Design and test of fault monitoring system for corn precision planter

Abstract

With the growing demand and working complexity of corn precision planter, it becomes more important to monitor the working performance through intelligent systems. A new fault monitoring system for corn precision planters was designed and tested. This system consisted of the information acquisition module, controller module, alarm module, input module and display module. A capacitive sensor was utilized to monitor the seed flow without changing the track of a precision planter. This system can monitor the whole sowing process of a seed-metering device in real-time. The sowing status, fault type and fault location can be displayed on liquid crystal display (LCD). Warning light on the LCD reminds the operator of abnormal conditions. Bench tests and field tests showed that the minimum monitoring accuracies of missing sowing and total sowing number were 92.11% and 94.28%, respectively, and the seed level sensor and the opener sensor worked well. This system can accurately prompt the seed-metering mechanism in real-time.

Headnote

Abstract: With the growing demand and working complexity of corn precision planter, it becomes more important to monitor the working performance through intelligent systems. A new fault monitoring system for corn precision planters was designed and tested. This system consisted of the information acquisition module, controller module, alarm module, input module and display module. A capacitive sensor was utilized to monitor the seed flow without changing the track of a precision planter. This system can monitor the whole sowing process of a seed-metering device in real-time. The sowing status, fault type and fault location can be displayed on liquid crystal display (LCD). Warning light on the LCD reminds the operator of abnormal conditions. Bench tests and field tests showed that the minimum monitoring accuracies of missing sowing and total sowing number were 92.11% and 94.28%, respectively, and the seed level sensor and the opener sensor worked well. This system can accurately prompt the seed-metering mechanism in real-time.

Keywords: corn, precision planter, fault monitoring system, precision agriculture, capacitive sensor, missing sowing

DOI: 10.3965/j.ijabe.20150806.1968

(ProQuest: ... denotes formulae omitted.)

1 Introduction

Precision planting with the advantage of saving quality seeds can improve crop yield and solve the problem of grain shortage[1]. In conservation agriculture, land surfaces are covered by numerous corn stalks and stubbles[2-4], and ground wheels skid to block seed drop pipes. However, after sowing is completed with these coverings, the sowing status is hardly detectable. Missing sowing or box emptying, if not discovered in time, will cause huge losses[5,6]. The status of working machine is a basis for farmers to inspect the working quality of precision planting machinery and also a reference for them to manage agriculture machinery[7].

Currently, the studies about precision planting monitoring (PPM) systems are mainly focused on missing sowing, multiple-sowing, or design of missing sowing sensors[8]. Photosensors are widely used in the existing PPM systems[9]. Okopnik devised a system with the infrared sensor to determine the distance between seeds and the system was tested in the laboratory[9]. Xia et al.[10] established a PPM system on the platform of Laboratory Virtual Instrument Engineering Workbench (LabVIEW). The main performance index of seed metering devices was determined through laboratory bench tests[10]. Gong et al.[11] refitted the inner-fillingtyped metering device by installing a photosensor for inspection of missing sowing, but the application scope of this method should be broadened.

With the development of computer technology image processing and machine vision technologies were also used in sowing performance tests[12-15], but the technological application was limited by the bad field environment.

In recent years, capacitive sensors, piezoelectric sensors and other new types were also applied into planting monitoring. Zhou et al.[16] developed a capacitive sensor that could monitor the wheat flow rate by building a relationship between sensor capacitance and flow rate, which provided technical support for variable sowing. Zhou et al.[17] also analyzed the kinematic properties based on capacitance signal acquisition and the sowing performance monitoring method. At the bottom of the meter, Huang et al.[18] mounted a polyvinylidene fluoride (PVDF) piezoelectric film sensor, which generated a pulse signal when hit by a seed. However, system installation will change the seed track, thus reducing the sowing quality.

The complex and changeable field environment significantly affects the stability of metering mechanism and monitoring system. Analysis of fault types in the metering mechanism of planters showed that the faults can be caused by stop of a seed-metering wheel, much slower actual speed of seed-metering wheels than the theoretical speed, seed-box emptying and opener blocking, which can improve the sowing quality.

In this study, a PPM system from the perspective of fault part diagnosis in the metering mechanism. This study provides technical support for PPM.

2 System functions and working principle

2.1 System functions

This PPM system aims to detect the type and location of faults in a precision planter. To meet above analysis, the following four items into the functions of this PPM system.

(1) The fault location monitoring module for the seed metering mechanism will monitor seed level of the seed box, seed flow and opener block state. The monitoring system sends an alarm once a location fault occurs, and the type and location of the fault will be displayed on the liquid crystal display (LCD).

(2) The working parameters of the monitoring module for a precision planter include actual seed spacing, number of missing sowing, number of multiple-sowing, total sowing number and ground speed. When something wrong occurs to the seeder, the controller sends an alarm to inform the operator.

(3) Friendly human-computer interaction. To simplify the use of this system, we need a friendly human-computer interaction method. A matrix keyboard and an LCD module are used as the input and output devices, respectively.

2.2 Working principle

In the whole sowing process, a corn seed drops from the seed-metering mechanism, falls into the seed drop pipe, and drops on the seed bed after the opener ditches the soil. To monitor the sowing process completely, sensors have been installed into this system at the seed box, the seed drop pipe and the opener separately. The monitor sensors for seed box level, seed flow, and opener block are installed at the bottom of the seed box, on the upper part of the seed drop pipe, and at the top of the opener, respectively (Figure 1).

These sensors monitor the working states of the corresponding parts, and transport signals to the controller module. The controller module monitors the fault types and fault locations by utilizing different subroutines. The specific monitoring process is described as Figure 2.

2.2.1 Monitoring of seed box level

The monitor sensor for seed box level is installed at the bottom of the seed box. According to the experimental data, when the seed level is less than 75 mm, the sensor sends a signal indicating the seed level is low and requires to add seeds. Otherwise, when the seed level is more than 75 mm, the sensor indicates the seed amount meets the sowing needs. The judgement of empty seed box subprogram is described as Figure 3.

2.2.2 Monitoring of seed flow

When seeds drop successively and intermittently through the sensor, a pulse signal with amplitude of 12 VDC is generated. Before transmission to the counter chip, this signal is converted to a Transistor-Transistor Logic (TTL) signal via the signal conditioning circuit.

The encoder located on the rear wheel is selected as a displacement sensor of the tractor. The encoder and the rear wheel rotate at the same angular velocity. Each revolution of the encoder generates a 3600-pulse signal.

The counter chip marks the time of each seed. If the number of encoder-generated pulses between two seeds is ni, the travel distance Xi or the seed spacing can be calculated as follows:

... (1)

where, ni is the number of pulses of the Hall element in Δt; N is the number of pulses of the driving wheel (N=3600 here); d is diameter of the driving wheel (d=1.57 m).

According to GBT/6973-2005 Testing Methods of Single Seed Drills (Precision Drills), Xi between 0 and 0.5 Xr (Xr is theoretical seed spacing) is defined as multiple-sowing, Xi between 0.5Xr and 1.5Xr as normal, and Xi > 1.5 Xr as missing sowing[19]:

... (2)

... (3)

... (4)

The system controller calculates the numbers of missing sowing, multiple-sowing and normal-sowing separately. Flow rate subprogram and flowchart of missing sowing subprogram are shown in Figures 4 and 5, respectively.

2.2.3 Monitoring of opener block state

The opener block sensor has been installed on the upper part of the opener. The sensor normally outputs a low level signal. The sensor generates a pulse signal when the seed passes through in a normal sowing progress, as well as seed or soil bounce. Opener block judgement subprogram is shown in Figure 6. Once the opener is blocked, the sensor will generate a continuous high-level signal.

3 System hardware structure

The system hardware includes an information acquisition module (e.g. ground speed acquisition, seed flow acquisition), a controller module (consisting of a single-chip microcomputer), an alarm module, an input module and a display module (Figure 7).

3.1 Information acquisition module

3.1.1 Monitoring sensor unit

Each sowing unit has been installed with a seed box level sensor, a seed drop pipe sensor and an opener sensor. All capacitive sensors are TAP-30D40N1-D3 model with diameter of 30 mm and sensing distance of 0-30 mm. The details are shown in Table 1. The capacitive sensor, a non-contact sensor, can directly monitor the seed flow. The capacitive sensor has two coaxial metal electrodes inside, which form a capacitor. When the measured object (metal or nonmetal) approaches the sensor surface, it will enter the electric field generated by the two electrodes, thus changing the electric capacity of the capacitor. The output circuit detects the change and generates an output signal.

The monitoring system designed here can simultaneously monitor the working states of 6 sowing units. Each unit requires a counter to monitor the seed flow. The counter used here is a count chip 74LS590 containing storage register. Two 74LS590 chips compose a 16 bit counter. The 74LS590 chip emits tri-state outputs (high, low and high impedance), so it can be connected directly with the system data bus, thus reducing the system demand for counter resources.

3.1.2 Ground speed acquisition module

The tractor displacement is acquired from the PHB8-3600-G05L encoder. The controller gains the number of pulses every unit time, and then calculates the working velocity v and the working area Si of the tractor:

... (5)

where, v is ground speed of tractor, km/h; N is the number of pulses per revolution (N=3600 here); p is the number of pulses per second; R is the radius of the rear wheel, m.

... (6)

where, n is total number of pulses since the start-up of work; d is width of the seeder, m.

3.2 Controller module

The monitoring system needs an appropriate controller, which is very important. To achieve high performance, we selected an STC12C5A60S2 single-chip microcomputer as the controller. This system needs many I/Os in order to meet this requirement. An 8255A chip is used to extend system I/O resources.

3.3 Human-computer interaction module

In the working process, if fault (e.g. missing sowing, opener blocking and box emptying) is detected in one or several rows, the alarm module emits an alarm signal from the speaker, and displays the fault type and location on the LCD panel.

The keyboard and the display panel are important ways for the user to interact with the monitoring system. The JM160128BLCD module has been used as the display module in this system.

The system utilizes a 4×4 matrix keyboard to input information. The keyboard has 10 number buttons (0-9), 4 direction buttons (up, down, left and right), a " Confirm " button and a "Back" button.

4 Bench tests and field tests

4.1 Bench tests

Monitoring accuracies in missing sowing, multiple-sowing, number of qualified sowing and number of total sowing are significant indicators to evaluate the system performance. Bench tests and field tests are designed by reference to GBT/6973-2005, with the following division methods:

... (7)

... (8)

... (9)

... (10)

where, ni is frequency of seeds in each section, Hz; n1 is number of repeated sowing seeds; n2 is number of qualified seeds; n3 is number of missing sowing; N is total number of seeds.

The bench tests were carried out at the Agricultural Engineering Laboratory of Jilin University. A JPS-12 seed-metering mechanism performance test bench (Figure 8) was used for mechanical sowing and pneumatic sowing experiments. The measuring errors of shaft speed and seed spacing are less than 0.5% and less than or equal to 2%, respectively.

The normal plant spacing of corns in Northeast China is 260 mm. The socket of the seed metering mechanism bench has 10 holes. To guarantee the plant spacing, we set the machine working speeds at 3.12 km/h and 7.80 km/h, corresponding to the sowing shaft speeds of 20 r/min and 50 r/min, respectively. The shaft speeds were set at 20 r/min, 25 r/min, 30 r/min, 35 r/min, 40 r/min, 45 r/min and 50 r/min, respectively. In each test, the fault monitoring system monitored the sowing process in real time. The monitored indicators include the numbers of qualified sowing, missing sowing, multiple-sowing, and total sowing. The actual seed spacing is guaranteed by the image processing system in the bench, and 500 seeds are chosen as the test samples. Results are shown in Table 2.

4.2 Field tests

The field tests were carried out in the Agriculture Experimental Center of Jilin University (Figure 9). The monitoring system was installed on a 2BGH-6 inter-row tillage seeder and worked at a velocity of 4.00 km/h. The water contents at soil depth of 0-0.1 m, 0.1-0.2 m, 0.2-0.3 m and 0.3-0.4 m are 21.3%, 24.3%, 22.5% and 22.8%, respectively. To count the number of seeds facilitated, the seeder dropped the seeds on the loose surface of soil without soil covering. We measured the actual planting performance (Figure 10) and compared with the results of the monitoring system (Table 3).

The seed level and blocking condition were qualitatively judged. In the field tests, 50 tests were carried out to verify the performances of the seed level senor and the opener sensor. Results showed the monitoring system would alarm and display the fault type and fault location when the seed level is below the safe line or when the operator blocks the opener.

4.3 Result analysis

The minimum monitoring accuracies (MMAs) in numbers of missing sowing, multiple-sowing, qualified sowing and total sowing are 92.11%, 65.00%, 99.10% and 98.00% in the bench tests, respectively, and are 93.33%, 66.67%, 94.87% and 94.28% in the field tests, respectively. The MMA of missing sowing in the two situations is 92.11%, indicated the system can well monitor the missing sowing of the seed-metering mechanism. The MMA of total sowing number (94.28%) is also acceptable for monitoring of the seed-metering mechanism. Thus, this system can accurately determine the total number of seeds.

However, the MMA of multiple -sowing is only 65.00%. According to analysis, when two seeds fall through the sensor monitoring area, the sensor will give a signal. Unfortunately, the monitoring system failed to detect the multiple-sowing. Therefore, more research is needed to investigate how to improve the monitoring accuracy of multiple-sowing.

5 Conclusions

A fault monitoring system for corn precision seeders was developed. This system used capacitive sensors to monitor seed box level, seed flow condition, and opener block state. Via the capacitive sensors, the system can monitor fault type and fault location of the seed-metering mechanism.

Bench tests and field tests showed the MMAs of missing sowing number and total sowing number are 92.11% and 94.28%, respectively. In the 50 tests, the seed level sensor and the opener senor worked well. This system can meet the requirement of field working.

Acknowledgments

This paper is supported by two projects: the 12th Five Years National Science and Technology Support Plan Projects of China (No. 2014BAD06B03), the National Natural Science Foundation of China (No. 31401284). Furthermore, we would like to express our special thanks to Professor Ma Chenglin and Associate Professor Guo Li for the kind advice on our paper.

Sidebar

Citation: Qi J T, Jia H L, Li Y, Yu H B, Liu X H, Lan Y B, et al. Design and test of fault monitoring system for corn precision planter. Int J Agric & Biol Eng, 2015; 8(6): 13-19.

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