Reservoir data acquisition system and method based on peer-to-peer looped network

Abstract

The invention relates to a reservoir data acquisition system and method based on a peer-to-peer looped network. The system comprises a plurality of looped network data acquisition units, an intelligent central station and a monitoring platform, each looped network data acquisition unit is used for acquiring real-time data of a plurality of sensors and is in communication connection with an adjacent looped network data acquisition unit or an intelligent center to form a peer-to-peer communication looped network; and filtering the data of the peer-to-peer communication ring network based on a dual-event triggering mechanism, the intelligent central station is used for performing consistency verification on the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; uploading the data passing the consistency verification to a monitoring platform; and the monitoring platform is used for carrying out trend analysis and early warning analysis on the received data and visualizing an analysis result. According to the invention, through an annular redundant topological structure, data redundancy and link redundancy are realized, high-speed real-time response and big data transmission of the system are ensured, and reliability and consistency of system communication are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of Internet of Things, and in particular relates to a reservoir data acquisition system and method based on a peer-to-peer ring network. Background Art

[0002] The architecture of a data acquisition system can also vary, depending on the system requirements, application scenarios, and the types of sensors used. The following are some common data acquisition system architectures: (1) Hierarchical architecture In this architecture, the data network is divided into multiple layers. The nodes at the lower level are responsible for data collection and preliminary processing, and then pass the data to the nodes at the higher level for further analysis and integration in a master-slave manner. This architecture helps to reduce the load of data transmission. In a hierarchical architecture, if a key layer or component fails, it may cause the entire data acquisition system to fail. In particular, when a problem occurs in a middle layer or key node, it may block the transmission and processing of data, affecting the stability and availability of the entire system.

[0003] (2) Peer-to-peer network architecture In this architecture, each sensor node has similar functions and status, and they communicate and exchange data in a point-to-point manner. This architecture is highly flexible and fault-tolerant because even if some nodes fail, other nodes can still work normally. Summary of the invention

[0004] In order to improve the reliability and consistency of the reservoir data acquisition system, a first aspect of the present invention provides a reservoir data acquisition system based on a peer-to-peer ring network, including multiple ring network data collectors, an intelligent central station and a monitoring platform, each ring network data collector is used to obtain real-time data of multiple sensors, and communicate with an adjacent ring network data collector or intelligent central station to form a peer-to-peer communication ring network; and based on a dual event trigger mechanism, the data of the peer communication ring network is filtered; the intelligent central station is used to verify the consistency of the data of the peer communication ring network through infinite-dimensional norm consensus filtering; the data that passes the consistency verification is uploaded to the monitoring platform; the monitoring platform is used to perform trend analysis and early warning analysis on the received data, and visualize the analysis results.

[0005] In some embodiments of the present invention, the ring network data collector includes: a collection module for acquiring real-time data from multiple sensors; and a filtering module for filtering the data of the peer communication ring network based on a dual event trigger mechanism.

[0006] Furthermore, the filtering module includes: a determination unit, used to determine the trigger parameters of the dual event trigger mechanism of the real-time data; a trigger unit, used to filter the real-time data or upload it to the intelligent central station based on the trigger parameters.

[0007] In some embodiments of the present invention, the intelligent central station includes: a verification module, which is used to verify the consistency of the data of the peer communication ring network through an infinite-dimensional norm consensus filtering method and a consistency verification model; and an upload module, which is used to upload the data that has passed the consistency verification to a monitoring platform.

[0008] Furthermore, the verification module includes: a determination unit for determining filtering parameters of infinite-dimensional norm consensus filtering; a filtering unit for iterating the data of the peer communication ring network according to the filtering parameters; and a verification unit for performing consistency check on the iterated data.

[0009] In the above-mentioned embodiment, the monitoring platform includes: an analysis module for performing trend analysis and early warning analysis on the received data; and a visualization module for visualizing the analysis results.

[0010] The second aspect of the present invention provides a reservoir data collection method based on a peer-to-peer ring network, including multiple ring network data collectors, an intelligent central station and a monitoring platform, including: each ring network data collector acquires real-time data of multiple sensors, and communicates with an adjacent ring network data collector or intelligent center to form a peer-to-peer communication ring network; based on a dual event trigger mechanism, the data of the peer-to-peer communication ring network is filtered; the data that passes the consistency verification is uploaded to the monitoring platform; the intelligent central station verifies the consistency of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; the data that passes the consistency verification is uploaded to the monitoring platform; the detection platform performs trend analysis and early warning analysis on the received data, and visualizes the analysis results.

[0011] Furthermore, the consistency verification of the data of the peer communication ring network through infinite-dimensional norm consensus filtering includes: determining filtering parameters of infinite-dimensional norm consensus filtering; iterating the data of the peer communication ring network according to the filtering parameters; and performing consistency verification on the iterated data.

[0012] The third aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the reservoir data collection method based on the peer-to-peer ring network provided in the second aspect of the present invention.

[0013] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the reservoir data collection method based on a peer-to-peer ring network provided in the second aspect of the present invention.

[0014] The beneficial effects of the present invention are: The data acquisition system is mainly composed of multiple ring network data collectors. The ring network data collector adopted by the present invention realizes data redundancy and link redundancy through a ring redundant topology structure, ensures the high-speed real-time response and large data transmission of the system, and improves the communication reliability of the system. At the same time, it is equipped with a ring network power supply management module to realize the output voltage stabilization function, ensure the power supply stability of the field sensor, and intelligently switch the load according to the actual situation, while greatly saving the hardware wiring cost. Any node can use multiple paths to communicate with other nodes. In the event of a disconnection or node failure, the data transmission will not be interrupted. The direct connection between nodes eliminates the transmission bottleneck. Each node can exchange data with other nodes at high speed to maintain the high efficiency of the network. It has an automatic redundancy function. When a node fails, other nodes can quickly take over to ensure the continuous operation of network services. It supports centralized and distributed management, simplifies monitoring and maintenance work, and improves the operability of the network. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a basic structural diagram of a reservoir data acquisition system based on a peer-to-peer ring network in some embodiments of the present invention; Figure 2 It is a specific structural schematic diagram of a reservoir data acquisition system based on a peer-to-peer ring network in some embodiments of the present invention; Figure 3 It is one of the specific structural schematic diagrams of the reservoir data acquisition system based on the peer-to-peer ring network in some embodiments of the present invention; Figure 4 The second is a specific structural schematic diagram of a reservoir data acquisition system based on a peer-to-peer ring network in some embodiments of the present invention; Figure 5 It is a structural schematic diagram of a reservoir data collection method based on a peer-to-peer ring network in some embodiments of the present invention; Figure 6 It is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. DETAILED DESCRIPTION

[0016] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0017] refer to Figure 1 and Figure 2In the first aspect of the present invention, a reservoir data acquisition system 1 based on a peer-to-peer ring network is provided, comprising a plurality of ring network data collectors 11, an intelligent central station 12 and a monitoring platform 13, wherein each ring network data collector 11 is used to obtain real-time data of a plurality of sensors, and is connected to a communication network through a ring network data collector 11 or an intelligent central station 12 adjacent thereto, so as to form a peer-to-peer communication ring network; and based on a dual event trigger mechanism, the data of the peer-to-peer communication ring network is filtered; the intelligent central station 12 is used to verify the consistency of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; and the data that passes the consistency verification is uploaded to the monitoring platform; the monitoring platform 13 is used to perform trend analysis and early warning analysis on the received data, and visualize the analysis results.

[0018] In some embodiments of the present invention, the ring network data collector 11 includes: a collection module for acquiring real-time data of multiple sensors; Specifically, the ring network data collector 11 adopts a bidirectional ring network design and cooperates with the asynchronous communication mode between nodes, using the serial port transceiver as the transmission interface, providing communication redundancy, improving the availability and robustness of the ring network communication, and reducing the design complexity of the ring network communication. Each ring network data collector 11 is connected to the sensor communication through hardware such as PLC and HMI to obtain various data of the dam in real time.

[0019] It should be noted that the collected data includes but is not limited to rainwater monitoring data, termite activity data, dam seepage pressure, dam surface deformation detection data, etc.; the infinite-dimensional norm consensus filter in the above-mentioned intelligent central station can also be deployed in the data collector, that is, one or more nodes in the peer-to-peer communication ring network.

[0020] (2) Built-in power supply voltage regulation, overcurrent protection and other load management functions.

[0021] (3) Connectable sensor types: vibrating string type, differential resistance type standard analog signal sensor and support for standard 4~20mA or 1-5V, SDI-12, RS-485, rainfall pulse, frequency signal and other input methods.

[0022] (4) Only one multi-core cable is required between each monitoring station. The maximum distance allowed between each station is 100m. If it exceeds 100m, adding a ring network data acquisition module as a relay between the two stations can increase the connection distance.

[0023] The main equipment selection and performance parameter requirements are as follows: (1) Measurement method: scheduled reporting, polling, and active reporting; (2) Collection frequency: can be set; (3) Working voltage: DC9V-28V: (4) Network structure: full-duplex, network ring redundant topology connection (5) Peer ring network interface: at least 2 (6) Load protection function: support (7) Automatic crossover detection: MDI / MDIX (8) Sensor interface: Standard type: 2 RS485 interfaces, 1 IO interface; Mixed sampling type: 4 RS485 interfaces, 4 vibrating string signal interfaces; (9) Communication distance: Maximum communication distance between modules: 50 meters (CAT6 shielded network cable) / 100 meters (CAT6E shielded network cable); (10) Protection grade: IP67; (11) Ring network data collector configuration: The filtering module is used to filter the data of the peer-to-peer communication ring network based on a dual event trigger mechanism.

[0024] Specifically, the dual event trigger mechanism needs to set two main trigger conditions, namely data anomaly trigger and delay trigger. Data anomaly trigger: If the data collected by the sensor suddenly fluctuates violently, that is, the data increment exceeds the preset threshold, the consistency check is triggered. For example, suppose the sensor is at time t The data collected at x t , the data at the previous moment is x t-1 If the increment exceeds the threshold δ , the event is triggered.

[0025]

[0026] in, δ The threshold for triggering data anomalies is set according to the range of changes in historical data.

[0027] Delay trigger: Delay trigger is used to monitor the real-time performance of data transmission. d t If the allowed delay threshold Δ is exceeded, a consistency check is triggered.

[0028] d t＞ Δ, Here, Δ is the delay trigger threshold, which is generally set based on the real-time requirements of the network environment and application scenarios.

[0029] Furthermore, the filtering module includes: a determination unit, used to determine the trigger parameters of the dual event trigger mechanism of the real-time data; a trigger unit, used to filter the real-time data or upload it to the intelligent central station based on the trigger parameters.

[0030] Specifically, the trigger condition is expressed as:

[0031] Among them, E event triggers the variable, 1 means triggered, 0 means not triggered; Indicates data increment, used to determine data fluctuations; δ Indicates the data anomaly trigger threshold, which can be dynamically adjusted according to the historical data distribution and fluctuation; d t Indicates the transmission delay time; Δ indicates the delay trigger threshold, which is used to control the real-time requirements of data and is set according to network conditions.

[0032] refer to Figures 2 to 4 In some embodiments of the present invention, the intelligent central station 12 includes: a verification module, which is used to verify the consistency of the data of the peer communication ring network through an infinite-dimensional norm consensus filtering method and a consistency verification model; an upload module, which is used to upload the data that has passed the consistency verification to the monitoring platform.

[0033] Furthermore, the verification module includes: a determination unit for determining filtering parameters of infinite-dimensional norm consensus filtering; a filtering unit for iterating the data of the peer communication ring network according to the filtering parameters; and a verification unit for performing consistency check on the iterated data.

[0034] Specifically, in a sensor network, an initial state estimate is set for each node xi,0 and the covariance matrix Pi,0 , and set the filter gain matrix Ki To control the data fusion effect.

[0035] Then, H∞ filtering iteration (infinite norm consensus filtering) is performed after each event is triggered or directly, and each node uses the H∞-filtering algorithm to update the collected data. i The data is xi,t , the global data consistency of the current system is estimated to be , the previous global data consistency estimate of the system is The filter update formula is: , in, Ki Represents the filter gain, that is, the node i The weight of influence on global estimation can be dynamically adjusted according to the quality or reliability of node historical data; xi,t Representation Node i In time t Observational data of; Then, a consistency check is performed. After each update, the H∞-consensus filter checks the deviation between each node and the global consistency result to determine whether the nodes have reached consistency. If the deviation exceeds the preset range, further data verification or alarm is triggered: , in, ϵ The permissible error range for consistency is set according to the accuracy requirements or needs of the monitoring platform 13; The consistency check is expressed as: , C represents the consistency variable, 1 indicates consistency and 0 indicates inconsistency; ϵ is the error tolerance for consistency checking.

[0036] In particular, through distributed feedback mechanism and adaptive parameter optimization, the trigger threshold and filtering parameters in the system are dynamically adjusted to improve the effectiveness of data acquisition and the responsiveness of the system.

[0037] Therefore, the intelligent central station 12 also includes a feedback module to feed back the H∞-consensus filtering result to each node. If the data of the node is significantly different from the global estimate, the feedback information prompts the node to adjust the sampling frequency or transmission rate.

[0038] If the node i Data bias Greater than threshold ϵ , the node will enter the adjustment state.

[0039] Optionally, optimize the adaptive trigger parameters, that is, according to the feedback information and historical data distribution, the system can optimize the dual event trigger threshold. δ and Δ are adjusted dynamically to enable the system to adapt to different environmental changes.

[0040] , δnew Indicates the updated data anomaly trigger threshold; α represents the adjustment coefficient; N represents the number of nodes; di,t Representation Node i deviation.

[0041] Accordingly, the adaptive filter gain is optimized: if the deviation of a node frequently exceeds the range, the system will adjust the filter gain of the node. The adjustment method is: , in, Ki,new Represents the updated filter gain, which is used for the next round of consensus filtering; β To adjust the rate, it means that the node's trust in the global estimate decreases as the deviation increases, which is used to control the gain change speed; di,t Representation Node i In time t Deviation value of ; ϵ Indicates the allowable error range for consistency.

[0042] It can be understood that the real-time data consistency guarantee system based on dual event triggering and H∞-consensus filtering can be efficiently implemented. First, the dual event triggering mechanism ensures the real-time and accuracy of data verification; second, the H∞-consensus filtering algorithm ensures data consistency in a noisy environment; finally, through distributed feedback and adaptive parameter optimization, the system dynamically adjusts the acquisition frequency, trigger threshold and filter gain of each node to adapt to different monitoring needs and environmental changes.

[0043] In the above-mentioned embodiment, the monitoring platform 13 includes: an analysis module for performing trend analysis and early warning analysis on the received data; and a visualization module for visualizing the analysis results.

[0044] In the provincial monitoring platform, a ring network is formed by connecting N ring network data loggers in series, creating an efficient and reliable communication network. They are connected to the intelligent central station to ensure high reliability and redundancy of data transmission.

[0045] Even if any node in the ring network has a network anomaly, other nodes can still maintain normal data transmission, thus ensuring the continuous operation of the monitoring system. The intelligent central station is the core of data aggregation, and can flexibly choose to aggregate the data and report it or report it separately, and then efficiently transmit the information to the cloud platform through the 4G / 5G network.

[0046] It can be understood that the peer-to-peer ring network data collection function can realize the real-time and accurate collection of information from various monitoring stations (various types of sensors) on the reservoir peer-to-peer ring network. These data include but are not limited to equipment status, operating parameters, environmental parameters, power status, etc., which are summarized to the intelligent central station for comprehensive management, and realize data redundancy and link redundancy for the working condition data of each station, ensuring the high-speed real-time response of the system, improving the communication reliability of the system, and saving hardware wiring costs.

[0047] Example 2 refer to Figure 5 In a second aspect of the present invention, a reservoir data collection method based on a peer-to-peer ring network is provided, comprising a plurality of ring network data collectors, an intelligent central station and a monitoring platform, including: S100. Each ring network data collector acquires real-time data from multiple sensors, and communicates with an adjacent ring network data collector or intelligent center to form a peer-to-peer communication ring network; based on a dual-event trigger mechanism, the data of the peer-to-peer communication ring network is filtered; the data that passes the consistency verification is uploaded to the monitoring platform; S200. The intelligent central station verifies the consistency of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; the data that passes the consistency verification is uploaded to the monitoring platform; S300 The detection platform performs trend analysis and early warning analysis on the received data, and visualizes the analysis results.

[0048] Further, in step S00, the consistency verification of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering includes: S201. Determine the filtering parameters of the infinite-dimensional norm consensus filter; S202. Iterate the data of the peer-to-peer communication ring network according to the filtering parameters; S203. Perform consistency check on the iterated data.

[0049] Example 3 refer to Figure 6 According to the third aspect of the present invention, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the reservoir data collection method based on a peer-to-peer ring network according to the second aspect of the present invention.

[0050] The electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0051] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 6 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0052] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, the above functions defined in the method of the embodiment of the present disclosure are executed. It should be noted that the computer-readable medium described in the embodiment of the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In an embodiment of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus, or a device. In an embodiment of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus, or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wire, optical cable, RF (radio frequency), etc., or any suitable combination of the foregoing.

[0053] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more computer programs. When the one or more programs are executed by the electronic device, the electronic device: Computer program code for performing the operations of embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, Python, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0054] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A reservoir data acquisition system based on a peer-to-peer ring network, comprising a plurality of ring network data collectors, an intelligent central station and a monitoring platform, characterized in that: Each ring network data collector is used to obtain real-time data of multiple sensors and communicate with an adjacent ring network data collector or intelligent central station to form a peer-to-peer communication ring network; and filtering the data of the peer-to-peer communication ring network based on a dual event trigger mechanism; An intelligent central station, used for verifying the consistency of data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; Upload the data that has passed the consistency verification to the monitoring platform; The monitoring platform is used to perform trend analysis and early warning analysis on the received data and visualize the analysis results.

2. The reservoir data acquisition system based on peer-to-peer ring network according to claim 1 is characterized in that: The ring network data collector comprises: Acquisition module, used to obtain real-time data from multiple sensors; The filtering module is used to filter the data of the peer-to-peer communication ring network based on a dual event trigger mechanism.

3. The reservoir data acquisition system based on peer-to-peer ring network according to claim 2 is characterized in that: The filtering module comprises: A determination unit, used to determine trigger parameters of a dual event trigger mechanism for real-time data; The trigger unit is used to filter the real-time data or upload it to the intelligent central station based on the trigger parameters.

4. The reservoir data acquisition system based on peer-to-peer ring network according to claim 1 is characterized in that: The intelligent central station comprises: A verification module, used to verify the consistency of data of the peer-to-peer communication ring network through an infinite-dimensional norm consensus filtering method and a consistency verification model; The upload module is used to upload data that has passed consistency verification to the monitoring platform.

5. The reservoir data acquisition system based on peer-to-peer ring network according to claim 4 is characterized in that: The verification module comprises: A determination unit, used to determine filtering parameters of infinite-dimensional norm consensus filtering; A filtering unit, configured to iterate the data of the peer-to-peer communication ring network according to filtering parameters; The verification unit is used to perform consistency verification on the iterated data.

6. The reservoir data acquisition system based on peer-to-peer ring network according to claim 1 is characterized in that: The monitoring platform comprises: Analysis module, used to perform trend analysis and early warning analysis on the received data; Visualization module, used to visualize the analysis results.

7. A reservoir data collection method based on a peer-to-peer ring network, comprising a plurality of ring network data collectors, an intelligent central station and a monitoring platform, characterized in that: include: Each ring network data collector acquires real-time data from multiple sensors and communicates with an adjacent ring network data collector or intelligent center to form a peer-to-peer communication ring network; Based on the dual event trigger mechanism, the data of the peer-to-peer communication ring network is filtered; the data that passes the consistency verification is uploaded to the monitoring platform; The intelligent central station verifies the consistency of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering; Upload the data that has passed the consistency verification to the monitoring platform; The detection platform conducts trend analysis and early warning analysis on the received data and visualizes the analysis results.

8. The reservoir data collection method based on peer-to-peer ring network according to claim 7 is characterized in that: The consistency verification of the data of the peer-to-peer communication ring network through infinite-dimensional norm consensus filtering includes: Determine the filter parameters of the infinite-dimensional norm consensus filter; Iterating the data of the peer-to-peer communication ring network according to the filtering parameters; Perform consistency check on the iterated data.

9. An electronic device, comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the reservoir data collection method based on the peer-to-peer ring network as described in any one of claims 7 to 8.

10. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the reservoir data collection method based on a peer-to-peer ring network as described in any one of claims 1 to 6 is implemented.

Images