scholarly journals RF signal calibration for improvement of 3D mapping image to locate moisture distribution in rice silo

2021 ◽  
Vol 2107 (1) ◽  
pp. 012059
Author(s):  
A A Almaleeh ◽  
A Zakaria ◽  
M H F Rahiman ◽  
Y B Abdul Rahim ◽  
L Munirah ◽  
...  
Keyword(s):  
Moisture Content ◽  
Real Time ◽  
Current Method ◽  
Moisture Distribution ◽  
Rice Grain ◽  
Tomographic Images ◽  
Grain Moisture ◽  
A New Technique ◽  
Assurance Process ◽  
Rf Signal

Abstract Grain storage is an important part of the post-harvest quality assurance process. The moisture level of the grains during storage is one of the primary problems. The current method of measuring rice grain moisture content is based on random sampling, which is relatively localised, and there is no real-time moisture content measurement available. The RF signal was used to build a new technique for detecting moisture and its presence in rice in real-time in this paper. The mapping of an RF signal, in particular, can be transformed into volumetric tomographic images that can be used to forecast moisture distribution.

Portable Wireless Yield Monitoring System on Conventional Rice Combine

2021 ◽  
Vol 37 (1) ◽  
pp. 193-203
Author(s):  
Renny Eka Purti ◽  
Azmi Yahya ◽  
Oh Yun Ju ◽  
Maryam Mohd Isa ◽  
Samsuzana Abdul Aziz
Keyword(s):  
Moisture Content ◽  
Embedded System ◽  
Real Time ◽  
Crop Yield ◽  
Field Capacity ◽  
Base Station ◽  
Grain Moisture ◽  
The Embedded System ◽  
Yield Monitoring ◽  
Grain Elevator

Abstract. A simple, portable, and rugged instrumentation system has been successfully developed and field demonstrated to monitor, measure, and record the harvested crop yield and selected machine field performance parameters from the typical rice combines in Malaysia. The complete system comprises of two ultrasonic sensors located at the combine header to measure the cutting width, microwave solid flow, and microwave moisture sensors at the combine clean grain auger to measure the flow rate and moisture content of the cleaned grains going into the grain tank, electromagnetic detector on the combine grain elevator drive shaft to monitor the grain elevator rotational speed, and lastly a DGPS receiver on the combine console roof to indicate the travel speed and geo-position in the field. All these measured parameters were made to display in-real time on the touch panel screen of the embedded system on-board the combine for the interest of the combine operator and also made to display in-real time on the monitor of the toughbook at the on-ground base station for the interest of the system controller. Static calibrations on the individual sensors showed excellent measurement linearity having R2 values within 0.8760 to 1.000 ranges. The wireless communication between the embedded system on-board the combine and the toughbook at the on-ground base station could be sustained to a maximum distance of 185 m apart. Site specific variability maps of crop yield, harvested grain moisture content, combine cutting width, combine traveling speed, combine field capacity, and combine field efficiency within the harvested area could be produced from the data obtained with the instrumentation system using a GIS software. Keywords: Grain harvesting, Paddy mechanization, Precision farming, Wireless data transmission, Yield monitoring.

Finite Element Simulation of Rough Rice Kernel (Oryza sativa L.) cv. Fajer Drying

2008 ◽  
Vol 3 (1) ◽  
Author(s):  
Shahin Rafiee ◽  
Mahmoud Omid ◽  
Alireza Yadollahinia
Keyword(s):  
Finite Element ◽  
Oryza Sativa ◽  
Oryza Sativa L ◽  
Moisture Distribution ◽  
Element Formulation ◽  
Rice Grain ◽  
Conductive Heat ◽  
Drying Time ◽  
Rough Rice ◽  
Grain Moisture

This study was conducted to present a mathematical model with numerical solutions to predict the mass distributions inside a cross sectional area of an individual Fajer variety of rough rice (Oryza Sativa L.) kernel as a function of drying time considering the effects of coupled heat and mass transfer processes. The modified Luikov's equation was used for the simulation of drying kinetics of a single rough rice grain. The applied drying models with simultaneous heat and mass diffusion in biological materials were developed by finite element method. A finite element formulation and solution of a set of nonlinear coupled conductive heat and diffusive moisture transfer equation to improve grain drying simulation of axisymmetric bodies is presented. Axisymmetric linear triangular elements with two degrees of freedom per node were used to discretize the rice grain. Moisture distribution inside the individual rough rice kernel was produced by the model. Good agreement was observed when the output of nonlinear model was compared to experimental data.

scholarly journals Rancang Bangun Prototype Mesin Pengering Gabah Otomatis Menggunakan Metode PID sebagai Kendali Temperatur

Jurnal INFORM ◽  
2020 ◽  
Vol 5 (2) ◽  
pp. 80
Author(s):  
Akhmad Fahruzi ◽  
Ricky Rhamdany
Keyword(s):  
Moisture Content ◽  
Dc Motor ◽  
Rice Grain ◽  
Large Area ◽  
Wet Season ◽  
Drying Temperature ◽  
Grain Moisture ◽  
Grain Drying ◽  
Driver Circuit ◽  
Thermocouple Temperature

The value of rice grain content after harvest is quite high, around 20-23% in the dry season, and around 24-27% in the wet season. It was drying grain after harvest was processed by the conventional or manual method that carried out the grain drying in the sun. This method has several disadvantages, such as the dependence on the weather, requires a large area, and 54 hours for drying so that the grain becomes dry with a moisture content of 14.12%. From this problem, the researchers made a grain drying machine that could work automatically. The drying machine is made to solve the issues of conventional grain drying so that the machine was completed with a K type thermocouple temperature sensor and grain moisture content. Whereas the heating media uses a fire that is fueled with LPG gas, and then the heat from the fire has flowed into the furnace or grain drying chamber. The heating arrangement was made by regulating of flowing LPG gas to the nozzle through the opened and closed variable valve where the valve shaft was connected to the DC motor shaft. The application of the PID method also used in this drying machine, which has a purpose while controlling the drying temperature to match the Set Value (SV) or the desired temperature at 38oC. The grain moisture content value is considered to have dried up when the grain moisture content value is 14%. The PID method that is implanted into the ATmega16 microcontroller will give a signal to the motor driver circuit to regulate the direction of rotation of the DC motor connected to the opened and closed valve variable. PID method testing was done by trial error and has produced a steady-state error of 5.2% at S0056=38oC with constant values Kp=2, Ki=2, and Kd=10. Whereas for drying grain testing on harvested is done by selecting Ciherang grain with a moisture content of 20% and a weight of 3 kg. The grain drying process takes 30 minutes so that the value of the water content becomes 14% with a drying temperature of 38oC, so the grain drying rate on this machine is 0.17% per minute.

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

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 897
Author(s):  
Chaiyan Sirikun ◽  
Grianggai Samseemoung ◽  
Peeyush Soni ◽  
Jaturong Langkapin ◽  
Jakkree Srinonchat
Keyword(s):  
Moisture Content ◽  
Grain Yield ◽  
Geographical Information ◽  
Rice Grain ◽  
Coefficients Of Variation ◽  
Grain Moisture ◽  
Pertinent Information ◽  
Yield Values ◽  
Combine Harvester ◽  
Yield Monitoring

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.

scholarly journals Developing an Online Measurement Device Based on Resistance Sensor for Measurement of Single Grain Moisture Content in Drying Process

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4102 ◽  
Author(s):  
Chengjie Li ◽  
Bin Li ◽  
Junying Huang ◽  
Changyou Li
Keyword(s):  
Moisture Content ◽  
Real Time ◽  
Calculation Method ◽  
Measurement Properties ◽  
Dynamic Resistance ◽  
Online Measurement ◽  
Drying Process ◽  
Measuring Device ◽  
Grain Moisture ◽  
Single Grain

The online measurement of moisture content for grains is an essential technology to realize real-time tracking and control, improve drying quality and reduce energy consumption of the drying process. To improve the measurement accuracy and reliability of the dynamic measurement process as well as expand the application scope of the device, the present work constructed an experimental equipment for determining dynamic resistance characteristics of a single grain. The relations between moisture content and real-time resistance waveform were revealed, and an analytical calculation method of peak value and peak area of waveform was proposed, which correctly revealed the electrical measurement properties of grain. The results demonstrated that the gap width between the electrodes had large influence on the sensor’s performance. Moreover, an online measuring device was developed based on the experimental analysis and calculation method, and the test results in both lab and field for different grains showed that online real-time absolute measurement error are within ±0.5% in the varied moisture content (10–35%w.b.) and the temperature (−20–50 °C). The main results and the developed device might provide technical support for developing intelligent grain drying equipment.

scholarly journals A New Method of Rice Moisture Content Determination Using Voxel Weighting-Based from Radio Tomography Images

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3686
Author(s):  
Nurul Amira Mohd Ramli ◽  
Mohd Hafiz Fazalul Rahiman ◽  
Latifah Munirah Kamarudin ◽  
Latifah Mohamed ◽  
Ammar Zakaria ◽  
...  
Keyword(s):  
Moisture Content ◽  
Single Point ◽  
Moisture Distribution ◽  
New Method ◽  
Rice Grain ◽  
Gravimetric Analysis ◽  
Fibre Degradation ◽  
One Step ◽  
Radio Tomographic Imaging ◽  
Moisture Content Determination

This manuscript presents a new method to monitor and localize the moisture distribution in a rice silo based on tomography images. Because the rice grain is naturally hygroscopic, the stored grains’ quality depends on their level of moisture content. Higher moisture content leads to fibre degradation, making the grains too frail and possibly milled. If the moisture is too low, the grains become brittle and are susceptible to higher breakage. At present, the single-point measurement method is unreliable because the moisture build-up inside the silo might be distributed unevenly. In addition, this method mostly applies gravimetric analysis, which is destructive. Thus, we proposed a radio tomographic imaging (RTI) system to address these problems. Four simulated phantom profiles at different percentages of moisture content were reconstructed using Newton’s One-Step Error Reconstruction and Tikhonov Regularization algorithms. This simulation study utilized the relationship between the maximum voxel weighting of the reconstructed RTI image and the percentage of moisture content. The outcomes demonstrated promising results, in which the weighting voxel linearly increased with the percentage of moisture content, with a correlation coefficient higher than 0.95 was obtained. Therefore, the results support the possibility of using the RTI approach for monitoring and localizing the moisture distribution inside the rice silo.

Development of an Eighth-scale Grain Drying System with Real-time Microwave Monitoring of Moisture Content

2019 ◽  
Vol 35 (5) ◽  
pp. 767-774
Author(s):  
Micah A. Lewis ◽  
Samir Trabelsi ◽  
Stuart O. Nelson
Keyword(s):  
Relative Humidity ◽  
Moisture Content ◽  
Real Time ◽  
Real Time Monitoring ◽  
Seed Moisture Content ◽  
Moisture Sensor ◽  
Grain Moisture ◽  
Cereal Grain ◽  
Grain Drying ◽  
Drying System

Abstract. After being harvested, cereal grain and oilseed are stored and dried in large cylindrical storage bins. Drying is necessary to prevent spoilage and degradation; however, because of the significant depth of material in the drying bin, a common problem in grain and oilseed drying is overdrying the bottom layer while trying to dry the top layer. This is due to insufficient knowledge of moisture throughout the bin. In some cases, an operator is limited to probing reachable locations to determine moisture content. However, this does not lend to observing the dynamics of moisture content within the bin continuously, and the lower layers of grain or seed within the bin are susceptible to being overdried. Temperature and/or moisture cables to monitor conditions throughout the bin are more widely used. These sensors use a correlation between grain moisture content and temperature and relative humidity. However, error in moisture content determination increases greatly at high relative humidity and/or temperature. By using a microwave moisture sensor operating at 5.8 GHz, developed within USDA ARS, the moisture content of the cereal grain or oilseed can be measured continuously, providing real-time moisture content with 12-s resolution. An automated, eighth-scale grain drying system was developed utilizing temperature and relative humidity sensors at different heights within the grain bin and the microwave moisture sensor to observe drying parameters and moisture migration as the grain or seed dried. Grain and seed moisture content was determined in real-time with a standard error of calibration of = 0.54% moisture content when compared to the reference oven-drying method. Overall evaluation showed that the automated grain drying system is an effective solution for real-time monitoring of moisture content and other parameters during drying. Keywords: Dielectric properties, Grain drying bin, Moisture content, Microwave sensing, Real-time monitoring, Sensors.

Modelling and Simulation Moisture Transfer in Wheat Stored in a Simulated Sealed Pit

2008 ◽  
Vol 4 (3) ◽  
Author(s):  
Mohamed A. Ismail ◽  
Michael P. Douglass ◽  
Brian C. Stenning
Keyword(s):  
Finite Difference ◽  
Moisture Content ◽  
Input Data ◽  
Moisture Transfer ◽  
Storage Period ◽  
Moisture Distribution ◽  
Wall Material ◽  
Moisture Contents ◽  
Grain Moisture ◽  
Grain Temperature

A mathematical model, coupled to another one which was used to calculate the conductive heat transfer, was developed to predict the change of moisture distribution with time in the radial and axial directions in a simulated sealed cylindrical pit storing wheat. The finite difference method was used in the model to calculate the diffusive moisture transfer. The model predicts the grain moisture contents in the pit during the storage period using input data of initial grain temperature, initial grain moisture content, storage time and number of spatial elements in both radial and axial directions. Other input data include the finite difference spatial increment in both directions, the finite time increment, temperatures of soil surrounding the pit and the physical properties of grain, pit wall material and surrounding soil. To validate the model, predicted moisture contents were compared with measured data for wheat of Apollo variety being stored in a simulated sealed pit for a period of 70 days. The wheat was stored in a cylindrical mild steel tank with 0.6 m in both diameter and height. The initial uniform grain temperature was 15 °C and the initial uniform grain moisture content was 12.45% (w.b.). Both measured and predicted moisture contents show that the major change in wheat moisture content took place during the first week of the storage and an establishment of steady state under the storage conditions of the pit is unattainable i.e. moisture diffusion is a very slow process. At the end of the storage period, the grain moisture contents were increased by an average of 1.62% (w.b.) and the grain temperatures were decreased by an average of 2.63°C at the top layer of the pit. For the bottom layer of the pit, the grain moisture contents were decreased by an average of 0.50% (w.b.) and the grain temperatures increased by an average of 7.04°C. The diffusive moisture transfer model predicted the grain moisture contents with a standard error of estimate between measured and predicted of 0.18 -0.75% and of 0.18-0.74% (w.b.) using Chung's equation and modified Henderson's equation, respectively. There was no difference between the two sorption equations (Chung's and modified Henderson's equations) used in predicting grain moisture contents.

Effects of Different Solar Drying Methods on Drying Time and Rice Grain Quality

2011 ◽  
Vol 7 (5) ◽  
Author(s):  
Pyseth Meas ◽  
Anthony H. J. Paterson ◽  
Donald J. Cleland ◽  
John E. Bronlund ◽  
A. John Mawson ◽  
...  
Keyword(s):  
Moisture Content ◽  
Grain Quality ◽  
Drying Methods ◽  
Rice Grain ◽  
Drying Time ◽  
Rice Farmers ◽  
Grain Moisture ◽  
Harvest Moisture ◽  
Grain Bulk ◽  
Air Circulation

Paddy rice was sun dried in Cambodia in 2004 using a range of methods practiced by local rice farmers. For each treatment in the experiment, a grain sample at about 22% moisture (typical harvest moisture content) was sun dried between 8 a.m. and 4 p.m. During experiments, the grain moisture content was measured at regular intervals. The grain varieties used, bed depths, stirring of the grain, bulk tempering after drying and the drying pads had significant effects on the drying time. Drying was faster when bed depth was reduced, regularly stirred but not shaded or covered and when the drying was carried out on a porous pad. Damage to the dried grain was reduced when the bed was thin, stirred and shaded and when the drying was slow on pads with less air circulation.

scholarly journals Inline 3D Volumetric Measurement of Moisture Content in Rice Using Regression-Based ML of RF Tomographic Imaging

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 405
Author(s):  
Abd Alazeez Almaleeh ◽  
Ammar Zakaria ◽  
Latifah Munirah Kamarudin ◽  
Mohd Hafiz Fazalul Rahiman ◽  
David Lorater Ndzi ◽  
...  
Keyword(s):  
Moisture Content ◽  
Low Cost ◽  
Economic Value ◽  
Tomographic Imaging ◽  
Moisture Distribution ◽  
Rice Grain ◽  
Wireless Devices ◽  
Volumetric Measurement ◽  
Grab Sampling ◽  
Current State

The moisture content of stored rice is dependent on the surrounding and environmental factors which in turn affect the quality and economic value of the grains. Therefore, the moisture content of grains needs to be measured frequently to ensure that optimum conditions that preserve their quality are maintained. The current state of the art for moisture measurement of rice in a silo is based on grab sampling or relies on single rod sensors placed randomly into the grain. The sensors that are currently used are very localized and are, therefore, unable to provide continuous measurement of the moisture distribution in the silo. To the authors’ knowledge, there is no commercially available 3D volumetric measurement system for rice moisture content in a silo. Hence, this paper presents results of work carried out using low-cost wireless devices that can be placed around the silo to measure changes in the moisture content of rice. This paper proposes a novel technique based on radio frequency tomographic imaging using low-cost wireless devices and regression-based machine learning to provide contactless non-destructive 3D volumetric moisture content distribution in stored rice grain. This proposed technique can detect multiple levels of localized moisture distributions in the silo with accuracies greater than or equal to 83.7%, depending on the size and shape of the sample under test. Unlike other approaches proposed in open literature or employed in the sector, the proposed system can be deployed to provide continuous monitoring of the moisture distribution in silos.

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