JPH0530819A - Mud surface detector for paddy field - Google Patents

Abstract

PURPOSE:To provide the title detector, a contact-type sensor for detecting paddy surface capable of easily, accurately detect the paddy surface state such as air, water, or mud. CONSTITUTION:A vibration-type mud surface sensor 48 designed to bring its vibration surface 48a into contact with paddy surface is provided, and based on the change in the pressure due to vibratory action detected by said sensor 48, the paddy surface state is detected.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a paddy field mud level detection device for use in a rice transplanter, for example, when performing constant control of planting depth.

[0002]

2. Description of the Related Art As this kind of detecting device for detecting the position of the mud surface below the water surface, for example, an ultrasonic sensor disclosed in Japanese Patent Laid-Open No. 64-20017 or Japanese Patent Laid-Open No. 1-181715 is used.
There is one using a pressure-sensitive sensor disclosed in Japanese Unexamined Patent Publication.

[0003]

However, when it is attempted to directly detect the mud surface with such an ultrasonic sensor or a pressure-sensitive sensor, an extremely high detection accuracy is required, and accordingly false detection is performed. There are many drawbacks that make the planting depth control based on these detections unstable.

[0004]

SUMMARY OF THE INVENTION Therefore, the present invention provides a vibrating mud surface sensor for bringing a vibrating surface into contact with a paddy surface, and detects the paddy surface state based on a change in the magnitude of the vibration acting pressure detected by the mud surface sensor. By doing so, the mud surface can be detected more accurately, and the planting depth control can be made highly accurate.

[0005]

Embodiments of the present invention will now be described in detail with reference to the drawings. FIG. 1 is a side view of a planting section, FIG. 2 is a side view of a riding rice transplanter, and FIG. 3 is a plan view thereof. In the figure, (1) is a traveling vehicle on which an operator rides, and an engine (2). The rear end of the vehicle body frame (3) on which the vehicle is mounted is connected to the mission case (4), and the front wheels (6) for traveling the paddy field are supported on both sides of the front part of the mission case (4) through the axle case (5). At the same time, a transmission case (7) is continuously provided on both sides of the rear portion of the transmission case (4), and a rear wheel (8) for traveling a paddy field is supported at a rear end portion of the transmission case (7). Then, a spare seedling stand (10) is attached to both sides of the hood (9) that covers the engine (2) and the like, and the transmission case (7) and the like are covered by a vehicle body cover (12) forming a step (11). Driver's seat (13) above the body cover (12)
A steering handle (14) is provided at the rear of the hood (9) in front of the driver's seat (13).

Reference numeral (15) in the drawing denotes a planting section provided with a seedling table (16) for multi-row planting, a plurality of planting claws (17), etc. Forward tilting seedling stand (1
6) is supported by the planting case (20) via the lower rail (18) and the guide rail (19) so as to be slidable left and right, and at the same time, the rotary case (21) is rotated at a constant speed in one direction. The nail case (22) (22), which is a pair of planting arms, is disposed in a symmetrical position about the rotation axis of the case (20) and is supported by the case (20). Attach the planting claws (17) (17) to the. A support frame (24) is provided on the front side of the planting case (20) via a rolling fulcrum shaft (23), and a three-point link mechanism (27) including a top link (25) and a lower link (26) is provided. The link frame (27) by connecting a support frame (24) to the rear side of the traveling vehicle (1).
Lifting cylinder (2) that lifts and lowers the planting part (15) via the
8) is connected to the lower link (26), and the front and rear wheels (6) and (8) are driven to move and move at a substantially constant speed, and at the same time, the stock is placed from the seedling stand (16) that slides back and forth to the left and right. The seedlings are picked up by the planting claws (17), and the seedlings are continuously planted.

Further, reference numeral (29) in the figure denotes a traveling speed change lever,
(30) is a planting lift lever, (31) is a planting sensitivity adjusting lever, (32) is a traveling clutch pedal, and (33) (3
3) is a left and right brake pedal, (34) ... is a float for leveling the field, and supports the float (34) ... under the planting case (20) via a planting depth adjusting link (35) and the like. To do.

As shown in FIG. 4, the support frame (2
4) A central vertical frame (35) integrally connected to the upper end of 4),
Seedling support columns (36) that support the left and right sides of the seedling mounting table (16)
A hydraulic horizontal reciprocating rolling cylinder (37), which is a rolling control actuator, is interposed between the (36) and the fixing bracket (3) of the frame (35).
8) Rolling cylinder (37) via support shaft (39)
While mounting the cylinder (37), attach both ends of the left and right piston rods (40) to the left and right columns (36).
The cylinder (3) is connected to the connecting rod (41) between the (36) via the arm (42) and the universal joint (43).
When the piston rod (40) is moved left and right by operating the solenoid valve (45) that supplies the hydraulic pressure from the hydraulic pump (44) to 7), the planting part (15) is moved left and right about the fulcrum shaft (23). It is structured so as to swing horizontally to maintain this level.

Further, one pendulum type horizontal sensor (46) for rolling detection is provided in the center of the planting case (20).
And a piezoelectric rolling angular velocity sensor (47) for detecting the angular velocity when the machine body rotates left and right on the body frame (3) on the machine side.
6) With (47), the right and left inclination of the planting part (15),
The angular velocity generated at the time of this inclination is detected.

Further, two right and left vibrating mud surface sensors (48) for detecting the rice field condition are provided on both left and right sides of the central planting case (20), and a gear case fixedly connected to the planting case (20) side. The support arm (50) of the mud level sensor (48) is movably supported by (49), and the rack and pinion mechanism (5) is attached to the vertical position adjusting motor (51).
The support arm (50) is interlockingly connected via the (2), and the mud level sensor (4) is moved from the lowest point of the planting claw (17).
The distance (d) to the vibrating surface (48a) of 8) can be adjusted by driving the motor (51).

As shown in FIGS. 5 to 6, the mud surface sensor (48) includes a piezoelectric ceramic thin plate (53) having electrodes (a) and (b) formed on both sides thereof, and a thin metal vibrating plate (54).
A piezoelectric vibrator (55) bonded to the main electrode (55a) and the common electrode (5) between the electrodes (a) and (b) are used.
5b) voltage is applied to the piezoelectric ceramic thin plate (5
3) expands and contracts in the radial direction, and when the whole vibrator (55) vibrates flexibly, the common electrode (55b) and the return electrode (55)
Distortion of piezoelectric ceramics generated during c) (amplitude of vibration)
By detecting a feedback output voltage which is a charge according to the above, it is configured to determine whether the vibrating surface (48a) is in contact with air, water or mud.

A solenoid valve (56) for operating the lifting cylinder (28) and a control circuit (57) for controlling the drive of the solenoid valve (45) of the rolling cylinder (37) are provided with:
Automatic switch (58) and lever switch with plant (59)
And the respective sensors (46) (47) (48) are input-connected to control the planting depth of the planting section (15) based on the detection of the mud surface sensor (48) and the horizontal sensor (46).
The fuzzy inference is used for horizontal control of the planting part (15) based on the detection of the angular velocity sensor (47).

This embodiment is configured as described above, and is for controlling the planting depth by operating the solenoid valve (56) of the lifting cylinder (28) based on the detection of the mud level sensor (48). As shown in FIG. 7, the feedback output from the sensor (48), that is, the magnitude of the amplitude of the vibrator (55) is the vibration surface (4
The mud surface sensor (48) is used to determine which of air, water and mud is in contact by utilizing the fact that the contact state of air, water and mud of 8a) and the difference in density change.
The output characteristics are, for example, in the order of air>water> mud, and the hardness of the mud surface varies within a certain range (D) depending on the field. Therefore, the setting level (C) of the sensor (48) is The height of the planting part (15) is controlled so as to maintain it at a level slightly lower than the water at the boundary with the planting claws (17) so that seedlings can be planted at a certain depth from the mud surface. The distance (d) from the lowest point to the vibrating surface (48a) is adjusted and set in advance.

This control will be described below with reference to the flow charts of FIGS. When the automatic switch (58) is on and the planting lever switch (59) is on, automatic control is started. When the mud level sensor (48) detects the set level (A), the planting section In (15), the current position is maintained, and when the above or below the set level (A) is detected, the raising / lowering control is performed so that the planting section (15) is on the deep planting side or the shallow planting side. Then, next, the lateral correction amount (S) of the planting part (15) is obtained by fuzzy inference according to the values of the inclination angle θ and the angular velocity V detected by the horizontal sensor (46) and the angular velocity sensor (47). When the rolling cylinder (37) is driven by the correction instruction amount (S0) to perform the fuzzy horizontal control for keeping the planting part (15) horizontal, and after this control, the planting lever switch (59) is turned on. The same planting depth control and horizontal control as described above are repeatedly performed, and when the switch (59) is off, the planting section (1
Drive control of the rolling cylinder (37) is performed in which 5) is raised and the center is horizontally returned to the left and right at this raised position.

Next, fuzzy control will be described with reference to the subroutine flowchart of FIG. Now, when the detected values of the tilt angle θ and the angular velocity V are read (step 1),
In step 2, the specific values of the detected values θ and V are changed from −5 to +
Allocate to 11 divisions by integers up to 5 (areaize). For example, in the case of indicating the inclination angle θ, if the negative sign (−) is the left downward slope and the positive sign (+) is the right downward slope, θ is −
The range from 1 degree to +1 degree is the range of "0", and the value from -8 degrees to +8 degrees is a total of 11 categories in the following 1.4 degree divisions, [-5, -4, -3, -2, -1, 0, 1, 2,
3, 4, 5] (see FIGS. 11 to 12).

Then, for both θ and V, the weight of the membership function with respect to the value in the region from −5 to +5 is obtained from the data read from the read-only memory (ROM).

Next, in step 3, the fuzzy rule based on fuzzy inference is applied, and in step 4, the table of the membership function of the correction amount S for posture control of the planting part (15) is referred to MAX-MINIMUM. Then, the correction instruction amount S0 is obtained by the center of gravity method in step 5, and in step 6, an output signal to the rolling cylinder (37) which is an actuator is output corresponding to the instruction amount S0.
The right and left posture of the planting part (15) is controlled to be substantially horizontal.

That is, the fuzzy inference generally uses a control algorithm as an input variable of a plurality of information for controlling, for example,
It is described as an ambiguous relationship between two input variables (x, y) and an output (manipulation amount) z to the control device. For example, "if x is small and y is large, z is set to the inside. The control algorithm is expressed by (if-then ...) fuzzy rules in the form of (if-then). Now, when applying this fuzzy rule to attitude control, In the example, it is expressed by 17 rules shown in FIG. 10, the inclination angle θ and the angular velocity V which are the “if” part of the rule are the antecedent parts, and the correction amount S which is the “then” part is the latter part. The subject section.

Further, the fuzzy variables taken by the input variables θ, V and the output variable S are shown as discrete fuzzy variables discretized into integer regions, which are shown in FIGS. 11 to 13.

These fuzzy variables are "large right", "small right", "0", "small left", as labels.
There are five types of "large left".

In this case, the fuzzy variable area, which is an ambiguous area, is defined by giving the degree (grade) in which the elements (members) of the entire set of input variables are included in the area (domain). The function that gives this grade is called the membership function. For example,
The region of the fuzzy variable of θ is defined by giving the degree (grade) in which the elements (members) of the whole set of the inclination angle θ are included in the region (domain), and in the embodiment, the grade in each domain is 0. It is represented by an integer from 1 to 10.

The reasoning method in fuzzy control is as follows. For example, the output S (consequent part) for the antecedent part ((1) to (17)) of a two-input set of θ and V
Considering the case of, first, the membership function A (θi) is obtained from the chart (FIG. 11) of the membership function corresponding to the value of the antecedent part of each input θ, and the value of the antecedent part of the input G is obtained. The value of the membership function A (Vi) is obtained from the membership function chart (FIG. 12) corresponding to. Since it can be seen that there can be a plurality of labels for the regions of each input θ and V, among the combinations of the labels, ((1) to (1
The values of the membership functions A (θi) and A (Vi) in the i-th rule (up to 7) are obtained from FIG. 10, and the goodness of fit ωi = A (θi) depending on the set of the inputs θi and Vi.
* Calculate A (Vi). Here, * is a symbol of mini (intersection in a fuzzy set, the same applies hereinafter).

Then, the inference result corresponding to the i-th rule is obtained from FIG. 13, and its membership function B (si)
Then, the goodness of fit wiB (si) = ωi * B (si) is obtained.

Next, similarly to the above, the values of the membership functions A (θj) and A (Vj) in the j-th rule corresponding to the values of the antecedent parts of the inputs θ and V are shown in FIGS.
And the goodness of fit ωj = A (θj) * A (Vj)
Ask for.

Next, the inference result corresponding to the j-th rule is obtained from FIG. 9, and the goodness of fit wjB (sj) = ωj * B (sj) is obtained from the membership function B (sj) (FIG. 1).
2).

When the consequent parts of the plurality are, for example, i-th, j-th, k-th, and l-th, the total inference result S0 by these four rules is wiB (si), wj.
From B (sj), wkB (sk), and wlB (si),
B * = wiB (si) UwjB (sj) UwkB (s
k) UwlB (sl) is created (U is a symbol of union), and is calculated as the center of gravity of the membership function of B *.

This control will be described by applying actual numerical values. Now, it is assumed that the inclination angle θ and the angular velocity V are detected, and the region of θ is “0” and the region of V is “−3”.

First, looking at the vertical frame in the area "0" from FIG. 11, the label "5" in "small right" is displayed.
Since it spans "10" in "0" and "5" in "small left", it can be understood that the labels of these three fuzzy variables can be taken.

For the angular velocity V, the area "-" in FIG.
Looking at the vertical frame corresponding to the category of "3", the label "0"
It is possible that these three fuzzy variables can be adopted, because they span “3” in “3”, “8” in “small left”, and “5” in “large left”.

However, the fuzzy rule based on the data set of θ and V is (1), if found from FIG.
(3), (4), (5), (6), (9), (11),
The eight rules of (17) correspond, and the labels of the consequent part S corresponding to these eight rules are "0 (neutral)", "small right up", "small left up", and "small left up", respectively. ,
It can be seen that the values are "0", "small left raising", "large left raising", and "large left raising".

These membership functions are shown in FIG.
Referring to FIG. 13, the fuzzy rule (1) is shown in (1), (2) and (3) of FIG. 14, and the fuzzy rule of (3) is shown in (1) and (2) of FIG. , (3), and regarding the fuzzy rule of (4), (1) of FIG.
Shown in (2) and (3). Other fuzzy rules are obtained in the same manner, so illustrations are omitted.

In this case, for example, regarding the fuzzy rule of (1), when the values of ωi of θ and V are compared,
Is 0, the value at the position of “0” is “10”, and the value of V is at the position of “−3” is “3”.
Is the minimum value, the minimum value is adopted, and the conformity ωi of the correction amount S is the area surrounded by the thick line which is a portion below the height “3” as shown in (3) of FIG. Become.

Similarly, the membership function in each consequent part S in the rules (3) and (4) is the area surrounded by the thick line shown in (3) of FIG. 15 and (3) of FIG. Become.

Similarly, other (5), (6),
Regarding the rules of (9), (11), and (17), θ and V
The values of ω are compared and the minimum side is adopted, and the region of the membership function in each consequent part S is obtained from these.

Then, the correction instruction amount S0 of the whole inference result by the above eight rules is obtained by calculating the union of the minimum regions of the membership function in each consequent part S (this is MA
X-MINIMUM method), is obtained as the center of gravity of the area surrounded by the outermost area when the membership functions of 8 S are overlapped (this is called the center of gravity method), and the horizontal coordinate position is instructed to be corrected. The amount (see FIG. 17). At this time,
Do not add overlapping area parts.

In this embodiment, the correction instruction amount S0 is approximately 1.07.
Becomes According to this numerical value, an output signal is output from the control circuit (57) to activate the rolling cylinder (37) which is an actuator for rolling control, and the planting section (1
5) is corrected so that the posture is horizontal.

Further, the membership function in each of the fuzzy inferences may be replaced by the above-mentioned "discrete type (step type)", and "well-bell type" or "triangular type" well known in fuzzy theory may be adopted. It's good.

As described above, when the fuzzy control is performed in which the inclination angle and the inclination angular velocity are used as the antecedent section (input section) and the correction amount of the lateral inclination of the planting section (15) is used as the consequent section (output section). , Compared to conventional numerical control that considers the tilt angle and acceleration and tilt speed in some cases (control that uses a mathematical relationship with the detected value of the input as a variable), it is ambiguous but lacks precision. However, it is possible to realize a quick and smooth (not jerky) movement control.

Therefore, in the case of the embodiment, not only the central position sensor float (34) can be eliminated by using the mud level sensor (48) but also the horizontal sensor (46) and the angular velocity sensor. With the combination of (47), it is possible to eliminate all floats (34).

The greater the number of the mud level sensors (48) installed, the higher the detection accuracy. Further, in the fuzzy horizontal control in the above-described embodiment, the configuration is shown in which only the correction instruction amount S0 is obtained for control, but at the same time, the control speed is also obtained, and the correction speed changes to the optimum speed when correcting the left and right inclination. By doing so, the control can be performed with higher accuracy.

[0041]

As is apparent from the above embodiments, according to the present invention, a vibrating mud surface sensor (48) for contacting the vibrating surface (48a) with the rice field is provided and detected by the mud surface sensor (48). Since the rice field condition is detected based on the magnitude change of the vibration acting pressure, the vibration surface (4) of the mud surface sensor (48) is detected.
8a) makes it possible to easily detect the soft and hard condition of the paddy field that comes into contact with it, and as a result, it becomes possible to control the absolute value of the vegetation depth. It has a remarkable effect that it can be abolished.

[Brief description of drawings]

FIG. 1 is a side view of a planting section.

FIG. 2 is an overall side view of a rice transplanter.

FIG. 3 is an overall plan view of a rice transplanter.

FIG. 4 is an explanatory diagram of horizontal control.

FIG. 5 is an explanatory diagram of a mud level sensor.

FIG. 6 is a control circuit diagram.

FIG. 7 is an output characteristic diagram of a mud level sensor.

FIG. 8 is a flowchart.

FIG. 9 is a flowchart.

FIG. 10 is an explanatory diagram of a fuzzy rule.

FIG. 11 is an explanatory diagram showing a membership function of a tilt angle θ.

FIG. 12 is an explanatory diagram showing a membership function of an angular velocity V.

FIG. 13 is an explanatory diagram showing a membership function of a correction amount S.

FIG. 14 is an explanatory diagram of a membership function in the case of fuzzy rule (1).

FIG. 15 is an explanatory diagram of a membership function in the case of fuzzy rule (3).

FIG. 16 is an explanatory diagram of a membership function in the case of fuzzy rule (4).

FIG. 17 is an explanation of the MAX-MINIMUM method and the area centroid method.

[Explanation of symbols]

 (48) Mud surface sensor (48a) Vibration surface

Claims (1)

Claim: What is claimed is: 1. A vibrating mud surface sensor for contacting a vibrating surface with a rice field surface is provided, and the rice field state is detected based on a change in the magnitude of the vibration acting pressure detected by the mud surface sensor. A mud level detection device for paddy fields, which is configured.