CN112602562A - Irrigation pipeline fault detection system based on machine learning and intelligent irrigation system - Google Patents
Irrigation pipeline fault detection system based on machine learning and intelligent irrigation system Download PDFInfo
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- 238000003973 irrigation Methods 0.000 title claims abstract description 111
- 230000002262 irrigation Effects 0.000 title claims abstract description 111
- 238000001514 detection method Methods 0.000 title claims abstract description 89
- 238000010801 machine learning Methods 0.000 title claims abstract description 29
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 118
- 238000004891 communication Methods 0.000 claims abstract description 84
- QVFWZNCVPCJQOP-UHFFFAOYSA-N chloralodol Chemical compound CC(O)(C)CC(C)OC(O)C(Cl)(Cl)Cl QVFWZNCVPCJQOP-UHFFFAOYSA-N 0.000 claims description 11
- 239000000126 substance Substances 0.000 claims description 3
- 238000009428 plumbing Methods 0.000 claims 1
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 238000012544 monitoring process Methods 0.000 abstract description 2
- 230000005477 standard model Effects 0.000 description 8
- 230000002159 abnormal effect Effects 0.000 description 5
- 238000000034 method Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000009313 farming Methods 0.000 description 2
- 238000012271 agricultural production Methods 0.000 description 1
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- 238000003745 diagnosis Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G25/00—Watering gardens, fields, sports grounds or the like
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G25/00—Watering gardens, fields, sports grounds or the like
- A01G25/16—Control of watering
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
- F17D5/06—Preventing, monitoring, or locating loss using electric or acoustic means
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Abstract
The invention discloses an irrigation pipeline fault detection system based on machine learning, which comprises: the detection communication device is arranged in the irrigation pipeline and used for detecting the flowing water in the irrigation pipeline and outputting a corresponding flowing water detection signal; the wireless receiver is in communication connection with the detection communication device and is used for receiving a flowing water detection signal output by the detection communication device; the cloud server is in communication connection with the wireless receiver and is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device is in fault according to the flowing water detection signal; and the user terminal is in communication connection with the cloud server and is used for receiving the fault alarm signal and prompting. The invention solves the problem of lack of an irrigation pipeline fault monitoring system, and is beneficial to improving the detection efficiency of irrigation pipeline system faults.
Description
Technical Field
The invention relates to the technical field of fault diagnosis and detection, in particular to an irrigation pipeline fault detection system based on machine learning and an intelligent irrigation system.
Background
Irrigation is a high-frequency farming behavior in the agricultural production process, and when irrigation is carried out, farmers need to manually check whether the irrigation pipeline system has the problems of water pipe burst, pipeline blockage, electromagnetic valve failure and the like one by one, so that the detection efficiency is low. In addition, under normal conditions, if the faults can not be found and solved in time after the faults occur, more water pipe faults can be caused and are difficult to position, the farming season is delayed, and great loss is brought to farmers. However, the irrigation equipment is often in a large quantity and distributed in a dispersed manner, and farmers check the irrigation equipment one by one, so that the labor consumption is high and the detection accuracy is low.
Disclosure of Invention
The invention mainly aims to provide an irrigation pipeline fault detection system based on machine learning and an intelligent irrigation system, and aims to improve the fault detection efficiency of the irrigation pipeline system.
In order to achieve the above object, the present invention provides an irrigation pipeline fault detection system based on machine learning, which is applied to an intelligent irrigation system, wherein the intelligent irrigation system comprises a plurality of irrigation pipelines and pipeline control devices arranged on the irrigation pipelines, and the irrigation pipeline fault detection system based on machine learning comprises:
the detection communication device is arranged in the irrigation pipeline and used for detecting the flowing water in the irrigation pipeline and outputting a corresponding flowing water detection signal;
the wireless receiver is in communication connection with the detection communication device and is used for receiving a flowing water detection signal output by the detection communication device;
the cloud server is in communication connection with the wireless receiver and is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device is in fault according to the flowing water detection signal;
and the user terminal is in communication connection with the cloud server and is used for receiving the fault alarm signal and prompting.
Optionally, the detection communication device includes any one or more of a water pressure sensor and a flow sensor.
Optionally, the wireless receiver includes a Lora communication module, and the Lora communication module is in communication connection with the detection communication device;
or, the wireless receiver comprises a Zeta communication module, and the Zeta communication module is in communication connection with the detection communication device.
Optionally, the cloud server comprises a communication server and a central server;
the communication server is used for receiving the flowing water detection signal output by the wireless receiver;
and the central server is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device has a fault according to the flowing water detection signal received by the communication server.
Optionally, the cloud server further includes:
a memory to store a pipelined reference signal.
Optionally, the user terminal is any one or a combination of a computer, a mobile phone and a smart bracelet.
The invention also provides an intelligent irrigation system which comprises a plurality of irrigation pipelines, pipeline control devices arranged on the irrigation pipelines and the machine learning-based irrigation pipeline fault detection system.
Optionally, the line control device comprises:
a master cylinder;
the electromagnetic valves are arranged at the output end of the master pump in parallel; wherein the content of the first and second substances,
each electromagnetic valve is connected with at least one irrigation pipeline.
According to the invention, the detection communication device is arranged in the irrigation pipeline and is used for detecting the flowing water in the irrigation pipeline and outputting the corresponding flowing water detection signal to the wireless receiver, so that the flowing water data is sent to the cloud server through the wireless receiver, and therefore, when the cloud server determines that any one of the irrigation pipelines and/or the pipeline control device is in fault according to the flowing water detection signal, the cloud server outputs a fault alarm signal to the user terminal to inform the user of the fault.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
FIG. 1 is a schematic diagram of an embodiment of a machine learning based irrigation pipe fault detection system of the present invention;
FIG. 2 is a schematic flow chart diagram of an embodiment of a machine learning based irrigation pipe fault detection system of the present invention;
fig. 3 is a schematic structural diagram of an embodiment of the intelligent irrigation system of the present invention.
The reference numbers illustrate:
| reference numerals | Name (R) | Reference numerals | Name (R) |
| Detecting |
10 | |
30 |
| |
20 | |
40 |
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that all the directional indicators (such as up, down, left, right, front, and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
In the present invention, unless otherwise expressly stated or limited, the terms "connected," "secured," and the like are to be construed broadly, and for example, "secured" may be a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the descriptions related to "first", "second", etc. in the present invention are only for descriptive purposes and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
The invention provides an irrigation pipeline fault detection system based on machine learning, which is used for detecting faults generated by an irrigation pipeline system.
In order to solve the above problem, referring to fig. 1 to 3, in an embodiment of the present invention, the irrigation pipe fault detection system based on machine learning is applied to an intelligent irrigation system, the intelligent irrigation system includes a plurality of irrigation pipes and pipe control devices disposed on the plurality of irrigation pipes, and the irrigation pipe fault detection system based on machine learning includes:
the detection communication device 10 is arranged in the irrigation pipeline and used for detecting the flowing water in the irrigation pipeline and outputting a corresponding flowing water detection signal;
a wireless receiver 20, wherein the wireless receiver 20 is in communication connection with the detection communication device 10, and the wireless receiver 20 is configured to receive the flowing water detection signal output by the detection communication device 10;
the cloud server 30 is in communication connection with the wireless receiver 20, and the cloud server 30 is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device is faulty according to the running water detection signal;
and the user terminal 40 is in communication connection with the cloud server 30 and is used for receiving the fault alarm signal and prompting.
Detect communication device 10 can realize through sensor and processing circuit, wireless communication module, the sensor can be water pressure sensor, flow sensor, the sensor sets up any department in irrigating the main, and the sensor of establishing in the main can detect the flowing water data that corresponds when arbitrary quantity solenoid valve was opened, flowing water data when for example all solenoid valves were closed, flowing water data when all solenoid valves were opened, flowing water data when different quantity's solenoid valve was opened, the sensor is handled the flowing water data that detects through processing circuit, and rethread wireless communication module exports, wireless communication module can set up to loRa communication module, ZeTa communication module. In a specific embodiment, the water pressure sensor is used for detecting flowing water data, the water pressure sensor converts the received flowing water pressure into an electric signal, the corresponding flowing water data is generated through a series of processing of the processing circuit, and the flowing water data is output through the wireless communication module.
The cloud server 30 may establish a standard state model according to the acquired initial flowing water data, the number and time of opening the master pump and the electromagnetic valves in the corresponding irrigation pipelines, and record and store the flowing water data of the standard state model. Specifically, pipeline running water data under different conditions, such as running water data when all the electromagnetic valves are closed, running water data when all the electromagnetic valves are opened, and running water data when different numbers of the electromagnetic valves are opened, are recorded according to the working states of the electromagnetic valves, errors which may be generated are estimated by combining factors such as actual pipeline lengths and volumes, and on the basis, initial running water data are modeled to generate a standard state model. The cloud server 30 can also learn the operation of the irrigation pipe system by the user, such as opening/closing different solenoid valves, opening/closing a master pump, and the like.
When a subsequent farmer irrigates, the cloud server 30 judges whether the running water data range of the pipeline in irrigation is reasonable or not according to the control instruction (corresponding to the on/off of the electromagnetic valve) of the current user, the running water data acquired in real time, and the standard running water data range stored in the standard state model, for example, when the electromagnetic valve of a certain irrigation pipeline is opened, when the running water data (continuously for one minute) exceeds the standard range in real time within a preset time, the fault type in the irrigation system at the moment is determined, for example, the electromagnetic valve in the certain irrigation pipeline has a fault, a water pipe is blocked, or the water pipe bursts and the like, and a corresponding alarm signal is generated and then output to the user terminal 40, so that the user can quickly know the fault type, and the farmer is informed of timely handling abnormal conditions.
The user terminal 40 can be a computer, a mobile phone, an intelligent bracelet and the like, the user terminal 40 receives fault signals such as a master cylinder fault, an electromagnetic valve fault and a pipeline fault which are sent by the cloud server 30 through a TCP/IP communication protocol, so that the fault can be quickly detected according to specific information provided by the user terminal 40, the problem that a farmer cannot timely find when the equipment is in fault is solved, and the effect that the farmer can master the working state of the equipment at any time is achieved.
As shown in fig. 2, in an embodiment, the detection process of the detection system is as follows: the method comprises the steps of firstly starting a detection system, then starting an irrigation pipeline system, recording pipeline water pressure data under different conditions according to the working state of an electromagnetic valve during initialization, wherein the pipeline water pressure data include water pressure data when the electromagnetic valve is completely closed, water pressure data when the electromagnetic valve is completely opened, and water pressure data when different quantities of electromagnetic valves are opened, the detection system estimates errors which are possibly generated by combining factors such as actual pipeline length and volume, and models initial water pressure data on the basis to generate a standard state model. Then the detection system starts to detect the water pressure change, if the water pressure change continuously exceeds the range of the standard model for one minute, the fault of the irrigation pipeline system is determined, alarm information is sent to a user, the user confirms the problem on site according to the alarm information and calibrates the problem, and after the user calibrates the problem, the system collects data and learns the problem by self, the standard model is perfected, and one-time detection is completed; if the water pressure change does not continuously exceed the standard model range for one minute, the irrigation pipeline system is normal, and the detection system continues to detect the water pressure change. The detection system solves the problem that a common irrigation pipeline system cannot find out pipeline abnormity in time and inform a user. The effects of quick discovery, quick positioning and quick processing are realized.
According to the invention, the detection communication device 10 is arranged in the irrigation pipeline to detect the flowing water in the irrigation pipeline and output the corresponding flowing water detection signal to the wireless receiver 20, so that the flowing water data is sent to the cloud server 30 through the wireless receiver 20, and therefore, when the cloud server 30 determines that any one of the irrigation pipelines and/or the pipeline control device is in fault according to the flowing water detection signal, a fault alarm signal is output to the user terminal 40 to inform a user of the occurrence of the fault.
In a specific embodiment, the cloud server 30 determines whether any one of the irrigation pipelines and/or the pipeline control device has a fault, such as a master cylinder fault, an electromagnetic valve fault, a pipeline fault between the master cylinder and the electromagnetic valve, a pipeline fault after the electromagnetic valve, and the like, according to the matching of an operation instruction of a user, real-time pipeline data, and a corresponding standard pipeline data range in a standard state model, and generates and outputs a corresponding alarm signal. For example, the master cylinder is opened according to user operation, the pressure sensor is used for measuring the flowing water data, the standard water pressure data which is recorded by the cloud server 30 and corresponds to the time when the master cylinder is opened is matched with the real-time water pressure data, and when the real-time water pressure data continuously exceeds the range of the standard model for one minute, the master cylinder can be determined not to be normally opened; according to the master cylinder closing operation operated by a user, when the standard water pressure data recorded by the cloud server 30 after the master cylinder is closed is matched with the real-time water pressure data, and the real-time running water data continuously exceeds the standard model range for one minute, the master cylinder can be determined not to be normally closed; according to the method, a master cylinder and two electromagnetic valves are opened according to user operation, a recorded standard running water data range corresponding to the master cylinder and the two electromagnetic valves is matched with real-time running water data by a cloud server 30, if the real-time running water data are in a standard model range, no fault occurs, if the real-time running water data continuously exceed the standard model range for one minute within a preset time, the faults such as abnormal opening of the master cylinder, abnormal opening of the two electromagnetic valves, pipeline blockage/leakage between the master cylinder and the electromagnetic valves, pipeline blockage/leakage behind the electromagnetic valves and the like are determined by combining the standard running water data range when the master cylinder and the two electromagnetic valves are opened independently or in other combination modes, and meanwhile, the phenomenon that the obtained running water data are short-time abnormal and misjudgment is caused can be avoided.
Referring to fig. 1 to 3, in an embodiment, the detection communication device 10 includes any one or more of a water pressure sensor and a flow sensor.
In this embodiment, the detecting communication device 10 may be implemented by arranging one or more water pressure/flow sensors in the main pipe, where the more the sensors are arranged, the more accurate the detected flowing water data is, the less the sensors are arranged, and the lower the detection cost is. The sensors arranged in the header pipes can detect the flowing water data when all the electromagnetic valves are closed, the flowing water data when all the electromagnetic valves are opened and the flowing water data when different numbers of the electromagnetic valves are opened. The water pressure sensor is used for detecting the water flow data, the standard water flow data range in the corresponding standard state model is the standard water pressure, the flow sensor can detect the water flow flowing through the sensor in unit time, and whether the irrigation system is abnormal or not can be determined according to the difference of the water flow. In a specific embodiment, the detection communication device 10 uses a water pressure sensor to detect the flowing water data, and the collected flowing water data is water pressure, which is beneficial to reducing the detection cost. Of course, in other embodiments, at least one water flow sensor may be disposed in each irrigation pipe, so that the detection accuracy can be improved, and the detection accuracy of the machine learning-based irrigation pipe fault detection system can be improved.
Referring to fig. 1 to 3, in an embodiment, the wireless receiver 20 includes a Lora communication module, which is communicatively connected to the detection communication device 10;
alternatively, the wireless receiver 20 includes a Zeta communication module, and the Zeta communication module is in communication connection with the detection communication device 10.
In this embodiment, wireless receiver 20 can adopt LoRa communication module, ZeTa communication module to realize the receipt of flowing water data, adopts LoRa, ZeTa wireless communication technique to realize flowing water data transmission, and transmission cost is low, efficient, can be applicable to the wisdom agricultural of present high-speed development. Of course, in other embodiments, other communication modules, such as a radio frequency communication module, etc., may also be used, and are not limited herein.
Referring to fig. 1-3, in one embodiment, the cloud server 30 includes a communication server and a central server;
the communication server is used for receiving the flowing water detection signal output by the wireless receiver 20;
and the central server is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device has a fault according to the flowing water detection signal received by the communication server.
In this embodiment, the communication server may be in communication connection with the wireless receiver 20 in a LoRa and ZeTa wireless communication manner to obtain the pipeline data, and output the pipeline data to the central server according to an internet protocol, the central server matches the received real-time pipeline data with a standard pipeline data range corresponding to the standard status model according to the operation of the user, and if the pipeline data measured by the pipeline sensor and the pipeline data in the standard status model exceed the standard model range within a certain time (one minute in succession), and the standard pipeline data range related to the operation of the user is combined, specific faults may be determined, such as the master pump not being normally opened or closed, the solenoid valve not being normally opened/closed (the user opens the corresponding solenoid valve but not opened, the user closes the solenoid valve but not closed, the central server may determine whether the corresponding fault is a fault or not closed, or not open the solenoid valve, The user adjusts the solenoid valve opening degree without the solenoid valve opening to a corresponding degree), irrigation line blockage/leakage, and the like. If the user opens the master cylinder and the three electromagnetic valves, the cloud server 30 matches the real-time running water data with the standard running water data range of the master cylinder and the three electromagnetic valves according to the operation that the master cylinder and the three electromagnetic valves are opened by the user, and combines the running water data in the standard state that the master cylinder and the three electromagnetic valves are opened independently or in other combinations, so as to determine whether the water pump is normally opened, whether the three electromagnetic valves are normally opened, whether the pipelines between the master cylinder and the electromagnetic valves corresponding to the combination of the three electromagnetic valves and the pipelines behind the electromagnetic valves are blocked/leaked, and generate and output a specific fault alarm signal.
Referring to fig. 1 to 3, in an embodiment, the cloud server 30 further includes:
a memory to store a pipelined reference signal.
In this embodiment, the memory in the cloud server 30 is used to store the pipeline data detected by the sensor and store a standard pipeline data range corresponding to the standard state model. Still be equipped with machine learning system in the high in the clouds server 30, machine learning system can carry out the analysis according to the flowing water data of memory storage and the standard flowing water data range that standard state model corresponds, constantly perfects standard state model, for example in user's several irrigation, open the solenoid valve of same combination every time, flowing water data that the sensor measured inevitably has certain error, machine learning system carries out the analysis and obtains more accurate flowing water data according to certain algorithm according to the flowing water data that constantly produces and have little error to constantly update the standard flowing water data range in the standard state model, thereby realize more accurate detection. Meanwhile, the machine learning system can also predict the faults of a master cylinder, an electromagnetic valve, a pipeline and the like according to the historical running water data of irrigation. The monitoring effect can be continuously optimized through new technologies such as machine learning and the like.
Referring to fig. 1 to 3, in an embodiment, the user terminal 40 is any one or more combination of a computer, a mobile phone, and a smart bracelet.
In this embodiment, the user can receive the fault alarm signal that cloud server 30 sent through computer, cell-phone, one or more in the intelligent bracelet, and through PC software, APP, little program display fault information, in order to remind the user specifically be solenoid valve trouble, master cylinder trouble, pipeline trouble between master cylinder and the solenoid valve or the pipeline trouble behind the solenoid valve, after the anomaly appears, the user can be according to the quick location problem pipeline of the specific information that software provided, in time solve the problem, avoid further enlarging the loss. The user can also view the real-time working states of the master pump, the electromagnetic valve and the irrigation pipeline through the user terminal 40 during irrigation.
The invention also provides an intelligent irrigation system which comprises a plurality of irrigation pipelines, pipeline control devices arranged on the irrigation pipelines and the machine learning-based irrigation pipeline fault detection system.
In this embodiment, the intelligent irrigation system collects real-time flowing water data in the main pump pipeline through a sensor of the irrigation pipeline fault detection system based on machine learning, so as to match with a standard flowing water data range in a standard state model, and judge faults generated by the irrigation pipeline and the pipeline control device. The user can confirm and calibrate on site according to the specific fault information, and the problem that a common intelligent irrigation system cannot find out pipeline abnormity in time and inform the user is solved.
Referring to fig. 1 to 3, in an embodiment, the line control device includes:
a master cylinder;
the electromagnetic valves are arranged at the output end of the master pump in parallel; wherein the content of the first and second substances,
each electromagnetic valve is connected with at least one irrigation pipeline.
In this embodiment, the master cylinder realizes intelligent irrigation system's water supply or stops supplying water under the control of master cylinder controller, and master cylinder, a plurality of solenoid valve pass through irrigation pipe and connect to realize the irrigation of crops, wherein, parallelly connected set up in the solenoid valve quantity of the output of master cylinder can be arbitrary, does not do the restriction here, and an irrigation pipe can be connected to each solenoid valve, also can connect many irrigation pipes, and the user can set up by oneself according to the convenient degree of irrigation.
The above description is only an alternative embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. The utility model provides an irrigation pipe fault detection system based on machine learning, is applied to in the intelligent irrigation system, intelligent irrigation system includes many irrigation pipe and sets up in many the last pipeline controlling means of irrigation pipe, its characterized in that, irrigation pipe fault detection system based on machine learning includes:
the detection communication device is arranged in the irrigation pipeline and used for detecting the flowing water in the irrigation pipeline and outputting a corresponding flowing water detection signal;
the wireless receiver is in communication connection with the detection communication device and is used for receiving a flowing water detection signal output by the detection communication device;
the cloud server is in communication connection with the wireless receiver and is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device is in fault according to the flowing water detection signal;
and the user terminal is in communication connection with the cloud server and is used for receiving the fault alarm signal and prompting.
2. The machine learning based irrigation pipe fault detection system of claim 1, wherein the detection communication device comprises any one or a combination of a water pressure sensor and a flow sensor.
3. The machine-learning based irrigation pipe fault detection system of claim 1, wherein the wireless receiver comprises a Lora communication module communicatively coupled to the detection communication device;
or, the wireless receiver comprises a Zeta communication module, and the Zeta communication module is in communication connection with the detection communication device.
4. The machine learning based irrigation pipe fault detection system of claim 1, wherein the cloud server comprises a communication server and a central server;
the communication server is used for receiving the flowing water detection signal output by the wireless receiver;
and the central server is used for outputting a fault alarm signal when determining that any one of the irrigation pipelines and/or the pipeline control device has a fault according to the flowing water detection signal received by the communication server.
5. The machine learning based irrigation pipe fault detection system of claim 4, wherein the cloud server further comprises:
a memory to store a pipelined reference signal.
6. The machine learning-based irrigation pipe fault detection system of any one of claims 1-5, wherein the user terminal is any one or more of a computer, a mobile phone, and a smart bracelet.
7. An intelligent irrigation system, comprising a plurality of irrigation pipes, a pipe control device disposed on the plurality of irrigation pipes, and the machine learning-based irrigation pipe fault detection system of claims 1 and 6.
8. The intelligent irrigation system as recited in claim 7 wherein said plumbing control comprises:
a master cylinder;
the electromagnetic valves are arranged at the output end of the master pump in parallel; wherein the content of the first and second substances,
each electromagnetic valve is connected with at least one irrigation pipeline.
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| CN113537741A (en) * | 2021-07-02 | 2021-10-22 | 南通大学 | Control method of intelligent agricultural management system |
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