Dam safety monitoring method and system based on multi-device cooperative communication

Abstract

The invention discloses a dam safety monitoring method and system based on multi-device cooperative communication, and relates to the technical field of safety monitoring technologies, and the method comprises the steps: obtaining a working state signal of each target processor in a preset monitoring time period, each target processor being distributed at a plurality of monitoring points of a dam, the adjacent target processors are in communication connection based on a preset communication rule, each working state signal is compared with a preset threshold value, when the comparison result is abnormal operation, the target processors generate fault signals and send the fault signals to the adjacent target processors, and the adjacent target processors adjust acquisition parameters based on a preset distribution rule and the fault signals. And calling the adjusted adjacent target processor to carry out data acquisition to obtain a target feature data set, and feeding back the target feature data set to the terminal. The problem that in the prior art, the actual water level and osmotic pressure conditions of the dam cannot be accurately reflected, and consequently the dam safety monitoring efficiency and accuracy are affected is solved. The method has the effect of improving the dam safety monitoring efficiency and accuracy.

Description

Technical Field

[0001] This invention relates to the technical field of safety monitoring technology, and in particular to a method and system for dam safety monitoring based on multi-device collaborative communication. Background Technology

[0002] With the development of large-scale and intelligent water conservancy projects, dams, as the core facilities of water conservancy projects, are directly related to the safety of people's lives and property and the stable development of the economy and society in downstream areas. Accurate monitoring of key parameters such as dam water level and seepage pressure is an important basis for assessing the safety status of dams and preventing major accidents such as dam failure. Therefore, higher requirements are placed on the real-time, accuracy and reliability of dam water level safety monitoring.

[0003] The current method for monitoring the safety of dam water levels mainly uses shielded twisted-pair cables as the medium. Through point-to-point direct connection or star topology cabling, the server terminal deployed in the monitoring center is physically connected to various sensors distributed at multiple key monitoring points such as the dam surface, the dam foundation, the spillway, and the reservoir area to ensure stable data transmission.

[0004] However, in the special environment of a dam, cables need to be exposed to the outdoors for a long time, which will be affected by rainwater erosion and long-term exposure to ultraviolet rays, causing damage to the cable sheath and a decrease in insulation performance. At the same time, due to cable failure, errors will inevitably occur in the data transmission from the sensor to the terminal, thus failing to accurately reflect the actual water level and seepage pressure of the dam, thereby affecting the efficiency and accuracy of dam safety monitoring. Summary of the Invention

[0005] The purpose of this invention is to provide a dam safety monitoring method based on multi-device collaborative communication, which improves the efficiency and accuracy of dam safety monitoring.

[0006] The above-mentioned objective of this invention is achieved through the following technical solution: A dam safety monitoring method based on multi-device collaborative communication includes: The working status signals of each target processor during the preset monitoring period are acquired. Each target processor is distributed at multiple monitoring points on the dam. Adjacent target processors are connected to each other based on preset communication rules. Compare each working status signal with the preset threshold; When the comparison result indicates an abnormal operation, the target processor generates a fault signal and sends it to the adjacent target processor; Adjacent target processors adjust their acquisition parameters based on preset allocation rules and fault signals; The adjusted adjacent target processor is invoked to collect data, obtain the target feature dataset, and feed it back to the terminal.

[0007] By adopting the above technical solution, the present invention establishes a target processor collaborative network through preset communication rules, obtains the working status signal of the target processor within a preset monitoring time period, and quickly transmits the fault signal to the adjacent target processor when an anomaly occurs. The adjacent target processor adjusts its own acquisition parameters based on the preset allocation rules and the fault signal, so that it can undertake the acquisition task of the target processor, ensuring data integrity and real-time performance, thereby effectively improving the efficiency and accuracy of dam safety monitoring.

[0008] In a preferred embodiment, the present invention can be further configured as follows: A dam safety monitoring method based on multi-device collaborative communication also includes: When the comparison result indicates normal operation, the seepage pressure signal of the associated monitoring point is collected and preprocessed to obtain the target seepage pressure dataset and fed back to the terminal.

[0009] By adopting the above technical solution, the present invention can efficiently acquire seepage pressure signals and perform preprocessing under normal conditions, ensuring the real-time nature and accuracy of monitoring data, and assisting in the stable assessment of the dam's safety status.

[0010] In a preferred embodiment, the present invention can be further configured as follows: A dam safety monitoring method based on multi-device collaborative communication also includes: When the terminal does not receive the target seepage pressure dataset uploaded by the target processor within a preset time period, the geographical location information of the target processor is obtained. Based on geographical location information, multiple adjacent target processors within a preset range are identified; Multiple adjacent target processors are dynamically filtered to obtain a backup processor, and a backup command is sent to the backup processor.

[0011] By adopting the above technical solution, the present invention sets up a terminal to monitor each target processor in real time. When the target processor uploads an abnormality, it quickly locates the optimal backup processor within the preset range of the processor and sends a backup command, so that the optimal backup processor can adjust the acquisition parameters, ensuring the continuity and integrity of the monitoring data, and effectively improving the reliability of dam safety monitoring.

[0012] In a preferred embodiment, the present invention can be further configured as follows: Dynamically filter multiple adjacent target processors to obtain a backup processor and send backup instructions to the backup processor, including: Acquire geographical location information and communication strength information between the target processor and multiple adjacent target processors; Euclidean distance is calculated based on geographic location information to obtain multiple calculated Euclidean distances; The calculated Euclidean distances are sorted according to a preset sorting standard to determine multiple candidate adjacent target processors; Based on the communication strength information, multiple candidate adjacent target processors are sorted a second time according to a preset sorting standard to obtain backup processors and send backup instructions to the backup processors.

[0013] By adopting the above technical solution, this invention dynamically determines the backup processor based on two dimensions: geographical distance and communication quality. It prioritizes selecting the backup processor that is close and has a strong signal to perform backup data acquisition, ensuring the efficiency and reliability of data replacement acquisition in abnormal situations, and further improving the continuity and accuracy of dam monitoring data.

[0014] In a preferred embodiment, the present invention can be further configured as follows: When the comparison result indicates normal operation, the seepage pressure signals from the associated monitoring points are collected and preprocessed to obtain the target seepage pressure dataset, which is then fed back to the terminal, including: The target processor collects seepage pressure signals from monitoring points according to preset acquisition frequency and accuracy; Preprocessing the osmotic pressure signal yields multiple osmotic pressure characteristic data; Data processing is performed on multiple seepage pressure characteristic data to obtain the target seepage pressure dataset and transmit it to the terminal.

[0015] By adopting the above technical solution, the present invention can accurately collect seepage pressure signals as needed under normal operating conditions, perform preprocessing, and then execute the corresponding data processing flow. This effectively filters out redundant information and retains key parameters, ensuring that the seepage pressure dataset transmitted to the terminal is low in redundancy, thereby improving the data quality and analysis efficiency of dam safety monitoring.

[0016] In a preferred embodiment, the present invention can be further configured as follows: Adjacent target processors adjust their acquisition parameters based on preset allocation rules and fault signals, including: The fault signal contains faulty device information of the target processor; The monitoring area of ​​the target processor is determined based on the faulty equipment information, thus obtaining the target monitoring area; Adjacent processors collect their own working status information for the current time period and obtain status feature values; The acquisition parameters are adjusted according to the status characteristic values ​​and the target monitoring area in accordance with the preset allocation rules.

[0017] By adopting the above technical solution, the present invention accurately locates the abnormal monitoring area based on the fault equipment information, and dynamically adjusts the acquisition parameters in combination with the real-time working status of adjacent processors, ensuring that the monitoring task of the fault area is reliably taken over, effectively maintaining the integrity and continuity of data acquisition, and improving the robustness of dam safety monitoring.

[0018] The second objective of this invention is to provide a dam safety monitoring system based on multi-device collaborative communication, which improves the efficiency and accuracy of dam safety monitoring.

[0019] The second objective of this invention is achieved through the following technical solution: The data acquisition module is used to acquire the working status signals of each target processor within a preset monitoring period. Each target processor is distributed at multiple monitoring points on the dam, and adjacent target processors are connected to each other based on preset communication rules. The comparison module is used to compare the signals of each working state with the preset threshold. The first processing module is used to generate a fault signal and send it to the adjacent target processor when the comparison result is abnormal. The second processing module is used to adjust the acquisition parameters of adjacent target processors based on preset allocation rules and fault signals; The feedback module is used to call the adjusted adjacent target processors to collect data, obtain the target feature dataset, and then feed it back. By adopting the above technical solution, this invention establishes a target processor collaborative network through preset communication rules, obtains the working status signal of the target processor within a preset monitoring time period, and quickly transmits the fault signal to the adjacent target processor when an anomaly occurs. The adjacent target processor adjusts its own collection parameters based on the preset allocation rules and the fault signal, so that it can undertake the collection task of the target processor, ensuring data integrity and real-time performance, thereby effectively improving the efficiency and accuracy of dam safety monitoring.

[0020] The third objective of this invention is to provide a device that improves the efficiency and accuracy of dam safety monitoring.

[0021] The above-mentioned objective three of this invention is achieved through the following technical solution: A device includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described above for a dam safety monitoring method based on multi-device collaborative communication.

[0022] The fourth objective of this invention is to provide a computer storage medium capable of storing corresponding programs, which facilitates the improvement of efficiency and accuracy in dam safety monitoring.

[0023] The fourth objective of this invention is achieved through the following technical solution: A computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the above-mentioned dam safety monitoring methods based on multi-device collaborative communication.

[0024] In summary, the present invention has at least one of the following beneficial technical effects: 1. This invention establishes a target processor collaborative network through preset communication rules, obtains the working status signal of the target processor within a preset monitoring time period, and quickly transmits the fault signal to the adjacent target processor when an anomaly occurs. The adjacent target processor adjusts its own acquisition parameters based on the preset allocation rules and the fault signal, so that it can undertake the acquisition task of the target processor, ensuring data integrity and real-time performance, thereby effectively improving the efficiency and accuracy of dam safety monitoring.

[0025] 2. This invention enables real-time monitoring of each target processor by setting up a terminal. When an abnormality is uploaded by a target processor, the optimal backup processor within the preset range is quickly located and a backup command is sent. This allows the optimal backup processor to adjust the acquisition parameters, ensuring the continuity and integrity of the monitoring data and effectively improving the reliability of dam safety monitoring.

[0026] 3. This invention dynamically determines the backup processor based on two dimensions: geographical distance and communication quality. It prioritizes the backup processor that is close and has a strong signal to perform backup data acquisition, ensuring the efficiency and reliability of data replacement acquisition in abnormal situations, and further improving the continuity and accuracy of dam monitoring data. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating the steps of a dam safety monitoring method based on multi-device collaborative communication, according to one embodiment of the present invention.

[0028] Figure 2 This is a structural block diagram of a dam safety monitoring system based on multi-device collaborative communication, according to one embodiment of the present invention. Detailed Implementation

[0029] The present invention will be further described in detail below with reference to the accompanying drawings.

[0030] This specific embodiment is merely an explanation of the present invention and is not intended to limit the invention. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of the claims of the present invention.

[0031] It should be noted that, in the embodiments of this invention, the data related to object information, when applied to specific products or technologies, requires the permission or consent of the object. Furthermore, the collection, use, and processing of this data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. In other words, if the embodiments of this invention involve data related to an object, it must be obtained with the object's authorization and consent, the authorization and consent of relevant departments, and in accordance with the relevant laws, regulations, and standards of the country and region. If the embodiments involve personal information, the acquisition of all personal information requires the individual's consent. If sensitive information is involved, the separate consent of the information subject is required. The embodiments also need to be implemented with the object's authorization and consent.

[0032] Example 1: Please see Figure 1 This invention provides a dam safety monitoring method based on multi-device collaborative communication, comprising: S1. Obtain the working status signal of each target processor within a preset monitoring period. Each target processor is distributed at multiple monitoring points on the dam. Adjacent target processors are connected to each other based on preset communication rules.

[0033] The target processor refers to a vibrating wire piezometer monitoring processor used for dam safety monitoring, specifically a device for monitoring seepage pressure in soil, rock, or hydraulic structures. Vibrating wire piezometer monitoring processors include, but are not limited to, HRPT-4P, TID08, and PTP-300-07-CJQ.

[0034] The target processor is cylindrical in shape, its dimensions matching the space for cable storage, facilitating direct cable replacement during installation. The cylindrical casing is made of durable materials, including but not limited to stainless steel and high-strength plastics, offering waterproof, dustproof, vibration-resistant, and corrosion-resistant properties, making it well-suited to the complex environmental conditions of dams.

[0035] It is worth mentioning that each vibrating wire pressure sensor monitoring processor integrates: The data processing module is used to preprocess the collected seepage pressure signals and then perform data processing. It is also used to collect its own working status signals.

[0036] The wireless communication module, which includes, but is not limited to, LoRa and 4G modules, is used to enable short-range communication with adjacent processors and long-range data upload to the terminal.

[0037] Preferably, the wireless communication module uses a Lora module for wireless communication.

[0038] The power module is used to provide a stable power supply to the processor. The power module has a variety of power supply methods, including but not limited to solar power, battery power, and external power supply.

[0039] The preset monitoring period refers to the periodic data collection time window set by the system.

[0040] Preferably, the preset monitoring period is once every 15 minutes.

[0041] A GPS module is used to obtain one's latitude and longitude coordinates by receiving satellite signals.

[0042] Multiple monitoring points for a dam refer to the deployment of monitoring points at various key locations along the dam, with a processor installed at each monitoring point. Key locations include, but are not limited to, the dam body, dam foundation, and spillway.

[0043] Operating status signals refer to the processor's own operating status signals collected by its internal monitoring unit, including but not limited to power status, communication status, and sensor status. Power status can be the remaining battery power, communication status can be the signal strength with adjacent processors, and sensor status can be used to determine the sampling success rate, which can be determined based on the ratio of historical successful samplings to the total number of samplings.

[0044] It is worth mentioning that the internal monitoring units include, but are not limited to, IMU-200, MSM-300 and ISM-150 models. Through the configuration of the internal units, the basic power status, communication status and hardware status of the processor are collected, which provides key data support for the processor's self-diagnosis and fault early warning, and ensures the stable operation of the dam safety monitoring system.

[0045] Preset communication rules refer to the rules followed when establishing communication connections between adjacent processors, including but not limited to distance thresholds, signal strength thresholds, etc., in order to form a local wireless sensor network.

[0046] When the preset communication rule is a distance threshold, a preset threshold between two processors is set based on the average distribution density of the dam monitoring points. When the distance between two processors is less than the preset distance, they are identified as potential communicable nodes, and a LoRa communication link is automatically established, thus forming a self-organizing wireless sensor network with real-time topology updates. The preset distance can be 50 meters, 100 meters, 500 meters, etc., and is not limited here.

[0047] When the preset communication rule is strength, similarly, the attenuation effect of the dam's concrete structure on the wireless signal can be considered, and a specific value can be set for the strength signal threshold. When the received signal strength between processors is greater than the preset threshold, it is determined that the signal quality meets the standard, and thus a communication connection is established.

[0048] This can be understood as follows: when there is only one case of the preset communication rule, the communication connection is established by comparing a single case; if there are multiple cases of the preset communication rule, the communication connection is established only when each case is satisfied.

[0049] It is worth mentioning that when the target processor's distance from its original neighboring processors exceeds a distance threshold due to device displacement, or when signal strength drops below a threshold due to heavy rain, a preset rule triggers a link assessment, automatically disconnecting the connection. Simultaneously, the target processor re-detects surrounding processors, establishing connections with new neighboring processors that meet the preset communication rules, maintaining the integrity of the local network. The establishment of preset communication rules ensures the stability and efficiency of the local wireless sensor network, provides a reliable communication foundation for the dynamic coordination and fault response of the dam monitoring system, and ultimately achieves continuous and accurate monitoring of seepage pressure signals.

[0050] Two adjacent processors exchange status signals bidirectionally at preset intervals. Specifically, the sender broadcasts a signal frame containing its own operating status via the LoRa wireless communication module. The receiver first verifies whether the signal strength conforms to preset communication rules; if so, it stores the status signal, completing one exchange and facilitating mutual monitoring of each other's operational status. Simultaneously, each processor periodically aggregates two sets of data: its own operating status signal and the status signals from previously received and stored adjacent processors. This data is then uploaded to the terminal via the wireless communication module, with CRC checks used before upload to ensure data integrity.

[0051] It is worth mentioning that during off-peak monitoring periods, the processor enters a sleep state, retaining only the internal monitoring unit to collect working status signals, and wakes up once every preset time to communicate with adjacent processors, thereby reducing power consumption and extending battery life.

[0052] In this embodiment of the invention, the working status signal of each vibrating wire seepage pressure sensor monitoring processor is obtained within the predicted monitoring time period. Each processor is distributed in each monitoring point of the dam. Adjacent processors communicate with each other based on preset communication rules. By setting the preset rules, the stability and reliability of data interaction between adjacent processors can be guaranteed.

[0053] S2. Compare each working status signal with the preset threshold.

[0054] Set a corresponding preset threshold for each working status signal.

[0055] The preset threshold for the remaining power supply can be 10%, 20%, 50%, etc. Preferably, the preset threshold is 20%.

[0056] The preset threshold for signal strength can be -100dBm, -110dBm, etc. Preferably, the preset threshold is -100dBm.

[0057] The preset threshold for sampling success rate can be 90%, 95%, 98%, etc. Preferably, the preset threshold is 98%.

[0058] Each preset threshold can be adjusted according to the actual situation, and no specific limit is specified here.

[0059] It is worth mentioning that the terminal can receive the status comparison results of each processor in real time. When more than two processors in a certain area are detected to be in an abnormal state at the same time, the dynamic routing protocol is automatically triggered to adjust the data transmission path in that area, thereby avoiding network congestion and data loss.

[0060] In this embodiment of the invention, the working status signal is compared one by one with its corresponding preset threshold.

[0061] S3. When the comparison result is abnormal, the target processor generates a fault signal and sends it to the adjacent target processor.

[0062] An abnormal operation is determined when any of the following conditions occur: Scenario 1: The remaining battery power is lower than a preset threshold; Case 2: The communication connection is in failure. Case 3: When the sampling success rate is lower than the preset threshold.

[0063] In this embodiment of the invention, if any condition is found in the comparison results, it is determined to be an abnormal operation. The target processor will generate a fault signal and send it to the adjacent processors that are communicating with the target processor. By judging the abnormal state in a multi-dimensional way and triggering the fault signal transmission in a timely manner, the coordinated response of adjacent processors can be quickly initiated, effectively ensuring the continuity and reliability of osmotic pressure data acquisition.

[0064] S4. Adjacent target processors adjust the acquisition parameters based on preset allocation rules and fault signals.

[0065] In this embodiment of the invention, adjacent target processors adjust their own acquisition parameters according to preset allocation rules and fault signals, thereby accurately taking over the acquisition task of the faulty processor, ensuring that data acquisition is not affected by the faulty processor, thus effectively protecting the integrity of the data, and improving the efficiency and accuracy of security monitoring.

[0066] Preferably, step S4 includes the following sub-steps: S401, the fault signal contains fault device information of the target processor.

[0067] Fault equipment information refers to relevant information of the vibrating wire pressure sensor monitoring processor that has malfunctioned. This information is included in the fault signal and is used to help adjacent processors and terminals understand the fault situation and respond accordingly. This allows adjacent processors to automatically adjust the acquisition parameters according to preset rules and take over some or all of the acquisition tasks of the faulty processor.

[0068] Preferably, the faulty device information includes the target processor's number, which is used to accurately locate the monitoring position of the faulty device.

[0069] In this embodiment of the invention, the fault signal includes the target processor's number.

[0070] S402. Determine the monitoring area of ​​the target processor based on the faulty equipment information to obtain the target monitoring area.

[0071] The target monitoring area refers to the dam monitoring area that the vibrating wire seepage pressure sensor monitoring processor is responsible for.

[0072] After receiving a fault signal from the target processor, the adjacent processor extracts the unique number of the target processor from the fault device information. Since the location and monitoring range of each monitoring point are preset at the beginning of deployment (e.g., a certain hardware number corresponds to the seepage pressure monitoring of the 100-150 meter section of the dam body), the adjacent processor can quickly match the physical monitoring area corresponding to the hardware number through the built-in location mapping table, and use it as the target monitoring area.

[0073] This can be understood as follows: if the fault processor is numbered "08", its preset monitoring area is the dam body within 200-250 meters on the left bank of the dam and a 5-meter radius around it. The adjacent processors "07" and "09", which have established a communication connection with "08", will, upon receiving the fault signal, determine the target monitoring area as the 200-250 meter range on the left bank based on the preset information corresponding to that number. Subsequently, to avoid data gaps in the fault processor's monitoring area, "07" and "09" will automatically adjust their monitoring parameters and data acquisition parameters according to the system's preset coverage rules (such as "extending a fixed distance in numerical order").

[0074] For example, the original monitoring area of ​​processor "09" might be to the right of "08" (e.g., 250-300 meters on the left bank). After extending it 20 meters to the right, its monitoring range extends to 230-320 meters, covering the 230-250 meter portion of the original "08" area. The original monitoring area of ​​processor "07" might be to the left of "08" (e.g., 150-200 meters on the left bank). After extending it 20 meters to the left, its monitoring range extends to 130-220 meters, covering the 200-220 meter portion of the original "08" area. Through the coordinated adjustment of "07" extending 20 meters to the left and "09" extending 20 meters to the right, the monitoring ranges of both processors jointly cover the 200-250 meter area originally covered by processor "08" (200-220 meters covered by "07", and 220-250 meters covered by "09"). This mechanism ensures that even if the "08" processor fails, the acquisition of seepage pressure data in the area can continue seamlessly without interruption, thus guaranteeing the integrity and continuity of dam safety monitoring.

[0075] In this embodiment of the invention, adjacent processors determine the target monitoring area based on the number in the faulty device information, thereby achieving accurate replacement of the monitoring range of the faulty processor, avoiding monitoring blind spots caused by device failure, and improving the reliability of the system.

[0076] S403. Adjacent processors collect their own working status information for the current time period and obtain status feature values.

[0077] State characteristic value refers to the characteristic data that reflects the working status of adjacent vibrating wire pressure sensor monitoring processors after they have collected their own working status information for the current period and then preprocessed by the data processing module.

[0078] Upon receiving a fault signal, the adjacent processor will collect its own operating status information, which includes the remaining battery level of the power module, signal strength, sampling frequency, etc., as status characteristic values.

[0079] In this embodiment of the invention, the remaining battery level, signal strength, and sampling frequency at the current time point are obtained through adjacent state processors as state feature values. The acquisition of state feature values ​​provides a guarantee for subsequent parameter adjustment.

[0080] S404. Adjust the acquisition parameters according to the preset allocation rules based on the status characteristic values ​​and the target monitoring area.

[0081] Preset allocation rules refer to the rules followed when adjacent processors receive a fault signal and undertake part or all of the acquisition tasks of the faulty processor. These preset allocation rules include, but are not limited to, priority and coverage.

[0082] The acquisition parameters refer to the relevant parameters set by the vibrating wire osmotic pressure sensor monitoring processor when acquiring osmotic pressure data. These parameters affect the effectiveness and efficiency of data acquisition, including but not limited to sampling frequency, acquisition accuracy, and acquisition range.

[0083] Taking priority as the preset allocation rule as an example, the processor with better state characteristic value has higher priority and is given priority in the target monitoring area with a larger area.

[0084] Understandably, assuming the status characteristics of a first-priority processor meet the following criteria (battery remaining > 80%, signal strength > -100dBm, sampling success rate > 98%), it has the capability to take over 60% of the target monitoring area, and is therefore allocated that 60% of the target monitoring area. The status characteristics of a second-priority processor meet the following criteria (50% ≤ battery remaining ≤ 80%, -110dBm ≤ signal strength ≤ -100dBm, sampling success rate > 95%), it has the capability to take over 30% of the target monitoring area, and is therefore allocated that 30% of the target monitoring area. The status characteristics of a third-priority processor meet the following criteria (30% ≤ battery remaining ≤ 50%, -120dBm ≤ signal strength ≤ -110dBm, sampling success rate > 90%), it has the capability to take over 10% of the target monitoring area, and is therefore allocated that 10% of the target monitoring area, thus ensuring full coverage of the target monitoring area. If multiple adjacent processors are at the same priority level, the task is evenly distributed according to the target monitoring area to avoid new failures caused by excessive load on a single processor.

[0085] Based on this, after taking over 60% of the target monitoring area, the first-priority processor increases the sampling frequency from the default 5 times / minute to 8 times / minute to obtain more dense osmotic pressure data, while maintaining a communication interval of 30 minutes / time with the cloud to ensure the real-time upload of key data; since its battery has sufficient reserve (>80%), there is no need to reduce the energy consumption of other non-essential functions, and it can maintain full-load operation to efficiently cover the core area.

[0086] After the secondary priority processor takes over 30% of the target monitoring area, it adjusts the sampling frequency to 6 times / minute and extends the communication interval to 45 minutes / time, balancing energy consumption while ensuring data validity. Considering that its signal strength is in the range of -100 to -110dBm, it will automatically switch to the enhanced communication mode of the LoRa module to reduce attenuation and distortion during signal transmission.

[0087] After the Level 3 priority processor takes over 10% of the target monitoring area, the sampling frequency remains unchanged at 5 times / minute, but the duration of each sampling is reduced to decrease the load on the data processing module. Due to the relatively low battery level (30%-50%), the energy-saving mode is activated, shutting down some auxiliary circuits during non-sampling periods and keeping only the core monitoring unit running. At the same time, the communication interval is set to 60 minutes / time to prioritize the stability of the power supply.

[0088] It is worth mentioning that by allocating target monitoring areas according to priority and combining this with the average allocation rule under the same priority, the original monitoring area of ​​the faulty processor is ensured to be covered without blind spots, avoiding data gaps caused by the failure of a single processor. At the same time, parameters such as sampling frequency and communication interval corresponding to different priorities are matched with the area under control, and the overall monitoring capability is maintained through dynamic adjustment, providing efficient and robust technical support for dam safety monitoring.

[0089] Meanwhile, even if the faulty processor is no longer working, the original data acquisition work of the adjacent processor will continue. During the adjustment period, the adjacent processor has already acquired data within the original range before receiving the fault signal. After the acquisition parameter adjustment command is triggered, the adjacent processor continues to acquire data in its original area while executing in parallel, until the new configuration takes effect and expands to the target area.

[0090] Understandably, assuming processor "08" malfunctions, the adjacent "07" and "09" need to expand their range to take over: Before adjustment: "07" collects data from 150-200 meters on the left bank, and "09" collects data from 250-300 meters, both sampling at 5 times / minute, continuously; When adjustment is triggered: "07" and "09" receive the fault signal and begin calculating the new monitoring range ("07" expands to 200-220 meters, and "09" expands to 230-250 meters), but the ongoing Nth sampling continues until it is completed and stored; In the next sampling cycle (N+1th time): "07" and "09" automatically collect data according to the new range, while maintaining the original area's data collection unchanged. This method ensures the accuracy of the adjustment process and the continuity of data collection.

[0091] In this embodiment of the invention, adjacent processors precisely adjust the acquisition parameters according to preset allocation rules based on state feature values ​​and target monitoring areas. This ensures the continuity and accuracy of data acquisition in the target monitoring area, avoids overloading of their own operation, and improves the collaborative efficiency of the entire monitoring system.

[0092] Combining steps S401-S404, it can be understood that each adjacent processor first accurately locates the target monitoring area of ​​the faulty processor through the device number in the fault signal, and clarifies the physical range that needs to be taken over. Then, each adjacent processor collects its own working status characteristics such as battery level, signal strength, and sampling frequency in real time to determine its current working capacity. Finally, based on preset priority rules and the quality of status characteristics, the coverage area is dynamically allocated—processors with better status take on a larger proportion of the area first, and those with the same priority are assigned tasks equally. At the same time, the monitoring range is dynamically adjusted to achieve precise filling, thereby adjusting the original acquisition parameters to ensure complete coverage and balanced load of seepage pressure data acquisition in the target monitoring area, avoiding single-point overload or monitoring blind spots.

[0093] S5. Call the adjusted adjacent target processor to collect data, obtain the target feature dataset, and feed it back to the terminal.

[0094] The adjusted adjacent target processor is invoked to collect data such as peak pressure, frequency, and duration. This data is then preprocessed to obtain a target feature dataset, which is transmitted to the terminal via a wireless communication module at preset intervals. The preprocessing steps here are the same as the subsequent sub-steps in S6, and will not be described again here.

[0095] It is worth mentioning that the terminal will integrate and verify the received feature data. If it finds that the data in a certain area is missing or abnormal, it will send a supplementary sampling instruction to the corresponding adjacent processor again until complete and reliable target feature data is obtained.

[0096] Preferably, the preset time is 10 minutes.

[0097] In this embodiment of the invention, the adjusted adjacent target processor is invoked to collect data, which can efficiently complete the data collection task of the fault area, ensure the real-time performance and accuracy of the target feature data, and provide reliable support for the safety monitoring of dam water level.

[0098] S6. When the comparison result is normal operation, the seepage pressure signal of the associated monitoring point is collected and preprocessed to obtain the target seepage pressure dataset and fed back to the terminal.

[0099] In this embodiment of the invention, when all working status signals meet the preset threshold, the system is in normal operation. The target processor collects the feature data of the monitoring points, performs preprocessing, obtains the target seepage pressure dataset that meets the requirements, and transmits it to the terminal according to the preset time.

[0100] Preferably, step S6 includes the following sub-steps: S601, the target processor collects the seepage pressure signal of the monitoring point according to the preset acquisition frequency and accuracy.

[0101] The acquisition frequency refers to the number of times the vibrating wire osmotic pressure sensor monitoring processor acquires the osmotic pressure signal per unit time. The data processing module will acquire characteristic data according to the set acquisition frequency.

[0102] Preferably, the sampling frequency is set to 5 times / minute.

[0103] Acquisition accuracy refers to the range and precision of the deviation between the data obtained by the processor when acquiring and measuring seepage pressure signals and the actual seepage pressure value. The preset acquisition accuracy is determined based on actual needs and sensor performance. No specific limit is set here.

[0104] The seepage pressure signal refers to the signal related to seepage pressure at the dam monitoring point. It is collected by the sensor in the vibrating wire seepage pressure sensor monitoring processor and is the raw signal reflecting the seepage pressure at that monitoring point of the dam.

[0105] In this embodiment of the invention, the target processor collects the seepage pressure signals of its associated monitoring points according to a preset acquisition frequency and precision.

[0106] S602. Preprocess the seepage pressure signal to obtain multiple seepage pressure characteristic data.

[0107] Preprocessing refers to the process of processing the raw osmotic pressure signal collected by the vibrating wire osmotic pressure sensor through a series of targeted technical means to eliminate interference, improve signal quality, and transform the signal form, ultimately obtaining "osmotic pressure characteristic data" that can be used for subsequent analysis.

[0108] The specific preprocessing process is as follows: Signals are processed using filters to obtain filtered signals. These filters include, but are not limited to, low-pass filters, high-pass filters, band-pass filters, and band-stop filters. The goal is to remove high-frequency noise or low-frequency interference from the signal while retaining the useful signal components.

[0109] The filtered signal is processed using Kalman filtering technology to obtain a denoised signal, thereby reducing random noise in the signal and improving the clarity and reliability of the signal.

[0110] The denoised signal is amplified using an amplifier to obtain an amplified signal, thereby improving the signal-to-noise ratio and making subsequent processing more accurate.

[0111] The amplified signal is sampled and quantized using an analog-to-digital converter to obtain multiple osmotic pressure characteristic data.

[0112] In this embodiment of the invention, filtering, noise reduction, amplification, and a digital-to-analog converter are used to preprocess the osmotic pressure signal to obtain multiple osmotic pressure characteristic data.

[0113] S603. Perform data processing on multiple seepage pressure characteristic data to obtain the target seepage pressure dataset and transmit it to the terminal.

[0114] The osmotic pressure characteristic data includes the peak value, frequency, and duration of osmotic pressure.

[0115] Peak osmotic pressure refers to the maximum value of osmotic pressure during the period monitored by the target processor, frequency refers to the frequency of osmotic pressure changes, and duration refers to the duration of a specific osmotic pressure state.

[0116] The preprocessed osmotic pressure characteristic data are filtered and integrated to form a target osmotic pressure dataset. The wireless communication module in the vibrating wire osmotic pressure sensor monitoring processor uploads the target osmotic pressure dataset to the terminal via a wireless network.

[0117] Data processing includes filtering and integration, and the specific steps are as follows: First, the pre-processed seepage pressure characteristic data is screened, that is, peak values ​​exceeding the safety warning value are filtered out by setting a threshold, and outliers with no practical reference value are removed; for frequency data, the number of changes per unit time is calculated and combined with the needs of dam safety monitoring, key frequency information that can reflect the periodic changes in seepage pressure is retained; for duration data, the duration of different seepage pressure states (such as normal, warning, and dangerous) is statistically analyzed.

[0118] Then, a unified timestamp is added to the selected osmotic pressure characteristic data to ensure the correspondence of different characteristic data in the time dimension. For example, the specific time when a certain peak occurs, the frequency corresponding to that time, and the duration of the osmotic pressure state are all associated with the same timestamp.

[0119] Next, the seepage pressure characteristic data are integrated according to a preset data structure framework, which may include fields such as "monitoring point number - timestamp - peak data - frequency data - duration data", so that the various data form interrelated records.

[0120] Next, the integrated dataset undergoes redundancy checks to remove duplicate or contradictory data entries, ensuring data consistency and uniqueness. After integration, a structured target seepage pressure dataset is formed. Finally, the target seepage pressure dataset is transmitted to the terminal for storage and analysis.

[0121] In this embodiment of the invention, the peak value, frequency, and duration of osmotic pressure are filtered and integrated to obtain a target osmotic pressure dataset, which is then transmitted to the terminal.

[0122] S7. When the terminal does not receive the target seepage pressure dataset uploaded by the target processor within a preset time period, obtain the geographical location information of the target processor.

[0123] Geographic location information refers to the geographic coordinates determined by the processor's GPS module.

[0124] In this embodiment of the invention, when the terminal does not receive the feature dataset uploaded by the target processor within a preset time period, the geographical location information of the faulty processor is obtained through the positioning module built into the target processor. This geographical location information can help staff quickly locate the specific location of the target processor.

[0125] S8. Determine multiple adjacent target processors within a preset range based on geographical location information.

[0126] Based on the geographical location information of the target processor, a preset range centered on it can be defined. Then, based on the pre-established local wireless sensor network, neighboring processors in normal working condition within this range can be retrieved as target processors that can undertake the task of collecting faulty processor data.

[0127] It is worth mentioning that when defining the preset range, the distribution density of the dam monitoring points can be adjusted to ensure that a sufficient number of adjacent processors can be selected.

[0128] In this embodiment of the invention, based on the geographical location information of the target processor, multiple target processors within a preset range centered on the target processor are determined as processors capable of undertaking the data acquisition task.

[0129] S9. Dynamically filter multiple adjacent target processors to obtain a backup processor and send a backup command to the backup processor.

[0130] Dynamic filtering refers to the process of combining the real-time status of adjacent target processors with preset filtering rules to filter adjacent processors within a preset range and determine the standby processors that meet the conditions.

[0131] In this embodiment of the invention, multiple adjacent target processors are dynamically filtered to obtain multiple backup processors, and backup instructions are sent to the multiple backup processors. The multiple backup processors adjust the acquisition parameters according to the preset allocation rules, and then perform data acquisition.

[0132] Preferably, step S9 includes the following sub-steps: S901, Obtain geographical location information and communication strength information between the target processor and multiple adjacent target processors.

[0133] Geographic location information can be obtained by using the GPS module to obtain the latitude and longitude coordinates of each target processor.

[0134] Communication strength information can be obtained by directly measuring the received signal strength indication through the wireless communication module.

[0135] In this embodiment of the invention, the geographical location information and communication strength information between the target processor and multiple adjacent target processors are obtained through a GPS module and a wireless communication module.

[0136] S902. Calculate the Euclidean distance based on the geographical location information to obtain multiple calculated Euclidean distances.

[0137] Based on the geographical location information of the target processor and multiple adjacent target processors, the straight-line distance between them is calculated using the Euclidean distance formula.

[0138] The formula for calculating Euclidean distance is: For two points (x1, y1) and (x2, y2), their Euclidean distance is...

[0139] It is understandable that if the geographic coordinates of the target processor are (116.5, 39.9) and the coordinates of a neighboring target processor are (116.6, 40.0), the Euclidean distance between the two can be calculated by substituting them into the formula. Similarly, by calculating the distances for other neighboring target processors in turn, multiple calculated Euclidean distances can be obtained. These distances can be used as a basis for judging the spatial relationship between neighboring processors and the target processor, and can assist in subsequent operations such as task allocation.

[0140] In this embodiment of the invention, the geographical location information of the target processor and multiple adjacent target processors is calculated to obtain multiple calculated Euclidean distances.

[0141] S903. Sort the calculated Euclidean distances according to the preset sorting criteria to determine multiple candidate adjacent target processors.

[0142] The default sorting criterion is based on Euclidean distance from smallest to largest.

[0143] In this embodiment of the invention, multiple calculated Euclidean distances are sorted in ascending order, and processors with closer distances are selected as multiple candidate adjacent target processors, thereby ensuring that the candidate processors are within the effective communication range and providing spatial feasibility for subsequent acquisition tasks of faulty processors.

[0144] S904. Based on the communication strength information, multiple candidate adjacent target processors are sorted a second time according to a preset sorting standard to obtain a backup processor and send a backup command to the backup processor.

[0145] The default sorting criterion is from strongest to weakest communication strength.

[0146] In this embodiment of the invention, the candidate adjacent target processors are sorted in a second order according to the communication strength from strong to weak to obtain multiple backup processors, and backup instructions are sent to the multiple backup processors.

[0147] Understandably, by combining steps S903-S904, the processors are first sorted from smallest to largest according to Euclidean distance, prioritizing those with closer physical locations as candidates. This effectively reduces the number of adjacent target processors in the subsequent communication strength assessment. Then, based on the distance-based selection, a second sort is performed according to communication strength from strongest to weakest, further refining backup processors from the perspective of actual communication performance. This reduces invalid task allocation attempts, thereby lowering the communication interaction cost between processors and the system's computing power consumption. Through multiple sorting steps, the selection efficiency is improved while maximizing the reliability of backup processors, thus effectively improving the efficiency and accuracy of dam safety monitoring.

[0148] Example 2: Please see Figure 2 This invention provides a dam safety monitoring system based on multi-device collaborative communication, comprising: This invention provides a dam safety monitoring system based on multi-device collaborative communication, comprising: The data acquisition module 101 is used to acquire the working status signals of each target processor within a preset monitoring period. Each target processor is distributed at multiple monitoring points on the dam, and adjacent target processors are connected to each other based on preset communication rules.

[0149] The comparison module 102 is used to compare each working status signal with a preset threshold.

[0150] The first processing module 103 is used to generate a fault signal and send it to the adjacent target processor when the comparison result is abnormal.

[0151] The second processing module 104 is used to adjust the acquisition parameters of adjacent target processors based on preset allocation rules and fault signals.

[0152] Feedback module 105 is used to call the adjusted adjacent target processor to collect data, obtain the target feature dataset, and feed it back to the terminal.

[0153] Since the above is a system corresponding to a dam safety monitoring method based on multi-device collaborative communication, its implementation principle is the same as that of a dam safety monitoring method based on multi-device collaborative communication, and will not be described in detail here.

[0154] Example 3: The present invention provides a device, comprising: a memory and a processor, wherein the memory stores a computer program; when the computer program is executed by the processor, the processor performs a dam safety monitoring method based on multi-device collaborative communication as described in any of the above embodiments.

[0155] The memory can be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory has storage space for program code used to perform any of the method steps described above. For example, the storage space for program code may include individual program codes for implementing the various steps in the methods described above. This program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed, for example, in a suitable form. When run by a computing processing device, this code causes the computing processing device to perform the various steps in the methods described above.

[0156] Example 4: The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements a dam safety monitoring method based on multi-device collaborative communication as described in any embodiment of the present invention.

[0157] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0162] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dam safety monitoring method based on multi-device cooperative communication, characterized in that, The method comprises the following steps: acquiring working state signals of each target processor within a preset monitoring period, the target processors being distributed at multiple monitoring points of a dam, wherein adjacent target processors are connected in communication based on a preset communication rule; comparing each working state signal with a preset threshold value; when the comparison result is abnormal operation, the target processor generates a fault signal and sends it to the adjacent target processor; the adjacent target processor adjusts the collection parameters based on a preset allocation rule and the fault signal; the adjusted adjacent target processor is called to collect data, target feature data sets are obtained and fed back to a terminal.

2. The method for dam safety monitoring based on multi-device collaborative communication according to claim 1, characterized in that, Further comprising: when the comparison result is normal operation, collecting and preprocessing seepage pressure signals of the associated monitoring points to obtain target seepage pressure data sets and feed them back to the terminal.

3. The dam safety monitoring method based on multi-device cooperative communication according to claim 1 or 2, characterized in that, Further comprising: when the terminal does not receive the target seepage pressure data sets uploaded by the target processor within a preset time period, acquiring the geographic location information of the target processor; determining multiple adjacent target processors within a preset range according to the geographic location information; dynamically screening the multiple adjacent target processors to obtain a backup processor and send a backup instruction to the backup processor.

4. The method for dam safety monitoring based on multi-device cooperative communication according to claim 3, characterized in that, Dynamically screening the multiple adjacent target processors to obtain a backup processor and send a backup instruction to the backup processor, comprising: acquiring the geographic location information and communication strength information between the target processor and the multiple adjacent target processors; performing Euclidean distance calculation according to the geographic location information to obtain multiple calculated Euclidean distances; sorting the multiple calculated Euclidean distances according to a preset sorting standard to determine multiple candidate adjacent target processors; performing secondary sorting on the multiple candidate adjacent target processors according to the communication strength information and a preset sorting standard to obtain a backup processor and send a backup instruction to the backup processor.

5. The method for dam safety monitoring based on multi-device collaborative communication according to claim 2, characterized in that, When the comparison result is normal operation, collecting and preprocessing seepage pressure signals of the associated monitoring points to obtain target seepage pressure data sets and feed them back to the terminal, comprising: the target processor collects the seepage pressure signals of the monitoring points according to a preset collection frequency and accuracy; preprocessing the seepage pressure signals to obtain multiple seepage pressure feature data; performing data processing on the multiple seepage pressure feature data to obtain target seepage pressure data sets and transmit them to the terminal.

6. The method for dam safety monitoring based on multi-device collaborative communication according to claim 1, characterized in that, The adjacent target processor adjusts the collection parameters based on a preset allocation rule and the fault signal, comprising: the fault signal contains fault device information of the target processor; determining the monitoring area of the target processor according to the fault device information to obtain a target monitoring area; the adjacent processor collects its own working state information in the current period to obtain a state feature value; adjusting the collection parameters according to the state feature value and the target monitoring area according to a preset allocation rule.

7. A dam safety monitoring system based on multi-device cooperative communication, characterized in that, The method comprises the following steps: a data collection module is configured to acquire working state signals of each target processor within a preset monitoring period, the target processors being distributed at multiple monitoring points of a dam, wherein adjacent target processors are connected in communication based on a preset communication rule; a comparison module is configured to compare each working state signal with a preset threshold value; a first processing module is configured to, when the comparison result is abnormal operation, the target processor generates a fault signal and sends it to the adjacent target processor; The second processing module is configured to adjust the acquisition parameters of the adjacent target processor based on a preset allocation rule and the fault signal; The feedback module is configured to call the adjusted adjacent target processor to perform data acquisition, obtain target feature data sets, and feed back to the terminal.

8. An apparatus, comprising: The memory and the processor are included, and the memory stores a computer program capable of being loaded and executed by the processor to perform the dam safety monitoring method based on the multi-device cooperative communication according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The memory stores a computer program capable of being loaded and executed by the processor to perform the dam safety monitoring method based on the multi-device cooperative communication according to any one of claims 1 to 6.

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