A method and system for quickly locating pipeline faults of a pump station house

Abstract

The present application relates to the technical field of pipeline operation and maintenance, and particularly relates to a method and system for quickly locating faults of a pipeline in a pump station house, which solves the technical problem of low fault locating efficiency in the prior art. The method comprises: obtaining normal operation data of a plurality of pipe sections in the pipeline of the pump station house, and collecting real-time operation data of the plurality of pipe sections in real time; the normal operation data comprises normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe sections under various working conditions; the real-time operation data comprises real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe sections; performing anomaly detection according to the real-time operation data and the normal operation data of the plurality of pipe sections, identifying an abnormal pipe section in the plurality of pipe sections and a fault mode corresponding to the abnormal pipe section; and based on the fault mode corresponding to the abnormal pipe section, performing fault locating according to the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding working condition, and determining a fault point position.

Description

Technical Field

[0001] This invention relates to the field of pipeline operation and maintenance technology, specifically to a method and system for rapid fault location in pipelines of pumping stations. Background Technology

[0002] Pump station pipelines are the core pipeline network system for transporting liquids such as raw water, supplied water, and chemical media. They undertake the critical tasks of pressurization, lifting, and transportation, and their operational status directly affects production continuity, energy utilization, and operational safety. During the long-term operation of pump station pipelines, they are prone to leaks or blockages due to factors such as media corrosion, pipeline aging, and external disturbances. If the fault point cannot be detected and accurately located in a timely manner, it may lead to media loss, energy waste, production interruption, and even secondary disasters such as equipment damage and foundation settlement. Therefore, rapid and accurate location of faults in pump station pipelines is crucial.

[0003] Currently, the mainstream methods for locating pipeline faults in pumping stations in the industry mostly rely on pressure or flow monitoring based on fixed thresholds. This involves setting fixed limits for pressure and flow, and triggering an alarm when the sensor reading exceeds these limits. However, this approach struggles to identify faults effectively and promptly in some scenarios, and can only roughly determine the abnormal pipe section, failing to pinpoint the exact fault location. It still requires manual experience for subsequent troubleshooting, resulting in low fault handling efficiency and hindering rapid repairs and system recovery. Summary of the Invention

[0004] To address the problem of low efficiency in fault diagnosis in existing technologies, the present invention aims to provide a method and system for rapid fault location in pipelines of pumping stations. The specific technical solution adopted is as follows:

[0005] This application provides a method for rapid fault location in pipelines of pumping stations, including:

[0006] The system acquires normal operating data for multiple pipe sections in the pump station pipeline and collects real-time operating data for multiple pipe sections. Normal operating data includes normal upstream and downstream pressure data and normal upstream and downstream flow data for each pipe section under various operating conditions. Real-time operating data includes real-time upstream and downstream pressure data and real-time upstream and downstream flow data for each pipe section.

[0007] Anomaly detection is performed based on real-time and normal operating data of multiple pipe sections to identify abnormal pipe sections and their corresponding fault modes; the fault modes include leakage faults and blockage faults.

[0008] Based on the fault mode corresponding to the abnormal pipe section, the fault location is determined by comparing the real-time upstream and downstream pressure data of the abnormal pipe section with the normal upstream and downstream pressure data under the corresponding operating conditions.

[0009] In one possible implementation, the method includes:

[0010] For each pipe segment, the healthy dynamic impedance data of the pipe segment under each operating condition is determined based on the normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe segment under each operating condition, and the real-time dynamic impedance data of the pipe segment is determined based on the real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe segment.

[0011] By comparing and analyzing the real-time dynamic impedance data of each pipe segment with the healthy dynamic impedance data of the corresponding operating conditions, abnormal pipe segments among multiple pipe segments can be identified.

[0012] By comparing and analyzing the real-time upstream and downstream pressure data of abnormal pipe sections with normal upstream and downstream pressure data, as well as the real-time upstream and downstream flow data of abnormal pipe sections with normal upstream and downstream flow data, the corresponding fault mode of abnormal pipe sections can be determined.

[0013] In one possible implementation, the method includes:

[0014] For each pipe segment, the deviation coefficient is determined based on the real-time dynamic impedance data of the pipe segment and the healthy dynamic impedance data of the corresponding operating condition; the deviation coefficient is used to characterize the degree of deviation between the real-time dynamic impedance data and the healthy dynamic impedance data.

[0015] Abnormal pipe segments among multiple pipe segments are identified based on the deviation coefficient of each segment.

[0016] In one possible implementation, the method includes:

[0017] Based on the real-time upstream and downstream pressure data of abnormal pipe sections and normal upstream and downstream pressure data, determine the upstream pressure deviation value and downstream pressure deviation value at each time point within the target time window. Based on the real-time upstream and downstream flow data of abnormal pipe sections and normal upstream and downstream flow data, determine the upstream flow deviation value and downstream flow deviation value at each time point within the target time window.

[0018] The upstream deviation distribution characteristics of the abnormal pipe section are determined based on the upstream pressure deviation and upstream flow deviation values ​​at each time point, and the downstream deviation distribution characteristics of the abnormal pipe section are determined based on the downstream pressure deviation and downstream flow deviation values ​​at each time point.

[0019] The fault mode corresponding to the abnormal pipe section is determined based on the upstream and downstream deviation distribution characteristics of the abnormal pipe section.

[0020] In one possible implementation, the upstream deviation distribution characteristics include a first distribution ratio and a second distribution ratio;

[0021] The first distribution ratio is the percentage of time points within the target time window where the upstream pressure deviation is negative and the upstream flow deviation is positive, out of the total number of time points within the target time window; the second distribution ratio is the percentage of time points within the target time window where the upstream pressure deviation is positive and the upstream flow deviation is less than or equal to zero, out of the total number of time points within the target time window.

[0022] The downstream deviation distribution characteristics include the proportion of the third distribution;

[0023] The third distribution ratio is the proportion of the number of time points within the target time window where both the downstream pressure deviation and downstream flow deviation are negative to the total number of time points within the target time window.

[0024] In one possible implementation, the method includes:

[0025] If the first distribution ratio is greater than or equal to the first preset threshold and the third distribution ratio is greater than or equal to the third preset threshold, the fault mode is determined to be a leakage fault.

[0026] If the second distribution ratio is greater than or equal to the second preset threshold and the third distribution ratio is greater than or equal to the third preset threshold, the fault mode is determined to be a blockage fault.

[0027] In one possible implementation, the method further includes:

[0028] If the fault mode corresponding to the abnormal pipe segment cannot be determined based on the upstream and downstream deviation distribution characteristics of the abnormal pipe segment, the fault mode determination operation is repeated until the preset number of times is reached.

[0029] The fault mode determination operation includes: redetermining the window range of the target time window, and determining the fault mode corresponding to the abnormal pipe segment according to the redetermined target time window.

[0030] In one possible implementation, the method further includes:

[0031] When the number of executions reaches the preset number, the upstream and downstream pressure abnormality time points of the abnormal pipe sections are determined based on the upstream and downstream pressure deviation values ​​at each time point within the target time window.

[0032] When the upstream pressure anomaly occurs after the downstream pressure anomaly, the fault mode is determined to be a leakage fault.

[0033] When the upstream pressure anomaly occurs before the downstream pressure anomaly, the fault mode is determined to be a blockage fault.

[0034] In one possible implementation, the method includes:

[0035] Based on the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding operating conditions, the upstream pressure deviation amplitude and the downstream pressure deviation amplitude of the abnormal pipe section are calculated. Among them, the upstream pressure deviation amplitude is determined based on the absolute value of the upstream pressure deviation at each time point within the target time window, and the downstream pressure deviation amplitude is determined based on the absolute value of the downstream pressure deviation at each time point within the target time window.

[0036] For abnormal pipe sections with leakage fault mode, the distance between the fault point and the upstream of the abnormal pipe section is determined based on the proportion of the downstream pressure deviation to the total amplitude of the upstream and downstream pressure deviations, as well as the length of the abnormal pipe section.

[0037] For abnormal pipe sections with a blockage fault mode, the distance between the fault point and the upstream of the abnormal pipe section is determined based on the ratio of the upstream pressure deviation to the downstream pressure deviation and the length of the abnormal pipe section.

[0038] This application provides a system for rapid fault location in pipelines of pumping stations, comprising:

[0039] The data acquisition module is used to acquire normal operation data of multiple pipe sections in the pump station pipeline and collect real-time operation data of multiple pipe sections. Normal operation data includes normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe section under various operating conditions. Real-time operation data includes real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe section.

[0040] The anomaly detection module is used to detect anomalies based on real-time and normal operating data of multiple pipe segments, identify abnormal pipe segments and their corresponding fault modes; the fault modes include leakage faults and blockage faults.

[0041] The fault location module is used to locate the fault based on the fault mode corresponding to the abnormal pipe section, and by comparing the real-time upstream and downstream pressure data of the abnormal pipe section with the normal upstream and downstream pressure data under the corresponding operating conditions.

[0042] The present invention has the following beneficial effects:

[0043] In view of the technical problem of low efficiency in fault diagnosis in existing technologies, this application provides a method and system for rapid fault location in pump station pipelines. This application provides a complete data foundation for fault diagnosis by acquiring normal operation data and real-time operation data of each pipe section in the pump station pipeline, ensuring the effectiveness of data comparison. Through data comparison between normal operation data and real-time operation data, abnormal pipe sections are identified and fault modes are distinguished. Thus, this application can calculate the fault location based on the fault mode, achieving rapid and accurate fault location, significantly improving the efficiency and accuracy of fault location in pump station pipelines, providing strong support for rapid repair, and effectively reducing economic losses caused by faults. Attached Figure Description

[0044] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a system architecture diagram of a rapid fault location system for pump station pipelines provided in one embodiment of the present invention;

[0046] Figure 2 This is a flowchart illustrating a method for rapid fault location in pipelines of a pumping station, provided in one embodiment of the present invention.

[0047] Figure 3 This is a flowchart illustrating another method for rapid fault location in pump station pipelines, provided in one embodiment of the present invention.

[0048] Figure 4 This is a flowchart illustrating another method for rapid fault location in pump station pipelines, provided in one embodiment of the present invention.

[0049] Figure 5 This is a flowchart illustrating another method for rapid fault location in pump station pipelines, provided in one embodiment of the present invention.

[0050] Figure 6 This is a flowchart illustrating another method for rapid fault location in pump station pipelines, provided as an embodiment of the present invention. Detailed Implementation

[0051] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method and system for rapid fault location in pump station pipelines according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0053] The following description, in conjunction with the accompanying drawings, details a specific scheme for a method and system for rapid fault location in pump station pipelines provided by the present invention.

[0054] In view of the technical problem of low efficiency in fault diagnosis in existing technologies, this application provides a method and system for rapid fault location in pump station pipelines. This application provides a complete data foundation for fault diagnosis by acquiring normal operation data and real-time operation data of each pipe section in the pump station pipeline, ensuring the effectiveness of data comparison. Through data comparison between normal operation data and real-time operation data, abnormal pipe sections are identified and fault modes are distinguished. Thus, this application can calculate the fault location based on the fault mode, achieving rapid and accurate fault location, significantly improving the efficiency and accuracy of fault location in pump station pipelines, providing strong support for rapid repair, and effectively reducing economic losses caused by faults.

[0055] Please see Figure 1 The diagram illustrates a system architecture diagram of a rapid fault location system for pump station pipelines provided by an embodiment of the present invention. The system 10 includes: a data acquisition module 11, an anomaly detection module 12, and a fault location module 13.

[0056] The data acquisition module 11 is used to acquire normal operation data of multiple pipe sections in the pump station pipeline and to collect real-time operation data of multiple pipe sections.

[0057] The normal operation data includes the normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipeline section under various operating conditions, while the real-time operation data includes the real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipeline section.

[0058] For example, operating conditions include typical operating states such as pump speed settings and valve opening combinations. In practical applications, the data acquisition module 11 can collect data through pressure sensors and flow sensors deployed in the pipeline. The pipeline is divided into multiple pipe segments by the deployed pressure sensors and flow sensors. The installation position of the sensors can be dynamically adjusted according to the importance of the pipe segment and the probability of historical failures. For example, for critical delivery areas or areas with frequent historical failures, the sensor layout can be densified to improve the accuracy of data acquisition.

[0059] The anomaly detection module 12 is used to perform anomaly detection based on the real-time operation data and normal operation data of multiple pipe sections, and to identify the abnormal pipe sections and the corresponding fault modes of the abnormal pipe sections.

[0060] The fault modes include leakage faults and blockage faults. For example, the anomaly detection module 12 can call the real-time data and normal data of the same pipe section and the same operating condition acquired by the data acquisition module 11, and determine whether the deviation between the two (such as pressure deviation, flow deviation) exceeds the preset reasonable fluctuation range. If it exceeds the range, the pipe section is marked as an abnormal pipe section, and then the deviation characteristics are further analyzed to identify the fault mode.

[0061] In some embodiments, the anomaly detection module 12 also needs to have a data caching function to cache real-time data and anomaly judgment results of historical detections, so as to facilitate subsequent fault tracing and mode optimization.

[0062] The fault location module 13 is used to locate the fault point based on the fault mode corresponding to the abnormal pipe section, according to the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding operating conditions.

[0063] In some embodiments, the fault location module 13 can pre-store the physical parameters of all pipe segments (including the total length of the pipe segment, pipe diameter, pipe friction coefficient, etc.). During location, based on the fault mode output by the anomaly detection module 12, it calls the real-time and normal pressure data of the pipe segment and determines the specific location of the fault point through the correlation calculation between pressure deviation and pipe segment length.

[0064] In addition, in order to achieve structured integration of fault information and automated response, the fault location module 13 can also have a result output function, which can transform the scattered diagnostic results into standardized operation and maintenance instructions to ensure real-time information transmission and timely fault alarm.

[0065] For example, the fault location module 13 can encapsulate the final faulty pipe segment identifier, fault mode (leakage / blockage), fault location, fault severity, and fault confidence level into standardized data (such as JSON structured data). This standardized data can include timestamps, pipe segment identifiers, fault modes, location coordinates, fault severity, and suggested handling measures. The encapsulated standardized data is then transmitted to the host computer in the pump station monitoring center via a standard interface, enabling visualization of fault information. The system can display fault alarms and location information in real time through a human-machine interface, highlight abnormal segments in graphical pipeline diagrams, trigger audible and visual alarms, and automatically generate maintenance work orders to be pushed to the maintenance terminal.

[0066] It should be noted that the various embodiments of this application can be referenced or learned from each other. For example, the same or similar steps, method embodiments, system embodiments and device embodiments can be referenced from each other without limitation.

[0067] Please see Figure 2 The diagram illustrates a method flowchart for rapid fault location in pump station pipelines according to an embodiment of the present invention. The method includes the following steps:

[0068] Step 201: Obtain normal operation data of multiple pipe sections in the pump station pipeline, and collect real-time operation data of multiple pipe sections.

[0069] The normal operation data includes normal upstream and downstream pressure and flow data for the pipeline segment under various operating conditions. Real-time operation data includes real-time upstream and downstream pressure and flow data for the pipeline segment. Normal upstream and downstream pressure data can include upstream and downstream pressure at multiple time points under the corresponding operating conditions during normal operation. Normal upstream and downstream flow data can include upstream and downstream flow rates at multiple time points under the corresponding operating conditions. Real-time upstream and downstream pressure data can include upstream and downstream pressure at multiple time points during real-time operation of the pipeline segment. Real-time upstream and downstream flow data can also include upstream and downstream flow rates at multiple time points during real-time operation of the pipeline segment. The normal upstream and downstream pressure data and real-time operation data can be time-series aligned, for example, using a daily cycle, where the normal upstream and downstream pressure data and real-time operation data can be data from various corresponding time points within each day.

[0070] A pipe segment refers to an independent analysis unit divided according to the actual topology of the pump station pipeline and the installation positions of adjacent sensors. Each pipe segment corresponds to the interval between the upstream and downstream sensors. An operating condition refers to the combination of operating states of the pump station pipeline, including key operating parameters affecting pipeline pressure and flow such as pump speed, valve opening, and temperature of the conveyed medium. Normal operating data for the pipeline varies under different operating conditions; therefore, it is necessary to cover all typical operating conditions to ensure the comprehensiveness of the health status benchmark.

[0071] For example, the normal operation data can be collected when the pump station pipeline is fault-free and operating stably. The collection period needs to cover all typical operating conditions, such as a collection period of ≥72 hours, to ensure the comprehensiveness and representativeness of the data.

[0072] During pipeline operation, the acquisition frequency of real-time operating data of multiple pipe sections collected in this application must be consistent with the acquisition frequency of normal operating data (for example, the acquisition frequency can be set to 10Hz) to ensure the effectiveness of data comparison.

[0073] During data acquisition, this application can divide the pump station pipeline into segments based on the sensor installation locations. For example, according to the actual topology of the pump station pipeline system and the importance and failure frequency of each area in the management system, the entire pipeline can be divided into several independent analysis segments according to the installation locations of adjacent sensors. Each segment is defined as the corresponding interval between upstream and downstream sensors. In Corresponding to the upstream sensor number, In addition to the corresponding downstream sensor numbers, the physical parameters of each pipe segment (such as the total length L of the pipe segment) can also be obtained. mn Pipe diameter D mn (such as pipe material characteristic parameters), which serve as a basic reference for subsequent data processing.

[0074] Step 202: Perform anomaly detection based on real-time and normal operating data of multiple pipe sections to identify abnormal pipe sections and their corresponding fault modes.

[0075] The failure modes include leakage failures and blockage failures. Leakage failures refer to failure modes in which the transported medium leaks out due to pipeline damage, loose joints, etc., while blockage failures refer to failure modes in which the flow cross-section of the pipeline is reduced due to media deposition, foreign object intrusion, etc.

[0076] An abnormal pipe section refers to a pipe section whose real-time operating data deviates from normal operating data beyond a reasonable range. Its identification logic is based on the operating patterns under pipeline health conditions, determining whether there are systematic deviations in real-time data caused by non-operating condition fluctuations. This application can first determine whether the deviation between real-time data and normal data exceeds a reasonable range. If it does, the pipe section is marked as an abnormal pipe section. Then, based on the deviation characteristics between real-time data and normal data, it can distinguish whether the fault mode of the abnormal pipe section is a leakage fault or a blockage fault.

[0077] Step 203: Based on the fault mode corresponding to the abnormal pipe section, locate the fault by comparing the real-time upstream and downstream pressure data of the abnormal pipe section with the normal upstream and downstream pressure data under the corresponding operating conditions.

[0078] After identifying the failure mode of the abnormal pipe section, this application can further determine the specific location of the failure, facilitating rapid and accurate pipeline repair. Since both leakage and blockage disrupt the original pressure distribution of the pipeline, this application can determine the location of the failure point through pressure data analysis.

[0079] In this process, a leak creates a new pressure outlet at the leak point, causing a drop in pipeline pressure. The closer the sensor is to the leak point, the more significant the pressure drop is detected. Conversely, a blockage increases local resistance, leading to increased upstream pressure and decreased downstream pressure. This application quantifies the relative impact on pressure at both upstream and downstream ends to determine the distance of the fault point relative to the sensors at both ends, thus achieving accurate fault location.

[0080] Based on the above technical solution, this application provides a complete data foundation for fault diagnosis by acquiring normal operation data and real-time operation data of each pipe section in the pump station pipeline, ensuring the effectiveness of data comparison. By comparing normal operation data and real-time operation data, abnormal pipe section identification and fault mode differentiation are achieved. In this way, this application can calculate the fault point location based on the fault mode, realize the rapid and accurate location of the fault point, significantly improve the efficiency and accuracy of fault location in the pump station pipeline, provide strong support for rapid emergency repair, and effectively reduce the economic losses caused by the fault.

[0081] Furthermore, existing technologies typically use single, fixed pressure or flow thresholds when detecting pipeline faults, which cannot distinguish between normal operating fluctuations such as pump speed adjustments and valve opening changes and actual fault conditions. This results in a large number of invalid alarms. Moreover, minor leaks or blockages usually cause very subtle parameter changes in the early stages, making it difficult to trigger fixed thresholds, which leads to potential problems being overlooked.

[0082] To overcome the limitations of the traditional methods mentioned above, this application can also achieve anomaly detection based on dynamic impedance, thereby effectively distinguishing between normal operating condition fluctuations and real faults.

[0083] As one possible embodiment of this application, combined with Figure 2 ,like Figure 3 As shown, step 202 above can be achieved through the following steps:

[0084] Step 301: For each pipe segment, determine the healthy dynamic impedance data of the pipe segment under each operating condition based on the normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe segment under each operating condition, and determine the real-time dynamic impedance data of the pipe segment based on the real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe segment.

[0085] Among them, the health dynamic impedance data includes the dynamic impedance of the pipe section at multiple time points during normal operation, and the real-time dynamic impedance data includes the dynamic impedance of the pipe section at multiple time points during real-time operation.

[0086] It should be noted that for a pipe section with a fixed structure in normal operation, all physical parameters affecting resistance, such as inner wall roughness and local resistance elements (e.g., elbows), remain constant. According to fluid mechanics principles, the sum of the frictional resistance and local resistance (also known as pressure drop or pressure loss) generated by the pipe section on the fluid is proportional to the square of the flow rate. In other words, the ratio of the sum of frictional resistance and local resistance to the square of the flow rate (i.e., dynamic impedance) is a constant determined by the physical properties of the pipe section itself. When a fault occurs in the pipe section, its physical properties are disrupted, leading to a change in dynamic impedance. Therefore, this application can use this dynamic impedance to assess whether each pipe section is abnormal.

[0087] For example, taking health dynamic impedance data as an example, the health dynamic impedance in the health dynamic impedance data satisfies the following formula:

[0088]

[0089] in, For the pipe section at a certain time point The healthy dynamic impedance, For the normal upstream and downstream pressure data of the pipeline segment at the time point Upstream pressure, For the normal upstream and downstream pressure data of the pipeline segment at the time point Downstream pressure, For the pipe section at a certain time point The flow rate of this pipe section can be obtained from the normal upstream and downstream flow data at a given time point. The average of the upstream and downstream flows is represented by . It is a very small positive number (e.g.) This is to avoid the denominator being zero. Real-time dynamic impedance data can be calculated using the method described above, and will not be repeated here.

[0090] Step 302: Based on the real-time dynamic impedance data of each pipe segment and the healthy dynamic impedance data of the corresponding operating conditions, identify abnormal pipe segments among multiple pipe segments.

[0091] In one possible implementation, this application can determine the deviation coefficient of each pipe segment based on the real-time dynamic impedance data of the pipe segment and the health dynamic impedance data of the corresponding operating condition. Then, abnormal pipe segments among multiple pipe segments can be identified based on the deviation coefficient of each pipe segment.

[0092] The deviation coefficient is used to characterize the degree of deviation between real-time dynamic impedance data and healthy dynamic impedance data.

[0093] For example, the deviation coefficient satisfies the following formula:

[0094]

[0095] in, This is the deviation coefficient for this pipe section. For this pipe section at a certain time point Real-time dynamic impedance, This represents the average dynamic impedance of the pipe section at multiple time points during normal operation. This represents the standard deviation of the dynamic impedance of the pipe section at multiple time points during normal operation. It is a very small positive number (e.g.) (to avoid the denominator being zero). The larger the value, the greater the deviation between the current dynamic impedance and the healthy dynamic impedance; the greater the deviation coefficient. The larger the value, the more severe the deviation of the real-time dynamic impedance from the healthy state.

[0096] For example, this application can compare a preset deviation coefficient threshold with the deviation coefficient of each pipe segment, thereby identifying pipe segments with deviation coefficients greater than the deviation coefficient threshold as abnormal pipe segments. The deviation coefficient threshold is used to characterize the sensitivity of anomaly detection, and this application can adjust the deviation coefficient threshold according to actual application scenarios.

[0097] Step 303: Compare and analyze the real-time upstream and downstream pressure data of the abnormal pipe section with the normal upstream and downstream pressure data, as well as the real-time upstream and downstream flow data of the abnormal pipe section with the normal upstream and downstream flow data, to determine the fault mode corresponding to the abnormal pipe section.

[0098] For example, this application can distinguish between leakage and blockage faults by analyzing the pressure and flow deviation characteristics of abnormal pipe sections and utilizing the hydrodynamic differences between them. For instance, it can determine the corresponding fault mode by calculating the deviation between real-time pressure and flow and normal data and analyzing the distribution characteristics of the deviation.

[0099] Based on the above technical solution, this application can determine the healthy dynamic impedance data of the pipeline segment under various operating conditions based on the normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipeline segment under various operating conditions, and determine the real-time dynamic impedance data of the pipeline segment based on the real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipeline segment. Compared with the existing technology that judges faults based on a single, fixed pressure or flow threshold, dynamic impedance is an inherent property of the pipeline and is not affected by fluctuations in operating conditions. It only shows a systematic deviation when the pipeline experiences faults such as leakage or blockage. Therefore, the anomaly detection based on dynamic impedance is more accurate and effectively reduces the false alarm rate. At the same time, by further analyzing the characteristics of pressure and flow deviations, the fault mode can be accurately distinguished, providing a reliable basis for subsequent targeted positioning.

[0100] As one possible embodiment of this application, combined with Figure 3 ,like Figure 4 As shown, step 303 above can be achieved through the following steps:

[0101] Step 401: Based on the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data, determine the upstream pressure deviation value and downstream pressure deviation value at each time point within the target time window. Based on the real-time upstream and downstream flow data of the abnormal pipe section and the normal upstream and downstream flow data, determine the upstream flow deviation value and downstream flow deviation value at each time point within the target time window.

[0102] The target time window is a continuous time interval that includes the start time of the anomaly. Its length must be sufficient to capture the pressure and flow deviations caused by the fault, avoiding incomplete features due to a too-short time period or irrelevant interference due to a too-long time period. For example, the target time window can be denoted as... , This is the starting point of the anomaly. Set the preset analysis window duration, for example, it can be set to 30 seconds.

[0103] In some embodiments, this application may preprocess real-time data and normal data, for example, by first performing synchronization alignment processing (ensuring that real-time data and normal data correspond at the same time), and then using low-pass filtering for smoothing processing to eliminate noise interference and obtain a smooth data sequence.

[0104] For example, the upstream pressure deviation value satisfies the following formula:

[0105]

[0106] in, For abnormal pipe sections at a certain time point The upstream pressure deviation value, For real-time upstream and downstream pressure data of abnormal pipe sections at a specific time point Upstream pressure, For the normal upstream and downstream pressure data of the abnormal pipe section at the time point Upstream pressure.

[0107] The downstream pressure deviation value satisfies the following formula:

[0108]

[0109] in, For abnormal pipe sections at a certain time point Upstream and downstream pressure deviation values, For real-time upstream and downstream pressure data of abnormal pipe sections at a specific time point Upstream and downstream pressures, For the normal upstream and downstream pressure data of the abnormal pipe section at the time point Upstream and downstream pressures.

[0110] The upstream flow deviation value satisfies the following formula:

[0111]

[0112] in, For abnormal pipe sections at a certain time point Upstream flow deviation value, For real-time upstream and downstream flow data of abnormal pipe sections at a specific time point Upstream traffic, For the normal upstream and downstream flow data of the abnormal pipe section at the time point Upstream flow.

[0113] The downstream flow deviation value satisfies the following formula:

[0114]

[0115] in, For abnormal pipe sections at a certain time point Upstream and downstream flow deviation value For real-time upstream and downstream flow data of abnormal pipe sections at a specific time point Upstream and downstream flow For the normal upstream and downstream flow data of the abnormal pipe section at the time point Upstream and downstream flow.

[0116] Step 402: Determine the upstream deviation distribution characteristics of the abnormal pipe section based on the upstream pressure deviation value and upstream flow deviation value at each time point, and determine the downstream deviation distribution characteristics of the abnormal pipe section based on the downstream pressure deviation value and downstream flow deviation value at each time point.

[0117] Among them, the above deviation values ​​can reflect the degree of impact of the fault on pressure and flow rate, and the deviation distribution characteristics refer to the distribution pattern of the deviation values ​​at each time point, which is used to distinguish the differences between the two fault modes.

[0118] In some embodiments, the upstream deviation distribution characteristics include a first distribution ratio and a second distribution ratio.

[0119] The first distribution ratio is the percentage of time points within the target time window where the upstream pressure deviation is negative and the upstream flow deviation is positive, out of the total number of time points within the target time window. The second distribution ratio is the percentage of time points within the target time window where the upstream pressure deviation is positive and the upstream flow deviation is less than or equal to zero, out of the total number of time points within the target time window.

[0120] The downstream deviation distribution characteristics include the third distribution proportion.

[0121] The third distribution ratio is the proportion of the number of time points within the target time window where both the downstream pressure deviation and downstream flow deviation are negative to the total number of time points within the target time window.

[0122] For example, this application can also map the pressure deviation and flow deviation values ​​at each time point to a two-dimensional rectangular coordinate system, thereby intuitively reflecting the above-mentioned distribution characteristics. For instance, a two-dimensional rectangular coordinate system can be established with the pressure deviation value on the horizontal axis and the flow deviation value on the vertical axis, representing the time points within the target time window. The coordinates of the upstream deviation data points can be represented as ( , The coordinates of the downstream deviation data points can be represented as ( , The upstream and downstream deviation data points can be marked with different colors to generate a scatter plot. Based on the scatter plot, the proportions of the first, second, and third distributions are determined.

[0123] Step 403: Determine the fault mode corresponding to the abnormal pipe section based on the upstream and downstream deviation distribution characteristics of the abnormal pipe section.

[0124] It should be noted that existing solutions can typically only identify abnormal parameters, but struggle to distinguish fault modes, and the physical mechanisms and handling methods for different fault modes differ significantly. To accurately differentiate between leakage and blockage, two common fault modes in pump station pipelines, this application can effectively distinguish fault modes by analyzing the distribution characteristics of upstream and downstream pressure and flow deviations.

[0125] Leakage will create a new pressure relief point, resulting in a decrease in upstream pressure and a relative increase in flow, while both downstream pressure and flow will decrease significantly. Blockage will increase local resistance, causing upstream pressure to accumulate and increase, flow to be obstructed and reduced, and downstream pressure to decrease significantly.

[0126] Based on the constructed two-dimensional Cartesian coordinate system, the upstream deviation distribution characteristics can be characterized by the quadrant distribution and clustering patterns of upstream data points in the two-dimensional coordinate system, while the downstream deviation distribution characteristics can be characterized by the corresponding distribution patterns of downstream data points. For example, in a leakage fault, due to the negative pressure deviation and positive flow deviation upstream, upstream data points will concentrate in the second quadrant (i.e., , Due to negative pressure and flow deviations downstream, downstream data points will be concentrated in the third quadrant (i.e., , ).

[0127] In cases of blockage, due to positive pressure deviations and no or slight positive flow deviations upstream, upstream data points will be concentrated in the fourth quadrant or on the positive side of the horizontal axis. , Downstream data points will also be concentrated in the third quadrant (i.e., , ).

[0128] Thus, this application can determine the fault mode through the proportional threshold.

[0129] In one possible implementation, if the first distribution ratio is greater than or equal to the first preset threshold and the third distribution ratio is greater than or equal to the third preset threshold, the fault mode is determined to be a leakage fault; if the second distribution ratio is greater than or equal to the second preset threshold and the third distribution ratio is greater than or equal to the third preset threshold, the fault mode is determined to be a blockage fault.

[0130] For example, the first, second, and third preset thresholds can be set based on extensive experimental data and engineering practices, and they can be the same or different. For instance, they can all be set to 70%. These thresholds can also be adjusted according to the characteristics of the pipe section and maintenance requirements. For example, for pipe sections with high sensitivity requirements, the threshold can be reduced to 60%.

[0131] Based on the above technical solution, this application can accurately distinguish between two fault modes by analyzing the two-dimensional distribution characteristics of pressure and flow deviations and utilizing the essential differences in the fluid dynamics of leakage and blockage faults. Compared to the shortcomings of traditional methods that cannot identify fault modes, the deviation distribution characteristic analysis of this application can capture subtle parameter changes caused by faults. Even for early, slowly changing faults, the fault type can be clearly identified through the differences in deviation distribution patterns, providing a key basis for subsequent targeted fault location and further improving the comprehensiveness and reliability of fault diagnosis.

[0132] Furthermore, when fault characteristics are not significant enough within the aforementioned target time window, the reliability of pattern discrimination based directly on distribution characteristics will decrease. Therefore, this application can also adjust the window range of the target time window to capture more complete transient fault characteristics, thereby ensuring the reliability of fault mode discrimination.

[0133] As one possible embodiment of this application, combined with Figure 4 ,like Figure 5 As shown, the method also includes the following steps:

[0134] Step 501: If the fault mode corresponding to the abnormal pipe segment cannot be determined based on the upstream and downstream deviation distribution characteristics of the abnormal pipe segment, repeat the fault mode determination operation until the preset number of executions is reached.

[0135] The fault mode determination operation includes: redetermining the window range of the target time window, and determining the fault mode corresponding to the abnormal pipe segment according to the redetermined target time window. The window range of the redetermined target time window is larger than the window range of the previously redetermined target time window.

[0136] For example, "fault mode not determined" means that the conditions for judging the two fault modes mentioned above are not met. That is, neither "the first distribution ratio is greater than or equal to the first preset threshold and the third distribution ratio is greater than or equal to the third preset threshold" nor "the second distribution ratio is greater than or equal to the second preset threshold and the third distribution ratio is greater than or equal to the third preset threshold" are met. This situation usually occurs in the early stage of the fault, when the fault characteristics are not obvious, or when there is slight interference.

[0137] For example, this application can obtain more comprehensive dynamic data by extending the window range of the target time window used for analysis, thereby capturing more complete transient characteristics of the fault. For instance, the adjusted target time window can be denoted as... , This is the starting point of the anomaly. This is the preset analysis window duration. After extending the actual target window, this application can re-perform the fault mode determination through steps 401-403 above. The preset number of times can be set to 2, meaning the time window can be extended a maximum of 2 times.

[0138] In addition, if the judgment criteria are still not met, this application may also use other methods to assist in the judgment, so as to avoid increased interference due to an excessively long window.

[0139] As one possible embodiment of this application, combined with Figure 4 ,like Figure 5 As shown, the method also includes the following steps:

[0140] Step 502: When the number of executions reaches the preset number, determine the upstream pressure abnormality time point and the downstream pressure abnormality time point of the abnormal pipe section based on the upstream pressure deviation value and the downstream pressure deviation value at each time point within the target time window.

[0141] It should be noted that in a leakage fault, the leak point forms a new pressure relief port, and the pressure drop wave propagates downstream from the leak point first. Therefore, downstream sensors will detect the pressure anomaly earlier (i.e., the downstream pressure anomaly occurs earlier than the upstream). In a blockage fault, the blockage point increases local resistance, and the pressure rise wave feeds back upstream from the blockage point first. Therefore, upstream sensors will detect the pressure anomaly earlier (i.e., the upstream pressure anomaly occurs earlier than the downstream).

[0142] For example, this application can, based on the upstream and downstream pressure deviation values ​​at each time point within a target time window, designate the first time point in which the upstream pressure deviation value and the downstream pressure deviation value continuously exceed a pressure threshold as the upstream pressure anomaly time point and the downstream pressure anomaly time point, respectively. This pressure threshold can be determined using corresponding normal pressure data, for example, it can be twice the standard deviation of the corresponding normal pressure data.

[0143] Step 503: If the upstream pressure anomaly time point is after the downstream pressure anomaly time point, determine the fault mode as a leakage fault.

[0144] Step 504: If the upstream pressure anomaly occurs before the downstream pressure anomaly, the fault mode is determined to be a blockage fault.

[0145] Based on the above technical solutions, this application addresses the problem of difficulty in determining fault modes when fault characteristics are not significant by employing a time window extension mechanism and timing logic-assisted judgment. Extending the time window allows for the acquisition of more complete dynamic fault characteristics, making the distribution ratio more reflective of the fault's essence. The timing logic utilizes the physical propagation laws of the two types of faults to provide a judgment path independent of deviation distribution characteristics, ensuring accurate fault mode identification even in complex interference scenarios. The introduction of supplementary mechanisms enhances the robustness and adaptability of the method, enabling fault mode recognition to cover more practical working conditions.

[0146] As one possible embodiment of this application, combined with Figure 2 ,like Figure 6 As shown, step 203 above can be achieved through the following steps:

[0147] Step 601: Based on the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding operating conditions, calculate the upstream pressure deviation amplitude and downstream pressure deviation amplitude of the abnormal pipe section.

[0148] The upstream pressure deviation amplitude is determined based on the absolute value of the upstream pressure deviation at each time point within the target time window, while the downstream pressure deviation amplitude is determined based on the absolute value of the downstream pressure deviation at each time point within the target time window.

[0149] For example, the upstream pressure deviation magnitude satisfies the following formula:

[0150]

[0151] in, This represents the upstream pressure deviation amplitude of the abnormal pipe section. For the target time window The number of time points in the data. For abnormal pipe sections at a certain time point The absolute value of the upstream pressure deviation. For abnormal pipe sections at a certain time point The upstream pressure deviation value. The magnitude of the upstream pressure deviation characterizes the average degree to which the upstream pressure is affected by the fault.

[0152] The downstream pressure deviation magnitude satisfies the following formula:

[0153]

[0154] in, This represents the downstream pressure deviation of the abnormal pipe section. For the target time window The number of time points in the data. For abnormal pipe sections at a certain time point The absolute value of the upstream and downstream pressure deviation For abnormal pipe sections at a certain time point The downstream pressure deviation value. The magnitude of the downstream pressure deviation characterizes the average degree to which the downstream pressure is affected by the fault.

[0155] This application eliminates the interference of instantaneous fluctuations by taking the arithmetic mean of the absolute values ​​of pressure deviations within the target time window, highlighting the steady-state pressure change characteristics caused by the fault, and enabling the deviation amplitude to accurately reflect the degree of impact of the fault on the upstream and downstream pressures.

[0156] Step 602: For abnormal pipe sections with leakage fault mode, determine the distance between the fault point and the upstream of the abnormal pipe section based on the proportion of the downstream pressure deviation amplitude to the total amplitude of the upstream and downstream pressure deviation amplitudes, and the length of the abnormal pipe section.

[0157] In leakage faults, the closer the sensor is to the leak point, the greater the pressure drop. Therefore, the proportion of the upstream pressure deviation in the total deviation is negatively correlated with the distance from the fault point to the upstream, while the proportion of the downstream pressure deviation in the total deviation is positively correlated with the distance from the fault point to the upstream. The proportion of the downstream pressure deviation in the total deviation reflects whether the fault point is closer to the upstream or downstream. The larger this proportion is, the farther the fault point is from the upstream sensor. The accurate distance to the fault point can be calculated by combining the pipe section length.

[0158] For example, the distance between the fault point and the upstream of the abnormal pipe section satisfies the following formula:

[0159]

[0160] in, This represents the distance between the fault point and the upstream of the abnormal pipe section during a leakage fault. The length of the abnormal pipe section. This represents the upstream pressure deviation amplitude of the abnormal pipe section. This represents the downstream pressure deviation of the abnormal pipe section.

[0161] Step 603: For abnormal pipe sections with a blockage fault mode, determine the distance between the fault point and the upstream of the abnormal pipe section based on the ratio of the upstream pressure deviation amplitude to the downstream pressure deviation amplitude and the length of the abnormal pipe section.

[0162] In a blockage failure, the blockage point causes an increase in upstream pressure and a decrease in downstream pressure. The closer the blockage point is to the upstream of the pipe segment, the more significant the increase in upstream pressure and the weaker the decrease in downstream pressure; that is, the larger the ratio of the upstream deviation to the downstream deviation. Conversely, the smaller this ratio, the closer the blockage point is to the downstream.

[0163] For example, the distance between the fault point and the upstream of the abnormal pipe section satisfies the following formula:

[0164]

[0165] in, This refers to the distance between the fault point and the upstream of the abnormal pipe section when a blockage occurs. The length of the abnormal pipe section. This represents the upstream pressure deviation amplitude of the abnormal pipe section. This represents the downstream pressure deviation of the abnormal pipe section. The adjustment coefficient can be determined based on historical data statistical analysis; for example, it can be initially set to 1. When the blockage point is very close to the upstream, the upstream pressure deviation is greater than the downstream pressure deviation. Approaching infinity It is close to 0.

[0166] Based on the above technical solution, this application quantifies the impact of a fault on upstream and downstream pressure by measuring the pressure deviation amplitude. Furthermore, based on the pressure distribution patterns of the two types of faults, a targeted fault location calculation method is determined, achieving precise quantification of the fault location. Compared to traditional methods that can only determine the approximate location of anomalies, the solution in this application provides accurate fault location distance information, enabling maintenance personnel to directly access the fault location for repairs, significantly shortening troubleshooting time and improving fault handling efficiency.

[0167] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0168] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for quickly locating pipeline faults of a pump station house, characterized in that, The method comprises: acquiring normal operation data of a plurality of pipe sections in a pump station house pipeline, and collecting real-time operation data of the plurality of pipe sections in real time; the normal operation data comprises normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe sections under various working conditions; the real-time operation data comprises real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe sections; performing anomaly detection on the real-time operation data and the normal operation data of the plurality of pipe sections, identifying an abnormal pipe section in the plurality of pipe sections and a fault mode corresponding to the abnormal pipe section; the fault mode comprises a leakage fault and a blockage fault; based on the fault mode corresponding to the abnormal pipe section, performing fault positioning on the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding working condition, to determine a fault point position, comprising: calculating an upstream pressure deviation amplitude and a downstream pressure deviation amplitude of the abnormal pipe section according to the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding working condition; wherein the upstream pressure deviation amplitude is determined based on the absolute value of the upstream pressure deviation at each time point within a target time window, and the downstream pressure deviation amplitude is determined based on the absolute value of the downstream pressure deviation at each time point within the target time window; for the abnormal pipe section with the fault mode of the leakage fault, determining the distance between the fault point and the upstream of the abnormal pipe section according to the proportion of the downstream pressure deviation amplitude in the total amplitude of the upstream pressure deviation amplitude and the downstream pressure deviation amplitude, and the pipe section length of the abnormal pipe section; for the abnormal pipe section with the fault mode of the blockage fault, determining the distance between the fault point and the upstream of the abnormal pipe section according to the ratio of the upstream pressure deviation amplitude to the downstream pressure deviation amplitude, and the pipe section length of the abnormal pipe section.

2. The method for quick positioning of pipeline faults of pump station house according to claim 1, characterized in that, performing anomaly detection on the real-time operation data and the normal operation data of the plurality of pipe sections, identifying an abnormal pipe section in the plurality of pipe sections and a fault mode corresponding to the abnormal pipe section, comprising: for each pipe section, determining health dynamic impedance data of the pipe section under various working conditions according to the normal upstream and downstream pressure data and the normal upstream and downstream flow data of the pipe section under various working conditions, and determining real-time dynamic impedance data of the pipe section according to the real-time upstream and downstream pressure data and the real-time upstream and downstream flow data of the pipe section; comparing and analyzing the real-time dynamic impedance data of each pipe section and the health dynamic impedance data of the corresponding working condition, to identify the abnormal pipe section in the plurality of pipe sections; comparing and analyzing the real-time upstream and downstream pressure data and the normal upstream and downstream pressure data of the abnormal pipe section, and the real-time upstream and downstream flow data and the normal upstream and downstream flow data of the abnormal pipe section, to determine the fault mode corresponding to the abnormal pipe section.

3. The method for quick positioning of pipeline fault of pump station house according to claim 2, characterized in that, comparing and analyzing the real-time dynamic impedance data of each pipe section and the health dynamic impedance data of the corresponding working condition, to identify the abnormal pipe section in the plurality of pipe sections, comprising: For each pipe section, a deviation coefficient of the pipe section is determined according to real-time dynamic impedance data of the pipe section and healthy dynamic impedance data corresponding to a working condition of the pipe section; the deviation coefficient is used to represent a deviation degree of the real-time dynamic impedance data compared with the healthy dynamic impedance data; An abnormal pipe section is identified from the deviation coefficients of the plurality of pipe sections.

4. The method for quick positioning of pipeline fault of pump station house according to claim 2, characterized in that, Real-time upstream and downstream pressure data of the abnormal pipe section and normal upstream and downstream pressure data, and real-time upstream and downstream flow data of the abnormal pipe section and normal upstream and downstream flow data are compared and analyzed to determine a fault mode corresponding to the abnormal pipe section, including: Upstream pressure deviation values and downstream pressure deviation values at each time point within a target time window are determined based on the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data, and upstream flow deviation values and downstream flow deviation values at each time point within the target time window are determined based on the real-time upstream and downstream flow data of the abnormal pipe section and the normal upstream and downstream flow data; Upstream deviation distribution characteristics of the abnormal pipe section are determined based on the upstream pressure deviation values and the upstream flow deviation values at each time point, and downstream deviation distribution characteristics of the abnormal pipe section are determined based on the downstream pressure deviation values and the downstream flow deviation values at each time point; The fault mode corresponding to the abnormal pipe section is determined based on the upstream deviation distribution characteristics and the downstream deviation distribution characteristics of the abnormal pipe section.

5. The method for quick positioning of pipeline faults of pump station house according to claim 4, characterized in that, The upstream deviation distribution characteristics include a first distribution ratio and a second distribution ratio; The first distribution ratio is a proportion of a number of time points within the target time window at which the upstream pressure deviation value is negative and the upstream flow deviation value is positive to a total number of time points within the target time window, and the second distribution ratio is a proportion of a number of time points within the target time window at which the upstream pressure deviation value is positive and the upstream flow deviation value is less than or equal to zero to the total number of time points within the target time window; The downstream deviation distribution characteristics include a third distribution ratio; The third distribution ratio is a proportion of a number of time points within the target time window at which the downstream pressure deviation value is negative and the downstream flow deviation value is negative to the total number of time points within the target time window.

6. The method for quick positioning of pipeline faults of pump station house according to claim 5, characterized in that, The fault mode corresponding to the abnormal pipe section is determined based on the upstream deviation distribution characteristics and the downstream deviation distribution characteristics of the abnormal pipe section, including: In a case where the first distribution ratio is greater than or equal to a first preset threshold and the third distribution ratio is greater than or equal to a third preset threshold, it is determined that the fault mode is a leakage fault; In a case where the second distribution ratio is greater than or equal to a second preset threshold and the third distribution ratio is greater than or equal to the third preset threshold, it is determined that the fault mode is a blockage fault.

7. The method for quick positioning of pipeline faults of pump station house according to claim 4, characterized in that, The method further includes: In a case where the fault mode corresponding to the abnormal pipe section is not determined based on the upstream deviation distribution characteristics and the downstream deviation distribution characteristics of the abnormal pipe section, a fault mode determination operation is repeatedly performed until a preset number of times is reached; The fault mode determination operation includes: re-determining a window range of a target time window, and determining the fault mode corresponding to the abnormal pipe section according to the re-determined target time window.

8. The method for quick positioning of pipeline faults of pump station house according to claim 7, characterized in that, The method further comprises: in the case where the execution times reach a preset number, determining an upstream pressure abnormal time point and a downstream pressure abnormal time point of the abnormal pipe section according to the upstream pressure deviation value and the downstream pressure deviation value at each time point within the target time window; in the case where the upstream pressure abnormal time point is located after the downstream pressure abnormal time point, determining that the fault mode is a leakage fault; in the case where the upstream pressure abnormal time point is located before the downstream pressure abnormal time point, determining that the fault mode is a blockage fault.

9. A system for rapid pump station house pipeline fault location, comprising: Comprise: a data acquisition module, configured to acquire normal operation data of a plurality of pipe sections in a pump station house pipeline, and collect real-time operation data of the plurality of pipe sections in real time; the normal operation data comprises normal upstream and downstream pressure data and normal upstream and downstream flow data of the pipe sections under each working condition; the real-time operation data comprises real-time upstream and downstream pressure data and real-time upstream and downstream flow data of the pipe sections; an anomaly detection module, configured to perform anomaly detection according to the real-time operation data and the normal operation data of the plurality of pipe sections, identify an abnormal pipe section in the plurality of pipe sections and a fault mode corresponding to the abnormal pipe section; the fault mode comprises a leakage fault and a blockage fault; a fault positioning module, configured to perform fault positioning according to the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding working condition based on the fault mode corresponding to the abnormal pipe section, and determine a fault point position, comprising: calculating an upstream pressure deviation amplitude and a downstream pressure deviation amplitude of the abnormal pipe section according to the real-time upstream and downstream pressure data of the abnormal pipe section and the normal upstream and downstream pressure data under the corresponding working condition; wherein the upstream pressure deviation amplitude is determined based on the absolute value of the upstream pressure deviation at each time point within a target time window, and the downstream pressure deviation amplitude is determined based on the absolute value of the downstream pressure deviation at each time point within the target time window; for the abnormal pipe section with the fault mode of the leakage fault, determining the distance between the fault point and the upstream of the abnormal pipe section according to the proportion of the downstream pressure deviation amplitude in the total amplitude of the upstream pressure deviation amplitude and the downstream pressure deviation amplitude, and the pipe section length of the abnormal pipe section; for the abnormal pipe section with the fault mode of the blockage fault, determining the distance between the fault point and the upstream of the abnormal pipe section according to the ratio of the upstream pressure deviation amplitude to the downstream pressure deviation amplitude, and the pipe section length of the abnormal pipe section.

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