KR20240059052A - Loadcell-based mass measurement system for radish yield monitoring - Google Patents

Abstract

The present invention relates to a radish yield monitoring system, and more specifically to a load cell-based mass measurement system for radish yield monitoring. According to one aspect of the present invention, a load cell-based mass measurement system for monitoring radish harvest provided in a radish harvesting device including a conveyor belt is provided, and the load cell-based mass measurement system is installed at the bottom of the discharge port of the conveyor belt. an impulse detection means for detecting the impulse of falling radish discharged from the discharge port; and a control unit for calculating the weight of the radish from the falling impact of the radish detected by the impact detection means.

Description

Load cell-based mass measurement system for radish yield monitoring {LOADCELL-BASED MASS MEASUREMENT SYSTEM FOR RADISH YIELD MONITORING}

The present invention relates to a radish yield monitoring system, and more specifically to a load cell-based mass measurement system for radish yield monitoring.

1. Background

Radish is an important vegetable worldwide, commonly eaten raw in salads and used as a source of medicinal compounds. Radish is an annual or biennial crop usually planted in open fields. Globally, radish cultivation area and total annual production reached 3.1 million hectares and 95 million tons, respectively, by 2019. Radish production continues to decline globally, with a reported 24% decline in radish production in Japan from 2006 to 2020. The labor-intensive and time-consuming process of radish cultivation, low mechanization, increased labor wages and reduced labor force are some of the reasons for this decline. In recent years, mechanization has been promoted in several countries to accelerate harvesting and radish collection operations. Previous studies have reported that inappropriate management of radish, such as excessive and irrational nutrient application, is common even among radish growers without considering soil and environmental conditions, crop nutrient requirements, and other management practices that significantly affect radish yield and quality. . For sustainable radish production, mapping yield variability is a logical starting point for describing spatiotemporal distribution in the field. Therefore, it is essential to develop a monitoring system for radish mass to immediately determine yield and account for inter- and intra-field variability.

Real-time yield monitoring and spatiotemporal distribution analysis are the basis of precision agriculture that can confirm the current season's yield and guide precision agriculture in the next season. Today, a variety of commercial yield monitoring systems exist around the world, such as the John Deere Company's Green starTM yield mapping system, Case IH's Advanced Farming Systems AFSTM, and MICRO-TRAK's GRAIN-TRAK yield measurement system. Impulse yield monitoring systems, which measure impact force by converting gravity into a measurable electrical signal, have become the primary choice due to their low cost and convenient installation. Several impact-type sensors exist for grain crops and limited examples for non-cereal crops. An impact-type yield monitoring system was developed and tested on a potato harvesting machine. One design has four load cells and the second design has a single load cell. Impact plates were placed at the end of the conveyor boom in both systems. Both yield monitors provided highly accurate results under field conditions. Most of the early research focused on validating the performance of commercially available yield monitoring systems with little focus on the investigation of factors affecting the performance of sensors based on machine geometry and harvesting conditions. This type of research has been carried out by several research groups, most of them before 2010 and based on the yield characteristics of the crops studied. The results of these evaluations ranged from poor to excellent under the various conditions considered. Therefore, it is necessary to develop an accurate impact-type yield monitoring system designed according to the characteristics of radish harvesters and radish field conditions.

In the case of impact-type monitoring systems, yield measurements for mechanically harvested crops are mostly performed at the conveyor output. The system relies entirely on regression of a calibration curve to match the mass flow response signal to the actual mass flow rate of the harvested crop. Several factors such as harvesting conditions, harvest set rate, and crop characteristics are known to affect the quality and accuracy of a yield monitoring system. Therefore, research-based information is needed on the performance of these systems at different crop yields and under different field conditions. For example, the coefficient of restitution, a value that represents the ratio of velocities before and after impact, is an important crop characteristic of impact type systems. Knowledge of basic shock mechanics is important for analyzing these types of systems. Additionally, load cells typically have a damped vibration response that imposes long settling times. Measurements from vibrations due to uneven agricultural fields will increase. The main sources of this vibration in harvesting equipment are rotating shafts, transport operations such as hauling, and other moving parts. Significant measurement errors have also been reported due to field tilt variations. Unfortunately, a limited number of studies have been performed to evaluate the effect of field gradient on mass measurement errors. In other cases, researchers used various load cell layouts. This is due to the irregular shape of most crops and the variable structure of the conveyor system. To facilitate the integration of yield data into agronomic decisions, it is desirable to develop accurate yield monitors based on careful analysis of possible error-inducing factors.

Radish yield monitoring systems should be developed to facilitate the collection of detailed site-specific information within the field to manage input decisions on a spatially variable basis. Considerable experimentation using a test bench prior to manufacturing and field test validation will be useful to understand the impact of harvesting conditions on the output of the process and load cell signals to obtain accurate and suitable yield data. Therefore, the purpose of the present invention is to investigate the effect of various conditions on the determination of the mass of radish using a laboratory test bench.

Republic of Korea Patent Publication No. 10-2247648 (April 27, 2021)

The purpose of the present invention is to provide a load cell-based mass measurement system that can perform more accurate radish yield monitoring.

In order to achieve the above-described object, according to one aspect of the present invention, a load cell-based mass measurement system for monitoring radish yield provided in a radish harvesting device including a conveyor belt is provided, the load cell-based mass measurement system comprising: Impulse detection means installed at the bottom of the discharge port of the conveyor belt to detect the amount of impact of falling radish discharged from the discharge port; and a control unit for calculating the weight of the radish from the falling impact of the radish detected by the impact detection means.

In the above-described aspect, the load cell-based mass measurement system for monitoring radish yield further includes vibration detection means for detecting vibration of the radish harvesting device, and the control unit detects vibration when the impact amount of the radish falling is detected from the impact amount detection means. It is configured to detect vibration from the means and calculate the weight of the radish from the amount of impact of the radish falling when the vibration value detected from the vibration detection means is within a predetermined range.

In the above-described aspect, the control unit detects the vibration from the vibration detection means when the impulse of the object falling from the impulse detection means is detected, and when the vibration value detected from the vibration detection means is outside the predetermined range, the control unit detects the vibration from the impulse of the object falling. The weight of the radish is calculated so that the yield is excluded from the calculation.

In the above-described aspect, the load cell-based mass measurement system for monitoring radish harvest further includes a gyro sensor for detecting the posture of the radish harvesting device, and the control unit adjusts the inclination angle of the conveyor belt in response to the detection result from the gyro sensor. It is composed.

In addition, in the above-described aspect, the load cell-based mass measurement system for monitoring radish yield further includes a conveyor belt driving means for controlling the moving speed of the conveyor belt, and the control unit controls the moving speed of the conveyor belt through the conveyor belt driving means to a predetermined level. It is desirable to drive at high speed.

According to the present invention, it is possible to provide a load cell-based mass measurement system that can more accurately monitor radish yield.

1 is a diagram showing a three-dimensional model of a radish collection system and a radish harvester mounted on a tractor;
Figure 2 shows a yield monitoring test bench for zero mass measurement;
3 is a system diagram of a single load cell impact plate;
4 is a diagram showing sensor placement and blade adjustment for vibration table calibration;
5 is a diagram showing the impact plate layout and data collection system
Figure 6 is a diagram showing the effects of impact and impact force on an inclined plate;
Figure 7 shows the relative error trends due to various drop heights;
Figure 8 shows the relative error trends due to various plate angles;
Figure 9 is a diagram showing the relative error trend according to various conveyor speeds
Figure 10 shows the mass of radishes measured using equations using a weighing scale and single and dual load cells at 0.05 m/s and 0.25 m/s;
Figure 11 shows the trend of slope effect on the mass measurement of radish;
Figure 12 shows a no signal filtered using different moving average points; and
Figure 13 is a diagram showing one embodiment applied to the load cell-based mass measurement system of the present invention.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and will be implemented in various different forms.

The examples herein are provided to make the disclosure of the present invention complete and to fully inform those skilled in the art of the scope of the invention. And the present invention is only defined by the scope of the claims. Accordingly, in some embodiments, well-known components, well-known operations and well-known techniques are not specifically described in order to avoid ambiguous interpretation of the present invention.

Like reference numerals refer to like elements throughout the specification. Also, the terms used (mentioned) in this specification are for describing embodiments and are not intended to limit the present invention. As used herein, singular forms also include plural forms, unless specifically stated otherwise in the context. Additionally, components and operations referred to as 'including (or, including)' do not exclude the presence or addition of one or more other components and operations.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with meanings that can be commonly understood by those skilled in the art to which the present invention pertains. Additionally, terms defined in commonly used dictionaries are not interpreted ideally or excessively unless they are defined.

Hereinafter, embodiments of the present invention will be described with reference to the attached drawings.

2.1. Test stand design considering radish harvest conditions

2.1.1. Overall structure of commercial radish collector and harvester

Radish yield monitors should be adopted by both those who collect and harvest radish. The radish collector was designed with a three-point hitch for mounting on a tractor during the harvesting process, as shown in Figure 1. First, the radishes are manually removed from the soil and placed on the first conveyor. A collector equipped with stem cutters then cuts the stems of the radishes before they are transported to storage bags placed at the output end of a second conveyor belt. The storage bag can collect 30 radishes and the radish harvesting process is typically carried out at tractor speeds in the range of 0.1 to 0.2 ms-1, causing an average vibration level of approximately 0.41 ms-2 under loaded conditions on the second conveyor belt. . Radish harvesters, on the other hand, are equipped with a collection head/guide to collect the crop's leaves, break up the soil with vibrating excavator blades, uproot the radishes, and transport them through a load-out conveyor. The positioning guide installed on the transport path guides the position of the crop to a certain height during transport, and after cutting the leaves exactly at the desired location with a rotary cutter, the cut leaves are discharged to discharge the radish tubers and dropped onto the second conveyor. . Harvesting operations can be carried out at speeds of up to 1.8 m/s, but lower speeds are preferred due to the seeding density of radish. Radishes are usually planted 20 × 10 cm or 30 × 10 cm across the field with a slope level of up to 17%. Using both radish harvesting machine types, yield monitor sensors are mounted at the end of a second conveyor located at a minimum vertical height of 200 mm and 830 mm above the ground for the radish collector and harvester respectively. The feed rate into the storage container is about 1 to 6 kg/s due to the sowing pattern of radish and the slow movement of the radish harvester during the harvesting process. The advantage of both cases is that the top radish leaves are cut and discharged when leaving the first conveyor, so there is no greater amount of debris on the second conveyor. Therefore, a radish yield monitor based on the impact principle should be able to: Accurate regardless of harvesting machine used.

2.1.2. Design and construction of experimental test bench

The design and construction of the test bench for laboratory testing followed the structure and operating conditions of the radish collector and harvester conveyor belt. The conveyor output was selected as best suited to the installation of the mass measurement system. The frame for holding the measurement system was constructed in the laboratory using aluminum profiles (40 × 40 mm). The specifications of the vibration table used for vibration simulation are shown in Table 1, and the overall test bench is shown in Figure 2.

[Table 1] Vibration table specifications

2.2. Data acquisition system and sensor calibration

The load cell used (BCL-10L, CAS, Australia) provided an output of 2.0 ± 0.2 mV V-1 at a rated load of 100 N and was classified as a single point type with a recommended measurement platform of 300 mm × 300 mm. Additionally, the average geometry of the stemless The dimensions were 262 × 106 mm, so the platform was sufficient to ensure that all radishes were in contact with the plate. The load cell measured forces up to 100 N with a measurement accuracy of ±0.2 N. The data acquisition box consisted of a 4-channel, 24-bit, National Instruments (NI) 9237 (C Series strain/bridge input module) (Model: NI 9237; National Instruments, Austin, TX, USA). Additionally, strain/force measurements without phase lag between channels are possible, which is particularly suitable for dual load cell impact plates. A 10V excitation input was used to generate a 20mV signal at 100N.

The 9237 NI system was deployed in a 4-slot DAQ chassis (cDAQ NI-9174) with 50 ppm timing accuracy, and the output signals were sent to a laptop via an Ethernet cable. The front panel was developed using a software program (LabVIEW 2020, National Instruments, Austin, TX, USA) to store data from the load cell. A data acquisition diagram for a single load cell impact plate is shown in Figure 3.

For data collection from the dual shock plate, two of the four (4) channels of the NI 9237 were used to create two blocks of a single load cell full bridge. To test the suitability of the load cell sensor, the impact plate was adjusted to a horizontal position and five different weights were loaded sequentially for a measurement time of approximately 5 seconds at a sampling rate of 1 kHz. Each test weight was measured in advance using a precision scale. The lightest is about 10N and the heaviest is about 90N. Calibration was performed before each experiment. For the full bridge sensor used in the present invention, the main cause of gain error is the voltage drop due to the resistance between the wires connecting the excitation voltage to the bridge. To compensate for this gain error, a remote sensing wire was connected to the point where the excitation voltage wire connects to the bridge circuit. Assuming that the mechanical load applied to the crash plate causes a linear difference in the sensor readings, the output of the data acquisition system was converted to theoretical force (N) as shown in Equation 1.

here,

Q = output of the data acquisition system

Rda = resolution of data acquisition system, 16,777,216 counts (60V) ^-1

Glc = load cell gain, 2.0 × 10 ^-3 VV ^-1 (100N) ^-1

Vin = load cell input voltage, 10V

Calibration of the shaking table was necessary to determine the frequency characteristics and ensure compliance with the vibration levels in field conditions. A series of tests were performed by adjusting the relative positions of the blades located at each of the four corners of the vibrating table. During calibration, a constant speed of 275 RPM (revolutions per minute) was randomly selected. To measure vibration, three vibration sensors (Model: 356A15, PCB Piezotronics Inc., Depew, NY, USA) were installed at three different positions on the vibration table as shown in Figure 4.

Vibration levels were measured in three different directions (X, Y and Z). The average acceleration (Aw) was calculated from equation (2) and equation (3) was used to calculate the total acceleration (Av) based on ISO standard 2631-1. For data collection, the sensor was interfaced with a data acquisition module (Model: NI USB-6234, National Instruments, Austin, TX, USA) and a software program (LabVIEW 2020, National Instruments, Austin, TX, USA). A total of 32 calibration tests were performed with data collected at a sampling rate of 1 kHz.

2.3. Experimental parameters and levels for mass-free measurements

Two different layouts of impact plates were considered to test the effect of medial and lateral radiance on mass measurements. One impact plate was supported by two load cells placed 150 mm apart (Figure 5(a)) and the other was equipped with a single load cell placed in the center of the acrylic plate. To prevent damage to the load cell, an acrylic plate (300 mm .

The Jeju winter radish used in the experiment was purchased from an online market and was selected due to its high ratio considering the radish production and cultivation area. Prior to each experiment, the mass and geometric properties of the radish were recorded using digital scales and calipers. The experimental variables considered are discussed in the following sections.

2.3.1. Effect of conveyor speed, impact plate angle and drop height

Conveyor speed, drop height, and impact plate angle were investigated as experimental variables. The falling height was defined as the vertical height the radish sample traveled to the impact plate. The height was selected considering the direction of the radish on the conveyor belt during harvest. Depending on the geometry, the radishes are loaded radially and must impact the impact plate in the same direction to ensure maximum impact force. Previous studies have reported different results for radial and axial impacts. Therefore, three levels of falling height were selected: 20, 30, and 40 cm. Vertical heights greater than 50 cm are not preferred to reduce the effect of trackless drift on the impact plate.

The impact plate angle was the angle at which the plate was made horizontal. The angular range was chosen to investigate the possibility of double impact and to find the optimal angle for measuring the mass of radish. Three different positions of the impact plate were considered. These include -10°, -30° and -50°.

The maximum operating speed of the conveyor system was 0.25 m/s. In this range, three speeds were selected, namely 0.05, 0.15 and 0.25 m/s, within the range used during radish harvesting under field conditions. The horizontal distance between the conveyor and the shock plate was kept constant.

A series of experiments were performed considering four different conditions. Experiments were performed for states without vibration or tilt, with vibration only, with tilt only, and with both vibration and tilt. In the absence of vibration or inclination, conveyor speed, impact plate angle, drop height, and impact plate layout were considered as experimental variables. For tests where the test bench was subject to vibration only, the conveyor system was mounted on a vibrating table and an incline platform was used to steer through various incline levels for testing under incline conditions only. A vibrating table was mounted on an inclined platform for a combination of incline and vibration effects.

Before each vibration or tilt test, static tests were performed to verify the performance of the system. Dynamic tests were then those performed under the influence of vibration or tilt. Nine experiments were performed for each of the static and dynamic tests, for a total of 18 experiments in each condition.

2.3.2. Effect of inclination angle

Harvesting operations are carried out on radish fields, which are typically grown on agricultural land with slopes of up to 17%. Therefore, three slope levels within that range were selected. 5.24%, 10.51% and 15.84% correspond to 3°, 6° and 9° respectively.

2.3.3. effects of vibration

Under load conditions, the non-collection conveyor belt experienced vibrations between 0.37 and 0.48 m/s2 and 1.01 and 1.66 m/s2 under no load conditions (Chowdhury et al., 2020). Laboratory tests were carried out considering loading conditions including vibration levels of up to 1 m/s2. Three vibration levels were chosen: 0.43, 0.78 and 0.98 m/s2. Lastly, considering both inclination and vibration, the experiment was performed at an optimal level of 0.43 m/s2 obtained through vibration tests at inclinations of 30, 60, and 90. All experiments were conducted at three different speed levels of 0.05, 0.15, and 0.25 m/s, constant impact plate angle of -100, and drop height of 40 cm based on initial test results. The experimental design is summarized in Table 2.

[Table 2] Experimental variables and levels for measuring the mass of radish

2.4. Analysis Procedure

2.4.1. Mathematical modeling of null trajectories for impact plates.

Figure 6 shows the expected impact characteristics when a piece of material falls from the end of the conveyor onto the impact plate. From the principles of mechanics, when the mass flow is below a certain speed difference (Ehlert, 2000) as shown in equation (4), the impact force (Fp) is directly proportional to the mass (m).

Here, Fp is the impact force, m is the mass of the material, u is the initial velocity, v is the velocity after the collision, and t2-t1 is the rate of change of momentum.

If θ is the approach angle and u is the speed of impact on the impact plate along the path AC due to the gravitational effect and conveyor speed, the change in momentum in the normal direction due to the impact plate can be mathematically expressed as equation (5). Then, the impact force (Fp) defined by Newton's laws of motion will be expressed mathematically as equation (6).

Here, θ is the angle of incidence and Ψ is the angle of reflection.

2.4.2. Statistical analysis of load cell mass measurements

Coefficient of determination (R2), root mean square relative error (RE), and root mean square error (SE) are statistical analyzes used to evaluate experimental results. Analysis of variance (ANOVA) without interaction was performed using the above parameters as characteristic values, except for R2. Experimental values were assessed for normality prior to analysis. The conversion functions used for RE and SE values are given in equations (7) and (8), respectively, for a single load cell impact plate.

The characteristic variables of the double impact plate were converted using a conversion function such as equation (9).

where y is the value for the ANOVA test and x is the characteristic variable.

After the ANOVA test, differences in means were compared using Duncan's multiple range test at a 5% significance level using SAS (SAS, Institute Inc, Campus Drive Cary, NC, USA).

2.5. result

A series of measurements were performed to verify the operation and application of the measurement system. The full results of the sensor measurements for the initial tests are shown in Table 3, while Tables 4 and 5 show the results for vibration and tilt.

2.5.1. full results

[Table 3] Experimental variables, levels and statistical parameters for initial testing

[Table 4] Experimental factors, levels and statistical indicators for vibration and tilt testing

[Table 5] Experimental factors, levels and statistical indices for combined tilt and oscillation effects and signal correction.

2.5.2. Specific results for experimental variables

2.5.2.1 Drop height, impact plate angle, conveyor speed and plate layout

The height of the drop to the impact plate was not a significant factor in the zero mass measurements for both impact plates, as shown in Table 6. The relative errors at different drop heights are shown in Figures 7(a) and 7(b) for single and double impact plates, respectively, for all 30 radish samples. In both cases, the relative errors show similar trends across all samples for each shock plate.

The plate angle was an important factor affecting the mass measurements of both impact plates, and the relative error trends for 30 blank samples are shown in Figures 8(a) and 8(b) for single and double impact plates, respectively.

[Table 6] Average statistical indicators for each experimental factor level

The precision of the impact plate was higher at low conveyor speeds. For single impact plates, speed had a significant effect on plate performance, unlike for dual load cell impact plates. The relative errors at different conveyor speeds are shown in Figures 9(a) and 9(b) for single and double impact plates, respectively.

The results in Table 6 show that the standard errors for both load cell layouts were less than 4%, with a minimum of 2.29 and 2.3 for the single and dual load cell impact plates, respectively. However, further analysis of the results shows that for the double impact plate, the no-clumps are overestimated, as shown in Figures 10(c) and 10(d). Measurements of a single shock plate under the same conditions followed the equation as shown in Figures 10(a) and 10(b).

3.2 Vibration, tilt and signal compensation

As shown in Table 4, the average relative errors for dynamic and static tests are 9.89% and 5.22% for vibration tests, respectively, with a percentage difference of 47.2%. For the slope test, the corresponding values are 13.92% and 7.62%, respectively, corresponding to a percentage difference of 45.3%. The impact plate was more accurate in vibration conditions than in slope conditions. Table 3 also shows that the average relative error increases as the vibration level increases. As a result of further analysis of the vibration data, as shown in Figure 11(a), there was no clear trend of vibration and conveyor speed for mass measurement error. On the other hand, as the speed increased, the influence of the slope decreased, as shown in Figure 11(b). When tilt and vibration were combined, relative errors of 6.37% and 9.13% were observed in static and dynamic tests, respectively. Figure 11(c) shows the relevant error trends. The error is smaller than that obtained from independently applied vibration or tilt effects.

To suppress noise from no signal, a moving average filter including 5-point, 10-point, and 15-point moving averages was used. Moving average filters are known to smooth load cell signals and have been applied in a variety of yield monitoring systems. Since filtering was performed on individual no-impact signals, the points were selected considering the maximum point that occurs in a single no-impact, which is about 70 points. Figure 12 shows that the signal becomes smoother as the moving average points increase. However, this increased the relative error measurements, as can be seen in Table 5. Here, the 15-point moving average led to an average relative error of 6.04% compared to 5.42% for the 5-point moving average. In general, when using a 5-point moving average, the error due to the combination of slope and oscillation effects was reduced by up to 14.9% at all considered filtering points.

4. Discussion

The performance of impact plates largely depends on operating conditions. In this invention, the influence of several experimental variables on load cell mass measurements was investigated. The drop height from the conveyor output to the shock plate was not a significant factor in measuring the free mass of the two shock plates. This indicates that the radish struck the impact plate at the same speed and maintained the direction of the discharge trajectory on the conveyor belt. Previous studies have shown that in these cases a direct relationship exists between impact force and mass flow. In real-world conditions, this would be a desirable effect because it would lead to consistent mass measurements. The relative error showed similar variation in variation for all samples measured for both impact plates.

In contrast to the incline effect, which decreased with increasing conveyor speed, no clear trend of the vibration effect was observed. Average relative errors of 13.92%, 9.89%, and 9.13% were calculated for tilt, vibration, and combination of vibration and tilt, respectively. The load cell output can be smoothed using simple averaging of the signal. In our invention, the five-point filter resulted in a 14.9% average relative error reduction for the combination of tilt and vibration effects. Comparative results can be achieved by different techniques of digital filtering. Proper data acquisition and signal processing are key features of a yield monitoring system, including the use of anti-aliasing filters and high sample rates to prevent output contamination by harmonic noise generated by the load cell system installed.

Our results show that load cell measurements are significantly affected by various operating conditions. In field conditions where minimal vibration occurs, shock sensors can provide excellent mass measurements. Additionally, the signal processing techniques used in individual mass-based detection may differ from those used when measuring the entire product at the harvester. In particular, the low relative error for a single load cell impact plate indicates the feasibility of zero mass measurement based on the impact principle. The system of the present invention may also be applied to other similarly harvested crops. With improved accuracy, next-generation yield monitoring technology has the potential to be widely adopted in the market.

Figure 13 is a diagram showing an implementation example of the mass measurement system based on load cell measurement as described above. As shown in FIG. 13, the mass measurement system based on load cell measurement can be applied to a system that is moved to a storage unit without weight through a conveyor belt or the like. For example, a conveyor belt may be provided in a harvesting device for harvesting radishes, and a storage tank for radishes may be provided at the lower end of the conveyor belt.

The conveyor belt is provided with a driving means (12) for moving the conveyor belt and a conveyor inclination adjustment means (13) for adjusting the inclination angle of the conveyor belt, and the impulse of the radish falling through the discharge port is measured on the discharge port side of the conveyor belt. an impulse detection means (14) for detecting the vibration applied to the system when an impact occurs, a vibration detection means (15) for detecting the vibration applied to the system when an impact occurs, and a gyro sensor (16) for detecting the attitude of a moving object such as a tractor or combine on which a mass measurement system is installed. is provided.

The control unit estimates the weight of the radish by detecting the amount of impact in response to the detection results from the impact amount detection means 14, vibration detection means 15, and gyro sensor 16. The conveyor driving means 12 is controlled by the control unit so that the conveyor belt operates at a constant speed, and the conveyor belt inclination adjustment means 13 moves the conveyor belt in response to the attitude of the moving object, that is, the inclination of the moving object read from the gyro sensor 16. It is driven to constantly adjust the inclination angle.

In addition, the control unit receives the vibration result detected from the vibration detection means when calculating the weight of the radish from the impulse detected through the impulse detection means, and if the detected vibration is determined to be within a predetermined range, the calculated weight of the radish is within the correct range. However, if the detected vibration is not within the predetermined range, the calculated weight of the radish is considered to be outside the correct range and the measured weight of the radish is removed from the cumulative statistics. Therefore, when calculating the average yield of radish, the problem of the average yield of radish being statistically inaccurate due to vibration can be eliminated.

The device described above may be implemented with hardware components, software components, and/or the device described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, the devices and components described in the embodiments include, for example, a processor, a controller, an Arithmetic Logic Unit (ALU), a Digital Signal Processor, a microcomputer, and a Field Programmable Gate Array (FPGA). , may be implemented using one or more general-purpose computers or special-purpose computers, such as a PLU (Programmable Logic Unit), a microprocessor, or any other device that can execute and respond to commands. A processing device may execute an operating system (OS) and one or more software applications that run on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, there are cases where a single processing device is described, but those skilled in the art will understand that the processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are also possible.

Software may include a computer program, code, commands, or a combination of one or more of these, and may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used on any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. It can be embodied in . Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (Magneto-Optical Media) and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

As described above, although the embodiments have been described with limited examples and drawings, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims should also be construed as falling within the scope of the claims described below.

12: Conveyor driving means 13: Conveyor inclination adjustment means
14: impulse detection means 15: vibration detection means
16: Gyro sensor 20: Control unit

Claims (5)

In the load cell-based mass measurement system for monitoring radish yield provided in a radish harvesting device including a conveyor belt,
The load cell-based mass measurement system includes an impulse detection means installed at the bottom of the discharge port of the conveyor belt to detect the amount of impact of falling of nothing discharged from the discharge port; and
Characterized by comprising a control unit for calculating the weight of the radish from the falling impulse of the radish detected by the impulse detection means.
Load cell-based mass measurement system for radish yield monitoring.
According to paragraph 1,
The load cell-based mass measurement system for monitoring radish yield further includes vibration detection means for detecting vibration of the radish harvesting device,
The control unit detects vibration from the vibration detection means when the impact amount of falling without being detected by the impact amount detection means,
A load cell-based mass measurement system for monitoring radish yield, characterized in that it is configured to calculate the weight of the radish from the impact of the radish falling when the vibration value detected by the vibration detection means is within a predetermined range.
According to paragraph 2,
The control unit detects vibration from the vibration detection means when the impact amount of falling without being detected by the impact amount detection means,
A load cell-based mass measurement system for monitoring radish yield, characterized in that if the vibration value detected by the vibration detection means is outside a predetermined range, the weight of the radish calculated from the impact of falling the radish is configured to exclude the yield from the calculation.
According to paragraph 2,
The load cell-based mass measurement system for monitoring radish harvesting further includes a gyro sensor for detecting the posture of the radish harvesting device,
A load cell-based mass measurement system for monitoring radish yield, wherein the control unit is configured to adjust the inclination angle of the conveyor belt in response to the detection result from the gyro sensor.
According to paragraph 2,
The load cell-based mass measurement system for monitoring radish yield further includes conveyor belt driving means for controlling the moving speed of the conveyor belt,
A load cell-based mass measurement system for monitoring radish yield, wherein the control unit drives the moving speed of the conveyor belt at a predetermined speed through the conveyor belt driving means.