An irrigation area patrol equipment and method based on augmented reality technology

Abstract

The application discloses a kind of based on augmented reality technology's irrigation area patrol equipment and method, it is related to agricultural water conservancy engineering and information technology field, including video acquisition, video and audio interaction, communication module, central processing unit, temperature and humidity sensor, positioning module, AI intelligent support module, it can realize the function of real-time transmission basic data in patrol process, and compared with theoretical data, reduce the requirement of patrol for the professionalism of patrol personnel;It also proposes the working system of "AR field perception-AI intelligent support-expert collaborative support-assisted operation guidance", based on the AR patrol equipment of head-mounted type carries out basic information collection and sends, is transmitted to AI intelligent support module, and the theoretical value under normal operation is given by the digital twin irrigation area AI calculation function in AI intelligent support module, and compared with the collection information, pre-judges whether the working condition is normal, and can be combined with expert online research and judge function, realizes the discovery and field research and judge of real-time patrol problem.

Description

TECHNICAL FIELD

[0001] The application relates to the field of agricultural water conservancy and information technology, and more particularly to a farmland inspection equipment and method based on augmented reality technology. BACKGROUND

[0002] At present, in the process of modernization construction of large and medium-sized irrigation areas, although multiple rounds of infrastructure upgrades have been completed, such as water gate, pump station, channel monitoring instruments and other hardware equipment, the operation and maintenance system still has significant shortcomings, which has become a key bottleneck restricting the play of engineering benefits and the improvement of operation efficiency. First, the overall skill level of irrigation area operation and maintenance personnel is low, and there is a lack of compound talents with multi-field knowledge reserve and cross-professional ability. Irrigation area operation and management covers multiple technical fields such as water resources scheduling, equipment maintenance, ecological protection, information system operation, etc., while the grass-roots team is generally aging and has low educational level, which leads to insufficient ability in dealing with digital and intelligent equipment and is difficult to meet the needs of modern operation and maintenance. A large number of intelligent sensing devices, remote monitoring systems and information platforms deployed have not been fully utilized in actual work due to the difficulty of operation and understanding threshold, and the technical efficiency lags far behind the hardware investment. Secondly, the current majority of irrigation areas still continue the traditional "experience dominant" management mode, and lack of standardized and systematic operation and maintenance framework, which leads to random inspection process, missing records, fuzzy responsibility division, weak supervision and examination mechanism, and forms phenomena such as loose management, hidden problems difficult to be found and closed-loop processed in time. Especially in the key facility inspection, manual omission, misdiagnosis or operation error often occurs, which seriously affects the operation reliability and safety of irrigation projects. Therefore, it is necessary to explore the irrigation area operation and maintenance method and wearable device based on augmented reality (AR) technology.

[0003] Many experts and scholars have explored the use of virtual reality technology for irrigation area design and operation improvement. Among them, a kind of irrigation area design method and system based on virtual reality technology (CN2017108179117) proposed by Heilongjiang Water Resources and Hydropower Investigation and Design Institute and China Water Resources and Hydropower Scientific Research Institute records that according to irrigation area parameters, irrigation area modules are established and three-dimensional modeling is carried out, and then virtual actual scenes are formed, which combines irrigation area planning with virtual reality technology, making virtual irrigation area scene realistic, facilitating staff communication and improving work efficiency. Although these methods have certain visualization advantages in the design level, they are highly dependent on pre-modeling and static data input, and are difficult to adapt to the actual needs of "problem scene identification-process real-time feedback" in the process of daily operation and maintenance of irrigation area, especially cannot provide on-site operation assistance and efficient inspection support for low-skilled operators.

[0004] Therefore, in the face of the problems of insufficient skills of grass-roots personnel, lack of intelligentization in the process of inspection, and low standardization of management process, how to provide a solution integrating "on-site perception, intelligent judgment, expert collaboration, and operation guidance" is a problem that needs to be solved by those skilled in the art. SUMMARY

[0005] Therefore, the application provides a kind of based on augmented reality technology's irrigation area inspection equipment and method, head-mounted AR inspection equipment as information collection and interactive terminal, and develops the working system based on the equipment "AR on-site perception-AI intelligent support-expert collaborative support-assisted operation guidance", solves the problem of the lack of current irrigation area digital inspection equipment and method.

[0006] To achieve the above object, the application adopts the following technical solutions:

[0007] A kind of based on augmented reality technology's irrigation area inspection equipment, including: head-mounted AR inspection equipment, AI intelligent support module;

[0008] The head-mounted AR inspection equipment includes data acquisition module, AR interaction lens, audio interaction module, communication module, central processing unit, positioning module;

[0009] Among them, AR interaction lens presents virtual information and real scene superposition, so that users can directly see the fusion picture, assist in inspection judgment;Audio interaction module realizes voice interaction, supports receiving instructions and feedback information;Communication module ensures data transmission between equipment and external;Central processing unit integrates the collected information and dispatches the work of each module;Positioning module determines the position of the equipment and the user;

[0010] AI intelligent support module, based on the data returned by head-mounted AR inspection equipment in real time, carries out real-time analysis and judgment, obtains abnormal results and corresponding processing suggestions, and establishes communication with the communication module, and feeds back to the user's field of vision in real time through the AR interaction lens.

[0011] Optionally, the data acquisition module includes a video acquisition module, a temperature sensor, and a humidity sensor.

[0012] The video acquisition module is responsible for capturing the scene, and provides real-time environmental visual information for the AR scene.

[0013] The temperature sensor detects the ambient temperature, converts the temperature data into an electrical signal or a digital signal, and feeds back to the processor for judging whether the environment is abnormal.

[0014] The humidity sensor monitors the ambient humidity and provides environmental humidity data for the inspection.

[0015] Optionally, it also comprises a communication sending and receiving unit, which undertakes the task of voice receiving and sending and ensures stable data transmission.

[0016] Optionally, the AI intelligent support module constructs a basic physical model of the device or pipe section according to engineering drawings and design parameters, uses digital twin to calculate the theoretical value of the operating condition of the AI irrigation district, and on this basis introduces a data-driven module to establish an operating prediction model under actual operating conditions through training and calibration of historical monitoring data and current real-time data; specifically, an algorithm based on gradient boosting tree is used to construct a function in the following form:

[0017]

[0018] Among them, Operating prediction model; Q(t): AI predicted current time flow; T(t), P(t), θ(t): temperature, pressure, water level angle time-varying input variable; ΔH(t): historical head change trend;

[0019] The physical model provides a reasonable interval and the AI model provides a dynamic expression of the nonlinear disturbance term, and the two are combined to form a hybrid prediction structure:

[0020] Q pred (t)=ω1Q phys (t)+ω2Q AI (t)

[0021] Among them, Q pred (t) is the predicted flow at time t, Q phys (t) is the calculated flow at time t, Q AI (t) is the AI predicted corrected flow at time t, ω1+ω2=1, and the AI intelligent support module automatically adjusts the weights ω1, ω2 to realize the prediction optimization strategy of "based on physics and supplemented by data" according to the importance of different devices, data completeness and interpretability requirements.

[0022] Optionally, the AI intelligent support module also integrates a sliding window anomaly detection mechanism to dynamically monitor the trend of time series data; specifically, a sliding window with a length of k is defined to calculate the anomaly score of the continuous data sequence and generate a risk index:

[0023] R(t)=f risk (ΔS(t-k+1),...,ΔS(t))

[0024] When R(t) exceeds the set threshold, an "operating trend anomaly" is automatically prompted, and the AI intelligent support module retrieves historical cases and provides problem tracing and repair suggestions in combination with the knowledge graph.

[0025] Optionally, the AI intelligent support module further comprises taking an AI large language model as a core knowledge engine to realize semantic understanding and question and answer interaction capability, automatically retrieving historical cases, treatment strategies and precautions in the knowledge base that are consistent with the recognized abnormal situation, generating a treatment suggestion with illustrations and texts, and establishing communication with the communication module to feed back to the field of view of the operator in real time through AR interaction lenses.

[0026] Optionally, when the AI intelligent support module determines that the current abnormal situation cannot be covered in the knowledge base, it automatically suggests entering an expert collaborative support mode; the on-site personnel initiate a help request through a head-mounted AR patrol equipment, and automatically package and upload the current first perspective video screen, recognized data and AI diagnosis results to a remote expert platform; the remote expert platform obtains the on-site screen in real time and makes a voice call, remotely labels key parts in the AR screen, provides operation path suggestions, and forms a stereoscopic remote guidance mechanism.

[0027] A kind of based on augmented reality technology's irrigation area patrol method, comprising:

[0028] AR patrol equipment first carries out on-site perception and identification, provides positioning and basic data for digital twin irrigation area AI calculation;

[0029] AI calculation obtains theoretical value, while AR patrol equipment obtains observation value, comparison, if consistent, then feedback to AR patrol equipment;

[0030] If inconsistent, check whether there is a solution, if yes, call the solution and feedback to AR patrol equipment, if not, form a solution after expert consultation and then feedback, to realize the monitoring and problem handling of related situation of irrigation area.

[0031] Through the above technical solutions, compared with the prior art, the present application provides an irrigation area patrol equipment and method based on augmented reality technology, including video acquisition, video and audio interaction, communication module, central processing unit, temperature and humidity sensor, positioning module, AI intelligent support module, which can realize the function of real-time transmission of basic data during patrol and comparison with theoretical data, reducing the requirement of patrol personnel's professionalism; a working system of "AR on-site perception-AI intelligent support-expert collaborative support-assisted operation guidance" is also proposed, based on head-mounted AR patrol equipment for basic information acquisition and transmission to AI intelligent support module, the digital twin irrigation area AI calculation function in the AI intelligent support module gives the theoretical value under normal operation, and compares with the collected information to predict whether the working condition is normal, and can be combined with the online research and judgment function of experts to realize the discovery and on-site research and judgment of real-time patrol problems. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0033] Figure 1 The system structure schematic diagram provided by the present application is shown in the figure.

[0034] Figure 2 The method principle schematic diagram provided by the present application is shown in the figure.

[0035] Among them, 1. Video acquisition module; 2. AR interactive lens; 3. Audio interactive module; 4. Communication module; 5. Central processing unit; 6. Temperature sensor; 7. Humidity sensor; 8. Positioning module; 9. Communication sending and receiving unit. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0037] The embodiment of the present application discloses a kind of based on augmented reality technology's irrigation area patrol equipment, as shown in the figure, including: head-mounted AR patrol equipment, AI intelligent support module; Figure 1

[0038] Head-mounted AR patrol equipment includes data acquisition module, AR interactive lens 2, audio interactive module 3, communication module 4, central processing unit 5, positioning module 8;

[0039] Among them, AR interactive lens 2 presents superposition to virtual information and real scene, let user see fusion picture directly, auxiliary inspection judgment;Audio interactive module 3 realizes voice interaction, supports receiving instruction, feedback information;Communication module 4 guarantees the data transmission of equipment and external;Mainly is the acceptance and sending of collected data and simulated data;Central processing unit 5 integrates the information collected and dispatches each module work;Positioning module 8 determines the position of equipment and user;

[0040] ​After the field operation personnel wear the AR inspection equipment, the video acquisition module 1 of the equipment can capture the working environment and equipment images in real time, and identify the field equipment and working conditions. For example, the AR glasses can determine the equipment type and number by identifying the identification (two-dimensional code, shape feature, etc.) on the equipment, and superimpose display the name, running parameters, historical maintenance records, etc. of the equipment in the field of view, and can also identify basic information such as water level, temperature, humidity, etc. and transmit them to the AI intelligent support module for processing through the communication module 4.

[0041] The AI intelligent support module performs real-time analysis and judgment based on the data transmitted in real time by the head-mounted AR inspection equipment, obtains abnormal results and corresponding processing suggestions, and establishes communication with the communication module 4 to feed back to the user's field of view in real time through the AR interaction lens 2.

[0042] In a specific embodiment, the data acquisition module includes a video acquisition module 1, a temperature sensor 6, and a humidity sensor 7.

[0043] The video acquisition module 1 is responsible for capturing the field picture to provide real-time environmental visual information for the AR scene.

[0044] The temperature sensor 6 detects the environmental temperature and converts the temperature data into an electrical signal or a digital signal, which is fed back to the processor for judging whether the environment is abnormal.

[0045] The humidity sensor 7 monitors the environmental humidity to provide environmental humidity data for the inspection.

[0046] In a specific embodiment, it also includes a communication sending and receiving unit 9, which undertakes the task of voice receiving and sending to ensure stable data transmission, such as voice transmission during real-time expert reply.

[0047] In a specific embodiment, the AI intelligent support module is used to realize intelligent auxiliary decision-making in the irrigation area inspection process. An irrigation operation knowledge base is established in the AI intelligent support module, which contains equipment operation knowledge, typical fault cases, operation process specifications, etc. and an intelligent decision support system is constructed, which has functions such as fault prediction, risk diagnosis and task suggestion. The AI intelligent support module mainly analyzes and judges in real time based on the data transmitted in real time by the front-end AR equipment, including images, videos, voice descriptions, and operating parameters such as temperature, humidity, and water level collected by sensors, combined with digital twin models. The AI intelligent support module calls the physical-data hybrid model embedded in the background, first performs numerical simulation and trend prediction on the key parameters in the normal operating state, generates the theoretical value or state interval corresponding to the current working condition, and dynamically compares with the field collected data. If the comparison result is within the allowable error range, it will indicate that the inspection can continue; if the deviation exceeds the normal threshold, it will automatically identify as a potential fault or abnormal working condition.

[0048] Its main operation and modeling method is as follows:

[0049] 1) Physical-data hybrid modeling method

[0050] First, according to the engineering drawings and design parameters, the basic physical model of the device or pipe section (such as one-dimensional hydraulic model, energy conservation model, heat exchange model, etc.) is constructed, and the theoretical value of the operating condition is calculated. On this basis, a data-driven module is introduced, and through the training and calibration of historical monitoring data and current real-time data, an operation prediction model under actual working conditions is established. For example, using algorithms based on gradient boosting tree (GBDT) or long short-term memory network (LSTM), an approximate function of the following form is constructed:

[0051]

[0052] Where, Operation prediction model; Q(t): AI predicted current flow; T(t), P(t), θ(t): temperature, pressure, water level angle and other time-varying input variables; ΔH(t): historical head change trend;

[0053] The physical model provides the structure boundary and reasonable interval, and the AI model provides the dynamic expression of the nonlinear disturbance term, and the two are combined to form a hybrid prediction structure:

[0054] Q pred (t) = ω1Q phys (t) + ω2Q AI (t) (ω1+ω2=1)

[0055] Where, Q pred (t) is the predicted flow at time t, Q phys (t) is the calculated flow at time t, and Q AI (t) is the AI predicted correction flow at time t. The system automatically adjusts the weights ω1, ω2 according to the importance of different devices, data completeness and interpretability requirements, to realize the prediction optimization strategy of "based on physics and supplemented by data".

[0056] 2) Abnormal trend identification and early warning mechanism

[0057] The AI intelligent support module also integrates a sliding window anomaly detection mechanism (Sliding Window Anomaly Detection) to dynamically monitor the trend of time series data. A sliding window of length k is defined, and the anomaly score of the continuous data sequence is calculated (such as Z-score, Mahalanobis distance or isolation forest method), and a risk index is generated:

[0058] R(t) = frisk (ΔS(t-k+1),...,ΔS(t))

[0059] When R(t) exceeds the set threshold, an automatic prompt of "running trend anomaly" is given, and the AI intelligent support module retrieves historical cases and provides problem tracing and repair suggestions based on the knowledge graph.

[0060] On this basis, the AI intelligent support module further relies on an AI large language model as a core knowledge engine to realize semantic understanding and question and answer interaction capabilities. The system can automatically retrieve historical cases, treatment strategies, and precautions in the knowledge base that match the identified abnormal conditions, generate processing suggestions with illustrations, and feed back to the field personnel's field of view in real time through the AR interaction lens 2. This process can cover various forms of expression, including written instructions, voice broadcasts, step-by-step prompts, and even three-dimensional animation demonstrations, so that even if the operator does not have a professional background, they can complete the initial processing under the guidance of the intelligent prompt. In addition, the system has voice recognition and semantic understanding capabilities, supporting on-site personnel to actively describe problems or consult instructions through voice. The AI intelligent support module can analyze the content of the sentence and generate personalized answers or emergency suggestions based on the current working conditions, improving the naturalness and efficiency of human-computer interaction. When the AI intelligent support module determines that the current abnormal situation is complex, the knowledge base cannot cover it, or the risk level is high, it will automatically suggest entering the expert collaborative support mode. Field personnel can initiate a request for help through the AR device, which will automatically package and upload the current first-person video, recognized data, and AI diagnosis results to the remote expert platform. Experts can access the on-site video in real time and make voice calls, label key parts and provide operation path suggestions in the AR interaction lens 2, forming a three-dimensional remote guidance mechanism to effectively solve the problem of "not understanding and not daring to move" for on-site personnel.

[0061] The AI intelligent support module not only realizes the "perception-judgment-feedback" closed loop of intelligent patrol in irrigation areas, but also greatly alleviates the operation problems caused by the lack of skills of on-site personnel, promoting the transformation of operation and management from "experience-driven" to "intelligent-driven", and providing key support for building an efficient, stable, and self-adaptive irrigation operation system.

[0062] (3) Real-time interactive solution

[0063] Based on the calculation results of the AI intelligent support module, the AR interaction lens 2 is prompted in the form of illustrations, for example, when a pump station device fails and alarms, the possible causes and processing steps are automatically matched with the known cases. This intelligent question and answer and decision-making function ensures that even people with low cultural level can complete the task by following simple and clear step-by-step instructions. The guidance provided by AI can include written instructions, voice explanations, and even three-dimensional animation demonstrations, which are intuitive and easy to understand.

[0064] The interaction with the expert can also be realized, the expert can talk with the on-site personnel through voice, and mark the key components or operation positions in real time on the AR interaction lens 2, help the on-site personnel to accurately locate the problem, and provide maintenance guidance. As the expert teaches on-site "hand in hand" in person, until the problem is solved. For example, when a channel gate is stuck and cannot be opened, the remote expert diagnoses the stuck position through the AR real-time picture, and circles the position in the field of view of the on-site personnel, guides them to clean up the debris and open the gate in the correct order. During the whole collaborative process, the system also supports sharing documents (such as wiring diagrams, specification fragments) to the on-site AR interface for reference by personnel. Through such remote cooperation, the efficiency of handling difficult faults can be greatly improved, and the time delay and travel cost caused by the expert's on-site visit in the past can be avoided. Especially in remote and vast irrigation areas, remote AR assistance can be twice the result with half the effort.

[0065] An irrigation area patrol method based on augmented reality technology, as shown in Figure 2 , comprising:

[0066] The AR patrol device first performs on-site sensing and identification to provide positioning and basic data for digital twin irrigation AI calculation;

[0067] The AI calculation obtains a theoretical value, and the AR patrol device obtains an observed value, and the two are compared. If they are consistent, feedback is given to the AR patrol device;

[0068] If they are not consistent, it is checked whether there is a reserved solution. If there is, the solution is called and fed back to the AR patrol device. If there is not, the solution is formed after expert consultation and then fed back, so as to realize the monitoring and problem handling of the related situation of the irrigation area.

[0069] Two specific examples are introduced below to further illustrate the method of the present application.

[0070] Example 1: Regular inspection and state identification of channel gate

[0071] In a typical daily operation and maintenance scene of an irrigation area, the inspection personnel wear the head-mounted AR patrol equipment of the present application to enter the channel operation site. After starting, the camera acquisition module obtains the image of the front view in real time, the device automatically identifies the channel gate number and type in front, and displays the basic information of the gate, including the device name, opening and closing state, water level, last maintenance time, etc. through the AR interaction lens 2 superimposed in the field of view of the personnel.

[0072] At the same time, the temperature sensor 6, the humidity sensor 7 and the positioning module 8 synchronously collect the on-site environment and equipment operation data and upload to the background management system. The AI intelligent support module compares the theoretical running state of the equipment under the current climate condition to judge whether the opening and closing response is normal. If a large data deviation is found, the AR interface will immediately prompt the abnormal risk, and push the standard operation process and possible problem causes. The inspection personnel can complete the preliminary inspection and treatment according to the prompt without referring to paper materials or additional communication.

[0073] Embodiment 2: Intelligent diagnosis of pump station sudden abnormality and remote expert cooperation

[0074] During the operation of a pump station, the operation and maintenance personnel received a system warning of abnormal temperature rise of the pump body and went to the scene. After wearing the AR equipment, the target pump group was identified, the current water flow, pump body temperature, inlet and outlet pressure difference and other data were collected and uploaded to the AI intelligent support module. The AI intelligent support module compares the standard running model of the pump group in the digital twin system and identifies the "potential bearing dry friction" fault.

[0075] Since the personnel have limited experience, they cannot independently complete the disassembly and inspection operation, so they issue a "request for expert support" instruction through voice. The AR device immediately synchronously transmits the current perspective picture, sensor data and AI preliminary judgment result to the remote expert platform. The expert accesses the AR perspective through the platform, talks with the on-site personnel, and marks the positions of the maintenance panels to be opened and the key inspection areas with a red frame line in their field of view, while pushing the corresponding structure diagram and operation specification.

[0076] Under the guidance of the expert "remote hand-in-hand", the on-site personnel successfully complete the local inspection and foreign matter removal of the pump body, and confirm the operation completion through voice. The system automatically uploads the inspection and disposal records to the database to form a complete closed loop.

[0077] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts are referred to the method part description.

[0078] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An irrigation area patrol equipment based on augmented reality technology, characterized in that, Comprise: Head-mounted AR patrol equipment, AI intelligent support module; The head-mounted AR patrol equipment comprises a data acquisition module, an AR interaction lens, an audio interaction module, a communication module, a central processor, and a positioning module; The AR interaction lens superimposes virtual information on the real scene to present a fusion picture to the user, assisting in inspection and judgment; the audio interaction module realizes voice interaction, supports receiving instructions and feedback information; the communication module ensures data transmission between the device and the outside world; the central processor integrates the collected information and dispatches the work of each module; the positioning module determines the location of the device and the user; The AI intelligent support module analyzes and judges the data transmitted in real time by the head-mounted AR patrol equipment, obtains abnormal results and corresponding processing suggestions, and establishes communication with the communication module to feed back to the user's field of view in real time through the AR interaction lens; The AI intelligent support module constructs a basic physical model of the device or pipe section based on engineering drawings and design parameters, uses digital twin to calculate the theoretical value of the operating condition of the AI irrigation area, and on this basis introduces a data-driven module to establish an operating prediction model under actual operating conditions through training and calibration of historical monitoring data and current real-time data; specifically, an algorithm based on gradient boosting trees is used to construct a function in the following form: wherein, : running the predictive model; Q(t) : AI predicted current time flow; T ( t ), P ( t ), θ ( t ): temperature, pressure, water level angle time-varying input variables; ΔH ( t ): historical head change trend; The physical model provides structural boundaries and reasonable intervals, and the AI model provides dynamic expressions of nonlinear disturbance terms, and the two are combined to form a hybrid prediction structure: Wherein, The predicted flow at time t is, The calculated flow at time t is, The AI predicted corrected flow at time t is, The AI intelligent support module automatically adjusts the weight according to the importance of different devices, data completeness and interpretability requirements ω 1、 ω 2Implement the "physical-based, data-supplemented" prediction optimization strategy; The AI intelligent support module also integrates a sliding window anomaly detection mechanism to dynamically monitor the trend of time series data; specifically, a sliding window with a length of k is defined to calculate the anomaly score of the continuous data sequence and generate a risk index: When R (t) When exceeding the set threshold, automatically prompt "running trend anomaly", and retrieve historical cases by AI intelligent support module, provide problem tracing and repair suggestions combined with knowledge graph; The AI intelligent support module also includes an AI large language model as a core knowledge engine to realize semantic understanding and question and answer interaction capabilities, automatically retrieve historical cases, processing strategies and precautions in the knowledge base that match the identified abnormal conditions, generate processing suggestions with pictures and texts, and establish communication with the communication module to feed back to the operator's field of view in real time through the AR interaction lens.

2. The equipment for checking the irrigation area based on the augmented reality technology according to claim 1, characterized in that, The data acquisition module comprises a video acquisition module, a temperature sensor, and a humidity sensor; The video acquisition module captures the scene to provide real-time environmental visual information for the AR scene; The temperature sensor detects the ambient temperature and converts the temperature data into an electrical signal or a digital signal to feed back to the processor for determining whether the environment is abnormal; The humidity sensor monitors the ambient humidity to provide environmental humidity data for the inspection.

3. The equipment for checking the irrigation area based on the augmented reality technology according to claim 1, characterized in that, It also includes a communication sending and receiving unit that is responsible for voice reception and transmission to ensure stable data transmission.

4. The equipment for checking the irrigation area based on the augmented reality technology according to claim 1, characterized in that, When the AI intelligent support module determines that the current abnormal situation cannot be covered in the knowledge base, it automatically suggests entering the expert collaborative support mode; the on-site personnel initiate a help request through the head-mounted AR patrol equipment, and the current first perspective video picture, identified data and AI diagnosis result are automatically packaged and uploaded to the remote expert platform; the remote expert platform obtains the on-site picture in real time and conducts voice communication, remotely labels key parts in the AR picture and provides operation path suggestions, forming a stereoscopic remote guidance mechanism.

5. A method for checking an irrigation area based on augmented reality technology, characterized by, The application is applied to the irrigation area patrol equipment based on the augmented reality technology in any one of claims 1-4, comprising: The AR patrol equipment first performs on-site sensing and identification to provide positioning and basic data for digital twin irrigation area AI calculation; The AI calculation obtains a theoretical value, and the AR patrol equipment obtains an observation value, and the two are compared, if consistent, feedback to the AR patrol equipment; If inconsistent, check whether there is a reserved solution, if yes, call the solution and feedback to the AR patrol equipment, if not, form a solution after expert consultation and feedback, so as to realize the monitoring and problem handling of the related situation of the irrigation area.

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