CN113408166B - Reliability analysis method of adaptive spike Gao Bo receptor type intelligent breeding system - Google Patents
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- 238000009395 breeding Methods 0.000 title claims abstract description 50
- 230000001488 breeding effect Effects 0.000 title claims abstract description 49
- 238000004458 analytical method Methods 0.000 title claims abstract description 28
- 230000003044 adaptive effect Effects 0.000 title claims description 7
- 241000209094 Oryza Species 0.000 claims abstract description 25
- 235000007164 Oryza sativa Nutrition 0.000 claims abstract description 25
- 235000009566 rice Nutrition 0.000 claims abstract description 25
- 230000003068 static effect Effects 0.000 claims abstract description 17
- 238000012360 testing method Methods 0.000 claims abstract description 16
- 230000010152 pollination Effects 0.000 claims abstract description 15
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- 239000000463 material Substances 0.000 claims description 12
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- 229920001778 nylon Polymers 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004804 winding Methods 0.000 claims description 6
- PMGQWSIVQFOFOQ-YKVZVUFRSA-N clemastine fumarate Chemical compound OC(=O)\C=C\C(O)=O.CN1CCC[C@@H]1CCO[C@@](C)(C=1C=CC(Cl)=CC=1)C1=CC=CC=C1 PMGQWSIVQFOFOQ-YKVZVUFRSA-N 0.000 claims description 3
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- 210000005069 ears Anatomy 0.000 claims description 3
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01H—NEW PLANTS OR NON-TRANSGENIC PROCESSES FOR OBTAINING THEM; PLANT REPRODUCTION BY TISSUE CULTURE TECHNIQUES
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Abstract
The invention discloses a reliability analysis method of a self-adaptive spike Gao Bo receptor type intelligent breeding system, which comprises the following steps: s1, three-dimensional modeling of an intelligent breeding system; s2, determining different working conditions of a breeding system based on an orthogonal test; s3, calculating the load under the complex working condition based on dynamic simulation; s4, checking statics analysis of the intelligent breeding system; s5, analyzing the fatigue life of the system based on stress curve correction. The method can effectively replace manpower to carry out supplementary pollination, and can improve pollination efficiency, reduce rice planting cost and improve mechanization rate in the rice planting process.
Description
Technical Field
The invention relates to the field of mechanical auxiliary pollination, in particular to a reliability analysis method of a self-adaptive spike Gao Bo receptor type intelligent breeding system.
Background
Rice is one of main grain crops, and related researches on hybrid rice with wide adaptability and high yield are more. The existing breeding method has the defects of low manpower and material consumption, low production efficiency, incapability of meeting the requirements of modern seed production, low integration level, easy damage and the like of the existing mechanized auxiliary device, and low practical applicability.
Under the background, the method provides a self-adaptive spike Gao Bo receptor type intelligent breeding system, performs spike pulling breeding work through self-adaptive spike height, performs reliability and safety verification analysis by combining dynamic, statics and fatigue life analysis, and has great research significance on intelligent rice breeding.
Disclosure of Invention
The invention aims to: the invention aims to provide a system capable of performing mechanical supplementary pollination, which can automatically detect the rice field environment and perform supplementary pollination.
The technical scheme is as follows: the invention provides a system capable of performing mechanical supplementary pollination, which comprises the following steps:
s1, three-dimensional modeling of an intelligent breeding system;
s2, determining different working conditions of a breeding system based on an orthogonal test;
s3, calculating the load under the complex working condition based on dynamic simulation;
s4, checking statics analysis of the intelligent breeding system;
s5, analyzing the fatigue life of the system based on the stress curve correction.
Further, S1, a three-dimensional modeling book system of the intelligent breeding system uses SolidWbrks software for modeling, and can be classified into five subsystems, namely a driving system (1), a lifting system (2), a ear picking system (3), a collecting and releasing system (4) and a detecting system (5). Wherein the drive system is responsible for powering the advance of the device; the lifting system is responsible for lifting the arc platform and parts on the arc platform; the ear pulling system is responsible for clamping the nylon rope and pulling the rice ears for pollination; the winding and unwinding system is responsible for winding and unwinding nylon ropes; the detection system is responsible for detecting the environment of the paddy field, ensuring that the current conditions are suitable for pollination and the like, and the five systems are mutually matched to finish the auxiliary pollination work of the paddy field.
Further, S2 is based on the determination of different working conditions of a breeding system of an orthogonal experiment: when (when)When the system works in a paddy field, the variety of actual working conditions faced by a breeding system is many because the wind direction of the working field and the thickness and height of the paddy are different. Therefore, the test design is carried out through an orthogonal test, and the field wind direction mainly comprises four conditions of no wind, horizontal wind direction, vertical wind direction and mixed wind direction; the diameter of the rice ear is divided into d 1 、d 2 、d 3 、d 4 Four cases; the height of the straw is divided into l 1 、l 2 、l 3 、l 4 In the method, 16 different working conditions are selected in total according to different level combinations of various factors, the test precision is ensured, the number of the working conditions is simplified, and the subsequent dynamic simulation in Adams is facilitated, so that the working condition with the largest stress is determined.
Further, S3, calculating the load under the complex working condition based on the dynamics simulation: and carrying out Adams multi-body dynamics analysis according to books with different working conditions obtained by the S2 orthogonal test, adding boundary constraint and driving in software, wherein the constraint comprises a moving pair, a rotating pair and a fixed pair, and the constraint needs to be added for the moving pair and the rotating pair. In the present invention, a STEP function is used as the driving function. For the swing of the swing rod in the device, the optimal range of the swing is as follows:
wherein alpha is min The initial angle of the swing motor; alpha max The end angle of the swing motor; l (L) min The minimum value of the length of a single rice spike in a rice breeding field; l (L) max The maximum value of the length of a single rice spike in a rice breeding field; r is the distance between the nylon rope and the infrared sensor, and is a fixed value, and the value is 40 cm.
Its driving function can be written as:
step(time，0，0，t 1 ，0)+step(time，t 1 ，0，t 2 ，α min )+step(time，t 2 ，α min ，t 3 ，α max )
wherein the function means that the wobble device is between 0 and t 1 Is not rotated for a period of time, at t 1 To t 2 In (2) the wobble motor rotates from 0 degrees to alpha min Degree from t 2 To t 3 Within a period of time from alpha for the swing motor min Degree of rotation to alpha max And finally, the ear picking operation is finished by analogy. And counting and summarizing the loaded conditions in all working conditions, and selecting the maximum load so as to perform statics simulation.
Further, S4 intelligent breeding system statics analysis check: and (3) extracting maximum loads under different working conditions according to the step S3, and performing simulation calculation in finite element analysis software. And (3) converting the model established in the step (S1) into an x-t format, importing the x-t format into ABAQUS, carrying out boundary constraint and load application on the model, obtaining the maximum stress value of the intelligent breeding system under complex and various working conditions in a post-processing interface through simulation calculation, and checking according to the material properties of the intelligent breeding system.
Further, S5, system fatigue life analysis based on stress curve correction: the fatigue life analysis of the system is performed based on the result of the finite element statics solution in S4, and the fatigue load to which the system is subjected is first clarified, which has been described in S3. Secondly, it is necessary to determine the fatigue properties of the material, i.e. to study and determine the S-N curve of the material. And finally, importing the finite element statics analysis model in the step S4 into Fe-Safe software, so that the service life of the key part of the device can be analyzed. In the actual working situation, r is not necessarily-1, so that the influence of r on the S-N curve needs to be considered, and the expression of m and C after correction is as follows:
m·log S+log N＝log C
wherein b is the fatigue strength index of the structure; sigma (sigma) b Is the strength limit of the system material; beta r Is an effective stress concentration coefficient under asymmetric cycles.
The beneficial effects are that: the method of the invention works under the optimal breeding time-space domain condition through the cooperation of various sensors (an infrared sensor, a wind direction sensor, a temperature and humidity sensor, an illuminance sensor and the like), can greatly improve the breeding efficiency, reduce the labor intensity, greatly help to improve the quality and the yield of rice, and verify the reliability and the safety through dynamic and static mechanics and fatigue life analysis.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of the intelligent breeding system of the present invention.
Detailed Description
The reliability analysis method of the adaptive spike Gao Bo receptor type intelligent breeding system mainly comprises the following steps:
s1, three-dimensional modeling of an intelligent breeding system:
the system uses SolidWorks software for modeling, and can be classified into five subsystems, namely a driving system 1, a lifting system 2, a ear-plucking system 3, a collecting and releasing system 4 and a detecting system 5. Wherein the drive system 1 is responsible for powering the advance of the device; the lifting system 2 is responsible for lifting the arc platform and parts thereon; the ear pulling system 3 is responsible for clamping nylon ropes and pulling rice ears for pollination; the winding and unwinding system 4 is responsible for winding and unwinding nylon ropes; the detection system 5 is responsible for detecting the environment of the paddy field, ensuring that the current conditions are suitable for pollination and the like, and the five systems are mutually matched to finish the auxiliary pollination work of the paddy field.
S2, determining different working conditions of a breeding system based on orthogonal tests:
when the system works in the paddy field, the wind direction of the working field and the paddy field are usedThe thickness and the height of the breeding system are different, and the variety of actual working conditions faced by the breeding system is many. Therefore, the test design is carried out through an orthogonal test, and the field wind direction mainly comprises four conditions of no wind, horizontal wind direction, vertical wind direction and mixed wind direction; the diameter of the rice ear is divided into d 1 、d 2 、d 3 、d 4 Four cases; the height of the straw is divided into l 1 、l 2 、l 3 、l 4 In the method, 16 different working conditions are selected in total according to different level combinations of various factors, the test precision is ensured, the number of the working conditions is simplified, and the subsequent dynamic simulation in Adams is facilitated, so that the working condition with the largest stress is determined.
S3, calculating the load under the complex working condition based on dynamic simulation:
and carrying out Adams multi-body dynamics analysis according to books with different working conditions obtained by the S2 orthogonal test, adding boundary constraint and driving in software, wherein the constraint comprises a moving pair, a rotating pair and a fixed pair, and the constraint needs to be added for the moving pair and the rotating pair. In the present invention, a STEP function is used as the driving function. For the swing of the swing rod in the system, the optimal range of the swing is as follows:
wherein alpha is min The initial angle of the swing motor; alpha max The end angle of the swing motor; l (L) min The minimum value of the length of a single rice spike in a rice breeding field; l (L) max The maximum value of the length of a single rice spike in a rice breeding field; r is the distance between the nylon rope and the infrared sensor, and is a fixed value, and the value is 40 cm.
Its driving function can be written as:
step(time，0，0，t 1 ，0)+step(time，t 1 ，0，t 2 ，α min )+step(time，t 2 ，α min ，t 3 ，α max )+
wherein the function means that the wobble device is between 0 and t 1 Is not rotated for a period of time, at t 1 To t 2 In (2) the wobble motor rotates from 0 degrees to alpha min Degree from t 2 To t 3 Within a period of time from alpha for the swing motor min Degree of rotation to alpha max And finally, the ear picking operation is finished by analogy. And counting and summarizing the loaded conditions in all working conditions, and selecting the maximum load so as to perform statics simulation.
S4, checking statics analysis of the intelligent breeding system:
and (3) extracting maximum loads under different working conditions according to the step S3, and performing simulation calculation in finite element analysis software. And (3) converting the model established in the step (S1) into an x-t format, importing the x-t format into ABAQUS, carrying out boundary constraint and load application on the model, obtaining the maximum stress value of the intelligent breeding system under complex and various working conditions in a post-processing interface through simulation calculation, and checking according to the material properties of the intelligent breeding system.
S5, analyzing the fatigue life of the system based on stress curve correction:
the fatigue life analysis of the system is performed based on the result of the finite element statics solution in S4, and the fatigue load to which the system is subjected is first clarified, which has been described in S3. Secondly, it is necessary to determine the fatigue properties of the material, i.e. to study and determine the S-N curve of the material. And finally, importing the finite element statics analysis model in the step S4 into Fe-Safe software, so that the service life of the key part of the device can be analyzed. In the actual working situation, r is not necessarily-1, so that the influence of r on the S-N curve needs to be considered, and the expression of m and C after correction is as follows:
m·log S+log N＝log C
wherein b is the fatigue strength index of the structure; sigma (sigma) b Is the strength limit of the system material; beta r Is an effective stress concentration coefficient under asymmetric cycles.
Claims (5)
1. A reliability analysis method of a self-adaptive spike Gao Bo receptor type intelligent breeding system is characterized by comprising the following steps: the method comprises the following steps:
s1, three-dimensional modeling of an intelligent breeding system;
s2, determining different working conditions of a breeding system based on an orthogonal test;
s3, calculating the load under the complex working condition based on dynamic simulation;
s4, checking statics analysis of the intelligent breeding system;
s5, analyzing the fatigue life of the system based on stress curve correction;
the system fatigue life analysis based on stress curve correction in the step S5: according to the result of finite element statics solution in the above S4, the fatigue life analysis of the system is performed, firstly, the fatigue load of the system is clarified, which has been described in the above S3, secondly, the fatigue characteristics of the material need to be determined, that is, the S-N curve of the material needs to be studied and determined, and finally, the finite element statics analysis model in the above S4 is imported into Fe-Safe software, that is, the life of the key part of the device can be analyzed, in the actual working condition, r is not necessarily-1, therefore, the influence of r on the S-N curve needs to be considered, and after the modification, the expression of m and C is:
m·log S+log N＝log C
wherein b is the fatigue strength index of the structure; beta r Is an effective stress concentration coefficient under asymmetric cycles.
2. The adaptive ear Gao Bo subject intelligent breeding system reliability analysis method of claim 1, characterized by: the three-dimensional modeling method of the intelligent breeding system in the step S1 comprises the following steps: the system uses SolidWorks software for modeling, is classified into five subsystems, namely a driving system (1), a lifting system (2), a ear picking system (3), a collecting and releasing system (4) and a detecting system (5), wherein the driving system (1) is responsible for providing power for the advancing of the device; the lifting system (2) is responsible for lifting the arc platform and parts on the arc platform; the ear pulling system (3) is responsible for clamping nylon ropes and pulling rice ears for pollination; the winding and unwinding system (4) is responsible for winding and unwinding nylon ropes; the detection system (5) is responsible for detecting the environment of the paddy field, ensuring that the current conditions are suitable for pollination and the like, and the five systems are mutually matched to finish the auxiliary pollination work of the paddy field.
3. The adaptive ear Gao Bo subject intelligent breeding system reliability analysis method of claim 2, characterized by: the method for determining different working conditions of the breeding system based on the orthogonal test in the step S2 comprises the following steps: when the system works in a paddy field, the experimental design is carried out through an orthogonal test, and the field wind direction mainly comprises four conditions of no wind, horizontal wind direction, vertical wind direction and mixed wind direction; the diameter of the rice ear is divided into d 1 、d 2 、d 3 、d 4 Four cases; the height of the straw is divided into l 1 、l 2 、l 3 、l 4 In the method, 16 different working conditions are selected in total according to different level combinations of various factors, the test precision is ensured, the number of the working conditions is simplified, and the subsequent dynamic simulation in Adams is facilitated, so that the working condition with the largest stress is determined.
4. The method for analyzing the reliability of the adaptive spike Gao Bo subject intelligent breeding system according to claim 3, which is characterized in that: the load calculation method based on the dynamic simulation in the step S3 under the complex working condition comprises the following steps: according to the S2 orthogonal test, adams multi-body dynamics analysis is carried out on books under different working conditions, boundary constraint and driving are added in software, the constraint comprises a moving pair, a rotating pair and a fixed pair, and the constraint needs to be added for the moving pair and the rotating pair, in the invention, a STEP function is used as a driving function, and for a swing rod in a system, the optimal range of swing is as follows:
wherein alpha is min The initial angle of the swing motor; alpha max The end angle of the swing motor; l (L) min The minimum value of the length of a single rice spike in a rice breeding field; l (L) max The maximum value of the length of a single rice spike in a rice breeding field; r is the distance between the nylon rope and the infrared sensor, and is a fixed value, the value is 40 cm,
its driving function can be written as:
step(time，0，0，t 1 ，0)+step(time，t 1 ，0，t 2 ，α min )+step(time，t 2 ，α min ，t 3 α max )
wherein the function means that the wobble device is between 0 and t 1 Is not rotated for a period of time, at t 1 To t 2 In (2) the wobble motor rotates from 0 degrees to alpha min Degree from t 2 To t 3 Within a period of time from alpha for the swing motor min Degree of rotation to alpha max And finally completing ear pulling work by analogy, counting and summarizing the loaded conditions in all working conditions, and selecting the maximum load so as to perform statics simulation.
5. The method for analyzing the reliability of the adaptive ear Gao Bo subject intelligent breeding system according to claim 4, which is characterized in that: the intelligent breeding system statics analysis and check method in the step S4 comprises the following steps: according to the maximum load under different working conditions in the step S3, simulation calculation is carried out in finite element analysis software, the model established in the step S1 is converted into an x-t format and is imported into ABAQUS, boundary constraint and load application are carried out on the model, the maximum stress value of the intelligent breeding system under complex multiple working conditions is obtained in a post-processing interface through simulation calculation, and verification is carried out according to the material properties of the intelligent breeding system.
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