مجله پژوهش های مکانیک ماشین های کشاورزی
سال دهم شماره 2 (تابستان 1400)

Collecting autumn tree leaves from the surfaces of passages and streets has always caused many problems, for which special machines have been designed. In designing such machines, factors such as simplicity of components, economic efficiency, high performance capacity and easy maneuverability are of special importance. In this study, the performance of a leaf collecting machine made for potted tractors was investigated. To build the machine, in addition to theoretical calculations, the simulation of different parts of the machine in Solid works ???? software was examined in terms of strength and durability. In order to the actual operation of the device, the leaves of sycamore and mulberry trees were used. The device was evaluated at three levels of advance speed of ?.?, ? and ? km / h in three replications. The results showed that with increasing the advancing speed, the amount of leaf collection by both suction chambers and suction tube decreased so that increasing the advancing speed of the device from ?.? to ? km / h caused a ??.?% drop by suction tube and drop ??.?% will be sucked by the chamber. The results of the machine test showed that the suction pipe collects more leaves. Also, the results of the fan evaluation show that the larger the leaf size, the greater the amount of crushing and the smaller the leaf size, the less crushing. After the studies, it was found that with increasing the percentage of leaf moisture, the amount of leaf crushing also decreases. According to the results of the analysis of variance test, the mean of the variable of the suction chamber and the suction pipe of the three groups is not the same at the mentioned speeds and is significant at the ??% level. Scheffe test also showed that the mean of all two groups had a statistically significant difference at the level of ??% (p

Separation and weighing of broken of rice kernels within a batch is a common way for measuring the amount of brokens. Separation is carried out by sieve or hand that is time-consuming method and required periodical sampling. In the present study, some image texture features of a rice batch for determining the percentage of brokens were applied. In order to this, twenty-one samples of 100 g were prepared with different breakage percentages from mixture of broken and whole rice kernels (containing zero to 100 percent broken). Ten images were then taken from each sample batch. After pre-processing of the images such as noise removing and creating binary images, the texture features of the images were extracted using MATLAB software. Twenty-three texture features were extracted using a grayscale co-occurrence matrix method. The principal components analysis (PCA) method was employed to reduce number of the features. By which, 23 calculated and measured texture features was reduced to three principal components (latent variables). Then, the relationship between percentage of broken rice in the sample and the principle components of 23 extracted texture features from the images by artificial neural network method was pinpointed. Four different topology of neural networks with different neurons in two hidden layers were employed. The results of neural networks outputs revealed that 3-6-8-1 topology could determine the percentage of broken in a batch of rice kernels with 0.958 coefficient of determination (R2) and total estimation error of 1.5 percent. Moreover, it was found that 10 texture features were related to first principal component, four features related to second component, four related to third component, and five fractures were simultaneously related first and second principal components. Eight features with correlation more than 0.9 with the first and third principal component had the most impact on estimation of percentage of broken. This method of measurement is fast, affordable and has proper precision with respect to the common (hand) method for online applications.

Two-dimensional laser sensors (LIDAR) are fixed part of automatic navigation systems of vehicles used for obstacles detection and path determination; but very high price of these sensors has limited the commercialization of automated guidance systems. In this study, an obstacle detection system in front of tractor was constructed and evaluated using an inexpensive LIDAR. A RPLIDAR laser sensor, A1M1 model, was installed on a MF285 tractor bumper to monitor the space in front of the tractor. If an obstacle is detected in the path of movement, by sending the obstacle data to the micro-controller, the system is informed about the obstacle existence and finally the tractor is stops. Two types of experiments were performed to test the system, in the first experiment the tractor was stopped and in on/off modes and the obstacle was placed at different angles and distances to investigate the performance of the LIDAR at different angles and distances and the effect of tractor vibrations on it. In the second experiment, performance of the system was evaluated while the tractor was moving at 3.5 and 6 km/h speeds and the plastic and MDF obstacles were fixed. According to the results, at the first test, the maximum and minimum accuracy of the LIDAR in detecting obstacles at 0-300 cm distances were 97.73% and 89.5%, respectively. Also, the effects of obstacle type, distance and angle on the LIDAR accuracy were not significant. At the second test, both obstacle type and its interaction with tractor speed had significant effect on the system performance at 1% level. In total, the LIDAR performed poorly in outdoor and high light conditions and should be used with other sensors for outdoor applications.

Lack of drinking water and fresh water for agricultural purposes is one of the biggest problems in most arid and semi-arid countries. Therefore, desalination of saline water is necessary for the production of drinking water and irrigation. Due to the irradiative potential of south regions of Iran, the study of a solar subsurface irrigation system was performed experimentally and theoretically in Dehdasht. The system used a solar still and a subsurface reverse flow heat exchanger. The mixture of hot and humid air inside the solar still was directed to the underground pipe by a fan. Using the condensation process, the required water for subsurface irrigation was obtained. Using a suitable system for injecting compost tea into the pure water, a solution with a suitable composition was produced to irrigate and supply soil and plant nutrients. By measuring and monitoring environmental information and using MATLAB software, a fuzzy inference model was designed and Temperature changes, humidity ratio and mass of produced water were investigated. According to the simulation performed in MATLAB, the maximum temperature of the still reached 90°c in August and 60°c in April. Compared with its experimental values, the error values were reached 5.8% and 9%, respectively. The maximum and minimum amount of condensed water in the pipe was 6.13 liters and 3.09 liters per day for August and April, respectively. Compared to the experimental value obtained, the error values were 7% and 15%, respectively. According to the results, increasing the parameters such as solar radiation, ambient temperature, water temperature, diameter of condenser pipe and diameter of hot air pipe, as well as decreasing parameters such as condenser water temperature, relative humidity and pool water height, increased the amount of water produced. Therefore, this method is suitable for arid and semi-arid areas.

Quality assay and caring of fruit and vegetables has basic role on modern agricultures today. Photoacoustics is a new method of non-destructive detection of the properties of biological materials, in which light energy is used to produce ultrasonic waves in various materials.The received ultrasound waveform contains useful information about the textural properties of the adsorbent medium. This research investigated and evaluated the quality of three peach cultivars during their storage period using non-destructive photoacoustic method in comparison with destructive penetration method. For this purpose, a system for ultrasound wave generation was implemented using laser pulse radiation with a wavelength of 1064 nm. The maximum amplitude of the photoacoustic signal and the time of occurrence of this amplitude were extracted from the experimental samples. Also, by separate penetration test, the amount of firmness and modulus of elasticity were measured on the same samples. By selecting the factors of peach cultivar, size and caring time, the obtained data were analyzed in a completely randomized experimental design with 5 replications. Finally, the means of the two sets of data obtained from the two tests were compared by examining the correlation coefficients. The results showed that in all sources of variables in the measurement indices except the size factor in the maximum signal index there is a significant difference between the averages of the indices at the level of 5%. Over time, the maximum signal amplitude index decreased. As the sample size increases, the maximum amplitude time value increases more. There was a significant difference between the two levels of care. There was an interaction between factor of peach cultivar and factor of caring time. The results showed that the modulus of elasticity decreased in larger sizes. Comparison of the means of peach cultivar factor in firmness index showed that there is a significant difference in all three levels. The highest amount was in Balkhi cultivar and the lowest amount was in Zafarani cultivar. The mechanism of the photoacoustic signal produced by laser radiation on the surface of the material depends on the mechanical properties of the irradiated material and the properties of the light source. Therefore, the change in signal amplitude is affected by the initial pressure wave caused by the laser radiation on the surface of texture. Based on the results, the time of occurrence of the maximum signal is a good indicator to assess the quality of peach fruit texture during its care period. The results of correlation between the data of the two tests showed that the highest correlation coefficient between texture of firmness and the maximum amplitude of the photoacoustic signal is for three cultivars. So that Balkhi cultivar had the highest correlation coefficient equal to 0.821. These results prove the validity of non-destructive and non-contact measurement methods in texture quality.

Precision agriculture is rapidly growing worldwide, which is mainly based on positioning. While with the evolution of technology the accuracy of GPS data is continuously improved, the use of these sensors in the less developed countries is still challenging. The direct price link with the accuracy of the GPSs has led to attempts to use low-cost GPSs. The use of low-cost GPSs comes with various sources of error. In this study, a new method has been proposed to overcome the challenge of improving the accuracy of positioning while reducing equipment prices. The proposed method is based on the nature of the GPS error (random noise and bias) and is divided into two parts. First, the random noise was eliminated by employing the simple classic filter. In this regard, a comparison was made between the Kalman filter, Low-pass filter and the Moving Average filter. The settings of the filters were made in such a way that in addition to reducing the power of random error, it reaches the desired error range in the shortest possible time. The results showed that the Kalman filter was more efficient than the other filters. Bias removal is not possible except by using a DGPS receiver that can receive corrections sent from base stations. To solve this problem, a base station was designed that could send the corrections needed by low-cost receivers. The proposed low-cost differential positioning method leads to a 89% reduction in the horizontal error index, which is the accuracy obtained is suitable for various operations in precision agriculture. Second, the bias was removed by inspiring from DGPS technique, via providing a base station, incorporating three low-cost GPSs. in noise reduction and the proposed low-cost differential positioning at best resulted in 89% reduction in the error index. Such an enhanced accuracy can be used for many applications in precision agriculture.

The re-orientaion of human to nature and natural products has led to the development of pharmaceutical, cosmetic and food industries based on natural products. Therefore, the demand for raw materials has been increased, and one of the big batches of these raw materials are medical and aromatic herbs. One of the important issues in large pharmaceutical factories when preparing raw herbs is the differentiation and classification of different plants with similar sensory characteristics. In this study, the classification of five types of medical plants from the Lamiales order was investigated using electronic nose system based on metal oxide semiconductor (MOS) Sensors. After preparing the plant samples, the response of the system sensors to each of the tested plants was recorded and then by principal component analysis (PCA), linear discrimination analysis (LDA) and artificial neural network (ANN) was examined to classify these plants. Resault of principal components analysis (PCA) with using of electronic nose system data revealed that the two first main components cover the 95 percent of data variance. Accuracy of classification using electronic nose for LDA and ANN methods were obtained 92 and 100 percent respectively. The developed electronic nose system has succeeded in classifying the medical plants and could be used as a sensitive, reliable, and fast replacement for traditional methods.

The mill is one of the equipments which used in agricultural products processing. Impact or hammer mills are used for crushing grain, animal feed and spices due to their simplicity and ease of operation. In these mills, the crushing operation is done by impacts from the blades to the grains. The movement of the blade in the grain, after a relatively short period of time, leads to wear and erosion on the impacting edge of the blade. Frequent replacement of blades requires cost and time, which reduces the efficiency of the device and increases the cost of the product. Therefore, in this study, the evaluation of mechanical properties of steels with different alloys is considered as a suitable alternative to existing hammer mill blades. For this purpose, the effect of blade material on four levels and the effect of heat treatment in two different cycles for each sample on the hardness and abrasion resistance indices were investigated by laboratory test and practical test. Hardness test and abrasion test were performed using a hardness tester and pin on disk method in the metallurgical laboratory of the Islamic Azad University of Majlesi branch. The practical test of the blades was performed by installing the blades on the rotor of the milling machine and measuring their amount of wear in terms of mass losses, after grinding 1800 tons of grain. The results showed that DIN X 210Cr12 steel with SPK brand after quenching heat treatment cycle in oil, has more hardness and higher abrasion resistance than other samples. Appearance examination of the blades in the practical test showed that the DIN X 210Cr12 steel blades with different heat treatment cycles has the least erosion at the impact edge of the blade and is recommended as a suitable replacement for current blades.