monitoring method for the grain breakage rate of the rice combine harvester based on machine vision was proposed.The structure of the sampling device was designed to obtain rice kernel images of high quality in the harvesting process.According to the working characteristics of the combine,the illumination and installation of the light source were optimized,and the lateral lighting system was constructed.A two-step method of“color training-verification”was applied to identify the whole and broken kernels.In the first step,the local threshold algorithm was used to get the edge of kernel particles in a few training images with binary transformation,extract the color spectrum of each particle in color-space HSL and output the recognition model file.The second step was to verify the recognition accuracy and the breakage rate monitoring accuracy through grabbing and processing images in the laboratory.The experiments of about 2300 particles showed that the recognition accuracy of 96%was attained,and the monitoring values of breakage rate and the true artificial monitoring values had good trend consistency.The monitoring device of grain breakage rate based on machine vision can provide technical supports for the intellectualization of combine harvester.

Selection of proper combine harvesters to field conditions by an effective field capacity prediction model

Farmers have to finish their harvesting with high efficiency,because of time and cost.However,farmers are lacking knowledge and information required for selecting suitable combine harvesters and giving the conditions of their rice fields,because both information factors(combine harvester and field condition)impact the field capacity.The field capacity model was generated from combine harvesters with the Thai Hom Mali rice variety(KDML-105).Therefore,this study aimed to determine the prediction model for effective field capacity to combine harvesters when harvesting the Thai Hom Mali rice variety(KDML-105).The methods began by collecting data of 15 combine harvesters,such as field,crop,and machine conditions and operating times;to generate the prediction model for the KDML-105 variety.The prediction model was then validated using 12 combine harvesters that were collected similarly to the model creation.The results showed a root mean square error(RMSE)of 0.24 m^(2)/s for the model.The prediction model can be applied for farmers to select the proper combine harvesters and give their field conditions.

Modeling of working environment and coverage path planning method of combine harvesters

This paper mainly studied the working environment modeling and coverage path planning of combine harvesters.The boundaries of the farmland to be harvested were extracted through the farmland satellite imagery and canny algorithm.The polygon approximation method was used to fit the extracted boundaries as polygons.The edge offset of the farmland and obstacles was realized based on the principle of straight skeleton.According to the structure data of the split points which were obtained through the improved scan line algorithm,the coverage path planning of the combine harvester was realized.Moreover,the circular arc transition algorithm was used to optimize the harvesting paths to achieve the smooth turning of the combine harvester at the edge of farmland and when encountering obstacles.The simulation results show that the proposed the proposed polygon approximation method can accurately depict the boundaries of the farmland to be harvested,and reduce the amount of data to be stored.Additionally,the designed path planning method can realize the coverage path planning of the combine harvester in irregular and internal obstacle farmland.

Evaluation of operator visibility in three different cabins type Far-East combine harvesters

The purpose of this study was to develop and evaluate a visibility evaluation system for the cabin type Far-East combine harvester.The human field of view has been classified into five levels(perceptive,effective,stable gaze,induced,and auxiliary)depending on the rotation of the human head and eye.The divider,reaper lever,gearshift,dashboard,and conveying component were considered as major viewpoints of the cabin type Far-East combine harvester.The visibility of the cabin type Far-East combine harvester was evaluated quantitatively using viewpoints and human field of view levels.The visibility evaluation system for the cabin type Far-East combine harvester consisted of a laser pointer,stepping motors to control the directions of the view,gyro sensors to measure horizontal and vertical angles,and I/O interface to acquire the signals.The visibility evaluation tests were conducted at different postures(‘sitting straight’,‘sitting with a 15°tilt’,‘standing straight’,and‘standing with a 15°tilt’)for three cabin type Far-East combine harvesters.The LSD(least significant difference)multiple comparison tests showed that the visibilities of viewpoints differed significantly as the operator's posture changed.The results showed that the posture while standing with a 15°tilt provided the best visibility.The average visibility scores at sitting postures were 22.3(straight)and 24.4(15°tilt),and the scores at standing postures were 18.7(straight)and 29.5(15°tilt).Also,the average visibility scores were observed in order from highest to lowest as reaper lever(44.6),divider(28.7),dashboard(23.1),conveying part(12.2),and gearshift lever(10.1).Most viewpoints of the cabin type Far-East combine harvester were out of the stable gaze field of the view level.Modifications of the cabin type Far-East combine harvester design will be required to enhance the visibility during harvesting operation and to improve safety and convenience of farmers.

Simulation and analysis of the pneumatic recovery for side-cutting loss of combine harvesters with CFD-DEM coupling approach

A novel pneumatic recovery method was proposed to curb the problem of high losses caused by side-cutting in a rapeseed combine harvester header.The influence of recovery method and material status changes on the recovery effect was studied via the CFD-DEM(computational fluid dynamic-discrete element method)coupling simulation.The effect of airflow action on the recovery effect was compared and analyzed,and the composite pneumatic recovery method was determined.In addition,the influence of material status changes and material feeding rate on the recovery effect was explored,and the critical condition of material blockage in the recovery device was configured.As such,the relationship model between air velocity and recovery rate was constructed and the air distribution ratio of the flow field in the device under this condition was optimized,had verified the rationality of this pneumatic recovery method was verified by a series of field tests.The average rapeseed recovery rate of 92.95%was achieved with the application of the recovery device,and the total loss rate of the header reduced by 52.26%,which is of great significance in reducing the total loss rate of the combine harvesters and improving the operation performance of machinery.The research results can provide a reference for the design of the header structure of a rape combine harvester.

Fault prediction of combine harvesters based on stacked denoising autoencoders

Accurate fault prediction is essential to ensure the safety and reliability of combine harvester operation.In this study,a combine harvester fault prediction method based on a combination of stacked denoising autoencoders(SDAE)and multi-classification support vector machines(SVM)is proposed to predict combine harvester faults by extracting operational features of key combine components.In general,SDAE contains autoencoders and uses a deep network architecture to learn complex non-linear input-output relationships in a hierarchical manner.Selected features are fed into the SDAE network,deep-level features of the input parameters are extracted by SDAE,and an SVM classifier is then added to its top layer to achieve combine harvester fault prediction.The experimental results show that the method can achieve accurate and efficient combine harvester fault prediction.In particular,the experiments used Gaussian noise with a distribution center of 0.05 to corrupt the test data samples obtained by random sampling of the whole population,and the results showed that the prediction accuracy of the method was 95.31%,which has better robustness and generalization ability compared to SVM(77.03%),BP(74.61%),and SAE(90.86%).

Effects of Rice Combine Harvester Application to Harvest Chinese Milk Vetch Seeds

During the test, the seed yield, Iabor efficiency, harvesting costs and eco-nomic benefits were compared and analyzed between mechanical harvesting tech-noIogy and traditional artificial harvesting technoIogy of Chinese miIk vetch seeds to studied the mechanical harvesting technoIogy and appIication effects. The resuIts showed that mechanical harvesting technoIogy increased the yield of 92.7 kg/hm2, reducing the seeds Ioss. It improved the Iabor efficiency and reduced the harvesting cost. For exampIe, a rice combine harvester was the equal of 18-20 person in the harvest quantity in one day, which directIy reduced the Iabor cost of 2 175-3 000 yuan/hm2 and increased the economic income of 3 307-4 099 yuan/hm2. So it wiI pIay an important roIe in soIving the shortage of Chinese miIk vetch seeds and ac-ceIerating the deveIopment of Chinese miIk vetch green manure crop in south China rice region.

Optimization of Conventional Combine Harvester to Reduce Combine Losses for Basmati Rice (<i>Oryza Sativa</i>)

A study was conducted at PAU Regional Research Station, Gurdaspur (Punjab) to investigate the design and operational parameters of threshing mechanism of conventional combine harvester for basmati crop. This study was aimed to investigate the suitable changes required in the self-propelled conventional combine harvester for harvesting the basmati crop with minimum grain losses. Field evaluation of experiment was carried out to assess the influence of independent design variable i.e., arrangement of spikes (AS) and independent operational parameters such as concave clearance (CC) and cylinder speed (CS). The study was aimed to enumerate various combining losses viz., extent of visible and invisible grain damage and threshing efficiency at different AS, CC and CS levels. The first year data recorded during 2017 were processed for the optimization during 2018. The results of the present study revealed that during 2017, maximum visible and invisible losses was 5.49% ± 0.33% and 28.07% ± 3.21%, respectively whereas after modification, these losses remained only 4.00% ± 0.80% and 24.07% ± 2.86%, respectively. The threshing efficiency remained above 99.31% ± 0.47%, for both years. Thus, optimization of combine harvester was able to save the visible grain damage by 60% to 83% and invisible grain damage by 6% to 16%, respectively during 2018 than the year 2017.

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.

Influence of two-stage harvesting on the properties of cold-pressed rapeseed(Brassica napus L.)oils

Rapeseed(Brassica napus L.)harvesting method is critical since it significantly determines the seed yield,oil quality,and industrial efficiency.This study investigated the influences of harvesting methods on the quality of cold-pressed rapeseed oil of two varieties.Oil color,peroxide value(POV),tocopherol content,fatty acid composition,and polarity of total polyphenols(PTP)contents of two rapeseed varieties in Huanggang and Xiangyang were compared through artificially simulated combined harvesting and two-stage harvesting.Results showed significant differences in the quality of rapeseed oil between the two harvesting methods.The red value(R-value),POV,total tocopherol contents,linoleic and linolenic acid content,and PTP content of the pressed rapeseed oil prepared by the combined harvesting method were about 27.6,5.7,15.8,2.0,0.5,and 28.6%lower than those of the oil produced from the two-stage harvesting method,respectively.Xiangyang and Huayouza62 performed better in the two regions and two varieties,respectively.To sum up,the rapeseed oil obtained 41–44 days after final flowering of combined harvesting,35 days after final flowering,and six days of post-ripening of the two-stage harvesting had the best quality.

Parameter matching and experiment of the combined cyclone separation and cylinder sieve cleaning system for rape combine harvester

Existing rape combine harvester with a cyclone separation cleaning device has the challenge that the loss rate and the cleaning rate increase and decrease simultaneously.A cleaning process route was proposed,which involves the cyclone separation cleaning device removing light and tiny impurities,and the cylinder sieve device removing coarse and long impurities such as pod shells and short stems.A novel cleaning system combining the cyclone separation cleaning device and cylinder sieve cleaning devices was designed.The ranges of the structure and operation parameters for each component were analyzed based on kinematics and dynamic analysis.A four-factor five-level quadratic orthogonal test was carried out,in which the loss rate and cleaning rate were taken as the evaluation indexes.The velocity at the suction port,the rotation speed of the cylinder sieve,the screw pitch of the spiral blade and the diameter of the sieve hole were taken as the influencing factors.The orthogonal test results showed that the cleaning system performed best at a rotation speed of the winnower is 600 r/min,an airflow velocity at the suction port is 18.25 m/s,a rotation speed of the cylinder sieve is 87 r/min,a screw pitch of the spiral blade is 440 mm and a diameter of the sieve hole is 4.48 mm.At this time,the loss rate of the cleaning system is 3.22%,and the cleaning rate is 95.67%.Compared to the conventional cyclone separation cleaning device,the loss rate is reduced by 2.17%and the cleaning rate is increased by 1.05%.This study can provide a reference for the optimal cleaning system design for rape combine harvesters.

Mechanical Harvesting Effects on Seed Yield Loss,Quality Traits and Profitability of Winter Oilseed Rape (Brassica napus L.)

China is one of the most important rapeseed producing countries in the world. Effective mechanical harvesting time for decreasing harvesting loss of winter oilseed rape has been becoming a critical factor. An elite cultivar Zhongshuang 11 （Brassica napus L.） was employed in two rounds of field experiments from 2009 to 2011. Seeds were sown with machine, three combine harvesting times namely combine harvesting A, B, and C （CHA, CHB, and CHC） were designed and manual harvesting （MH） as control was performed at maturity. The harvesting treatments were determined according to color of pod and seed in the field. Seed yield loss and quality in different treatments were evaluated. Results showed that both seed yields and harvesting losses in 2009-2010 were higher than that in 2010-2011, whereas seed oil contents in 2010-2011 were higher than that in 2009-2010. The highest yield appeared in CHB, which was significantly higher than that in MH. Furthermore, harvesting loss in CHB were 50% that in MH. Seed oil content and chlorophyll exhibited no obvious difference between CHB and MH. Economic profit analysis demonstrated that mechanical sowing/combine harvesting （MS/CH） showed an input/output ratio of 1：1.6, and it was 1：1.2 in mechanical sowing/manual harvesting （MS/MH）. Labor-cost accounted for more than 70% of the total cost in MS/MH, which led to low profitability to a great extent. Our results suggested that CHB was the optimum harvesting time for winter oilseed rape along the Yangtze River.

Can harvest outsourcing services reduce field harvest losses of rice in China?

The purpose of this study is to quantify the rice harvest losses in China and to evaluate the impacts of machinery and harvest outsourcing services on these losses,given the background of high-speed mechanization and outsourcing services.Data were collected from a national survey conducted in 2016 by the research team in conjunction with the Research Center for the Rural Economy of the Ministry of Agriculture and Rural Affairs of China.A non-parametric method was used to test whether combine harvesting and outsourcing services could significantly reduce harvest losses.Next,quantile regression was used to estimate the real effects of machinery and outsourcing services on harvest losses.The analysis yielded four main study outcomes.First,the harvest loss rate of rice in China was 3.65%.Second,mechanical reaping and winnowing caused greater losses than manual methods,while the opposite was true of field transportation.Third,combine harvesting increased the losses.Fourth,the effects of an outsourcing service on losses differed among the different harvesting methods.Outsourcing services increased losses in segmented harvesting but they reduced losses in combine harvesting.

Experiment and parameter optimization of an automatic row following system for the traction beet combine harvester

To improve the automation level and operation quality of China's beet harvester and reduce the loss due to damaged and missed excavation,this study used a self-developed sugar beet combine harvester and field simulation experiment platform,based on the single-factor bench test of the automatic row following system in the early stage,taking hydraulic flow A,spring preload B,and forward speed C which have significant influence on performance indices as test factors,and taking the missed excavation rate,breakage rate and reaction time as performance indices,the orthogonal experimental study on the parameter optimization of the three-factor and three-level automatic row following system with the first-order interaction of various factors was carried out.The results of the orthogonal experiments were analyzed using range analysis and variance analysis.The results showed that there were differences in the influence degree,factor priority order and first-order interaction,and the optimal parameter combination on each performance index.A weighted comprehensive scoring method was used to optimize and analyze each index.The optimal parameter combination of the overall operating performance of the automatic row following system was A 2B 2C 1,that is,the hydraulic flow was 25 L/min,the forward speed was 0.8 m/s,and the spring preload was 198 N.Under this combination,the response time was 0.496 s,the missed excavation rate was 2.35%,the breakage rate was 3.65%,and the operation quality was relatively good,which can meet the harvest requirements.The comprehensive optimization results were verified by field experiments with different ridge shapes and different planting patterns.The results showed that the mean values of the missed excavation rate of different planting patterns of conventional straight ridges and extremely large"S"ridges were 2.23%and 2.69%,respectively,and the maximum values were 2.39%and 2.98%,respectively;the average damage rates were 3.38%and 4.14%,and the maximum values were 3.58%and 4.48%,which meet the industry standards of sugar beet harvester operation quality.The overall adaptability of the automatic row following system is good.This study can provide a reference for research on automatic row following harvesting systems of sugar beets and other subsoil crop harvesters.

Effects of working parameters on the performance of cyclone separator for rapeseed combine harvester based on CFD

Existing development for cyclone separation cleaning components of the rapeseed combine harvester,which employs the suspending airflow to separate the rapeseeds from the materials other than grain(MOG),has the challenge to figure out the optimal working parameters,highlighting a need for exploration of the invisible airflow based on Computational Fluid Dynamics(CFD).The airflow status was mainly affected by the air velocities of the inlet,and the outlet for the MOG.The single factor and response surface experiments were carried out.It could be found that the inlet and MOG outlet velocities affected the air velocities through the change in the air quantity.Furthermore,the mathematical model of the relationship between the air velocities inside the cyclone and the working parameters was built,and the optimal combination of working parameters was obtained by multi-objective optimization.The inlet and outlet velocities of the optimal combination were 4.25 m/s and 29.87 m/s,respectively.Under this condition,the cleaning ratio and loss ratio of the cleaning device was 94.62%and 5.39%,respectively,as validated by the field experiment.The findings provide references for the improvement of cleaning systems for rapeseed combine harvesters.

Research and optimization of the hand-over lifting mechanism of a sweet potato combine harvester based on EDEM

In order to meet the challenge of high loss rate and high tuber injury rate during the operation of the 4UZL-1 sweet potato combine harvester,the sweet potato tuber hand-over lifting mechanism was designed based on a comprehensive analysis of the entire structure of the harvester.Taking the average normal force on conveying sweet potato tubers as evaluation indexes,the EDEM simulation experiment was carried out considering the factors of the angle of the excavating and conveying mechanism,the conveying angle of the scraper chain,the speed of the excavating and conveying mechanism,and the speed of the scraper chain conveying.The experimental findings indicated that the optimal operational performance of the hand-over lifting mechanism was achieved at a speed of 1.15 m/s for the excavating and conveying mechanism,an angle of 24°for the excavating and conveying mechanism,a conveying speed of 0.66 m/s for the scraper chain,and a conveying angle of 60°for the scraper chain.Field experiments were conducted based on the EDEM simulation experiment,using the loss rate and the injury rate of conveying sweet potato tubers as evaluation indexes.The results showed that the hand-over lifting mechanism demonstrated optimal operational effectiveness with an excavating and conveying mechanism angle of 20°,a scraper chain angle of 68°,an excavating and conveying mechanism speed of 1.2 m/s,and a scraper chain speed of 0.66 m/s,while the machine running speed was maintained at 1 m/s.At the moment,the hand-over lifting structure exhibited a loss rate of 1.12%and a tuber injury rate of 0.94%.The conclusions obtained serve as a valuable reference for future research and optimization of sweet potato combines.

Design and initial testing of a maize cob collection system

Maize cobs are valuable plant residues that can be used for many different purposes,including as a renewable energy source.Despite their value,maize cobs are still underutilized,mainly because people are not aware of their potential and harvesting techniques for their collection are still being developed.Therefore,this research focused on finding the most suitable energy-and time-efficient method for mechanical collection of maize cobs.Upgrading the combine harvester with an additional hopper proved to be the most promising solution,as it allows harvesting and storage of maize grain and maize cobs in one pass,while the harvesting time remains almost the same and the maize cobs are of good quality,as they do not fall on the field.A prototype with enlarged openings in the straw walkers,an additional grab container for maize cobs,a transport auger,a transport cleaning fan with built-in knives,a transport tube and some other assemblies was fabricated and used in practice.The first test results are very encouraging(94.4%-96.0%purity of maize cobs)and the system has been patented as a promising solution,especially in times when the environmental sustainability of the planet and energy independence are becoming increasingly important.