CN111998923A - Internet of things livestock breeding data acquisition method - Google Patents
Internet of things livestock breeding data acquisition method Download PDFInfo
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- CN111998923A CN111998923A CN202010950205.1A CN202010950205A CN111998923A CN 111998923 A CN111998923 A CN 111998923A CN 202010950205 A CN202010950205 A CN 202010950205A CN 111998923 A CN111998923 A CN 111998923A
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- coordinate
- weighing sensor
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- livestock
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- 244000144972 livestock Species 0.000 title claims abstract description 57
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000009395 breeding Methods 0.000 title claims abstract description 17
- 230000001488 breeding effect Effects 0.000 title claims abstract description 17
- 238000005303 weighing Methods 0.000 claims abstract description 90
- 229910000831 Steel Inorganic materials 0.000 claims description 3
- 239000010959 steel Substances 0.000 claims description 3
- 241001465754 Metazoa Species 0.000 description 8
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 208000013403 hyperactivity Diseases 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009394 selective breeding Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G17/00—Apparatus for or methods of weighing material of special form or property
- G01G17/08—Apparatus for or methods of weighing material of special form or property for weighing livestock
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01K—ANIMAL HUSBANDRY; CARE OF BIRDS, FISHES, INSECTS; FISHING; REARING OR BREEDING ANIMALS, NOT OTHERWISE PROVIDED FOR; NEW BREEDS OF ANIMALS
- A01K29/00—Other apparatus for animal husbandry
- A01K29/005—Monitoring or measuring activity, e.g. detecting heat or mating
Abstract
The invention discloses an internet-of-things livestock breeding data acquisition method, which comprises the following steps: collecting a first value F1A second value F2A third value F3And a fourth value F4(ii) a Acquiring a first coordinate (x)10), second coordinate (x)20), third coordinate (0, y)3) And fourth coordinate (0, y)4) (ii) a Solving a fifth coordinate (x, y) of the first position where the livestock to be weighed is located; respectively solving for the first distance r1A second distance r2A third distance r3A fourth distance r4(ii) a And solving the weight G of the livestock to be weighed. In the present invention, the first values F are respectively matched1A second value F2A third value F3And a fourth value F4The weighting coefficient is added, so that the errors caused by different positions of the livestock to be weighed when the livestock to be weighed are weighed can be effectively reduced, the weighing mode of the livestock is simplified, and the weighing of the livestock is realizedThe automation of livestock weighing is realized.
Description
Technical Field
The invention relates to the technical field of livestock breeding, in particular to an internet of things livestock breeding data acquisition method.
Background
The livestock is an animal highly domesticated by human, is a social product of long-term labor of human, has unique economic characters, can meet the requirements of human, forms different varieties, can normally breed offspring under the condition of artificial breeding, can change along with the change of artificial selection and production direction, and can be stably inherited.
At the in-process that the domestic animal was bred, need monitor each item data index of domestic animal to learn the weight of domestic animal each stage of breeding, traditional mode of weighing is too troublesome, is difficult to in time discover the domestic animal that the weight reaches the standard, also is difficult to filter the domestic animal of different weights, extravagant manpower and materials, and easily because the deviation of the result of weighing is caused to the hyperactivity of domestic animal.
Disclosure of Invention
In view of the defects in the prior art, the invention aims to provide an internet-of-things livestock breeding data acquisition method, and aims to solve the problem that the traditional livestock weighing mode is too troublesome and effectively reduce the deviation of the weighing result.
In order to achieve the purpose, the invention provides an internet-of-things livestock breeding data acquisition method, which comprises the following steps:
step S1, collecting a first numerical value F of a first weighing sensor in a farm1A second value F of a second weighing cell2A third value F of a third weighing cell3And a fourth value F of a fourth load cell4(ii) a A bearing plate is laid on the farm; the first weighing sensor, the third weighing sensor, the second weighing sensor and the fourth weighing sensor are respectively arranged at four corners of the farm in a counterclockwise sequence and are positioned below the bearing plate; the field of the farm is square; the distance from four corners of the farm to the center of the farm is a; establishing a first coordinate system by taking the center of the farm as a coordinate origin O, taking a first straight line passing through the first weighing sensor and the second weighing sensor as an X axis and taking a second straight line passing through the third weighing sensor and the fourth weighing sensor as a Y axis;
step S2, obtaining a first coordinate (x) of the position of the first weighing sensor10), second coordinate (x) of the position of the second load cell20), third coordinate (0, y) of the location of the third load cell3) And the fourth load cell being in positionFourth coordinate (0, y)4) (ii) a Wherein a ═ x1＝x2＝-y3＝y4；
Step S3, according to the first numerical value F1The second value F2The third value F3The fourth value F4The first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Solving a fifth coordinate (x, y) of the first position where the livestock to be weighed is located; wherein, the
The above-mentioned
Step S4, according to the fifth coordinate (x, y) and the first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Respectively solving a first distance r between the first position and the first weighing sensor1A second distance r between the first position and the second weighing sensor2A third distance r between the first position and the third weighing sensor3A fourth distance r between the first position and the fourth sensor4(ii) a Wherein the first distance
The second distance
The third distance
The fourth distance
Step S5, according to the first numerical value F1The second value F2The third value F3The fourth value F4The first distance r1The second distance r2The third distance r3The fourth distance r4And a, solving the weight G of the livestock to be weighed; wherein the weight is
The above-mentioned
The above-mentioned
The above-mentioned
And the above-mentioned
And solving a weighting coefficient for the weight of the livestock to be weighed, wherein beta is an experimental preset value, and beta is more than 0.9 and less than 1.
In the technical scheme, the fifth coordinates (x, y) of the first position where the livestock to be weighed is located can be accurately solved by acquiring the numerical values of the weighing sensors and the coordinates corresponding to the positions where the weighing sensors are located; the first value F of the first weighing sensor1The second value F of the second weighing cell2The third value F of the third weighing sensor3And said fourth value F of said fourth load cell4Changes along with the difference of the positions of the livestock to be weighed, if the numerical values are directly added, certain errors are generated, and the first numerical values F are respectively subjected to1The second value F2The third value F3And the fourth value F4The weighting coefficient is added, so that errors caused by different positions of the livestock to be weighed when the livestock to be weighed are weighed can be effectively reduced, the weighing efficiency of the livestock is improved, and the livestock is simplifiedThe automation that the domestic animal was weighed is realized to the mode of weighing.
In a specific embodiment, the method further comprises: and solving the experimental preset value beta through a preliminary experiment.
In one embodiment, the bearing plate is a steel bearing plate.
In a specific embodiment, the initial values of the first, second, third and fourth load cells are corrected, i.e. when there is no livestock to be weighed on the bearing plate, the initial values of the first, second, third and fourth load cells are all zero.
In one embodiment, the bearing plate is a grid-like hollow.
In one embodiment, the livestock to be weighed is located on the load-bearing plate.
The invention has the beneficial effects that: in the invention, the fifth coordinates (x, y) of the first position where the livestock to be weighed is located can be accurately solved by acquiring the numerical values of the weighing sensors and the coordinates corresponding to the positions of the weighing sensors; the first value F of the first weighing sensor1The second value F of the second weighing cell2The third value F of the third weighing sensor3And said fourth value F of said fourth load cell4Changes along with the difference of the positions of the livestock to be weighed, if the numerical values are directly added, certain errors are generated, and the first numerical values F are respectively subjected to1The second value F2The third value F3And the fourth value F4The weighting coefficient is added, so that errors caused by different positions of the livestock to be weighed when the livestock to be weighed are weighed can be effectively reduced, the weighing efficiency of the livestock is improved, the weighing mode of the livestock is simplified, and the weighing automation of the livestock is realized.
Drawings
Fig. 1 is a flow chart of a livestock breeding data acquisition method of the internet of things according to an embodiment of the invention;
FIG. 2 is a diagram illustrating the positional relationship between each load cell and the livestock to be weighed in accordance with one embodiment of the present invention;
fig. 3 is a schematic view showing the respective load cells and the load applied to the livestock to be weighed according to an embodiment of the present invention.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
as shown in fig. 1, in an embodiment of the present invention, there is provided an internet of things livestock breeding data acquisition method, including:
step S1, collecting a first numerical value F of a first weighing sensor in a farm1A second value F of a second weighing cell2A third value F of a third weighing cell3And a fourth value F of a fourth load cell4(ii) a A bearing plate is laid on the farm; the first weighing sensor, the third weighing sensor, the second weighing sensor and the fourth weighing sensor are respectively arranged at four corners of the farm in a counterclockwise sequence and are positioned below the bearing plate; the field of the farm is square; the distance from four corners of the farm to the center of the farm is a; establishing a first coordinate system by taking the center of the farm as a coordinate origin O, taking a first straight line passing through the first weighing sensor and the second weighing sensor as an X axis and taking a second straight line passing through the third weighing sensor and the fourth weighing sensor as a Y axis;
step S2, obtaining a first coordinate (x) of the position of the first weighing sensor10), second coordinate (x) of the position of the second load cell20), third coordinate (0, y) of the location of the third load cell3) And a fourth coordinate (0, y) of the location of the fourth load cell4) (ii) a Wherein a ═ x1＝x2＝-y3＝y4；
Step S3 according to the aboveA value F1The second value F2The third value F3The fourth value F4The first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Solving a fifth coordinate (x, y) of the first position where the livestock to be weighed is located; wherein, the
The above-mentioned
Step S4, according to the fifth coordinate (x, y) and the first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Respectively solving a first distance r between the first position and the first weighing sensor1A second distance r between the first position and the second weighing sensor2A third distance r between the first position and the third weighing sensor3A fourth distance r between the first position and the fourth sensor4(ii) a Wherein the first distance
The second distance
The third distance
The fourth distance
Step S5, according to the first numerical value F1The second value F2The third value F3The fourth value F4The first distance r1The second distance r2The third distance r3The fourth distance r4And a, solving the weight G of the livestock to be weighed; wherein the weight is
The above-mentioned
The above-mentioned
The above-mentioned
And the above-mentioned
And solving a weighting coefficient for the weight of the livestock to be weighed, wherein beta is an experimental preset value, and beta is more than 0.9 and less than 1.
In this embodiment, the method further includes:
and solving the experimental preset value beta through a preliminary experiment.
It is worth mentioning that the method for solving the experiment preset value beta in advance through experiments comprises the following steps:
the livestock to be weighed is positioned at the center of the farm to obtain the standard weight G of the livestock to be weighed;
the livestock to be weighed is positioned at a second position to obtain a numerical value F of the first weighing sensor1', value F of said second load cell2', value F of said third load cell3', value F of said fourth load cell4′；
Solving for a sixth coordinate (x ', y') of the second location;
solving for the distance r between the second location and the first weighing cell1', a distance r between the second position and the second load cell2', a distance r between the second position and the third weighing sensor3' and the second position anddistance r of the fourth weighing sensor4′；
According to
And solving the experimental preset value beta.
In this embodiment, the bearing plate is a steel bearing plate.
In this embodiment, the initial values of the first weighing cell, the second weighing cell, the third weighing cell and the fourth weighing cell are corrected, that is, when there is no livestock to be weighed on the bearing plate, the initial values of the first weighing cell, the second weighing cell, the third weighing cell and the fourth weighing cell are all zero.
In this embodiment, the bearing plate is a grid-shaped hollow.
In this embodiment, the livestock to be weighed is located on the bearing plate.
The equations involved in this example are derived as follows:
as shown in fig. 2-3, the distance between two points can be calculated as:
a first distance between the first position and the first load cell
A second distance between the first position and the second load cell
A third distance between the first position and the third weighing sensor
And a fourth distance between the first position and the fourth sensor
In the direction along the X-axis, from the moment balance:
F1(x-x1)＝F2(x-x2) Is simplified to obtain
In the direction along the Y-axis, from the moment balance:
F3(y-y3)＝F4(y-y4) Is simplified to obtain
Specific embodiments of the present invention have been described above in detail. It is to be understood that the specific embodiments of the present invention are not exclusive and that modifications and variations may be made by one of ordinary skill in the art in light of the spirit of the present invention, within the scope of the appended claims. Therefore, technical solutions that can be obtained by a person skilled in the art through logic analysis, reasoning or limited experiments based on the prior art according to the embodiments of the present invention should be within the scope of protection defined by the claims.
Claims (6)
1. An internet-of-things livestock breeding data acquisition method is characterized by comprising the following steps:
step S1, collecting a first numerical value F of a first weighing sensor in a farm1A second value F of a second weighing cell2A third value F of a third weighing cell3And a fourth value F of a fourth load cell4(ii) a A bearing plate is laid on the farm; the first weighing sensor, the third weighing sensor, the second weighing sensor and the fourth weighing sensor are respectively arranged at four corners of the farm in a counterclockwise sequence and are positioned below the bearing plate; the field of the farm is square; the distance from four corners of the farm to the center of the farm is a; taking the center of the farm as a coordinate origin O, taking a first straight line passing through the first weighing sensor and the second weighing sensor as an X axis, and passing through the first weighing sensor and the second weighing sensorA second straight line of the third weighing sensor and the fourth weighing sensor is used as a Y axis to establish a first coordinate system;
step S2, obtaining a first coordinate (x) of the position of the first weighing sensor10), second coordinate (x) of the position of the second load cell20), third coordinate (0, y) of the location of the third load cell3) And a fourth coordinate (0, y) of the location of the fourth load cell4) (ii) a Wherein a ═ x1＝x2＝-y3＝y4；
Step S3, according to the first numerical value F1The second value F2The third value F3The fourth value F4The first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Solving a fifth coordinate (x, y) of the first position where the livestock to be weighed is located; wherein, the
The above-mentioned
Step S4, according to the fifth coordinate (x, y) and the first coordinate (x)10), the second coordinate (x)20), the third coordinate (0, y)3) And the fourth coordinate (0, y)4) Respectively solving a first distance r between the first position and the first weighing sensor1A second distance r between the first position and the second weighing sensor2A third distance r between the first position and the third weighing sensor3A fourth distance r between the first position and the fourth sensor4(ii) a Wherein the first distance
The second distance
The third distance
The fourth distance
Step S5, according to the first numerical value F1The second value F2The third value F3The fourth value F4The first distance r1The second distance r2The third distance r3The fourth distance r4And a, solving the weight G of the livestock to be weighed; wherein the weight is
The above-mentioned
The above-mentioned
The above-mentioned
And the above-mentioned
And solving a weighting coefficient for the weight of the livestock to be weighed, wherein beta is an experimental preset value, and beta is more than 0.9 and less than 1.
2. The internet of things livestock breeding data acquisition method of claim 1, further comprising: and solving the experimental preset value beta through a preliminary experiment.
3. The method for collecting livestock breeding data of the internet of things as claimed in claim 1, wherein said bearing plate is a steel bearing plate.
4. The method for acquiring livestock breeding data of the internet of things of claim 1, wherein the initial values of the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are corrected, that is, when there is no livestock to be weighed on the bearing plate, the initial values of the first weighing sensor, the second weighing sensor, the third weighing sensor and the fourth weighing sensor are all zero.
5. The method for collecting livestock breeding data of the internet of things as claimed in claim 1, wherein said bearing plate is a grid-like hollow.
6. The method for acquiring the livestock breeding data of the internet of things as claimed in claim 1, wherein the livestock to be weighed are positioned on the bearing plate.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020050411A1 (en) * | 2000-11-02 | 2002-05-02 | Shimazu Corporation | Electronic balance |
| US20040168836A1 (en) * | 2002-11-14 | 2004-09-02 | Steven Petrucelli | Weighing scale adapted for allowing a user to find an optimal weighing position on the scale |
| US20040245026A1 (en) * | 2003-05-09 | 2004-12-09 | Franco Brighenti | Weighing system |
| CN1659583A (en) * | 2002-05-08 | 2005-08-24 | 3M创新有限公司 | Baselining techniques in force-based touch panel systems |
| US20150268089A1 (en) * | 2012-12-04 | 2015-09-24 | Mettler Toledo (Changzhou) Precision Instrument Lt | Weighing system and weighing method having weighing uninterrupted functions |
| US20160342969A1 (en) * | 2015-04-29 | 2016-11-24 | Jorge Eduardo Perez Jacome | Force location apparatus, systems, and methods |
| CN106500810A (en) * | 2016-11-15 | 2017-03-15 | 北京万集科技股份有限公司 | A kind of target vehicle Weighing method and system |
| CN107290106A (en) * | 2017-07-18 | 2017-10-24 | 广州市残疾人辅助器具服务中心 | A kind of wheelchair device for detecting center of gravity and detection method |
| US20180340856A1 (en) * | 2017-05-26 | 2018-11-29 | Metter-Toledo (Changzhou) Measurement Technology Co. Ltd. | Center of gravity offset detection method and platform scale |
| WO2019054543A1 (en) * | 2017-09-15 | 2019-03-21 | 주식회사 스퀘어 | Weighing device having position-adjustable load cell |
| CN110689271A (en) * | 2019-10-02 | 2020-01-14 | 龙岩华崇信息科技有限公司 | Internet of things intelligent weighing integrated management platform and management method |
-
2020
- 2020-09-11 CN CN202010950205.1A patent/CN111998923B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020050411A1 (en) * | 2000-11-02 | 2002-05-02 | Shimazu Corporation | Electronic balance |
| CN1352380A (en) * | 2000-11-02 | 2002-06-05 | 株式会社岛津制作所 | Electronic balance |
| CN1659583A (en) * | 2002-05-08 | 2005-08-24 | 3M创新有限公司 | Baselining techniques in force-based touch panel systems |
| US20040168836A1 (en) * | 2002-11-14 | 2004-09-02 | Steven Petrucelli | Weighing scale adapted for allowing a user to find an optimal weighing position on the scale |
| US20040245026A1 (en) * | 2003-05-09 | 2004-12-09 | Franco Brighenti | Weighing system |
| US20150268089A1 (en) * | 2012-12-04 | 2015-09-24 | Mettler Toledo (Changzhou) Precision Instrument Lt | Weighing system and weighing method having weighing uninterrupted functions |
| US20160342969A1 (en) * | 2015-04-29 | 2016-11-24 | Jorge Eduardo Perez Jacome | Force location apparatus, systems, and methods |
| CN106500810A (en) * | 2016-11-15 | 2017-03-15 | 北京万集科技股份有限公司 | A kind of target vehicle Weighing method and system |
| US20180340856A1 (en) * | 2017-05-26 | 2018-11-29 | Metter-Toledo (Changzhou) Measurement Technology Co. Ltd. | Center of gravity offset detection method and platform scale |
| CN107290106A (en) * | 2017-07-18 | 2017-10-24 | 广州市残疾人辅助器具服务中心 | A kind of wheelchair device for detecting center of gravity and detection method |
| WO2019054543A1 (en) * | 2017-09-15 | 2019-03-21 | 주식회사 스퀘어 | Weighing device having position-adjustable load cell |
| CN110689271A (en) * | 2019-10-02 | 2020-01-14 | 龙岩华崇信息科技有限公司 | Internet of things intelligent weighing integrated management platform and management method |
Non-Patent Citations (1)
| Title |
|---|
| 朱亚男: "《轨道衡称重的建模方法与模拟加载仿真研究》", 《工业仪表与自动化装置》 * |
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Denomination of invention: A Data Collection Method for Livestock Breeding in the Internet of Things Granted publication date: 20211001 Pledgee: Agricultural Bank of China Limited by Share Ltd. Putian branch Pledgor: RUIMA ELECTRIC MANUFACTURING (FUJIAN) Co.,Ltd. Registration number: Y2024980001317 |