A valve water hammer self-adaptive monitoring and early warning system, method and device

Abstract

The application provides a valve water hammer self-adaptive monitoring and early warning system, method and device, relates to the technical field of valve monitoring, and obtains first pressure data at a first acquisition frequency, and sends the first pressure data to a dispatching monitoring device at a first reporting period; when the pressure data reaches a trigger condition, obtains second pressure data at a second acquisition frequency, and sends the second pressure data to the dispatching monitoring device at a second reporting period; water hammer feature analysis is carried out based on the second pressure data, and an early warning result is obtained, so that early warning information is quickly and accurately extracted from massive data, and the timeliness of water hammer early warning is improved.

Description

Technical Field

[0001] This invention relates to the field of valve monitoring technology, and more specifically, to a valve water hammer adaptive monitoring and early warning system, method, and device. Background Technology

[0002] In long-distance pressurized water transmission projects, water hammer is a major risk factor threatening the safe operation of pipelines. To effectively monitor and warn of water hammer, sensors are typically deployed in various valve wells along the pipeline, and the collected monitoring data is uploaded to a monitoring terminal to determine whether a water hammer event has occurred.

[0003] In existing technologies, water hammer monitoring systems typically employ a data processing mode of continuous acquisition and real-time uploading. This means all sensors collect data in real time and transmit it to the monitoring terminal. Under this mode, the monitoring terminal needs to receive and process massive amounts of continuously flowing pressure monitoring data, leading to a sharp increase in data processing load. This not only consumes a large amount of the monitoring terminal's processor and storage resources, reducing data processing efficiency, but also makes it difficult for the water hammer monitoring system to quickly and accurately extract early warning information from the massive amount of data, severely impacting the timeliness of water hammer warnings. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a valve water hammer adaptive monitoring and early warning system, method and device to improve the timeliness of water hammer early warning.

[0005] In a first aspect, this application provides a valve water hammer adaptive monitoring and early warning system, comprising: A local control device, installed inside the valve well, is used to acquire pressure data of the valve well in a first operating mode. The first operating mode acquires the first pressure data at a first acquisition frequency and sends the first pressure data to the dispatch monitoring device at a first reporting cycle. When the first pressure data reaches a trigger condition, the first operating mode is switched to a second operating mode. The second operating mode acquires the second pressure data at a second acquisition frequency and sends the second pressure data to the dispatch monitoring device at a second reporting cycle. The first acquisition frequency is less than the second acquisition frequency, and the first reporting cycle is greater than the second reporting cycle. The dispatch monitoring device performs water hammer characteristic analysis based on the second pressure data and obtains early warning results.

[0006] Optionally, the dispatch monitoring device is also used to send working mode switching instructions and / or valve switching instructions to the local control device; wherein, when sending working mode switching instructions and / or valve switching instructions to the local control device of the target valve well, working mode switching instructions and / or valve switching instructions are simultaneously sent to the local control devices of the adjacent valve wells of the target valve well, so as to trigger the local control devices of at least two valve wells to synchronously switch working modes.

[0007] Optionally, the triggering condition is that the pressure change rate of the first pressure data is not less than the first preset threshold; the local control device is also used to switch to the first working mode when the local control device is in the second working mode and the pressure change rate of the second pressure data is lower than the second preset threshold for M consecutive sampling periods; M is an integer greater than or equal to 2, the sampling period is the reciprocal of the second acquisition frequency, and the first preset threshold is greater than the second preset threshold.

[0008] Optionally, at least one of the first preset threshold and the second preset threshold is obtained by dynamic adjustment based on historical data of historical water hammer events; the historical data includes at least one of the peak value, mean value or standard deviation of the pressure change rate in historical water hammer events.

[0009] Optionally, the local control device further includes a time synchronization module, which is connected to a satellite for communication and is used to acquire a time reference; based on the time reference, the first pressure data and the second pressure data are time-aligned to obtain pressure data and second pressure data with time sequence.

[0010] Optionally, the local control device further includes a local storage module for storing time-series first pressure data and second pressure data in the first operating mode and the second operating mode; When the communication link between the local control device and the dispatch monitoring device is congested or interrupted, the local control device temporarily stores the first and second pressure data with time sequence to be sent to the local storage module. After the communication link is restored, the first and second pressure data with time sequence to be sent are sent to the dispatch monitoring device in chronological order.

[0011] Optionally, the valve water hammer adaptive monitoring and early warning system provided in this application also includes a camera, which is installed inside the valve well and communicates with the local control device to collect video data inside the valve well; Upon receiving a video upload command from the dispatch monitoring device or the local control device, the video data from the start time to the end time of the second working mode, as well as the preset time periods before and after, is sent to the dispatch monitoring device.

[0012] Optionally, the scheduling monitoring device is also used to obtain characteristic parameters based on the second pressure data, wherein the characteristic parameters include at least two of the following: pressure change rate, vibration acceleration, and hydrophone acoustic wave intensity. Based on the feature parameters, a weighted fusion is used to obtain the comprehensive confidence level. When the comprehensive confidence level exceeds the preset confidence threshold, it is determined that a water hammer event has occurred and the level of the water hammer event is determined.

[0013] Secondly, this application provides a valve water hammer adaptive monitoring and early warning method, applicable to the local control device in the aforementioned valve water hammer adaptive monitoring and early warning system, comprising: The pressure data of the valve well is acquired in the first working mode. The first working mode is to acquire the first pressure data at the first acquisition frequency and send the first pressure data to the dispatch monitoring device at the first reporting cycle. When the first pressure data reaches the trigger condition, the first working mode is switched to the second working mode. The second working mode is to acquire the second pressure data at the second acquisition frequency and send the second pressure data to the dispatch monitoring device at the second reporting cycle. The first acquisition frequency is less than the second acquisition frequency, and the first reporting cycle is greater than the second reporting cycle.

[0014] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned valve water hammer adaptive monitoring and early warning method.

[0015] This invention provides a valve water hammer adaptive monitoring and early warning system, method, and device. It acquires first pressure data at a first acquisition frequency and sends the first pressure data to a scheduling and monitoring device at a first reporting cycle. When the pressure data reaches a trigger condition, it acquires second pressure data at a second acquisition frequency and sends the second pressure data to the scheduling and monitoring device at a second reporting cycle. Based on the second pressure data, it performs water hammer characteristic analysis to obtain early warning results, thereby quickly and accurately extracting early warning information from massive amounts of data and improving the timeliness of water hammer early warning.

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This diagram illustrates the structure of a valve water hammer adaptive monitoring and early warning system provided in an embodiment of the present invention. Figure 2 A flowchart of an adaptive monitoring and early warning method for water hammer in valves provided by an embodiment of the present invention is shown; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present invention is shown. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0020] This application provides a valve water hammer adaptive monitoring and early warning system, see below. Figure 1 As shown, the valve water hammer adaptive monitoring and early warning system provided in this application includes: a local control device 110 and a dispatch monitoring device 120. The local control device 110 is installed in the valve well and is used to acquire pressure data of the valve well in a first working mode. The first working mode is to acquire the first pressure data at a first acquisition frequency and send the first pressure data to the dispatch monitoring device 120 at a first reporting cycle. When the first pressure data reaches the trigger condition, the first working mode is switched to a second working mode. The second working mode is to acquire the second pressure data at a second acquisition frequency and send the second pressure data to the dispatch monitoring device 120 at a second reporting cycle. The first acquisition frequency is less than the second acquisition frequency, and the first reporting cycle is greater than the second reporting cycle. The dispatch monitoring device 120 performs water hammer characteristic analysis based on the second pressure data to obtain an early warning result.

[0021] In this embodiment of the application, the scheduling and monitoring device 120 is further configured to send a working mode switching command and / or a valve switching command to the local control device 110; wherein, when sending the working mode switching command and / or a valve switching command to the local control device 110 of the target valve well, the working mode switching command and / or a valve switching command are simultaneously sent to the local control devices 110 of the adjacent valve wells of the target valve well, so as to trigger the local control devices 110 of at least two valve wells to switch their working modes synchronously.

[0022] In this embodiment of the application, each local control device 110 is installed inside each valve well along the water pipeline. The local control device 110 includes a pressure pulsation sensor, a data acquisition module, a communication module, and a processor.

[0023] The local control device 110 collects first pressure data through the pressure pulsation sensor at a first acquisition frequency, and sends all the first pressure data collected in the current period to the scheduling and monitoring device 120 through the communication module at a first reporting period (for example, the acquisition frequency is 1Hz and the reporting period is 5 minutes). That is, the local control device 110 operates in the first working mode (that is, the normal detection mode). When the pressure data reaches the trigger condition, the local control device 110 automatically switches to the second working mode (i.e., the water hammer warning mode). In the second working mode, the second pressure data is collected from the pressure pulsation sensor at a second acquisition frequency (higher than the first acquisition frequency, for example, 100Hz), and the second pressure data is sent to the dispatch monitoring device 120 in real time at a second reporting cycle (shorter than the first reporting cycle, for example, 1 second).

[0024] Furthermore, the triggering condition is that the pressure change rate of the first pressure data is not less than the first preset threshold, that is, the pressure change rate (the maximum change in pressure value per unit time, such as ±0.5MPa per second) exceeds the preset change rate threshold.

[0025] The dispatch monitoring device 120 is deployed in the irrigation district dispatch center to receive and store the second pressure data sent by the local control device 110 of each valve well, and to perform water hammer characteristic analysis on the second pressure data to obtain early warning results.

[0026] Furthermore, the dispatch monitoring device 120 is also used to analyze the early warning results of multiple valve wells to obtain the time sequence of pressure data changes of multiple valve wells, so as to infer the propagation direction and speed of pressure waves, thereby judging the severity of water hammer and the range of pipe sections that may be affected; based on the propagation direction and speed of pressure waves, it generates working mode switching instructions and / or valve opening and closing instructions for the local control device 110.

[0027] To achieve coordinated monitoring, when the dispatch monitoring device 120 needs to send a working mode switching command and / or valve opening and closing command to the local control device 110 of a target valve well, it simultaneously sends the same working mode switching command and / or valve opening and closing command to the local control devices 110 of the directly upstream and downstream (or multiple adjacent) valve wells within a preset range of the target valve well, thereby triggering the local control devices 110 of at least three valve wells to simultaneously switch from the first working mode to the second working mode.

[0028] In this embodiment, the local control device 110 operates in a low-power, low-data-volume mode under normal conditions through dual-mode adaptive switching, avoiding waste of communication and storage resources. Under water hammer anomalies or remote command triggering, it automatically switches to a high-frequency acquisition and rapid reporting mode to ensure complete capture of critical transient data. The linkage switching mechanism utilizes the characteristics of water hammer waves propagating along the pipeline, enabling adjacent valve wells to synchronously enter high-frequency monitoring mode, providing synchronous cross-sectional data for the scheduling monitoring device 120 to reconstruct the water hammer propagation path. Furthermore, each local control device 110 has the ability to independently determine triggering conditions. Even during communication interruptions, the local control device 110 can automatically switch to the second operating mode and cache the second pressure data, retransmitting it after communication is restored, thereby significantly improving the robustness and reliability of the system in remote, unstable signal areas.

[0029] In an optional embodiment, the local control device 110 is further configured to switch to the first working mode when the local control device 110 is in the second working mode and the pressure change rate of the second pressure data is lower than the second preset threshold for M consecutive sampling periods; M is an integer greater than or equal to 2, the sampling period is the reciprocal of the second acquisition frequency, and the first preset threshold is greater than the second preset threshold.

[0030] In this embodiment of the application, the local control device 110 is also used to monitor the pressure change rate of the pressure data when it is in the second working mode. When the pressure change rate of the second pressure data is lower than the second preset threshold for multiple consecutive sampling periods (e.g., 3 to 5 consecutive sampling periods), the local control device 110 automatically switches from the second working mode back to the first working mode. The sampling period is the reciprocal of the second acquisition frequency, that is, the time interval between two adjacent pressure acquisitions.

[0031] For ease of distinction, the rate of change threshold used to determine whether to enter the second working mode is denoted as the first preset threshold, and the rate of change threshold used to determine whether to exit the second working mode is denoted as the second preset threshold. Furthermore, the first preset threshold is greater than the second preset threshold. In other words, the conditions for transitioning from normal monitoring to water hammer early warning monitoring are more stringent than the conditions for reverting from water hammer early warning monitoring to normal monitoring, thus creating a hysteresis characteristic in mode switching. Specifically, when the water hammer process gradually subsides and the pipeline returns to a stable flow state, the pressure fluctuation amplitude decreases. After the local control device 110 detects that the pressure change rate is lower than the second preset threshold for multiple consecutive sampling periods, it performs the following operations: The sampling frequency is reduced from the higher second sampling frequency to the lower first sampling frequency; The reporting period was extended from the shorter second reporting period to the longer first reporting period.

[0032] Furthermore, the collection frequency and reporting cycle can be periodically updated based on historical stress data using a machine learning model, where the machine learning model can be a random forest regression or a lightweight classification tree.

[0033] In this embodiment, using multiple consecutive sampling periods below a threshold as the judgment condition effectively avoids frequent mode switching caused by accidental instantaneous pressure disturbances (i.e., anti-jitter design). Simultaneously, since the first preset threshold is greater than the second preset threshold, sufficiently drastic pressure changes are required to trigger entry into the second working mode, and the pressure change must significantly decrease and remain stable for a period before exiting the second working mode. Hysteresis characteristics further suppress repeated oscillations between modes, enabling rapid response and high-precision recording of transient data during water hammer events, and timely recovery to an energy-saving, low-load normal monitoring mode after the anomaly ends.

[0034] In one optional embodiment, at least one of the first preset threshold and the second preset threshold is dynamically adjusted based on historical data of historical water hammer events; the historical data includes at least one of the peak value, mean value, or standard deviation of the pressure change rate in historical water hammer events.

[0035] In this embodiment, the local control device 110 or the scheduling and monitoring device 120 continuously records the pressure data collected by the pressure pulsation sensor before and after each water hammer event, and extracts the statistical characteristics of the pressure change rate from it. As the system operates for a longer period of time, this historical data constitutes a sample library reflecting the hydraulic fluctuation characteristics of the valve well and the pipe section it is located in.

[0036] The dispatch monitoring device 120 analyzes historical data and dynamically adjusts the first preset threshold and the second preset threshold. The preset thresholds can be dynamically adjusted using the following methods: For the first preset threshold, statistics are based on the peak values ​​of pressure change rates in historical water hammer events. For example, the average of the peak pressures of the most recent N water hammer events is taken and then multiplied by a safety factor greater than 1 (such as 1.2), or the 95th percentile of the peak value is taken. The second preset threshold is calculated based on the pressure change rate during the stable operation phase of the pipeline after water hammer subsides. For example, the mean of the pressure change rate during the stable phase is taken plus 2 to 3 times the standard deviation, or twice the mean is taken directly.

[0037] Furthermore, the updates to the first and second preset thresholds can be periodically calculated and distributed to each local control device 110 by the scheduling and monitoring device 120, or can be periodically and autonomously updated by the local control device 110 based on locally stored historical data.

[0038] Because the location, diameter, design pressure, and water hammer sensitivity of different valve wells vary, using a uniform and fixed threshold is difficult to adapt to all scenarios. Therefore, in this embodiment, through the above-mentioned independent dynamic adjustment based on historical water hammer event data, the first and second preset thresholds of each local control device 110 can be matched with the actual hydraulic characteristics of its own pipeline, thereby significantly improving the accuracy and robustness of water hammer event identification. At the same time, the dynamic adjustment mechanism can also adapt to the long-term evolution of pipeline operating conditions (such as increased pipeline inner wall roughness or changes in the operation mode of upstream pumping stations). Historical data is continuously updated, and the thresholds are optimized accordingly, always maintaining optimal monitoring sensitivity, avoiding the subjectivity and maintenance workload of manually setting thresholds.

[0039] Furthermore, in this embodiment, a second preset threshold can be determined based on a first preset threshold and a switching coefficient. Specifically, the second preset threshold is obtained by multiplying the first preset threshold by the switching coefficient, wherein the switching coefficient is a constant greater than 0 and less than 1 (e.g., 0.5 or 0.8), which can be preset for the entire system or set individually according to the hydraulic characteristics of different pipe sections.

[0040] In this embodiment, it is not necessary to configure two independent thresholds for each valve well. Instead, only the first preset threshold needs to be dynamically determined, and the second preset threshold is automatically generated, greatly simplifying the complexity of system configuration. Since the switching coefficient is between 0 and 1, it ensures that the second preset threshold is always lower than the first preset threshold, thus forming a stable hysteresis range. When the pressure change rate rises above the higher first preset threshold, the system enters the second working mode; when the pressure change rate falls below the lower second preset threshold and meets the condition that it is below the threshold for multiple consecutive sampling periods, the system exits the second working mode. This avoids frequent mode switching caused by pressure fluctuations oscillating around the threshold, ensuring complete recording of water hammer data throughout the entire process.

[0041] It should be noted that in this embodiment, the second preset threshold may no longer be learned independently based on the statistical characteristics of the decay phase, but may change proportionally with the first preset threshold to be suitable for scenarios where the hysteresis width requirements between pipe segments are relatively consistent. When it is necessary to make fine-differentiated adjustments to the recovery sensitivity of different pipe segments, the switching coefficients of different valve wells can be configured separately.

[0042] In an optional embodiment, the local control device 110 further includes a time synchronization module 111, which is connected to a satellite for communication and is used to acquire a time reference; based on the time reference, the first pressure data and the second pressure data are time-aligned to obtain first pressure data and second pressure data with time sequence.

[0043] In this embodiment of the application, the local control device 110 integrates a time synchronization module 111. The time synchronization module 111 maintains a communication connection with the satellite navigation system through an antenna, such as establishing a wireless link with the BeiDou satellite system or the Global Positioning System, and extracts a high-precision time reference from the satellite signal.

[0044] The time synchronization module 111 contains a high-stability crystal oscillator (such as a temperature-compensated crystal oscillator (TCXO) or an oven-controlled crystal oscillator (OCXO)) that continuously receives Coordinated Universal Time (UTC) information broadcast by the satellite and disciplines and calibrates the local clock, ensuring that the system time of the local control device 110 remains highly consistent with the satellite time. Each time first or second pressure data is acquired, the local control device 110 reads the current absolute time value from the time synchronization module 111 and appends this absolute time value as a timestamp to the acquired data, thereby generating first and second pressure data with a precise and unified time reference.

[0045] Because the local control devices 110 of different valve wells are synchronized with the same satellite system, and the synchronization accuracy can reach the microsecond to sub-millisecond level (e.g., better than 100 microseconds), the data collected by all valve wells along the entire line adopt the same time reference. This time alignment process enables the data from different locations and different sensors to be accurately aligned on the time coordinate.

[0046] Once the dispatch monitoring device 120 receives timestamped data from multiple valve wells, it can accurately reconstruct the sequence and speed of water hammer pressure waves propagating along the pipeline directly based on the timestamps. This eliminates the need to rely on network transmission delay fluctuation estimation or perform complex time interpolation or compensation calculations. It effectively avoids data timing disorder caused by asynchronous wireless communication delays in long-distance water conveyance projects, providing a reliable data foundation for constructing an accurate online monitoring model of water hammer along the entire pipeline.

[0047] Furthermore, the high-precision timestamps also allow the local control device 110 to continue collecting and storing data in its local non-volatile memory during communication interruptions, and then transmit it uniformly after communication is restored. The scheduling and monitoring device 120 can still correctly arrange the time order of the data according to the timestamps, and will not misjudge the sequence of events due to transmission delays.

[0048] In an optional embodiment, the local control device 110 further includes a local storage module 112 for storing time-sequential first pressure data and second pressure data in the first working mode and the second working mode; when the communication link between the local control device 110 and the scheduling monitoring device 120 is congested or interrupted, the local control device 110 temporarily stores the time-sequential first pressure data and second pressure data to be sent in the local storage module 112, and sends the time-sequential first pressure data and second pressure data to be sent to the scheduling monitoring device 120 in chronological order after the communication link is restored.

[0049] In this embodiment of the application, the local control device 110 further includes a local storage module 112, which uses a non-volatile storage medium, such as flash memory or solid-state drive, and has a capacity sufficient to hold at least thirty consecutive days of first pressure data and second pressure data collected.

[0050] Furthermore, regardless of whether it is in the first or second operating mode, after acquiring pressure data from the sensor, the local control device 110 immediately reads the timestamp from the time synchronization module 111 and appends it to the data. Then, it stores the data with precise time stamps into the local storage module 112. The local storage module 112 manages the storage space according to the first-in, first-out principle. When the storage space is full and new data needs to be stored, it automatically overwrites the data with the earliest storage time, thereby ensuring that complete records within the most recent period are always retained.

[0051] The communication module in the local control device 110 establishes a wireless communication link with the scheduling monitoring device 120. When the communication module detects a weak network signal, excessive transmission delay, or complete interruption, it stores the first and second pressure data, which are to be sent and have been timestamped, in the local storage module 112 and marks them as unsent. The communication module continuously monitors the link status. When it detects that the communication link has returned to normal, it sends the first and second pressure data, which are to be sent and have been timestamped, to the scheduling monitoring device 120 in the order of data storage time, starting with the earliest unsent data. After successfully sending a piece of data to be sent and having been timestamped, and receiving an acknowledgment from the scheduling monitoring device 120, the communication module marks the data to be sent and has been timestamped as sent, or removes it from the transmission queue.

[0052] Since all data is accompanied by a precise timestamp, the scheduling and monitoring device 120, upon receiving delayed data, accurately inserts it into the correct time series based on the timestamp, thus avoiding misclassification of later-arriving but earlier-arriving data as the latest data due to transmission delays. Through the data retention mechanism of the local storage module 112, the system can readily cope with the realities of unstable wireless signals in remote areas. Even in the extreme case of complete communication interruption, the local control device 110 continues to operate normally according to the predetermined acquisition frequency and mode switching logic, ensuring no data loss, and retransmitting all data at once after communication is restored.

[0053] Furthermore, since the local storage module 112 adopts a first-in, first-out (FIFO) overwrite strategy, successfully transmitted data remains locally until the storage space is full. Therefore, the local storage module 112 objectively serves as a data backup for the scheduling and monitoring device 120: even if the data in the scheduling center is lost due to an accident, as long as the relevant data has not been overwritten by the local storage module 112, the original records can be retrieved from the field at any time for recovery, thereby significantly improving the data reliability and fault tolerance of the entire monitoring and early warning system.

[0054] In an optional embodiment, the valve water hammer adaptive monitoring and early warning system provided in this application further includes a camera 130, which is installed in the valve well and communicates with the local control device 110 to collect video data in the valve well; in response to a video upload command sent by the scheduling monitoring device 120 or the local control device 110, the camera 130 sends video data from the start time of the second working mode to the end time and the preset time periods before and after to the scheduling monitoring device 120.

[0055] In this embodiment, the camera 130 is fixedly installed at an appropriate location inside the valve well, such as facing key parts like the valve body exterior, vent, drain outlet, or level gauge, to collect real-time video data from inside the valve well. The camera 130 is equipped with an independent local storage card (such as a TF card) and continuously stores video data using a cyclic overwrite method. Under normal circumstances, the camera 130 does not actively send video streams to the scheduling and monitoring device 120 to save communication bandwidth and power consumption.

[0056] The camera 130 establishes a connection with the local control device 110 via a wired (e.g., USB, Ethernet) or short-range wireless (e.g., Wi-Fi) method. It can receive control commands sent by the local control device 110, including time synchronization commands and video upload commands. Specifically, the local control device 110 periodically sends time synchronization commands to the camera 130, which include high-precision Coordinated Universal Time (UTC) obtained from the time synchronization module 111. Upon receiving the time synchronization command, the camera 130 calibrates its own system clock to ensure that the time deviation with the local control device 110 is less than a preset threshold (e.g., ±1 second), thereby guaranteeing the accuracy of subsequent video segment extraction.

[0057] When the local control device 110 switches from the first operating mode to the second operating mode, it records the start and end times of the second operating mode. Video upload commands can be triggered locally or remotely. Local triggering occurs when the local control device 110 detects its switch from the first to the second operating mode (regardless of whether triggered by the local pressure change rate or a remote command), generating a video upload command. This method does not rely on the real-time availability of the communication link and is suitable for scenarios where communication may be interrupted. Remote command triggering occurs when the scheduling monitoring device 120, based on analysis results or operator instructions, sends a video upload command individually to a designated camera 130 to obtain video recordings at a specific time point. After receiving a video upload command, camera 130 reads a continuous video segment from local control device 110. This video segment begins at the start time of the second operating mode minus a first preset advance time and ends at the end time of the second operating mode plus a first preset delay time. The first preset advance time and the first preset delay time can be independently set during system configuration (e.g., both set to 15 seconds). Camera 130 packages this video segment into a video slice and transmits it to local control device 110. The local control device 110's long-distance communication module (e.g., 4G / 5G, NB-IoT) then forwards the video to scheduling and monitoring device 120. Since the amount of video data uploaded in a single session is controllable (e.g., several MB), it does not place a continuous high load on the processor and communication module of local control device 110.

[0058] After receiving the video slice, the dispatch monitoring device 120 correlates it with the sensor time-series data (pressure change rate, vibration data, etc.) within the same time period and displays it. The operators in the dispatch center can not only obtain the pressure fluctuation data during the water hammer, but also see the real-time picture inside the valve well at the same time, so as to more accurately determine the cause and consequences of the water hammer event (such as abnormal valve venting, water accumulation in the valve well, obvious pipeline leakage or splashing, etc.).

[0059] This application embodiment provides intuitive visual evidence for accident analysis by using video data and sensor time-series data as complementary information. Simultaneously, since the camera 130 normally only performs local loop storage without uploading, and only extracts and sends video slices of critical periods before and after the second working mode is triggered, communication traffic is limited to a very low level, avoiding the high traffic costs and backend storage pressure caused by 24 / 7 video transmission. This on-demand video uploading strategy is particularly suitable for widely distributed irrigation projects that rely on wireless communication, achieving economical and efficient operation while ensuring emergency response capabilities.

[0060] In an optional embodiment, the scheduling monitoring device 120 is further configured to: obtain characteristic parameters based on the second pressure data, wherein the characteristic parameters include at least two of pressure change rate, vibration acceleration and hydrophone sound wave intensity; obtain a comprehensive confidence level by weighted fusion based on the characteristic parameters; and determine the occurrence of a water hammer event and the level of the water hammer event when the comprehensive confidence level exceeds a preset confidence threshold.

[0061] In this embodiment of the application, after receiving the second pressure data sent by each local control device 110, the scheduling and monitoring device 120 performs feature analysis on the second pressure data. The second pressure data consists of pressure data, vibration data, and hydrophone acoustic wave data collected and reported by the local control device 110 at high frequency in the second working mode. The vibration data is collected by an acceleration sensor installed on the valve body or valve shaft. The hydrophone acoustic wave data is collected by a hydrophone installed inside the pipeline.

[0062] Furthermore, the dispatch monitoring device 120 uses the following steps to identify and classify water hammer events: First, the dispatch monitoring device 120 extracts at least two different types of characteristic parameters from the second pressure data. These characteristic parameters include: pressure change rate (the rate of change of pipeline pressure per unit time, calculated differentially from the time-series data of the pressure pulsation sensor), vibration acceleration (the intensity of vibration of the valve body or valve shaft), and hydrophone sound wave intensity (the intensity of the sound signal reflecting water flow impact or bubble collapse). For each characteristic parameter, the dispatch monitoring device 120 calculates the deviation between its current value and the normal baseline value to obtain the water hammer characterization confidence level for each characteristic parameter. The confidence level ranges from [0,1]. The normal baseline value is the statistical mean or median of the characteristic parameters during stable pipeline operation, such as 24 consecutive hours in the first operating mode. Then, the dispatch monitoring device 120 uses a weighted fusion algorithm to comprehensively calculate the confidence levels of the aforementioned multiple feature parameters. Specifically, a weight coefficient is pre-assigned to each feature parameter, with the sum of the weight coefficients being 1. These weight coefficients can be determined by the system administrator based on engineering experience or historical water hammer event data of the pipeline, or they can be obtained through machine learning methods (such as logistic regression) trained from labeled samples. For example, the pressure change rate is generally considered the most direct and sensitive indicator and can be assigned a weight of 0.6; vibration acceleration and hydrophone acoustic wave intensity, as auxiliary criteria, can be assigned weights of 0.2 and 0.2 respectively. The overall confidence level... The calculation formula is:

[0063] In the formula, For the first The confidence level of each feature parameter These are the weighting coefficients. Between 0 and 1 The closer it is to 1, the stronger multiple criteria point to a water hammer event. Finally, the scheduling monitoring device 120 pre-stores a confidence threshold. (For example, T=0.5, which can be set based on engineering experience and pipeline safety requirements, and the value range is usually 0.5 to 0.7); When At that time, the dispatch monitoring device 120 determines that a water hammer event has occurred; after confirming the occurrence of a water hammer event, the dispatch monitoring device 120 further determines the event based on the comprehensive confidence level. The magnitude of the water hammer event and the degree to which each characteristic parameter deviates from normal values ​​are used to determine the severity of the event. For example, a minor water hammer event: And the confidence level of all feature parameters does not exceed 0.7; typical water hammer events: Or, at least one characteristic parameter has a confidence level exceeding 0.8; severe water hammer event: Furthermore, at least two characteristic parameters have a confidence level exceeding 0.9; the grading threshold can be adjusted according to the hydraulic characteristics and safety requirements of different pipelines.

[0064] In this embodiment, the water hammer event identification method based on multi-feature parameter weighted fusion overcomes the shortcomings of single sensors or single criteria being easily affected by noise interference or accidental factors, resulting in false alarms or missed alarms. Based on the pressure change rate, vibration acceleration, and hydrophone sound wave intensity, the water hammer phenomenon is reflected from three physical dimensions: hydraulic transients, mechanical response, and acoustic characteristics, respectively. When all three are abnormal at the same time and the overall confidence level after weighted fusion exceeds the threshold, it can be confirmed as a real water hammer event, rather than a false alarm caused by sensor failure or environmental noise. Through the weighted fusion mechanism, the weight coefficients can be flexibly adjusted according to the actual conditions of different pipe sections and different valve wells. For example, for water hammer primarily characterized by pressure surges, the weight of the pressure change rate can be increased; for water hammer accompanied by strong cavitation noise, the weight of the hydrophone's acoustic wave intensity can be increased, thus enabling scenario-based water hammer assessment. By classifying water hammer events, the dispatch monitoring device 120 can adopt differentiated response strategies: for minor water hammer events, only record the event log and issue an alarm, without immediately taking control actions; for general water hammer events, remind operators to pay attention and suggest preventative measures; for severe water hammer events, immediately trigger emergency protection measures, such as remotely shutting off valves or notifying the pump station to adjust operating parameters, to minimize the damage caused by water hammer to pipelines and equipment.

[0065] In this embodiment, the above-mentioned hierarchical response mechanism ensures the real-time performance and reliability of the system as a whole, while avoiding unnecessary interference to normal water supply scheduling caused by overly conservative control actions.

[0066] This application provides an adaptive monitoring and early warning method for water hammer in valves, see below. Figure 2 As shown, the valve water hammer adaptive monitoring and early warning method provided in this application is applicable to the local control device in the above-mentioned valve water hammer adaptive monitoring and early warning system. The method includes at least the following steps: Step 210: Acquire pressure data of valve well in the first working mode. The first working mode is to acquire first pressure data at a first acquisition frequency and send the first pressure data to the dispatch monitoring device at a first reporting cycle. Step 220: When the first pressure data reaches the trigger condition, switch the first working mode to the second working mode. The second working mode is to acquire the second pressure data at the second acquisition frequency and send the second pressure data to the dispatch monitoring device at the second reporting cycle. The first acquisition frequency is less than the second acquisition frequency, and the first reporting cycle is greater than the second reporting cycle.

[0067] It should be noted that the principle of the valve water hammer adaptive monitoring and early warning method provided in this application embodiment to solve the technical problem is similar to that of the valve water hammer adaptive monitoring and early warning system provided in this application embodiment. Therefore, the implementation of the valve water hammer adaptive monitoring and early warning method provided in this application embodiment can refer to the implementation of the valve water hammer adaptive monitoring and early warning system provided in this application embodiment, and the repeated parts will not be described again.

[0068] After introducing the valve water hammer adaptive monitoring and early warning method and device provided in the embodiments of this application, the electronic equipment provided in the embodiments of this application will be briefly introduced next.

[0069] See Figure 3 As shown, the electronic device 500 provided in this application embodiment includes at least a processor 501, a memory 502, and a computer program stored in the memory 502 and capable of running on the processor 501. When the processor 501 executes the computer program, it implements the valve water hammer adaptive monitoring and early warning method provided in this application embodiment.

[0070] The electronic device 500 provided in this application embodiment may further include a bus 503 connecting different components (including processor 501 and memory 502). The bus 503 represents one or more types of bus structures, including memory bus, peripheral bus, local area bus, etc.

[0071] Memory 502 may include a readable storage medium in the form of volatile memory, such as random access memory (RAM) 5021 and / or cache memory 5022, and may further include read-only memory (ROM) 5023. Memory 502 may also include a program tool 5025 having a set (at least one) of program modules 5024, including but not limited to an operating subsystem, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0072] Processor 501 can be a single processing element or a collective term for multiple processing elements. For example, processor 501 can be a central processing unit (CPU) or one or more integrated circuits configured to implement the valve water hammer adaptive monitoring and early warning method provided in the embodiments of this application. Specifically, processor 501 can be a general-purpose processor, including but not limited to CPUs, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0073] Electronic device 500 can communicate with one or more external devices 504 (e.g., keyboard, remote control, etc.), and also with one or more devices that enable a user to interact with electronic device 500 (e.g., mobile phone, computer, etc.), and / or with devices that enable electronic device 500 to communicate with one or more other electronic devices 500 (e.g., router, modem, etc.). This communication can be performed through input / output (I / O) interface 505. Furthermore, electronic device 500 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 506. Figure 3 As shown, network adapter 506 communicates with other modules of electronic device 500 via bus 503. It should be understood that, although... Figure 3 As not shown, other hardware and / or software modules may be used in conjunction with the electronic device 500, including but not limited to microcode, device drivers, redundant processors, external disk drive arrays, Redundant Arrays of Independent Disks (RAID) subsystems, tape drives, and data backup storage subsystems.

[0074] It should be noted that, Figure 3 The electronic device 500 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0075] The computer-readable storage medium provided in the embodiments of this application is described below. The computer-readable storage medium provided in the embodiments of this application stores computer instructions, which, when executed by a processor, implement the valve water hammer adaptive monitoring and early warning method provided in the embodiments of this application. Specifically, the computer instructions can be built into or installed in the processor, so that the processor can implement the valve water hammer adaptive monitoring and early warning method provided in the embodiments of this application by executing the built-in or installed computer instructions.

[0076] In addition, the valve water hammer adaptive monitoring and early warning method provided in this application embodiment can also be implemented as a computer program product. The computer program product includes program code, which implements the valve water hammer adaptive monitoring and early warning method provided in this application embodiment when running on a processor.

[0077] The computer program product provided in this application embodiment may employ one or more computer-readable storage media, which may be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination thereof. Specifically, more specific examples (a non-exhaustive list) of computer-readable storage media include electrical connections with one or more wires, portable disks, hard disks, RAM, ROM, erasable programmable read-only memory (EPROM), optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0078] The computer program product provided in this application embodiment can be a CD-ROM and include program code, and can also run on electronic devices such as computers. However, the computer program product provided in this application embodiment is not limited thereto. In this application embodiment, the computer-readable storage medium can be any tangible medium that contains or stores program code, which can be used by or in conjunction with an instruction execution system, device, or apparatus.

[0079] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0080] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0081] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0082] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A valve water hammer self-adaptive monitoring and early warning system, characterized in that, include: A local control device is installed inside the valve well and is used to acquire pressure data of the valve well in a first working mode. The first working mode is to acquire the first pressure data at a first acquisition frequency and send the first pressure data to the scheduling and monitoring device at a first reporting cycle. When the first pressure data reaches the trigger condition, the first working mode is switched to the second working mode. The second working mode is to acquire the second pressure data at the second acquisition frequency and send the second pressure data to the scheduling and monitoring device at the second reporting cycle. The first sampling frequency is less than the second sampling frequency, and the first reporting period is greater than the second reporting period; The scheduling and monitoring device performs water hammer characteristic analysis based on the second pressure data to obtain early warning results.

2. The valve water hammer self-adaptive monitoring and warning system according to claim 1, wherein, The scheduling and monitoring device is further configured to send a working mode switching command and / or a valve switching command to the local control device; wherein, when sending the working mode switching command and / or the valve switching command to the local control device of the target valve well, the device simultaneously sends the working mode switching command and / or the valve switching command to the local control devices of the adjacent valve wells of the target valve well, so as to trigger the local control devices of at least two valve wells to synchronously switch their working modes.

3. The valve water hammer adaptive monitoring and warning system of claim 1, wherein, The triggering condition is that the pressure change rate of the first pressure data is not less than a first preset threshold. The local control device is further configured to switch to the first working mode when the local control device is in the second working mode and the pressure change rate of the second pressure data is lower than the second preset threshold for M consecutive sampling periods; M is an integer greater than or equal to 2, the sampling period is the reciprocal of the second acquisition frequency, and the first preset threshold is greater than the second preset threshold.

4. The valve water hammer self-adaptive monitoring and warning system according to claim 3, wherein, At least one of the first preset threshold and the second preset threshold is obtained by dynamic adjustment based on historical data of historical water hammer events; the historical data includes at least one of the peak value, mean value or standard deviation of the pressure change rate in historical water hammer events.

5. The valve water hammer adaptive monitoring and warning system of claim 1, wherein, The local control device also includes a time synchronization module, which is connected to a satellite for communication and is used to acquire a time reference; based on the time reference, the first pressure data and the second pressure data are time-aligned to obtain the first pressure data and the second pressure data with time sequence.

6. The valve water hammer self-adaptive monitoring and warning system according to claim 5, wherein, The local control device further includes a local storage module for storing the first pressure data and the second pressure data with time sequence in the first working mode and the second working mode. When the communication link between the local control device and the scheduling monitoring device is congested or interrupted, the local control device temporarily stores the first pressure data and the second pressure data with time sequence to be sent to the local storage module. After the communication link is restored, the first pressure data and the second pressure data with time sequence to be sent are sent to the scheduling monitoring device in chronological order.

7. The valve water hammer adaptive monitoring and warning system of claim 1, wherein, It also includes a camera, which is installed inside the valve well and communicates with the local control device to collect video data inside the valve well. Upon receiving a video upload command from the scheduling and monitoring device or the local control device, the video data from the start time to the end time of the second working mode, as well as the preset time periods before and after, is sent to the scheduling and monitoring device.

8. The valve water hammer adaptive monitoring and early warning system according to claim 1, characterized in that, The scheduling and monitoring device is further configured to obtain characteristic parameters based on the second pressure data, wherein the characteristic parameters include at least two of the following: pressure change rate, vibration acceleration, and hydrophone sound wave intensity. Based on the aforementioned feature parameters, a weighted fusion method is used to obtain a comprehensive confidence level. When the comprehensive confidence level exceeds a preset confidence threshold, it is determined that a water hammer event has occurred and the level of the water hammer event is determined.

9. A valve water hammer adaptive monitoring and early warning method, characterized in that, A local control device suitable for a valve water hammer adaptive monitoring and early warning system as described in any one of claims 1 to 8, comprising: The pressure data of the valve well is acquired in a first working mode, wherein the first working mode is to acquire the first pressure data at a first acquisition frequency and send the first pressure data to the scheduling and monitoring device at a first reporting cycle. When the first pressure data reaches the trigger condition, the first working mode is switched to the second working mode. The second working mode is to acquire the second pressure data at a second acquisition frequency and send the second pressure data to the scheduling and monitoring device at a second reporting period. The first acquisition frequency is less than the second acquisition frequency, and the first reporting period is greater than the second reporting period.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the valve water hammer adaptive monitoring and early warning method as described in claim 9.

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