Sieve Losses Research Articles

Techno-economic and energetic assessment of an innovative energy-saving separation process for electronic-grade acetone purification

With the impact of covid-19 and geopolitical instability, the price of energy and medical-related chemicals are increased. Acetone is used as the main material for the synthesis of important disinfectant isopropanol, which the price is influenced by covid-19 impact. The research on acetone purification, especially on the acetone refining section in the cumene hydroperoxide process is of great importance, which is high in energy cost but the most popular method for acetone production. This paper provided novel energy-saving acetone purification processes with heat integration, heat recovery, and molecular sieve adsorption, and made comprehensive research of different schemes applications with optimization. A modified TAC calculation model for adsorption units is first proposed in this paper, which includes the calculation of adsorption unit cost, molecular sieve loss, and molecular sieve regeneration cost. CO2 emission and thermodynamic efficiency of all the processes are compared. A semi-quantitative analysis is used to compare the relative industrial versatility and process controllability. The results show that the combination of adsorption and heat integration achieves a decrease of 27.75% in energy consumption, 15.30% in TAC, 7.09% in CO2 emission, and a 22.62% relative increase in thermodynamic efficiency.

Improving Cleaning Performance of Rice Combine Harvesters by DEM–CFD Coupling Technology

The cleaning device is an important part of combine harvesters, as its superior or inferior performance directly affects the performance of the combine harvester greatly. With an increasing rice yield, the current single-duct cleaning performance declines greatly, and causes a large grain sieve loss level and a direct grain loss for the farms. To optimize the existing single-duct cleaning device to meet the large feeding rate requirement, firstly, the terminal velocity of rice grain and MOG (material other than grain) for different varieties was experimentally measured by the custom-made device. The effects of the moisture content of rice grains and the length of short straws on terminal velocity were studied in detail. Then, the gas–solid two-phase flow theory was comprehensively applied by utilizing the discrete element method (DEM) and computational fluid dynamics (CFD) to study the working mechanism of the existing single-duct cleaning unit, and the cleaning performance was evaluated from the view of the motion law of the threshing output within the cleaning shoe. At last, a multi-duct cleaning device was put forward, and a field experiment was performed to assess the performance of the newly developed cleaning device. The results showed that the grain sieve losses ratio and grain impurity ratio improved dramatically, proving that structure optimization of the cleaning device was feasible.

Analyzing Rice Grain Collision Behavior and Monitoring Mathematical Model Development for Grain Loss Sensors

Grain loss in the harvesting process of combine harvesters not only causes economic losses to farmers but also affects the soil environment because of the lost grain covering the soil, influencing crop growth in the next season. Grain sieve loss-monitoring sensors represent an important accessory in combine harvesters, as they can not only provide current grain loss levels for the operator to adopt a rational action in time but also serve as an important performance signal for the control system. To reflect the rice grain sieve loss level of combine harvesters in real time, an indirect grain sieve loss-monitoring system is proposed in this paper. First, the grain collision rise time was obtained by the finite element method (FEM), and the parameters of the grain loss sensor signal processing circuit were determined accordingly to upgrade the monitoring accuracy. Then, grain loss distribution behind the cleaning shoe was analyzed in detail under different working parameters. Grain loss distribution functions at the end of the sieve and a monitoring mathematical model with relevant variables were established based on the laboratory experiment results. Finally, calibration experiments were carried out to verify the measurement accuracy of the sensor on a cleaning test bench, with an obtained relative monitoring error ≤6.41 % under different working conditions.

Investigation into Experimental and DEM Simulation of Guide Blade Optimum Arrangement in Multi-Rotor Combine Harvesters

The cleaning performance of the cleaning shoe of a multi-rotor combine harvester has proven to be poor owing to the threshed output entering the cleaning section in an uneven manner. Experimental results indicated that the arrangement of the guide blades on the return plate surface has a significant effect on the threshed output distribution. In this paper, DEM (discrete element method) simulations were carried out in the EDEM software to examine the effect of the height of the guide blade, the installation angle, and the number of guide blades on threshed output distribution before entering the cleaning shoe. Based on the simulated results under different guide blades arrangements, the optimum arrangement location was obtained. The simulation’s results were verified by a field experiment and were consistent with the experimental results. The field experiment results indicate that the cleaning performance significantly improved with the proper guide blade arrangement. The corresponding grain impurity ratio declined significantly from 1.26% to 0.67%, and the grain sieve loss ratio, with a decrease of 53.2%, was reduced from 1.11% to 0.52%.

Optimisation of a multi-duct cleaning device for rice combine harvesters utilising CFD and experiments

As the grain-cleaning process in a combine harvester relies on pneumatic separation of the grain and chaff, the aerodynamic forces created by the airflow have a large impact on the cleaning performance. Therefore, to optimise a multi-duct cleaning device in a rice combine harvester, First, the equivalent resistances for the different fan ducts were quantified with a resistance model of fluidised grain and an airflow resistance model for the cleaning sieve. Perforated plates with different opening ratios were designed to simulate working loads. A computational fluid dynamics (CFD) model was validated by comparing simulation results with hot-wire anemometer measurements. The effects of working loads on airflow velocity and volume distribution at the ducts, and total pressure distribution inside the fan were studied in simulation and experiments. After integration of the designed multi-duct fan into the cleaning system, airflow measurements inside the cleaning shoe were made and cleaning performance tests were carried out on a test bench. The ideal airflow velocity within the cleaning shoe was investigated by correlating airflow velocities at different measuring points and analysing the cleaning performance. An evaluation of this multi-duct cleaning system in the field showed large improvements in terms of the grain sieve losses ratio and grain impurity ratio compared to a combine harvester with the single-duct cleaning system. The corresponding grain sieve loss decreased from 2.46% to 0.08%, while the grain impurity ratio decreased from 4.78% to 0.511%.

Development and testing of a multi-duct cleaning device for tangential-longitudinal flow rice combine harvesters

Rice is one of the most important grain crops in China and most of these fields are harvested by combine harvesters. With increasing rice grain yields and feed rates, the cleaning systems rice combine harvesters have to deal with larger volumes of threshed output. Field experiments have shown that the standard single-duct cleaning systems used in most rice combine harvesters has become a limiting factor, resulting in high grain losses and producing high grain impurity ratios. To investigate the reasons for poor cleaning performance, the terminal velocity of the different categories of threshed outputs were quantified and turbine flow meter measurements were performed to obtain insights into the airflow distribution inside the cleaning shoe. Based on these insights, a multi-duct cleaning device with return pan was proposed for tangential-longitudinal-flow rice combine harvesters. The new cleaning system was benchmarked against a commercial system during parallel field tests and it was concluded that the design adaptations improved the sieve losses by 85% and the grain impurity ration by 73%.

Grain Sieve Loss Fuzzy Control System in Rice Combine Harvesters

The main working parts of the cleaning device of a rice combine harvester can be controlled by an established control strategy in real time based on the monitored grain sieve loss. This is an efficient way to improve their cleaning adaptability, since as a consequence, the main working parameters of combine harvesters can automatically adapt to crop and environment changes, and the corresponding cleaning performance can be improved. To achieve the target of cleaning control based on the monitored grain sieve loss, a fuzzy control system was developed, which selected S7-1200 PLC as the main control unit to build the lower computer hardware system, utilized ladder language to complete the system compilation, and used LabVIEW 14.0 software to design the host–computer interface. The effects of fan speed, guide plate angle, and sieve opening on the grain sieve loss and grain impurity ratio have been investigated through a large number of bench tests. The relevance level of the operating parameters on the performance parameters has been determined also, and finally, a fuzzy control model was developed for the cleaning system. The experiment results indicated that the designed fuzzy control model can control the cleaning section settings, such as fan speed and guide plate angle automatically, and reduce the grain sieve loss to some extent.

Comparative performance evaluation of high capacity wheat thresher with variable parameters

This research study was conducted in order to determine and compare the performances of two different high capacity wheat thresher and economic characteristics of threshing for wheat crop. The research was conducted in the farm of Sam Higginbottom Institute of Agriculture, Technology and Sciences, Allahabad. The treatments under the comparisons were different type of power thresher .Wheat crop which was ready for threshing in the field at SHIATS, Allahabad. Wheat was threshed by high capacity Himanchal and Haramba thresher on different cylinder speeds. Three replications were taken and values of dependent variables were computed to indicate the performance evaluation of high capacity flow through the Himanchal and Haramba wheat thresher were carried out for threshing of wheat w.r.t threshing efficiency, cleaning efficiency, output capacity and total machine losses including broken grain, sieve loss, blown or spilled grain and unthreshed grain. The observation were taken at three drum speeds of 850 rpm, 740 rpm and 685 rpm and three feed rate 34 kg/min, 36 kg/min and 39 kg/min at the moisture content of 16.2 per cent and two concave clearances (21 mm and 18 mm). The analysis of data and results obtained from the comparative evaluation of both the machines shows that threshing efficiency and cleaning efficiency for machine (M 1 ) 98.89 per cent and 98.96 and (M 2 )99.10 per cent and 99.08 per cent, respectively at the 850 rpm drum speed on given feed rate 39 kg/min. The highest machine losses were 10.07 per cent at 34 kg/min on 685 rpm and lowest grain losses were 6.30 per cent at 39 kg/min on 850 rpm. The cost of threshing through the high capacity thresher was obtained Rs. 417.70 per hour and the threshing cost Rs.41.77 per quintal through the Himanchal high capacity wheat thresher and Rs.27.84 per quintal through the Haramba high capacity wheat thresher. It was concluded that there is an inherent advantage of Haramba high capacity wheat thresher over the Himanchal high capacity wheat thresher and manual operation. It is necessary to maximize the use of the machine.

Sensor for monitoring rice grain sieve losses in combine harvesters

Grain sieve losses are important parameters to judge the performance of cleaning shoes in combine harvesters. To keep grain sieve loss within acceptable limits, an impact-type piezoelectric sensor was developed for real-time monitoring. Rice grain and short straw particle models were established according to their physical properties, and discrete element method (DEM) simulations were carried out to understand their collision behaviour with the sensor. The influence of grain shape, straw length and impact angle on variations of the maximum normal contact force and force rise-time were analysed in detail. Differences in normal collision force, and force rise-time occurred which lead to corresponding differences in signal frequency and voltage amplitude. A signal processing circuit, which mainly consisted of a band-pass filter circuit and a voltage comparator circuit, was designed to discriminate for full grains. Field tests results indicated that measurement errors recorded by the sensor and checked against manually measurements were

Optimum design of grain sieve losses monitoring sensor utilizing partial constrained viscoelastic layer damping (PCLD) treatment

Grain sieve losses has been an important dominant factor for automatic adjustment of the major working parameters of combine harvesters such as cylinder speed, concave clearance, fan speed and vehicle forward speed. To monitor grain sieve losses real-timely in the working processing of combine harvester, a grain sieve losses monitoring sensor, which utilizing YT-5 type piezoelectric ceramic as sensing material developed. To accelerate grain sieve losses monitoring sensor's detecting speed, theoretical analysis was performed from view of structural vibration and a partial constrained viscoelastic layer damping (PCLD) treatment was carried out on the surface of the grain sieve losses monitoring sensor. On the basis of analyzing the mechanical relationships among each layer of the sandwich in depth, an optimal position to past the viscoelastic layer was found. Grain collision experiment results found that grain collision signal attenuate time was shortened to about 2–3ms after treated with PCLD in places with relative larger modal deformation, namely, the developed sensor could identify more than 300–500 grains within 1s in theory, which verified that the sensor's detecting speed was significantly improved. To test the performance of the developed sensor, calibration experiments carried out in the laboratory, and analysed the influence of moisture content (MC), sensor mounts height and angle on measurement accuracy. At last, installed grain sieve losses monitoring sensor on a combine harvester field experiments took place; experimental results showed that the largest measurement relative error was 4.48% when harvesting rice.

Optimization of grain mass threshing regimes in stationary conditions

It is shown that automatic control system of grain mass threshing used in field or in stationary conditions will decrease rack, sieve and cylinder losses of grain, will ensure stable operation of suction conveyor.

English

  The economic situation in most developing countries have left farmers and processors operating at the small scale, hence the use of automated and electric power driven equipment is limited to the few large scale processors. The effect of the ergonomic parameters namely; weight, age, height and arm length in relation to the resulting efficiencies; shelling efficiency, cleaning efficiency, mechanical damage and percentage sieve loss of a hand powered Maize Sheller incorporating a blower were studied using a non linear regression analysis. The study was with a view to developing a model for the performance of the hand powered maize sheller. The power transmission increases the speed of the blower for high cleaning efficiency. Preliminary studies were carried out to determine the ergonomic data of operator, and moisture content and grain/chaff. The results on studies with maize with 12% dry basis moisture content and grain/chaff ratio of 3.04:1 show that weight has the most significant effect (p<0.05). The mean of the shelling efficiency, cleaning efficiency, sieve loss and mechanical damage of the machine are 94.3, 96.4, 2.3 and 5.23% respectively and the coefficient of determination for the regression equations relating the ergonomic parameters to machine efficiency and parameters ranges from 0.29 to 0.86 with quadratic regression obtained. Equations were derived to relate the variables and an approximate solution was obtained from a particular example, which validates the theoretical prediction with known results.   Key words: Shelling, efficiency, hand powered, ergonomic, model.

Identification of the cleaning process on combine harvesters, Part II: A fuzzy model for prediction of the sieve losses

The driving tasks of combine harvester operators can be described as being very exhausting because of the high environmental temperatures, long working days and time constraints operators have to deal with. In order to lighten the job, automation is being introduced. In this study, the focus lies on the automation of the cleaning unit. A non-linear prediction model for the sieve losses has been established by means of fuzzy modelling techniques. Excessive sieve losses can be predicted by making use of a differential pressure measurement under the upper sieve section and the derived sieve load signal. The latter signal is a measure for the loadings by grain and chaff on the upper sieve and can thus be linked with the aeration level of the upper sieve section. Validation results revealed that the best position for mounting a pressure sensor is at the rear section of the upper sieve. Grain loss kernels will be blown out by the fan when the loadings on the upper sieve are very low, while a high loading on the upper sieve will result in sieve overload and thus very high sieve losses.

Fuzzy control of the cleaning process on a combine harvester

Combine harvesters operate all over the world, harvesting different crops under different environmental conditions. In order to cope with varying soil, climate and crop conditions, it is important to adjust and optimize the internal settings of these machines to the varying conditions. Since many sub-processes (e.g. threshing, cleaning, speed control, header control) have to be continuously optimised or surveyed, automatic control systems are needed to aid the operator in this tedious task. In this study, automation of the cleaning section on a combine harvester was investigated. In preceding studies considerable knowledge about the working principles of the cleaning unit had been gathered using data-based models. Based on experimental data and fuzzy modelling techniques, optimum and non-optimum working conditions were identified. In this paper, a fuzzy control system which combines the knowledge of experienced operators with these data-based models is elaborated. The main goal of the controller for the cleaning section was defined as finding an optimum trade off between acceptable sieve losses and return volume for a desired level of MOG in the grain bin and a certain amount of incoming biomass. The performance and robustness of the control system have been evaluated by field tests during wheat harvest. Promising results were obtained, demonstrating the benefits of an automatic control system for the cleaning section of a combine harvester when environmental conditions rapidly change over time.

Design of fuzzy logic control system incorporating human expert knowledge for combine harvester

Many factors affect the yield loss in wheat harvesting with a grain combine harvester. Grain harvesting is a non-linear process, is of considerable complexity, and there is no mathematical model to describe the behavior of this complex system. In this paper, a fuzzy logic controller (FLC) incorporating human expert knowledge is designed for automatic adjustment and control of the harvester to achieve minimal grain losses especially at the position of straw walker and upper sieve. The FLC automatically adjusts cylinder speed, concave clearance, fan speed and forward speed of the combine based on the measured losses at straw walker and sieve sections. The designed FLC expert system consists two inputs and four outputs. Trapezoidal membership functions were selected for input fuzzy linguistic variables (straw walker and sieve losses), whereas fuzzy singletons were considered for the outputs. Based on human expert knowledge, six rules with logical AND operator and Mamdani implication are extracted. FLC was implemented in a programmable logic controller (PLC). Field experiments in two different irrigated or non-irrigated cultivated areas in order to evaluate the system. It was found the losses at the position of straw walker and upper sieve in the irrigated wheat cultivated area is much higher than the dry wheat cultivation area. Statistical analysis using t-test was also indicated a significant difference ( p < 1%) between loss mean in the combine equipped with the controller and the one without FLC.

A genetic input selection methodology for identification of the cleaning process on a combine harvester, Part I: Selection of relevant input variables for identification of the sieve losses

The cleaning process on a combine harvester is a complex process, which is influenced by a wide range of parameters such as e.g. machine settings, and field- and crop-related parameters. Because of the pressures on time faced by combine operators, optimal settings for the cleaning section are usually estimated only once for each crop, and as a consequence, differences in temporal- and site-specific conditions are neglected. Previous literature showed the importance of making use of the most appropriate settings to reduce grain losses. In order to gain insight into the cleaning process of a combine harvester, machine behaviour was registered for different machine settings. Different measurement devices were installed on a test combine to extract information from the combine harvesting process. In order to rank the candidate input variables as possible regression variables for the prediction of the sieve losses, an input selection methodology based on the principles of natural selection is presented. Results indicate that that the sieve losses are affected in a non-linear manner by differences in the pressure profile of the cleaning section and the upper sieve opening.

Measurement of some parameters of different spring wheat varieties affecting combine harvesting losses

For normal threshing procedure, parameters of 5 different spring wheat varieties (Opal, Orca, Peko, Jufy, and Gaby) were compared: the threshing of the kernels, loose ears and the amount of broken straw and chaff. For an exact assessment of the ripeness of the crop it is necessary to have a fair criterion for comparison of the different varieties. The frequently used eosine colour method does not give an exact indication of the ripeness stage. For seed, it is better to measure the hardness of the kernels. Although we could not measure an exact correlation between our plot parameters and the field losses of the combine harvester, we can give a correct rank order for the different varieties. If the suitability of new varieties for combine harvesting is to be tested, a good knowledge of the ripeness stage is necessary. The straw-shaker losses are fairly well characterized by the percentage threshed and the percentage of broken straw and chaff. Loose ears have an influence on the sieve losses.

The Biomass of the Bottom Fauna in the English Channel off Plymouth

A survey has been made of the biomass of the macrobenthos at twenty stations in the English Channel off Plymouth. The object was to provide a basis for following long-term fluctuations in the fauna.A brief survey of physical conditions in the area is given, and a gradeanalysis of the soil at each station has been made.Core-samples show that the sediment is shallow in many places and rock has been taken at 36 cm. or less below the surface at a number of stations.Samples totalling ½m.2 were taken at each station with a modified 'scoopsampler', covering 1/10m.2, which is briefly described.Sources of error in sampling are considered in detail. Some species may evade the sampler and others live too deep in the sediment to be taken. A comparison against a Petersen grab and a new ' suction-corer' show that the scoop-sampler does take a reasonably quantitative sample. The number of species taken in successive hauls, when plotted against the log of the area sampled, approaches a straight-line relationship similar to that obtained by Williams (1950).A statistical analysis is made of a series of samples taken at one station, and the variance between the two samples in each haul and between successive hauls calculated. At this pàrticular station the fauna in successive samples is shown to be fairly random.A sieve of 2-2 mm. mesh was employed. Compared with a finer sieve losses in terms of numbers may be quite large, but the total weight taken is little affected.