Desien, ConstruThe design, fabrication and evaluation of egg weighing device using capacitive sensor and neural networksction and Evaluation of Egg Weighing Device Using Capacitive Sensor and Neural Networks

Introduction: Grading agricultural products always has a particular important position for submission to domestic and overseas markets. The grading causes more profitable product ranges and customer satisfaction. Grading treatment is carried out based on various parameters such as color, ripeness level, dimensions and weight. Product weight is one of the most effective parameters in grading operation. Egg weight is directly related to the smallness and coarseness of eggs. In egg grading, the largeness value is very important in marketing. This research aimed to design, fabricate and evaluate the egg weighing system based on its dielectric properties. Materials and Methods: To perform this research, the stages of work are divided into several sections including, design and construction of the hardware section, writing code for the software section to collect data, conducting nondestructive tests and data collection, analysis of obtained data using artificial intelligence, and giving the results of analysis for device calibration of the system as the software code. The large eggs as dielectric substances cause more increase in the capacity of the capacitive sensor. Furthermore, by derivation of a relation between capacity of capacitive sensor and egg weight, one can predict the weight of the sample. A prototype unit of weighing system was designed and fabricated. The designed unit was composed of a chassis, a voltage source, a sinusoidal signal generator, a voltage measurement unit, an AVR micro controller, a COM port, a capacitive sensor, and an LCD and a keyboard. Neural network technique was used for egg weight prediction. The designed net receives 16 voltage values at different frequencies as inputs and its output is the egg weight. In order to calibrate and evaluate the weighing unit, 150 fresh egg samples were provided on egg laying day from a local poultry farm. Experiments were divided into three groups. The experiments were carried out on egg-laying day, and the second and fourth day after laying. Results and Discussion: In this study, two networks were built and evaluated. In the first series, two-layer networks and in the second series, three-layer networks were developed. In the two-layer neural networks, the number of neurons in the hidden layer was changed from 2 to 10.According to the given results for two-layer networks, two layer networks with 10 neurons offer the best results (the highest R-value and minimum RMSE) and it can be chosen as the most effective two-layer network. Three-layer neural networks have been composed of two hidden layers. The number of neurons in the first hidden layer was 10 and in the second layer it was changed from 1 to 20. Between three-layer networks, the network with 7 neurons with the highest R-value and the lowest error is the most appropriate network. It is even more efficient than the two-layer network with 10 neurons. So, the most appropriate structure is 1-7-10-16 and it has been selected for calibration of the weighing device. To evaluate and assess the accuracy of the weighing machine, weights of 24 samples of fresh eggs were predicted and compared with the actual values obtained using a digital scale with the accuracy of 0.01 gr. The paired t-test has been used to compare the measured and predicted values and the Bland-Altman method has been used for charting the accordance between the measured and predicted values. Based on the findings, the difference between the measured and predicted values was observed up to 5.4 gr that is related to a very large sample. The mean absolute error is equal to 2.21 gr and the mean absolute percentage error is equal to 3.75 %. According to the findings, 95% of the actual and approximate matching range to compare the two weighing methods is between -5.3 gr and 3.36 gr. Thus, the dielectric technique may underestimate the egg weight up to 5.3 gr or it may overestimate it up to 3.36 gr more than the actual prediction. Conclusions: The best results were obtained with a 3 layers net having 10 and 7 neurons, respectively in the first and the second hidden layers with the highest R-value, 0.983 and the lowest error, 0.502. Therefore, this net was applied for egg weight prediction. To evaluate the device, the weights of 24 fresh eggs were estimated using the device and were compared with actual values and the maximum error was observed to be equal to 5.4 gr

Effect of Temperature Changes on Dynamic Pull-in Phenomenon in a Functionally Graded Capacitive Micro-beam

ABSTRACT In this paper, dynamic behavior of a functionally graded cantilever micro-beam and its pull-in instability, subjected to simultaneous effects of a thermal moment and nonlinear electrostatic pressure, has been studied. It has been assumed that the top surface is made of pure metal and the bottom surface from a metal-ceramic mixture. The ceramic constituent percent of the bottom surface ranges from 0% to 100%. Along with the Volume Fractional Rule of material, an exponential function has been applied to represent the continuous gradation of the material properties through the micro-beam thickness. Attentions being paid to the ceramic constituent percent of the bottom surface, five different types of FGM micro-beams have been studied. Nonlinear integro-differential thermo-electro-mechanical equation based on Euler-Bernoulli beam theory has been derived. The governing equation in the static case has been solved using Step-by-Step Linearization Method and Finite Difference Method. Fixed points or equilibrium positions and singular points of the FGM micro-beam have been determined and shown in the state control space. In order to study stability of the fixed points, beam motion trajectories have been drawn, with different initial conditions, in the phase plane. In order to find the response of the micro-beam to a step DC voltage, the nonlinear equation of motion has been solved using Galerkin-based reduced-order model and time histories and phase portrait for different applied voltages and various primal temperatures have been illustrated. The effects of temperature change and electrostatic pressure on the deflection and stability of FGM micro-beams having various amounts of the ceramic constituent have been studied

Effect of turbo charger system on engine fuel consumption and tractor power and traction (ITM475, ITM485 and ITM800)

Introduction: Tractors are considered as the main power generators in mechanized agriculture. Hence, the experts and engineers in tractor manufacturing of the country, are required to focus on developing and designing new features in tractor manufacturing. This must be, of course, paralleled with the economic aspects. Achieving this goal, Iran Tractor Manufactories Co., (ITMCO) has designed and developed tractors equipped with turbochargers. This has been performed on ITM800 & ITM485 models, according to world standards. The turbocharger system, with harnessing of lost energy in engine output fumes, compresses the air entering the engine and more air enters the cylinder. This will cause the engine to burn fuel more efficiently and thus produce more power. Materials and Methods: This study has been carried out on ITM485 & ITM800 tractors (with turbocharger system) and ITM285 & ITM475 tractors (without turbocharger system) to assure the improvement of engine performance and compare them employing OECD world standards. Experiments were performed in the concrete runway of Tabriz Tractor Manufacturing Company. For experiments, a dynamometer was used to measure the traction force between two tractors, a measuring unit for fuel, a thermometer unit and a timer to measure the quantities of fuel consumption, drawbar force and power. For drawbar traction test, each of the tested tractors pulled the rear tractor in different gears and the dynamometer between these 2 tractors recorded the tractors traction force by data loggers. To measure tractors fuel consumption, a measuring unit of fuel (VDO - EDM 1404) was used that calculated the flow rate in the path of fuel from the fuel tank to the engine and the return path from the engine to the fuel tank and showed the quantity of fuel consumption in liters per hour digitally. Results and Discussion: In comparison of traction power and force of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. Traction power and force at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 have a significant difference in the level of one percent. Tukey post hoc test results also indicate that traction power and force in tractors with turbochargers ITM485 and ITM800 are significantly more than the tractor without turbocharger ITM475. The gear effect is also significant. Traction power and force in different gears have significant difference at the probability of one percent. Tukey post hoc test results indicate that power quantity is highest in the gears: (1+H, 2*H, 1*H, 3+L) and minimum in the gears: (1*L, 1+L, 2*L), (* Turtle and + Rabbit). But Tukey post hoc test results indicate that traction force quantity is highest in the gears: (1*L, 2*L, 1+L) and minimum in the gears: (2*H, 1+H). In the comparison of specific fuel consumption of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. The amount of specific fuel consumption at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 has a significant difference in the level of one percent. Tukey post hoc test results also indicate that specific fuel consumption quantity in tractors with turbochargers ITM485 and ITM800 in the level of one percent is significantly less than the tractor without turbocharger ITM475. The gear effect is also significant. The specific fuel consumption quantity in different gears has significant difference at the probability of one percent. Tukey post hoc test results indicate that specific fuel consumption quantity is highest in the gears: (1*L, 1+L, 2*L) and minimum in the gears: (1+H, 2*H, 1*H). Conclusions: The tests were performed on tractor drawbar traction. Results of variance analysis in this experiment on a concrete surface, indicated that the calculated traction power and force of ITM485 and ITM800 tractors (with turbocharger system) were higher than the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. Meanwhile specific fuel consumption in the ITM485 and ITM800 tractors (with turbocharger system) was lower than that of the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. This will lead to significant savings in fuel consumption

Preliminary design, construction and evaluation of robot of tomato seed planting for the trays of greenhouse

Introduction: From an economic viewpoint, tomato is considered as the second most valuable crop after potato. It is also preceded by the potato in terms of per capita consumption in the world. In 2008, the cultivation area used for the tomato as equal to 163,539 hectares in Iran and the production of it was equal to 5,887,715 tons with an average production of 117,887 tons in 4352 hectares in the provinces, respectively. Having high production volume and quality, costly hybrid seeds are currently used for the major planting areas of vegetable in Iran. Most of the used transplanted seedlings are 83%. Since the seeds are expensive, the percentage of seedlings and healthy and disease-free seeds should be used for maximized germination and be transferred to the fields of open space. Preparing seedlings in transplanting trays is a technology to respond to this need. Trays are covered with a layer of Peat and Miculite fertilizers. Then, one seed is manually placed in each cell after gauging and preparing a suitable field. However, manually placing seeds is time-consuming and requires hard labor. Sixteen working labors per hour are required for 15 × 7 cell in order to have 10200 seedlings grown in 100 trays. Due to lack of adequate labor, production capacity of greenhouses is reduced, especially in the farming season when finding labor for planting vegetable sprouts is laborious. Therefore, mechanizing tray seeding operations is essential to increase the capacity of the growing industry of greenhouses in Iran. Materials and Methods: Initially, the tomato seeds were examined in the laboratory. The most important parameters of the study included size, shape, weight, the speed of getting out of the tank and the minimum carrying speed. Then, a vacuum-based single seed picking unit was prepared to investigate the factors influencing the design, so that a single tomato seed can be harvested from the masses. The most important factors considered in the design and construction included: cost, ease of performance, portability, use of local equipment, the planter’s capacity as well as the style of picking single seeds (In Fig.1, the original scheme of the device is presented). The planter consists of several parts operating harmoniously to yield the desired results. These parts include a chassis and conveyor belt mechanism, primary and secondary fertilizer tanks, squashing unit, seed metering device and vibrating reservoir of the seed (The main text of modeling the device with SolidWorks software is shown in Fig.2). This device is designed in such a way that the position of the nozzle, the suction pressure, the height of removing seeds and the vibration frequency of the seeding tray are adjustable. Evaluation of the device was carried out by single seeding of tomato seeds in trays with 105 cells (7 × 15). Suction pressure and nozzle size were calculated for tomato seeds. Scaling distances were considered equal, based on the 30.5-mm intervals of the cells. Single seed picking efficiency of seeds was calculated by the system, as the single percentage of seeding and the total percentage of seeded cells. Seed consumption efficiency is the ratio of the total seeded cells to the total number of existing seeds in the cells. Seeding efficiency also refers to single, dual, and multiple harvested seeds. Furthermore, the device capacity is defined as the number of seeded tray cells per hour. In order to design and build a precise robot planter, an experiment including the designed planter and planting speed of workers in 10 repetitions was designed and implemented to estimate the seeding time and compare with automated and manual planting methods. Seedling trays with four replications were cultivated by the designed robot and the number of cultivated seeds per tray at each stage were correctly counted. After that, the spent planting time by a worker was determined with four replications. Results and Discussion: The planting rate of tomato seeds is different when comparing mechanized and manual methods. As it is known, the time required for cultivation in the mechanized method is at least one-tenth of the time required for cultivation in the conventional and manual method, which causes the planting rate to increase, and this robot is one of the components of cultivation in the mechanized method in cultivation and production of tomatoes. By assessing planting time using the mechanized method it was revealed that an average of 26.3 seconds is needed to fill a 7 × 15 centimeter tray of tomato seeds with 105 cells. The same planting procedure in the manual method takes an average of 357 seconds which is indicative of the high rate of the designed device. The planter capacity experimented using a seedling tray with the size of 15×7 cells, was calculated to be 17750 cells per hour showing that the suction pressure increases by a reduction in seed size. Thus, while working with small-sized seeds, fluctuations of the suction pressure must be carefully considered to be minimized and the seed being dual was only affected by the opening diameter. Therefore, the opening diameter should become the same in size in order to minimize the dual seed instances. In case of the tomato, the opening diameter had a great influence on the seeds being bulky. Conclusions: Manual planting takes a considerable time in comparison with the mechanized planting. Furthermore, using the designed device in addition to speeding up the planting process, caused regular and accurate cultivation of tomato seeds in order to produce seedlings. The results indicate that utilizing the device over time is highly economical for the major producers of tomatoes, and it is recommended to be used in agro-industry companies, and in the mechanized method of planting in large scales

SSM-iCrop2 : A simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.</p

SSM-iCrop2 : a simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees