Water hammer detection methods and equipment

Abstract

This application discloses a water hammer detection method and a water hammer detection device, relating to the field of water hammer detection technology. The water hammer detection device, after determining that the probability of water hammer effect occurring in the transport pipeline is greater than a probability threshold, can acquire a first pressure time series. If the water hammer detection device determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that the pressure in the transport pipeline has changed significantly in a short period of time, and thus, the occurrence of a water hammer effect in the transport pipeline can be determined. In this way, the monitoring of the water hammer effect in the transport pipeline can be achieved. Furthermore, since the water hammer detection device can acquire the first pressure time series only when the probability of water hammer effect occurring in the transport pipeline is high, the computational resources of the water hammer detection device can be saved.

Description

Technical Field

[0001] This application relates to the field of water hammer detection technology, and in particular to a water hammer detection method and water hammer detection equipment. Background Technology

[0002] If the valve of a water supply pipeline is suddenly opened or closed during the water supply process, it may cause a water hammer effect in the water supply pipeline, which can damage the water supply pipeline.

[0003] To reduce the damage caused by water hammer to water supply pipelines, it is necessary to detect whether water hammer occurs in the pipelines and take necessary protective measures in a timely manner when water hammer is confirmed to be occurring. Summary of the Invention

[0004] This application provides a method and equipment for detecting water hammer, the technical solution of which is as follows:

[0005] On the one hand, a water hammer detection method is provided, the method comprising:

[0006] If the probability of water hammer effect occurring in the pipeline is greater than the probability threshold, then the first pressure time series of the pipeline is obtained.

[0007] If the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than a time threshold, then it is determined that the conveying pipeline is experiencing a water hammer effect.

[0008] Optionally, the method further includes:

[0009] A second pressure time series of the conveying pipeline is obtained, wherein the sampling time of at least one pressure in the second pressure time series is earlier than the sampling time of each of the first pressures in the first pressure time series;

[0010] If the target pressure exists in the second pressure time series, then the probability that the water hammer effect occurs in the delivery pipeline is greater than the probability threshold.

[0011] Wherein, the target pressure is greater than the product of the median of the second pressure time series and the first coefficient, or the target pressure is less than the product of the median of the second pressure time series and the second coefficient, wherein the first coefficient is greater than 1 and the second coefficient is less than 1;

[0012] The sampling time of the first pressure in the first pressure time series is later than the sampling time of the target pressure.

[0013] Optionally, obtaining the second pressure time series of the delivery pipeline includes:

[0014] Obtain the first flow time series of the conveying pipeline;

[0015] Determine the first flow difference time series based on the first flow time series;

[0016] If the number of flow differences with absolute values ​​greater than the flow difference threshold in the first flow difference time series is greater than the number threshold, and the interquartile range of the first flow difference time series is less than the third threshold, then the second pressure time series of the conveying pipeline is obtained.

[0017] Optionally, obtaining the first flow time series of the delivery pipeline includes:

[0018] Obtain the second flow time series of the delivery pipeline;

[0019] Determine the second flow difference time series based on the second flow time series;

[0020] If a target flow difference exists in the second flow difference time series, then the first flow time series of the conveying pipeline is obtained;

[0021] Wherein, the absolute value of the target flow difference is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient, and the third coefficient is greater than 1;

[0022] The sampling time of the first flow in the first flow time series is later than the sampling time of the flow to which the target flow difference belongs.

[0023] Optionally, the method further includes:

[0024] Update the abnormal flow difference in the second flow difference time series. The updated abnormal flow difference is positively correlated with the normal flow difference adjacent to the abnormal flow difference.

[0025] Wherein, the difference between the abnormal flow difference and the expected value of the second flow difference time series is greater than the product of the standard deviation of the second flow difference time series and the fourth coefficient.

[0026] Optionally, the method further includes:

[0027] Update the abnormal pressures in the second pressure time series, and the updated abnormal pressures are positively correlated with the pressures adjacent to the abnormal pressures.

[0028] The difference between the abnormal pressure and the expected value of the second pressure time series is greater than the product of the standard deviation of the second pressure time series and the fifth coefficient.

[0029] Optionally, if the abnormal pressure is located at the end of the second pressure time series, the updated abnormal pressure is the pressure adjacent to the abnormal pressure.

[0030] If the abnormal pressure is not located at the end of the second pressure time series, then the updated abnormal pressure is the average of the two pressures adjacent to the abnormal pressure.

[0031] On the other hand, a water hammer detection device is provided, the water hammer detection device comprising: a processor; the processor being used for:

[0032] If the probability of water hammer effect occurring in the pipeline is greater than the probability threshold, then the first pressure time series of the pipeline is obtained.

[0033] If the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than a time threshold, then it is determined that the conveying pipeline is experiencing a water hammer effect.

[0034] Optionally, the processor is further configured to:

[0035] A second pressure time series of the conveying pipeline is obtained, wherein the sampling time of at least one pressure in the second pressure time series is earlier than the sampling time of each of the first pressures in the first pressure time series;

[0036] If the target pressure exists in the second pressure time series, then the probability that the water hammer effect occurs in the delivery pipeline is greater than the probability threshold.

[0037] Wherein, the target pressure is greater than the product of the median of the second pressure time series and the first coefficient, or the target pressure is less than the product of the median of the second pressure time series and the second coefficient, wherein the first coefficient is greater than 1 and the second coefficient is less than 1;

[0038] The sampling time of the first pressure in the first pressure time series is later than the sampling time of the target pressure.

[0039] In another aspect, a computer-readable storage medium is provided having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the water hammer detection method as described above.

[0040] The beneficial effects of the technical solution provided in this application include at least the following:

[0041] This application provides a water hammer detection method and a water hammer detection device. The water hammer detection device, after determining that the probability of water hammer effect occurring in the conveying pipeline is greater than a probability threshold, can acquire a first pressure time series. If the water hammer detection device determines that the difference between the maximum and minimum pressure in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that the pressure in the conveying pipeline has changed significantly in a short period of time, and thus, it can be determined that a water hammer effect has occurred in the conveying pipeline. In this way, the monitoring of the water hammer effect in the conveying pipeline can be achieved. Furthermore, since the water hammer detection device can acquire the first pressure time series only when the probability of water hammer effect occurring in the conveying pipeline is high, the computational resources of the water hammer detection device can be saved.

[0042] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0043] Figure 1 This is a flowchart of a water hammer detection method provided in an embodiment of this application;

[0044] Figure 2 This is a flowchart of another water hammer detection method provided in the embodiments of this application;

[0045] Figure 3 This is a flowchart of a method for preprocessing a second flow difference time series provided in an embodiment of this application;

[0046] Figure 4 This is a flowchart of a method for preprocessing a second pressure time series provided in an embodiment of this application;

[0047] Figure 5 This is a schematic diagram of the structure of a water hammer detection device provided in an embodiment of this application. Detailed Implementation

[0048] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0049] This application provides a water hammer detection method, which is applied to a water hammer detection device. This water hammer detection device can be installed at a pipeline transfer station (such as in a manhole) in a transport pipeline. The water hammer detection device can be a computer device. See also... Figure 1 The method includes:

[0050] Step 101: If the probability of water hammer effect in the pipeline is greater than the probability threshold, then obtain the first pressure time series of the pipeline.

[0051] Water hammer detection equipment can detect the probability of water hammer effects occurring in a transport pipeline. If the water hammer detection equipment determines that the probability of water hammer effects occurring in the transport pipeline is greater than a probability threshold, then the first pressure time series of the transport pipeline is obtained. The first pressure time series includes multiple pressures sampled in chronological order.

[0052] In this embodiment, a pressure sensor is installed on the inner wall of the conveying pipeline, and this pressure sensor can establish a communication connection with a water hammer detection device. The pressure sensor can periodically collect the pressure exerted by the liquid transported in the conveying pipeline on the pipeline, and can upload the collected pressure and the sampling time of the pressure to the water hammer detection device through the communication connection. Once the water hammer detection device determines that the probability of water hammer occurring in the conveying pipeline is greater than a probability threshold, it can obtain a first pressure time series from the pressure uploaded by the pressure sensor.

[0053] Step 102: Detect whether the difference between the maximum pressure and the minimum pressure in the first pressure time series is greater than the first threshold, and whether the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold.

[0054] In this embodiment, compared to when water hammer does not occur, when water hammer occurs in the delivery pipeline, the flow velocity of the liquid being transported in the pipeline changes significantly within a short period of time, resulting in a significant change in the pressure exerted by the liquid on the delivery pipeline within a short period of time. Based on this, after acquiring the first pressure time series, the water hammer detection device can detect whether the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and whether the sampling time of the maximum pressure and the sampling time of the minimum pressure are less than the time threshold, to determine whether the pressure exerted by the liquid on the delivery pipeline has changed significantly within a short period of time.

[0055] If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that the pressure of the liquid transported in the pipeline on the pipeline has changed significantly in a short period of time, and step 103 can be executed. If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is less than or equal to the first threshold, and / or the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is greater than or equal to the time threshold, then it can be determined that the pressure of the liquid on the pipeline has not changed significantly in a short period of time, and step 101 can continue to be executed.

[0056] The first threshold can be a fixed value pre-stored by the water hammer detection device, or it can be the median of the first pressure time series determined by the water hammer detection device based on the first pressure time series. This time threshold can be pre-stored by the water hammer detection device.

[0057] Step 103: Determine if water hammer occurs in the delivery pipeline.

[0058] If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that a water hammer effect has occurred in the pipeline.

[0059] In summary, the water hammer detection method provided in this application allows the water hammer detection device to acquire a first pressure time series after determining that the probability of water hammer effect occurring in the conveying pipeline is greater than a probability threshold. If the water hammer detection device determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that the pressure in the conveying pipeline has changed significantly in a short period of time, and thus it can be determined that water hammer effect has occurred in the conveying pipeline. In this way, the monitoring of water hammer effect in the conveying pipeline can be achieved. Furthermore, since the water hammer detection device can acquire the first pressure time series only when the probability of water hammer effect occurring in the conveying pipeline is high, the computational resources of the water hammer detection device can be saved.

[0060] Figure 2 This is a flowchart of another water hammer detection method provided in an embodiment of this application. This method can be applied to water hammer detection equipment. See also... Figure 2 The method may include:

[0061] Step 201: Obtain the second flow time series of the delivery pipeline.

[0062] The second flow time series includes multiple flows that are sampled in chronological order.

[0063] In this embodiment, a flow sensor is installed on the inner wall of the conveying pipeline, and this flow sensor can establish a communication connection with a water hammer detection device. Once activated, the flow sensor periodically collects the flow rate of the liquid being conveyed in the pipeline and uploads the collected flow rate to the water hammer detection device via the communication connection. The water hammer detection device can then obtain a second flow time series from the received flow rate.

[0064] Understandably, the water hammer detection equipment can start by receiving a reference flow rate. After receiving each flow rate transmitted from the flow sensor, it checks whether the total number of flows received from the reference flow rate reaches a first target value. If the water hammer detection equipment determines that the total number reaches the first target value, it can use the flow time series composed of the flows received from the reference flow rate as a second flow time series. That is, each second flow time series can include the first target value of flows.

[0065] The reference flow rate can be the first flow rate received after the water hammer detection equipment is started, or the N×T flow rate received after the water hammer detection equipment is started. q +1 flow. N is a positive integer, T q The first target value is set. This first target value can be pre-stored in the water hammer detection equipment or preset by the water hammer detection engineer based on actual engineering experience. For example, the first target value can be 500.

[0066] Alternatively, the water hammer detection equipment can read the flow rate uploaded by the flow sensor at sampling times greater than or equal to the start time and less than or equal to the end time of the flow acquisition cycle at regular intervals to obtain a second flow time series. This flow detection cycle can be pre-stored by the water hammer detection equipment and preset by the water hammer detection engineer based on practical engineering experience. For example, the flow detection cycle can be 1 second (s).

[0067] Optionally, the conveying pipeline can be a water pipeline. Accordingly, the liquid conveyed in the pipeline is water.

[0068] Step 202: Determine the second flow difference time series based on the second flow time series.

[0069] The water hammer detection equipment can traverse the second flow time series according to the sampling time of the flow rate from morning to night. For each flow rate traversed, the water hammer detection equipment can determine a flow difference by subtracting the current flow rate from the next flow rate, thus obtaining the second flow difference time series. This second flow difference time series includes multiple flow differences arranged in order from morning to night according to the determined time.

[0070] In this embodiment, the flow rate collected by the flow sensor may experience sudden changes due to external factors (such as construction), resulting in abnormal flow differences in the second flow difference time series. These abnormal flow differences can affect the accuracy of the water hammer detection equipment in detecting the water hammer effect in the pipeline. Therefore, after acquiring the second flow difference time series, the water hammer detection equipment can preprocess it to remove abnormal flow differences, thereby improving the accuracy of the water hammer detection equipment in detecting the water hammer effect in the pipeline.

[0071] Figure 3 This is a flowchart illustrating a method for preprocessing a second flow difference time series according to an embodiment of this application. See also... Figure 3 The process of preprocessing the second flow difference time series by the water hammer detection equipment may include:

[0072] Step 2021: Determine the expected value and standard deviation of the second flow difference time series.

[0073] Among them, the expectation of the second flow difference time series It can satisfy:

[0074]

[0075] Standard deviation of the second flow difference time series It can satisfy:

[0076]

[0077] In formulas (1) and (2), Let m be the m-th flow difference in the second flow difference time series, where m is a positive integer greater than or equal to 1 and less than or equal to M, and M is the number of flow differences in the second flow difference time series.

[0078] Step 2022: Based on the expected value and standard deviation of the second flow difference time series, determine the abnormal flow difference in the second flow difference time series.

[0079] Specifically, the difference between this abnormal flow difference and the expected value of the second flow difference time series is greater than the product of the standard deviation of the second flow difference time series and the fourth coefficient. Therefore, this abnormal flow difference is a flow difference in the second flow difference time series that deviates excessively from the expected value of the second flow difference time series.

[0080] For example, this abnormal traffic difference It can satisfy:

[0081]

[0082] In formula (3), k1 is the fourth coefficient, which can be pre-stored by the water hammer detection equipment.

[0083] In this embodiment of the application, for each flow difference in the second flow difference time series, the water hammer detection device can detect the flow difference based on the expected value and standard deviation of the second flow difference time series to determine whether the flow difference is an abnormal flow difference.

[0084] Step 2023: Update the abnormal flow difference in the second flow difference time series.

[0085] Specifically, the updated abnormal flow difference is positively correlated with the normal flow difference adjacent to the abnormal flow difference. The difference between this normal flow difference and the expected value of the second flow difference time series is less than or equal to the product of the standard deviation of the second flow difference time series and the fourth coefficient. That is, this normal flow difference is the flow difference in the second flow difference time series excluding the abnormal flow difference.

[0086] In this embodiment, if the water hammer detection device determines that the abnormal flow difference is located at the end of the second flow difference time series, the normal flow difference adjacent to the abnormal flow difference can be directly determined as the updated abnormal flow difference. If the water hammer detection device determines that the abnormal flow difference is not located at the end of the second flow difference time series, the average of the two normal flow differences adjacent to the abnormal flow difference can be determined as the updated abnormal flow difference. Therefore, the updated abnormal flow difference is the same as the normal flow difference.

[0087] It is understandable that if the water hammer detection equipment determines that the abnormal flow difference is the first flow difference in the second flow difference time series, or the last flow difference in the second flow difference time series, then the abnormal flow difference is determined to be located at the end of the second flow difference time series.

[0088] Optionally, the second flow difference time series may contain multiple consecutive anomalous flow differences. If the consecutive anomalous flow differences are located at the end of the second flow difference time series, then each of the updated consecutive anomalous flow differences is a normal flow difference adjacent to it. If the consecutive anomalous flow differences are not located at the end of the second flow difference time series, then each of the updated consecutive anomalous flow differences is the average of the normal flow differences adjacent to it. Therefore, the updated consecutive anomalous flow differences are equal.

[0089] In this embodiment, after determining that an abnormal flow difference exists in the second flow difference time series, the water hammer detection device can directly update the abnormal flow difference in the second flow difference time series. Alternatively, after determining that an abnormal flow difference exists in the second flow difference time series, the water hammer detection device can detect whether the total number of normal flow differences in the second flow difference time series is less than a second target value. If the water hammer detection device determines that the total number is less than the second target value, it can update at least one abnormal flow difference in the second flow difference time series.

[0090] Optionally, the water hammer detection equipment can update all abnormal flow differences in the second flow difference time series, or it can update only some abnormal flow differences in the second flow difference time series. This embodiment does not limit this, as long as the total number of normal flow differences in the updated second flow difference time series is at least equal to the second target value. The second target value can be pre-stored by the water hammer detection equipment or preset by the water hammer detection engineer based on actual engineering experience.

[0091] Understandably, when the water hammer detection equipment updates some abnormal flow differences in the second flow difference time series, it needs to remove the outdated abnormal flow differences. Similarly, when the total number of normal flow differences in the second flow difference time series is greater than or equal to the second target value, the water hammer detection equipment also needs to remove the abnormal flow differences. This avoids affecting the detection of the water hammer effect.

[0092] Optionally, the process of updating abnormal flow differences using water hammer detection equipment may include: first removing abnormal flow differences from the second flow difference time series, and then determining the updated abnormal flow difference based on the adjacent normal flow differences. The water hammer detection equipment can then add the updated abnormal flow difference to the position where the original abnormal flow difference was located before it was removed.

[0093] Understandably, when updating some abnormal flow differences in the second flow difference time series using water hammer detection equipment, the equipment can prioritize updating the abnormal flow differences that appear earlier in the time series. This means that the flow rates associated with some abnormal flow differences were sampled earlier.

[0094] Step 203: If a target flow difference exists in the second flow difference time series, then obtain the first flow time series of the delivery pipeline.

[0095] Specifically, the absolute value of the target flow difference is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient. This third coefficient is greater than 1.

[0096] In this embodiment, if water hammer occurs in the conveying pipeline, the flow rate of the liquid being transported in the pipeline will change significantly within a short period of time. The median of the second flow difference time series reflects the average level of the flow difference in the conveying pipeline over a period of time. Therefore, the water hammer detection device can detect whether a target flow difference exists in the second flow difference time series, thereby determining whether the flow rate of the conveying pipeline has changed significantly within a short period of time.

[0097] If the water hammer detection equipment determines that there is no target flow rate in the second flow difference time series, it can be determined that the flow rate in the conveying pipeline has not changed significantly in a short period of time, and step 201 can be continued. If the water hammer detection equipment determines that there is a target flow rate in the second flow difference time series, it can be determined whether the flow rate in the conveying pipeline has changed significantly in a short period of time.

[0098] However, a significant change in flow rate within a short period cannot definitively attribute it to water hammer. Furthermore, when water hammer occurs, the flow rate within the pipeline fluctuates drastically over a given timeframe. Therefore, after confirming the existence of a target flow difference in the second flow difference time series, the water hammer detection equipment can also acquire the first flow time series of the pipeline to further determine whether the flow rate within the pipeline will continue to fluctuate drastically over a period of time.

[0099] The first flow time series includes multiple flow rates whose sampling times are arranged in chronological order. Furthermore, the sampling time of the first flow rate in the first flow time series is later than the sampling time of the flow rate to which the target flow rate difference belongs. For example, the sampling time of the first flow rate and the sampling time of the flow rate to which the target flow rate difference belongs are separated by the sampling period of the flow sensor.

[0100] Optionally, the sampling time of the first flow in the first flow time series may be later than the sampling time of the flow with a later sampling time in the flow to which the target flow difference belongs. Alternatively, the sampling time of the first flow in the first flow time series may be later than the sampling time of the flow with an earlier sampling time in the flow to which the target flow difference belongs.

[0101] It is understood that the process of acquiring the first flow time series using the water hammer detection equipment can refer to the relevant implementation process of acquiring the second flow time series described above, and will not be repeated here in this application embodiment. The total flow rate in the first flow time series can be greater than or equal to the third target value. In this way, it can be ensured that the number of samples used to detect whether the water hammer effect has occurred is sufficient, thereby ensuring that the water hammer detection equipment has high accuracy in detecting the water hammer effect in the pipeline.

[0102] In this embodiment of the application, for each flow difference in the second flow difference time series, the water hammer detection device can detect whether the absolute value of the flow difference is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient. If the water hammer detection device determines that there is a flow difference in the second flow difference time series whose absolute value is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient, then the flow difference can be determined as the target flow difference.

[0103] For example, assuming the target flow difference is the s-th flow difference q(s) in the second flow difference time series, then this flow difference q(s) can satisfy:

[0104] |q(s)|>|(1+λ q )×M q | Formula (4)

[0105] In formula (4), 1+λ q λ is the third coefficient. q It is pre-stored by the water hammer testing equipment and determined by the water hammer testing engineer based on actual engineering experience. For example, λ q It can be greater than 0 and less than 1. For example, λ. q It can be 0.1. M q This is the median of the second flow difference time series.

[0106] Step 204: Determine the first flow difference time series based on the first flow time series.

[0107] The water hammer detection equipment can traverse the first flow time series according to the sampling time of the flow rate from morning to night. For each flow rate traversed, the water hammer detection equipment can determine a flow difference by subtracting the current flow rate from the next flow rate, thus obtaining the first flow difference time series. This first flow difference time series includes multiple flow differences arranged in order from morning to night according to the determined time.

[0108] Step 205: Detect whether the number of flow differences in the first flow difference time series whose absolute value is greater than the flow difference threshold is greater than the number threshold, and whether the interquartile range of the first flow difference time series is less than the third threshold.

[0109] When water hammer occurs in a pipeline, the flow rate within the pipeline will continuously fluctuate significantly over a period of time, and the value of the flow rate change will be relatively stable. The interquartile range (IVR) of the flow rate time series reflects the dispersion of the flow rate within that time series. Therefore, water hammer detection equipment can detect whether the number of flow differences with absolute values ​​greater than a certain threshold in the first flow difference time series exceeds a certain threshold, and whether the IVR of the first flow difference time series is less than a third threshold, in order to determine whether the flow rate in the pipeline will continuously fluctuate significantly over a period of time, and whether the value of the flow rate change is relatively stable.

[0110] If the water hammer detection equipment determines that the number of flow rates with absolute values ​​greater than the flow difference threshold in the first flow difference time series is less than or equal to the number threshold, and / or the interquartile range of the first flow difference time series is greater than or equal to the third threshold, then it can be determined that the flow rate change in the conveying pipeline has not continuously undergone significant changes over a period of time, and / or the flow rate change value fluctuates significantly, and step 201 can then be executed. If the water hammer detection equipment determines that the number of flow differences with absolute values ​​greater than the flow difference threshold in the first flow difference time series is greater than the number threshold, and the interquartile range of the first flow difference time series is less than the third threshold, then it can be determined that the flow rate change in the conveying pipeline has continuously undergone significant changes over a period of time, and the flow rate change value is relatively stable. However, the fact that the flow rate change in the conveying pipeline has continuously undergone significant changes over a period of time, and the flow rate change value is relatively stable, only indicates that the current flow rate state in the conveying pipeline is the same as the flow rate state when the water hammer effect occurs, and does not necessarily indicate that a water hammer effect has occurred in the conveying pipeline. Therefore, the water hammer detection equipment also needs to execute step 206 to further determine whether a water hammer effect has occurred in the conveying pipeline.

[0111] The number threshold, flow difference threshold, and third threshold can all be pre-stored in the water hammer detection equipment. Furthermore, these thresholds can be pre-determined by the water hammer detection engineer based on practical engineering experience.

[0112] In this embodiment of the application, the interquartile difference can be the value of the flow difference located at three-quarters of the sorted flow difference time series after the flow differences in the first flow difference time series are sorted in ascending order, minus the value of the flow difference located at one-quarter of the sorted flow difference time series.

[0113] Step 206: Obtain the second pressure time series of the delivery pipeline.

[0114] If the water hammer detection equipment determines that the number of flow differences with absolute values ​​greater than the flow difference threshold in the first flow difference time series is greater than the number threshold, and the interquartile range of the first flow difference time series is less than the third threshold, then the second pressure time series of the conveying pipeline can be obtained. The second pressure time series includes multiple pressures arranged in chronological order at the sampling times.

[0115] In this embodiment, a pressure sensor is installed on the inner wall of the conveying pipeline, and the pressure sensor can establish a communication connection with the water hammer detection equipment. The pressure sensor can periodically collect the pressure of the liquid being conveyed in the pipeline on the conveying pipeline, and can upload the collected pressure and the sampling time of the pressure to the water hammer detection equipment through the communication connection.

[0116] Understandably, the water hammer detection equipment can start by receiving a reference pressure. After receiving each pressure reading from the pressure sensor, it checks whether the total number of pressures received from the reference pressure reaches the fourth target value. If the water hammer detection equipment determines that the total number reaches the fourth target value, it can use the pressure time series composed of the pressures received from the reference pressure as the second pressure time series. That is, each second pressure time series can include the fourth target value of pressures.

[0117] The reference pressure can be the first pressure received after the water hammer detection equipment is started, or the N×T pressure received after the water hammer detection equipment is started. p +1 pressure. N is a positive integer, T p This is the fourth target value. This fourth target value can be pre-stored in the water hammer detection equipment or preset by the water hammer detection engineer based on practical engineering experience. For example, this fourth target value could be 500.

[0118] Alternatively, the water hammer detection equipment can read the pressure uploaded by the pressure sensor at sampling times greater than or equal to the start time and less than or equal to the end time of the pressure acquisition cycle at regular intervals to obtain a second pressure time series. This pressure detection cycle can be pre-stored by the water hammer detection equipment and preset by the water hammer detection engineer based on practical engineering experience. For example, the pressure detection cycle can be 1 second.

[0119] In this embodiment, the pressure collected by the pressure sensor may experience sudden changes due to external factors (such as construction), potentially leading to abnormal pressures in the second pressure time series. These abnormal pressures can affect the accuracy of the water hammer detection equipment in detecting the water hammer effect in the pipeline. Therefore, after acquiring the second pressure time series, the water hammer detection equipment can preprocess it to remove abnormal pressures, thereby improving the accuracy of its detection of the water hammer effect in the pipeline.

[0120] Figure 4 This is a flowchart illustrating a method for preprocessing a second pressure time series according to an embodiment of this application. See also... Figure 4 The process of preprocessing the second pressure time series by the water hammer detection equipment may include:

[0121] Step 2061: Determine the expected value and standard deviation of the second pressure time series.

[0122] Among them, the expected μ of the second pressure time series p It can satisfy:

[0123]

[0124] The standard deviation σ of the second flow difference time series p It can satisfy:

[0125]

[0126] In formulas (5) and (6), p(i) is the i-th flow difference in the second flow difference time series, i is an integer greater than or equal to 1 and less than or equal to I, and I is the number of pressures in the second pressure time series.

[0127] Step 2062: Determine the abnormal pressures in the second pressure time series based on the expected value and standard deviation of the second pressure time series.

[0128] The difference between the abnormal pressure and the expected value of the second pressure time series is greater than the product of the standard deviation of the second pressure time series and the fifth coefficient. Therefore, the abnormal pressure is a pressure in the second pressure time series that deviates excessively from the expected value of the second pressure time series.

[0129] For example, the abnormal pressure p0 can satisfy:

[0130] |p0-μ p |>k2×σ p Formula (7)

[0131] In formula (7), k2 is the fifth coefficient, which can be pre-stored by the water hammer detection equipment.

[0132] In this embodiment of the application, for each pressure in the second pressure time series, the water hammer detection device can detect the pressure based on the expected value and standard deviation of the second pressure time series to determine whether the pressure is an abnormal pressure.

[0133] Step 2063: Update the abnormal pressures in the second pressure time series.

[0134] The updated abnormal pressure is positively correlated with the normal pressure adjacent to the abnormal pressure. The difference between this normal pressure and the expected value of the second pressure time series is less than or equal to the product of the standard deviation of the second pressure time series and the fifth coefficient. That is, this normal pressure is the pressure in the second pressure time series other than the abnormal pressure.

[0135] In this embodiment, if the water hammer detection device determines that the abnormal pressure is located at the end of the second pressure time series, the normal pressure adjacent to the abnormal pressure can be directly determined as the updated abnormal pressure. If the water hammer detection device determines that the abnormal pressure is not located at the end of the second pressure time series, the average of the two normal pressures adjacent to the abnormal pressure can be determined as the updated abnormal pressure.

[0136] It is understandable that if the water hammer detection equipment determines that the abnormal pressure is the first pressure of the second pressure time series or the last pressure of the second pressure time series, then the abnormal pressure is determined to be located at the end of the second pressure time series.

[0137] Optionally, the second pressure time series may contain multiple consecutive anomalous pressures. If the consecutive anomalous pressures are located at the end of the second pressure time series, then each of the updated consecutive anomalous pressures is a normal pressure adjacent to that consecutive anomalous pressure. If the consecutive anomalous pressures are not located at the end of the second pressure time series, then each of the updated consecutive anomalous pressures is the average of the normal pressures adjacent to that consecutive anomalous pressure. Therefore, the updated consecutive anomalous pressures are equal.

[0138] It is understood that the conditions for updating the abnormal pressure in the second pressure time series by the water hammer detection equipment, the number of abnormal pressures to be updated, and the update method can all refer to the relevant implementation process of updating the abnormal flow difference in step 2023, which will not be repeated here in the embodiments of this application.

[0139] Step 207: If the target pressure exists in the second pressure time series, then the probability of water hammer effect occurring in the delivery pipeline is determined to be greater than the probability threshold.

[0140] The target pressure can be greater than the product of the median of the second pressure time series and the first coefficient. The first coefficient is greater than 1 and less than 2. Alternatively, the target pressure can be less than the product of the median of the second pressure time series and the second coefficient. The second coefficient is greater than 0 and less than 1. The first and second coefficients can be fixed values ​​pre-stored in the water hammer detection equipment, or they can be determined by the water hammer detection engineer based on actual engineering experience.

[0141] It is understandable that water hammer can be caused by the sudden opening and closing of valves in the pipeline. Water hammer generally includes both positive and negative effects. Therefore, setting a target pressure as either greater than the product of the median and the first coefficient of the second pressure time series, or less than the product of the median and the second coefficient, ensures accurate identification of the target pressure. Since this median reflects the average pressure level in the pipeline during the sampling period of the second pressure time series, using this median to determine whether a target pressure exists in the second pressure time series ensures high accuracy.

[0142] In this embodiment, when no water hammer effect occurs in the delivery pipeline, the pressure of the liquid transported in the pipeline is relatively stable. However, if a valve in the delivery pipeline is suddenly opened or closed, the pressure at a certain moment may be too high or too low. Therefore, the water hammer detection device can detect whether a target pressure exists in the second pressure time series, thereby determining the probability of a water hammer effect occurring in the delivery pipeline.

[0143] If the water hammer detection equipment determines that the target pressure does not exist in the second pressure time series, then the probability of water hammer effect occurring in the conveying pipeline is less than or equal to the probability threshold, i.e., the probability is low, and step 201 can then be executed. If the water hammer detection equipment determines that the target pressure exists in the second pressure time series, then the probability of water hammer effect occurring in the conveying pipeline is less than or equal to the probability threshold, i.e., the probability is high.

[0144] That is, the target pressure p(a) in the second pressure time series can satisfy:

[0145]

[0146] In formula (8), 1+λ p The first coefficient, 1-λ p λ is the second coefficient. p It is pre-stored by the water hammer testing equipment and determined by the water hammer testing engineer based on actual engineering experience, such as λ. p It can be greater than 0 and less than 1, for example, λ. p It can be 0.1. M p This is the median of the second stress time series.

[0147] Understandably, once the water hammer detection equipment first determines that the target pressure exists in the second pressure time series, it can determine that the probability of water hammer effect occurring in the pipeline is greater than the probability threshold.

[0148] As described in steps 201 to 207 above, the water hammer detection method provided in this application embodiment can detect the probability of water hammer effect occurring in the conveying pipeline by sequentially measuring the flow rate and pressure within the pipeline. This ensures a high accuracy in determining the probability, thereby ensuring high accuracy in detecting the water hammer effect in the conveying pipeline.

[0149] Step 208: Obtain the first pressure time series.

[0150] After determining that the probability of water hammer effect occurring in the pipeline is high, the water hammer detection equipment can acquire a first pressure time series and further determine whether water hammer effect has occurred based on this first pressure time series. The first pressure time series includes multiple pressures sampled in chronological order. The sampling time of the first pressure in the first pressure time series is later than the sampling time of the target pressure. For example, the sampling time of the first pressure and the sampling time of the target pressure are separated by the sampling period of the pressure sensor.

[0151] It is understood that the process of acquiring the first pressure time series by the water hammer detection equipment can refer to the relevant implementation process of acquiring the second pressure time series described above, and will not be repeated here in this application embodiment. The number of pressures in the first pressure time series is greater than or equal to a fifth target value, which can be pre-stored by the water hammer detection equipment. In this way, it can be ensured that the number of pressures used to detect whether the water hammer effect has occurred is sufficient, thereby ensuring that the water hammer detection equipment detects the water hammer effect in the conveying pipeline with high accuracy.

[0152] Step 209: Detect whether the difference between the maximum pressure and the minimum pressure in the first pressure time series is greater than the first threshold, and whether the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold.

[0153] In this embodiment, compared to when water hammer does not occur, when water hammer occurs in the delivery pipeline, the pressure of the liquid being transported in the pipeline changes significantly within a short period of time, resulting in a significant change in the pressure exerted by the liquid on the delivery pipeline within a short period of time. Based on this, after acquiring the first pressure time series, the water hammer detection device can detect whether the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and whether the sampling time of the maximum pressure and the sampling time of the minimum pressure are less than the time threshold, to determine whether the pressure exerted by the liquid on the delivery pipeline has changed significantly within a short period of time.

[0154] If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than a time threshold, then proceed to step 210. If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is less than or equal to the first threshold, and / or the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is greater than or equal to the time threshold, then proceed to step 211.

[0155] The water hammer detection equipment can obtain the maximum pressure and the position of the maximum pressure in the first pressure time series, as well as the minimum pressure and the position of the minimum pressure in the first pressure time series.

[0156] For example, the difference P between the maximum and minimum pressures max -P min It can satisfy:

[0157] P max -P min >μ p ×M p Formula (9)

[0158] In formula (9), P max P represents the maximum pressure in the first pressure time series. min μ is the minimum pressure in the first pressure time series. p ×M p For the first threshold, μ p The first threshold coefficient can be pre-stored by the water hammer detection equipment or determined by the water hammer detection engineer based on actual engineering experience.

[0159] Step 210: Determine if water hammer occurs in the delivery pipeline.

[0160] If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that a water hammer effect has occurred in the pipeline.

[0161] In this embodiment of the application, after the water hammer detection equipment determines that a water hammer effect has occurred in the conveying pipeline, it can issue a reminder message to prompt the staff to take protective measures in a timely manner to reduce the damage of the water hammer effect to the conveying pipeline.

[0162] Optionally, the water hammer detection equipment can send alert messages to the staff's mobile devices.

[0163] Step 211: Confirm that no water hammer effect has occurred in the delivery pipeline.

[0164] If the water hammer detection equipment determines that the difference between the maximum and minimum pressures in the first pressure time series is less than or equal to the first threshold, and / or the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is greater than or equal to the time threshold, then it is determined that no water hammer effect has occurred in the conveying pipeline.

[0165] It is understandable that pressure sensors and flow sensors are typically installed in current pipelines. Therefore, the water hammer detection method provided in this application can directly utilize these pressure and flow sensors to detect whether a water hammer effect occurs in the pipeline, eliminating the need for separate sensor installation and thus reducing the detection cost of water hammer effects in pipelines.

[0166] The multiple thresholds (such as the number thresholds, the first threshold, and the second threshold mentioned above) and multiple coefficients (such as the first coefficient and the second coefficient mentioned above) in the water hammer detection method provided in this application can all be adjusted according to the actual environment of the conveying pipeline. Therefore, the water hammer detection method provided in this application has high applicability.

[0167] It is also understood that the order of steps in the water hammer detection method provided in this application embodiment can be appropriately adjusted, and steps can be added or removed as needed. For example, steps 201 to 206 can be deleted as appropriate. Any variations that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application, and therefore will not be elaborated further.

[0168] In summary, the water hammer detection method provided in this application allows the water hammer detection device to acquire a first pressure time series after determining that the probability of water hammer effect occurring in the conveying pipeline is greater than a probability threshold. If the water hammer detection device determines that the difference between the maximum and minimum pressures in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it can be determined that the pressure in the conveying pipeline has changed significantly in a short period of time, and thus it can be determined that water hammer effect has occurred in the conveying pipeline. In this way, the monitoring of water hammer effect in the conveying pipeline can be achieved. Furthermore, since the water hammer detection device can acquire the first pressure time series only when the probability of water hammer effect occurring in the conveying pipeline is high, the computational resources of the water hammer detection device can be saved.

[0169] Figure 5 This is a structural schematic diagram of a water hammer detection device provided in an embodiment of this application. Figure 5 The water hammer detection device 100 includes a processor 110. The processor 110 can be used for:

[0170] If the probability of water hammer effect in the pipeline is greater than the probability threshold, then the first pressure time series of the pipeline is obtained.

[0171] If the difference between the maximum and minimum pressures in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, then it is determined that the pipeline is experiencing water hammer.

[0172] Optionally, the processor 110 can also be used for:

[0173] A second pressure time series of the delivery pipeline is obtained, wherein the sampling time of at least one pressure in the second pressure time series is earlier than the sampling time of each first pressure in the first pressure time series.

[0174] If the target pressure exists in the second pressure time series, then the probability of water hammer effect occurring in the pipeline is determined to be greater than the probability threshold.

[0175] Wherein, the target pressure is greater than the product of the median of the second pressure time series and the first coefficient, or the target pressure is less than the product of the median of the second pressure time series and the second coefficient, the first coefficient is greater than 1, and the second coefficient is less than 1;

[0176] In the first pressure time series, the sampling time of the first pressure is later than the sampling time of the target pressure.

[0177] Optionally, the processor 110 can be used for:

[0178] Obtain the first flow time series of the delivery pipeline;

[0179] Determine the first flow difference time series based on the first flow time series;

[0180] If the number of flow differences with absolute values ​​greater than the flow difference threshold in the first flow difference time series is greater than the number threshold, and the interquartile range of the first flow difference time series is less than the third threshold, then the second pressure time series of the conveying pipeline is obtained.

[0181] Optionally, the processor 110 can be used for:

[0182] Obtain the second flow time series of the delivery pipeline;

[0183] Determine the second flow difference time series based on the second flow time series;

[0184] If the target flow difference exists in the second flow difference time series, then the first flow time series of the delivery pipeline is obtained;

[0185] Among them, the absolute value of the target flow difference is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient, and the third coefficient is greater than 1;

[0186] The sampling time of the first flow in the first flow time series is later than the sampling time of the flow to which the target flow difference belongs.

[0187] Optionally, the processor 110 can also be used for:

[0188] Update the abnormal flow difference in the second flow difference time series. The updated abnormal flow difference is positively correlated with the normal flow difference adjacent to the abnormal flow difference.

[0189] Among them, the difference between the expected value of the abnormal flow difference and the second flow difference time series is greater than the product of the standard deviation of the second flow difference time series and the fourth coefficient.

[0190] Optionally, the processor 110 can also be used for:

[0191] Update the anomalous pressures in the second pressure time series. The updated anomalous pressures are positively correlated with the pressures adjacent to the anomalous pressures.

[0192] Among them, the difference between the abnormal pressure and the expected value of the second pressure time series is greater than the product of the standard deviation of the second pressure time series and the fifth coefficient.

[0193] Optionally, the processor 110 can be used for:

[0194] If the abnormal pressure is located at the end of the second pressure time series, then the updated abnormal pressure is the pressure adjacent to the abnormal pressure.

[0195] If the abnormal pressure is not located at the end of the second pressure time series, the updated abnormal pressure is the average of the two pressures adjacent to the abnormal pressure.

[0196] In summary, the water hammer detection device provided in this application can acquire a first pressure time series after determining that the probability of water hammer effect occurring in the conveying pipeline is greater than a probability threshold. If the water hammer detection device determines that the difference between the maximum and minimum pressure in the first pressure time series is greater than the first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than the time threshold, it can be determined that the pressure in the conveying pipeline has changed significantly in a short period of time, and thus it can be determined that water hammer effect has occurred in the conveying pipeline. In this way, the monitoring of water hammer effect in the conveying pipeline can be realized. Furthermore, since the water hammer detection device can acquire the first pressure time series only when the probability of water hammer effect occurring in the conveying pipeline is high, the computational resources of the water hammer detection device can be saved.

[0197] Please continue to refer to this. Figure 5 The water hammer detection device 100 also includes a memory 120. The processor 110 and the memory 120 are connected, for example, via a bus 130.

[0198] Processor 110 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 110 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0199] Bus 130 may include a pathway for transmitting information between the aforementioned components. Bus 130 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 130 may be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0200] The memory 120 is used to store a computer program corresponding to the water hammer detection method of the above embodiments of this application. The computer program is controlled and executed by the processor 110. The processor 110 is used to execute the computer program stored in the memory 120 to implement the content shown in the foregoing method embodiments.

[0201] This application provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the method for determining the cable force of bridge cables as provided in the above-described method embodiments. For example... Figure 1 or Figure 2 The method shown.

[0202] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0203] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0204] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0205] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0206] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0207] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method for detecting water hammer, characterized in that, The method includes: If the probability of water hammer effect occurring in the pipeline is greater than the probability threshold, then the first pressure time series of the pipeline is obtained. If the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than a time threshold, then it is determined that the conveying pipeline is experiencing water hammer; the method further includes: Obtaining a second pressure time series of the conveying pipeline, the method of obtaining a second pressure time series of the conveying pipeline includes: obtaining a first flow time series of the conveying pipeline; determining a first flow difference time series based on the first flow time series; if the number of flow differences in the first flow difference time series whose absolute value is greater than a flow difference threshold is greater than a number threshold, and the interquartile range of the first flow difference time series is less than a third threshold, then obtaining a second pressure time series of the conveying pipeline. The sampling time of at least one pressure in the second pressure time series is earlier than the sampling time of each first pressure in the first pressure time series; If the target pressure exists in the second pressure time series, then the probability that the water hammer effect occurs in the delivery pipeline is greater than the probability threshold. Wherein, the target pressure is greater than the product of the median of the second pressure time series and the first coefficient, or the target pressure is less than the product of the median of the second pressure time series and the second coefficient, wherein the first coefficient is greater than 1 and the second coefficient is less than 1; The sampling time of the first pressure in the first pressure time series is later than the sampling time of the target pressure.

2. The method according to claim 1, characterized in that, The step of obtaining the first flow time series of the delivery pipeline includes: Obtain the second flow time series of the delivery pipeline; The second flow difference time series is determined based on the second flow time series. If a target flow difference exists in the second flow difference time series, then the first flow time series of the conveying pipeline is obtained; Wherein, the absolute value of the target flow difference is greater than the absolute value of the product of the median of the second flow difference time series and the third coefficient, and the third coefficient is greater than 1; The sampling time of the first flow in the first flow time series is later than the sampling time of the flow to which the target flow difference belongs.

3. The method according to claim 2, characterized in that, The method further includes: Update the abnormal flow difference in the second flow difference time series. The updated abnormal flow difference is positively correlated with the normal flow difference adjacent to the abnormal flow difference. Wherein, the difference between the abnormal flow difference and the expected value of the second flow difference time series is greater than the product of the standard deviation of the second flow difference time series and the fourth coefficient.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Update the abnormal pressures in the second pressure time series, and the updated abnormal pressures are positively correlated with the pressures adjacent to the abnormal pressures. The difference between the abnormal pressure and the expected value of the second pressure time series is greater than the product of the standard deviation of the second pressure time series and the fifth coefficient.

5. The method according to claim 4, characterized in that, If the abnormal pressure is located at the end of the second pressure time series, then the updated abnormal pressure is the pressure adjacent to the abnormal pressure. If the abnormal pressure is not located at the end of the second pressure time series, then the updated abnormal pressure is the average of the two pressures adjacent to the abnormal pressure.

6. A water hammer detection device, characterized in that, The water hammer detection device includes: a processor; the processor is used for: If the probability of water hammer effect occurring in the pipeline is greater than the probability threshold, then the first pressure time series of the pipeline is obtained. If the difference between the maximum and minimum pressures in the first pressure time series is greater than a first threshold, and the absolute value of the difference between the sampling time of the maximum pressure and the sampling time of the minimum pressure is less than a time threshold, then it is determined that the conveying pipeline is experiencing a water hammer effect; the processor is further configured to: Obtaining a second pressure time series of the conveying pipeline, the method comprising: obtaining a first flow time series of the conveying pipeline; determining a first flow difference time series based on the first flow time series; if the number of flow differences in the first flow difference time series whose absolute value is greater than a flow difference threshold is greater than a number threshold, and the interquartile range of the first flow difference time series is less than a third threshold, then obtaining a second pressure time series of the conveying pipeline; wherein the sampling time of at least one pressure in the second pressure time series is earlier than the sampling time of each first pressure in the first pressure time series; If the target pressure exists in the second pressure time series, then the probability that the water hammer effect occurs in the delivery pipeline is greater than the probability threshold. Wherein, the target pressure is greater than the product of the median of the second pressure time series and the first coefficient, or the target pressure is less than the product of the median of the second pressure time series and the second coefficient, wherein the first coefficient is greater than 1 and the second coefficient is less than 1; The sampling time of the first pressure in the first pressure time series is later than the sampling time of the target pressure.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

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