A water system fault locating method and device

Abstract

The application discloses a kind of water affair system fault location method and device, method includes: according to water affair node operating state monitoring information and preset water affair operating state parameter calculation model, water affair operating state parameter information is calculated;Based on the preset water affair system fault location model, according to water affair operating state parameter information is screened and analyzed calculation, obtains water affair system fault location information.This method and device can realize the global perception of the operation of each node of water affair system, avoid the fault of missing monitoring information caused by missing, can quickly locate the fault from complex parameter information, greatly improve the precision and efficiency of water affair system fault location, effectively shorten the time of troubleshooting, reduce the waste of water resources, water supply service interruption and other problems caused by failure to locate in time.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a method and apparatus for locating faults in a water system. Background Technology

[0002] As a core urban infrastructure, the intelligent upgrading of urban water systems has become a core trend in the industry. The system is gradually evolving from the traditional manual inspection mode to an intelligent monitoring and operation mode that integrates IoT, big data, and 5G communication technologies. However, the wide coverage, numerous nodes, and complex operating status of water networks still pose many technical challenges to the implementation of intelligent water technology.

[0003] In existing technologies, basic monitoring data such as water pressure and water volume at water nodes are mostly obtained based on online monitoring equipment. Data collection and simple processing are completed by relying on a preliminarily established data management platform. Some solutions combine 5G communication technology to improve the transmission efficiency of monitoring data. Other solutions use technologies such as pipeline endoscopy and acoustic detection to detect faults at local water nodes. At the same time, SCADA, BIM, GIS and other systems are used to assist in the analysis of water operation data, thereby attempting to achieve the identification and location of faults in the water system.

[0004] However, existing technologies suffer from incomplete monitoring data coverage, blind spots in monitoring the health status of some key equipment, difficulty in effectively integrating multi-source monitoring data to form data barriers, insufficient value mining of massive, real-time, and multi-dimensional water operation data, inadequate intelligent analysis capabilities, reliance on manual experience or single data sources for fault diagnosis, weak ability to identify early, hidden, and complex faults, low fault location accuracy and long processing time, slow emergency response speed, and insufficient real-time remote monitoring data, making it difficult to achieve rapid and accurate determination of water system faults. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the prior art by providing a method and apparatus for locating faults in water systems.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: Firstly, a method for locating faults in a water system includes the following steps: Obtain operational status monitoring information from multiple water management nodes; Based on the monitoring information of the operation status of multiple water affairs nodes and multiple preset calculation models of water affairs operation status parameters, multiple water affairs operation status parameter information are calculated. Based on a pre-set water system fault location model, multiple water system fault location information is obtained by filtering and analyzing multiple water system operation status parameters.

[0007] Furthermore, the water node operation status monitoring information includes one-to-one corresponding water node monitoring spatial identification information, water node monitoring time identification information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information; Based on the water node operation status feature extraction rules, spatiotemporal features are extracted according to the water node monitoring spatial identifier information, water node monitoring time identifier information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information to generate water pressure status feature information, water quantity status feature information, water quality status feature information, and water pump operation status feature information. Based on the generated water pressure status characteristic information, water quantity status characteristic information, water quality status characteristic information, water pump operation status characteristic information, and the water operation status parameter calculation model, the water operation status parameter information is calculated.

[0008] Furthermore, the steps for calculating water system fault location information include: fitting a coordinate system based on preset water system fault parameters. Based on the water pressure status parameter information, the preset water pressure fault parameter threshold information, and the preset water pressure fault parameter identification weight information, the water pressure fault parameter variable is calculated. Based on the water volume status parameter information, the preset water volume fault parameter threshold information, and the preset water volume fault parameter identification weight information, the water volume fault parameter variable is calculated. Based on the water quality status parameter information, the preset water quality anomaly parameter threshold information, and the preset water quality anomaly parameter identification weight information, the water quality anomaly parameter variable is calculated. Based on the pump operating status parameter information, the preset pump operating fault parameter threshold information, and the preset pump operating fault parameter identification weight information, the pump fault parameter variables are obtained. Based on the water system fault location model, the water system fault location information is calculated according to the water pressure fault parameter variables, the water quantity fault parameter variables, the water quality anomaly parameter variables, and the water pump fault parameter variables.

[0009] Furthermore, the specific steps for calculating the water pressure fault parameter variables include: Based on the coordinate system fitted to the fault parameters of the water system, a time-series fitting calculation is performed according to the water pressure state parameter information to generate a water pressure state parameter change curve. Based on the water pressure state parameter change curve and the preset water pressure fault parameter benchmark fitting straight line, the intersection information of the water pressure state parameter curve is obtained; The difference between the intersection points of the water pressure state parameter curves is calculated to obtain the water pressure fault representation variable; The water pressure fault parameter variable is calculated based on the water pressure fault representation variable, the water pressure fault parameter threshold information, and the water pressure fault parameter identification weight information.

[0010] Furthermore, based on the water pressure fault representation variable and the preset water pressure fault parameter benchmark value, water pressure fault parameter judgment information is calculated; Determine whether the water pressure fault parameter determination information is greater than or equal to the preset water pressure fault parameter threshold information; If so, the water pressure fault parameter identification weight information is used to weight the water pressure state parameter information corresponding to the water pressure fault parameter determination information to calculate the water pressure fault parameter variable. If not, then the water pressure fault parameter penalty value information is calculated based on the water pressure state parameter information, water pressure fault parameter threshold information, and preset water pressure fault parameter penalty factor corresponding to the water pressure fault parameter determination information; the water pressure fault parameter variable is calculated based on the water pressure state parameter information, water pressure fault parameter penalty value information, and preset water pressure fault parameter identification weight information corresponding to the water pressure fault parameter determination information.

[0011] Furthermore, the pump operating status parameter information includes pump speed parameter information, pump power parameter information, pump vibration frequency parameter information, and pump inlet and outlet pressure difference parameter information. The specific steps for calculating the parameters of a water pump failure include: The pump speed parameter information, pump power parameter information, pump vibration frequency parameter information, and pump inlet and outlet pressure difference parameter information are normalized to obtain normalized information of each parameter. Based on the identified weight information of the pump operation fault parameters, these normalized information are weighted and summed to calculate the pump operation fault discrimination variable. The pump fault parameter variables are obtained by calculating the difference between the pump operation fault discrimination variable and the pump operation fault parameter threshold information.

[0012] Furthermore, after obtaining multiple water system fault location information steps, the process also includes: The water system fault location information is processed by feature extraction to obtain water system fault feature information; Based on the preset mapping relationship between water system fault characteristic information and water system fault early warning level, water system fault early warning level information is generated according to the obtained water system fault characteristic information. Based on the pre-defined mapping relationship between water system fault characteristic information and water system fault handling strategies, water system fault handling strategy information is generated according to the obtained water system fault characteristic information. Based on the water system fault warning level information and the water system fault handling strategy information, water system fault handling information is generated.

[0013] Secondly, a water system fault location device is provided for implementing the water system fault location method described above. The device includes: The water affairs node operation status monitoring information acquisition module is used to acquire the operation status monitoring information of multiple water affairs nodes; The water affairs operation status parameter information generation module is used to calculate multiple water affairs operation status parameter information based on the operation status monitoring information of multiple water affairs nodes and multiple preset water affairs operation status parameter calculation models; The water system fault location information generation module is used to obtain multiple water system fault location information by filtering and analyzing multiple water system operation status parameters based on a preset water system fault location model.

[0014] Thirdly, an electronic device is provided, the electronic device including at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the water system fault location method as described above.

[0015] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, characterized in that, when the program is executed by a processor, it implements the water system fault location method as described above.

[0016] Compared with existing technologies, the beneficial effects of this invention are: 1. This water system fault location method can achieve full-domain perception of the operation status of each node in the water system, avoiding missed fault detection due to missing monitoring information. It can quickly locate the fault from complex parameter information, significantly improving the accuracy and efficiency of water system fault location, effectively shortening the fault investigation time, and reducing problems such as water resource waste and water supply service interruption caused by failure to locate faults in a timely manner; 2. It realizes multi-dimensional comprehensive judgment of water system faults, effectively improving the accuracy and efficiency of fault location, and can quickly identify early, hidden, and complex water system faults, providing a comprehensive solution for water management. 3. Provides precise technical support for timely handling of system faults; 4. Weighted processing is applied to those meeting the standards to highlight the severity of the fault, while those not meeting the standards are penalized and calibrated using preset water pressure fault parameter penalty factors, enhancing the pertinence and accuracy of water pressure fault parameter variable calculations and effectively avoiding interference from slight water pressure fluctuations on fault location results; 5. Achieves full-process coverage from fault location to fault warning and fault handling, solving the problem of lack of standardized warnings and targeted handling guidelines after fault location in existing technologies, improving the efficiency and standardization of water system fault handling, making it easier for operation and maintenance personnel to distinguish the urgency of faults, prioritize the handling of severe faults, and reduce losses caused by the spread of faults. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall process of a water system fault location method according to the present invention; Figure 2 This is a flowchart illustrating the calculation of water system operation status parameter information in the water system fault location method of the present invention; Figure 3 This is a flowchart illustrating step 3 of the water system fault location method of the present invention. Figure 4 This is a flowchart of step 301 in the water system fault location method of the present invention; Figure 5 This is a flowchart of the fourth step in step 301 of the water system fault location method of the present invention; Figure 6 This is a flowchart of step 304 in the water system fault location method of the present invention; Figure 7 This is a flowchart of the further processing after step 103 in the water system fault location method of the present invention; Figure 8 This is a schematic diagram of a water system fault location device according to the present invention; Figure 9 This is a schematic diagram of the terminal device provided in an embodiment of the present invention; In the diagram: 810, Water Node Operation Status Monitoring Information Acquisition Module; 820, Water Operation Status Parameter Information Generation Module; 830, Water System Fault Location Information Generation Module; 9, Terminal Equipment; 90, Processor; 91, Memory; 92, Computer Program. Detailed Implementation

[0018] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: A method for locating faults in a water system is provided, such as... Figure 1 As shown, it includes the following steps: Step 1: Obtain operational status monitoring information from multiple water management nodes; In this step, the water node operation status monitoring information includes water node monitoring spatial identification information, water node monitoring time identification information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information. Among them, the water node monitoring spatial identification information, water node monitoring time identification information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information are all one-to-one correspondences.

[0020] The operational status monitoring information of these water management nodes can be collected through online monitoring equipment deployed at key nodes of the water management system. This includes water pressure sensors, flow meters, water quality analyzers, pump operation status monitors, spatial positioning modules, and time synchronization modules. Each monitoring device continuously collects corresponding data according to a preset collection frequency. The collected monitoring data is then initially integrated to ensure that the spatial and temporal identifiers in each set of water management node operational status monitoring information match the various operational status data. The integrated monitoring information is then transmitted to a data processing terminal via IoT communication technology, thereby obtaining operational status monitoring information covering multiple water management nodes across the entire water management system. The collection frequency and the deployment location of the monitoring equipment can be preset to adapt to the monitoring needs of water management systems of different sizes, ensuring the comprehensiveness and timeliness of the monitoring information.

[0021] Step 2: Based on the monitoring information of multiple water affairs nodes and multiple preset water affairs operation status parameter calculation models, calculate multiple water affairs operation status parameter information; In this step, the preset water operation status parameter calculation model can be pre-set by humans. It can be a trained deep learning model with a multi-layer network structure. The number of neurons in the input layer is consistent with the types of parameters in the water node operation status monitoring information. The number of neurons in the hidden layer is reasonably set according to the complexity of the actual water monitoring data. The activation function is a function suitable for nonlinear fitting of water data. It is trained through a large amount of historical monitoring data and fault case data of the water system, and can learn the nonlinear relationship between the water node operation status monitoring information and the water operation status parameter information.

[0022] First, the acquired water management node operation status monitoring information is preprocessed to remove abnormal data and supplement missing data. Standardization is used to eliminate dimensional differences between various monitoring information types, ensuring data consistency and usability. Then, based on preset water management node operation status feature extraction rules, spatiotemporal features are extracted from multiple water management node monitoring spatial identifiers, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information. This generates multiple water pressure status feature information, multiple water quantity status feature information, multiple water quality status feature information, and multiple water pump operation status feature information. These feature information are then input into multiple preset water management operation status parameter calculation models. Through model calculation and processing, multiple water management operation status parameter information is generated. The water management operation status parameter information includes water pressure status parameter information, water quantity status parameter information, water quality status parameter information, and water pump operation status parameter information. The preset water management node operation status feature extraction rules can be manually preset and can accurately extract key features from various monitoring information types, providing reliable data support for subsequent parameter calculations.

[0023] Step 3: Based on the preset water system fault location model, filter and analyze multiple water system operation status parameters to obtain multiple water system fault location information; In this step, the pre-designed water system fault location model is designed based on a combination of deep learning and fault diagnosis algorithms, enabling efficient screening and accurate analysis of multiple water system operation status parameters. First, based on the degree of matching between multiple water system operation status parameters and preset thresholds, parameters showing anomalies are screened from the multiple water system operation status parameters. These screening thresholds can be manually preset. Then, further analysis and calculations are performed on these anomaly-prone water system operation status parameters.

[0024] Specifically, based on a preset water system fault parameter fitting coordinate system, multiple water pressure fault parameter variables are calculated using multiple water pressure status parameters, preset water pressure fault parameter thresholds, and preset water pressure fault parameter identification weights. Then, based on this coordinate system, multiple water volume fault parameter variables are calculated using multiple water flow status parameters, preset water flow fault parameter thresholds, and preset water flow fault parameter identification weights. Simultaneously, based on this coordinate system, multiple water quality anomaly parameter variables are calculated using multiple water quality status parameters, preset water quality anomaly parameter thresholds, and preset water quality anomaly parameter identification weights. Then, multiple water pump fault parameter variables are calculated using multiple water pump operating status parameters, preset water pump operating fault parameter thresholds, and preset water pump operating fault parameter identification weights. All of these fault parameter variables are then input into a preset water system fault location model. Through comprehensive analytical calculation by the model, the fault type, fault location, and fault severity are accurately identified, finally generating multiple water system fault location information. Among them, the preset water pressure fault parameter threshold information, preset water pressure fault parameter identification weight information, preset water volume fault parameter threshold information, preset water volume fault parameter identification weight information, preset water quality anomaly parameter threshold information, preset water quality anomaly parameter identification weight information, preset water pump operation fault parameter threshold information, and preset water pump operation fault parameter identification weight information can all be preset manually and can be flexibly adjusted according to the actual operation of the water system to ensure the accuracy of fault location.

[0025] The water system fault location method provided in this application, through the above-mentioned steps, can solve the problems of low accuracy and low efficiency in existing water system fault location, ensure the comprehensiveness and integrity of monitoring data, significantly improve the accuracy and efficiency of water system fault location, effectively shorten the fault investigation time, and reduce water resource waste and water supply interruption caused by faults.

[0026] Furthermore, such as Figure 2 As shown, in step 1, based on the preset water node operation status feature extraction rules, spatiotemporal features are extracted according to multiple water node monitoring spatial identification information, multiple water node monitoring time identification information, multiple water pressure status monitoring information, multiple water quantity status monitoring information, multiple water quality status monitoring information, and multiple water pump operation status monitoring information, generating multiple water pressure status feature information, multiple water quantity status feature information, multiple water quality status feature information, and multiple water pump operation status feature information.

[0027] The aforementioned pre-defined rules for extracting the operational status features of water management nodes are formulated in conjunction with the spatiotemporal characteristics of water management system operation. They can simultaneously extract spatial correlation features and temporal change features from monitoring information. First, the spatial identification information of multiple water management nodes is analyzed to clarify the spatial location relationships between each node. Then, the temporal identification information of multiple water management nodes is sequentially analyzed, integrating various operational status monitoring information of the same water management node at different times. Next, the spatial location relationships and temporal monitoring information are merged. For multiple water pressure status monitoring information, multiple water quantity status monitoring information, multiple water quality status monitoring information, and multiple water pump operational status monitoring information, key features such as abnormal fluctuation features, trend change features, and threshold deviation features are extracted. Then, the extracted features are classified and integrated according to a pre-defined feature dimension classification standard, thereby generating multiple clearly defined and characteristic water pressure status feature information, multiple water quantity status feature information, multiple water quality status feature information, and multiple water pump operational status feature information. Each type of feature information maintains a one-to-one correspondence with the corresponding water management node monitoring spatial identification information and water management node monitoring temporal identification information, ensuring the traceability of the feature information.

[0028] Furthermore, in step 2, multiple water operation status parameter information is calculated based on multiple water pressure status characteristic information, multiple water quantity status characteristic information, multiple water quality status characteristic information, multiple water pump operation status characteristic information, and multiple preset water operation status parameter calculation models.

[0029] In this step, multiple preset water system operation status parameter calculation models are dedicated calculation models built for different operating states of the water system. These include water pressure status parameter calculation models, water quantity status parameter calculation models, water quality status parameter calculation models, and pump operation status parameter calculation models. Multiple water pressure status feature information can be input into the preset water pressure status parameter calculation model, multiple water quantity status feature information into the preset water quantity status parameter calculation model, multiple water quality status feature information into the preset water quality status parameter calculation model, and multiple pump operation status feature information into the preset water... The pump operation status parameter calculation model then performs quantitative analysis, nonlinear fitting, and parameter conversion on the input feature information of each model. The calculation results of each model are then validated to remove invalid calculation results that do not conform to the operation law of the water system. The validated valid results are then integrated according to the spatial and temporal identifiers of the water nodes to generate multiple water pressure status parameter information, water quantity status parameter information, water quality status parameter information, and pump operation status parameter information that correspond one-to-one with the water nodes. All kinds of water operation status parameter information can accurately reflect the actual operating conditions of the corresponding water nodes.

[0030] This step enables the precise extraction of spatiotemporal features from water node operation status monitoring information, eliminates redundant data in the monitoring information, retains key features with fault identification value, and enables the feature information to be efficiently transformed into water operation status parameter information that accurately reflects the operating conditions of water nodes. This lays a data foundation for the accuracy of subsequent fault location and significantly reduces the data processing cost of subsequent fault location analysis and calculation.

[0031] Furthermore, in step 3, the water supply operation status parameter information includes water pressure status parameter information, water quantity status parameter information, water quality status parameter information, and water pump operation status parameter information. For example... Figure 3 As shown, step 3 specifically includes the following sub-steps: Step 301: Based on the preset water system fault parameter fitting coordinate system, and according to multiple water pressure state parameter information, preset water pressure fault parameter threshold information, and preset water pressure fault parameter identification weight information, calculate multiple water pressure fault parameter variables.

[0032] In this step, a preset coordinate system for fitting water system fault parameters is used, with monitoring time as the horizontal axis and water pressure status parameters as the vertical axis. Multiple water pressure status parameters are first mapped to this coordinate system according to their corresponding monitoring times. Then, curve fitting is performed on the mapped water pressure status parameter data to generate a water pressure status parameter change curve. This curve is then compared with preset water pressure fault parameter threshold information to identify abnormal data segments that exceed the threshold range. Furthermore, combined with preset water pressure fault parameter identification weight information, the degree of parameter deviation in the abnormal data segments is weighted and quantified. Based on the quantification results and the normal fluctuation range of the water pressure status parameters, multiple water pressure fault parameter variables that reflect the degree and trend of water pressure faults are calculated. Each water pressure fault parameter variable corresponds to the abnormal water pressure state of a specific water node.

[0033] Step 302: Based on the preset water system fault parameter fitting coordinate system, and according to multiple water state parameter information, preset water fault parameter threshold information, and preset water fault parameter identification weight information, multiple water fault parameter variables are calculated.

[0034] Similarly, in this step, a preset coordinate system for fitting water system fault parameters is used, with monitoring time as the horizontal axis and water volume status parameters as the vertical axis. Multiple water volume status parameters can be mapped onto this coordinate system according to their corresponding monitoring times. Then, curve fitting is performed on the mapped water volume status parameter data to generate a water volume status parameter change curve. This curve is then compared point by point with the preset water volume fault parameter threshold information to filter out abnormal fluctuation data of water volume parameters. Combined with the preset water volume fault parameter identification weight information, the abnormal fluctuation amplitude and duration of water volume parameters are weighted and quantified. Based on the analysis results, the fault risk level of water volume status is quantified. Finally, multiple water volume fault parameter variables that can reflect the type and level of water volume faults are calculated, and each water volume fault parameter variable is accurately matched with the water volume operation status of the corresponding water node.

[0035] Step 303: Based on the preset water system fault parameter fitting coordinate system, and according to multiple water quality status parameter information, preset water quality anomaly parameter threshold information, and preset water quality anomaly parameter identification weight information, multiple water quality anomaly parameter variables are calculated.

[0036] Similarly, in this step, a preset water system fault parameter fitting coordinate system is used, with monitoring time as the horizontal axis and water quality status parameters as the vertical axis. Multiple water quality status parameter information can be fitted to this coordinate system according to the monitoring time series to generate a water quality status parameter change curve. Then, this curve is compared and analyzed with the preset water quality anomaly parameter threshold information to identify the abnormal intervals where water quality parameters exceed the normal range. Then, combined with the preset water quality anomaly parameter identification weight information, the degree of abnormal deviation of different water quality indicators is calculated differentially. Among them, the core water quality indicators that affect water supply safety are given higher identification weights. Then, the severity of water quality anomalies is quantified based on the weighted calculation results, thereby calculating multiple water quality anomaly parameter variables that can accurately reflect the type and degree of water quality anomalies.

[0037] Step 304: Based on the multiple pump operating status parameter information, the preset pump operating fault parameter threshold information, and the preset pump operating fault parameter identification weight information, multiple pump fault parameter variables are obtained.

[0038] In this step, the weight information sets different identification weights for the core operating indicators of the water pump, such as speed, power, and vibration amplitude. First, multiple water pump operating status parameters are classified and organized, and the parameter data of each core operating indicator of the water pump are extracted. The parameter data of each core operating indicator is compared with the corresponding water pump operating fault parameter threshold information to filter out abnormal operating indicator data. Then, combined with the preset water pump operating fault parameter identification weight information, the parameter deviation values ​​of each abnormal operating indicator are weighted and calculated. Finally, based on the weighted calculation results, the degree of water pump operating fault and the fault location are quantitatively determined to generate multiple water pump fault parameter variables that can reflect the characteristics of water pump faults.

[0039] Step 305: Based on the preset water system fault location model, obtain multiple water system fault location information according to the multiple water pressure fault parameter variables, multiple water quantity fault parameter variables, multiple water quality abnormality parameter variables, and multiple water pump fault parameter variables.

[0040] In this step, the water system fault location model integrates a multi-source fault parameter fusion algorithm and a water system topology association algorithm. First, multiple water pressure fault parameter variables, multiple water quantity fault parameter variables, multiple water quality anomaly parameter variables, and multiple water pump fault parameter variables are input into the model. The model performs multi-source fusion analysis on these fault parameter variables, uncovering the correlations between different types of fault parameter variables and identifying fault types caused by single or multiple factors coupled together. Then, combined with the topological information of the water system, the fused fault parameter variables are associated and matched with the corresponding spatial locations of water nodes to accurately locate the specific water node and pipeline section where the fault occurred. Next, the severity and development trend of the fault are comprehensively judged. Then, according to the preset fault location information output standards, information such as fault type, fault location, fault severity, and fault development trend are integrated to generate multiple complete and highly accurate water system fault location information sets. Each water system fault location information set can achieve a comprehensive and accurate representation of the water system fault.

[0041] This step enables a multi-dimensional comprehensive assessment of water system faults, effectively improving the accuracy and efficiency of fault location. It allows for the rapid identification of early, hidden, and complex water system faults, providing precise technical support for timely handling of water system faults.

[0042] Furthermore, such as Figure 4 As shown, step 301 specifically includes the following steps: Step 401: Based on the preset coordinate system for fitting water system fault parameters, perform time-series fitting calculations based on multiple water pressure state parameter information to generate water pressure state parameter change curves.

[0043] Specifically, the preset coordinate system for fitting water system fault parameters uses the monitoring time corresponding to the water node monitoring time identifier information as the horizontal axis and the parameter value corresponding to the water pressure status parameter information as the vertical axis. First, multiple water pressure status parameter information is sorted in time sequence according to the corresponding water node monitoring time identifier information to ensure that each water pressure status parameter information corresponds one-to-one with the monitoring time. Then, time sequence fitting calculation is performed on the sorted multiple water pressure status parameter information. A fitting algorithm suitable for the variation law of water operation parameters is used to fit the time sequence water pressure status parameter data to generate a water pressure status parameter variation curve that can accurately reflect the trend and fluctuation law of water pressure status parameters with monitoring time. This curve can clearly show the normal fluctuation range and abnormal fluctuation nodes of water pressure.

[0044] Step 402: Based on the water pressure state parameter change curve and the preset water pressure fault parameter benchmark, fit a straight line to obtain the intersection information of multiple water pressure state parameter curves.

[0045] Specifically, the preset water pressure fault parameter benchmark fitting line is formulated based on the standard water pressure range during normal operation of the water system. It is divided into an upper limit benchmark fitting line and a lower limit benchmark fitting line, which correspond to the highest and lowest thresholds of normal water pressure operation, respectively. First, the generated water pressure state parameter change curve is compared with the preset water pressure fault parameter benchmark fitting line, that is, with the upper and lower limits, to find the intersection of the water pressure state parameter change curve with the upper limit benchmark fitting line and the lower limit benchmark fitting line. Then, the monitoring time information and water pressure state parameter information corresponding to each intersection point are extracted. These intersection point information are the intersection point information of multiple water pressure state parameter curves. Each intersection point information corresponds to a key node where the water pressure state enters the abnormal range from the normal range or returns to the normal range from the abnormal range.

[0046] Step 403: Calculate the difference based on the intersection information of multiple water pressure state parameter curves to obtain multiple water pressure fault representation variables.

[0047] Specifically, the intersection information of multiple water pressure state parameter curves is first classified and organized to distinguish the intersection points where the water pressure state parameter change curves intersect with the upper and lower limits of the preset water pressure fault parameter benchmark fitting line. Then, the difference is calculated for the intersection information of the same water affairs node and the same abnormal period. The difference between the water pressure state parameter information corresponding to the intersection point and the parameter value corresponding to the preset water pressure fault parameter benchmark fitting line is calculated. At the same time, the monitoring time difference corresponding to two adjacent intersection points is calculated. Then, the water pressure parameter difference and the time difference are fused and calculated to obtain a value that can quantitatively reflect the degree of deviation of water pressure anomaly and the duration of anomaly. Finally, multiple water pressure fault representation variables are generated, and each water pressure fault representation variable corresponds to the core characteristics of a water pressure anomaly.

[0048] Step 404: Calculate multiple water pressure fault parameter variables based on multiple water pressure fault representation variables, preset water pressure fault parameter threshold information, and preset water pressure fault parameter identification weight information.

[0049] Specifically, the preset water pressure fault parameter threshold information defines the fault judgment criteria corresponding to the water pressure fault representation variables, distinguishing the threshold ranges for mild, moderate, and severe anomalies. The preset water pressure fault parameter identification weight information is set according to the degree of impact of water pressure anomalies on the operation of the water system, with higher identification weights assigned to fault representation variables corresponding to severe anomalies. Multiple water pressure fault representation variables can be compared with the preset water pressure fault parameter threshold information to determine the water pressure anomaly level corresponding to each water pressure fault representation variable. Then, combined with the preset water pressure fault parameter identification weight information, the water pressure fault representation variables of different anomaly levels are weighted and quantified. The weighted values ​​are then standardized and calibrated to ensure that the numerical range meets the input requirements of the subsequent fault location model. Finally, multiple water pressure fault parameter variables that can accurately quantify the degree and level of water pressure faults are calculated.

[0050] This step can improve the accuracy and specificity of water pressure fault parameters, clearly and accurately quantify the characteristics of water pressure anomalies, provide more reliable parameter support for the accuracy of subsequent water system fault location, and improve the efficiency of water system fault location.

[0051] Furthermore, such as Figure 5 As shown, step 404 specifically includes the following: Step 501: Calculate multiple water pressure fault parameter judgment information based on multiple water pressure fault representation variables and preset water pressure fault parameter benchmark values.

[0052] In this step, the preset water pressure fault parameter benchmark value is the standard value corresponding to the water pressure fault indicator variable under normal operating conditions of the water system. It is used as the benchmark for determining whether there is a water pressure fault. First, multiple water pressure fault indicator variables are compared with the preset water pressure fault parameter benchmark value. The deviation value of each water pressure fault indicator variable from the preset water pressure fault parameter benchmark value is calculated. Then, the deviation value is standardized to eliminate the influence of dimensional differences on the judgment result. Then, according to the magnitude of the deviation value, the direction (too high or too low) and degree of deviation of the water pressure anomaly are marked. Finally, multiple water pressure fault parameter judgment information containing the direction of the anomaly and the degree of deviation are generated. Each water pressure fault parameter judgment information can intuitively reflect the abnormal situation of the corresponding water pressure fault indicator variable.

[0053] Step 502: Determine whether the water pressure fault parameter determination information is greater than or equal to the preset water pressure fault parameter threshold information; if yes, proceed to step 503; if no, proceed to step 504.

[0054] In step 502, the preset water pressure fault parameter threshold information is the critical standard for distinguishing whether a water pressure abnormality constitutes a fault. It clarifies the minimum deviation value that can be determined as a water pressure fault. First, the deviation value of multiple water pressure fault parameter judgment information is extracted. Then, the deviation value is compared with the preset water pressure fault parameter threshold information one by one to determine whether the deviation value corresponding to each water pressure fault parameter judgment information reaches or exceeds the preset water pressure fault parameter threshold information. If the deviation value is greater than or equal to the preset water pressure fault parameter threshold information, it means that the water pressure abnormality has constituted a fault and needs to proceed to the subsequent normal weighted calculation step. If the deviation value is less than the preset water pressure fault parameter threshold information, it means that the water pressure abnormality has not constituted a fault or is only a slight fluctuation.

[0055] Step 503: Based on the preset water pressure fault parameter identification weight information, and combined with the multiple water pressure state parameter information corresponding to the water pressure fault parameter judgment information, perform weighted processing to calculate multiple water pressure fault parameter variables.

[0056] In this step, the preset water pressure fault parameter identification weight information is set according to the severity of the water pressure anomaly and the priority of its impact on the operation of the water system. Higher weights are assigned to water pressure fault parameter judgment information with greater deviation and more severe impact. First, multiple water pressure state parameter information corresponding to each water pressure fault parameter judgment information that meets the requirements, i.e., is greater than or equal to the preset threshold, is determined. Then, key data in these water pressure state parameter information is extracted, and the key data is weighted and calculated in combination with the preset water pressure fault parameter identification weight information to quantify the severity of the water pressure fault. Then, the weighted calculation results are calibrated to ensure that the results meet the input specifications of the subsequent fault location model, thereby calculating multiple water pressure fault parameter variables that can accurately quantify the severity of the water pressure fault.

[0057] Step 504: Calculate multiple water pressure fault parameter penalty values ​​based on the multiple water pressure state parameter information corresponding to the water pressure fault parameter determination information, the preset water pressure fault parameter threshold information, and the preset water pressure fault parameter penalty factor.

[0058] In this step, a preset water pressure fault parameter penalty factor is used to appropriately penalize minor water pressure fluctuations that do not reach the fault threshold, avoiding interference from minor fluctuations with subsequent fault location results and ensuring the accuracy of fault parameter variables. First, multiple water pressure state parameter information corresponding to the water pressure fault parameter judgment information that does not reach the preset threshold is extracted. The difference between these water pressure state parameter information and the preset water pressure fault parameter threshold information is calculated. Then, the difference is multiplied by the preset water pressure fault parameter penalty factor to obtain the penalty value corresponding to each minor fluctuation. Finally, the penalty value is standardized to make it consistent with the dimension of the result of normal weighted calculation, thereby generating multiple water pressure fault parameter penalty value information.

[0059] Step 505: Calculate multiple water pressure fault parameter variables based on the multiple water pressure state parameter information, multiple water pressure fault parameter penalty value information, and preset water pressure fault parameter identification weight information corresponding to the water pressure fault parameter determination information.

[0060] In this step, multiple water pressure state parameters corresponding to the water pressure fault parameter judgment information that has not reached the preset threshold can be extracted first. Combined with the preset water pressure fault parameter identification weight information, these water pressure state parameters are weighted and calculated to obtain a basic weighted value. Then, the calculated multiple water pressure fault parameter penalty values ​​are deducted from the basic weighted value to achieve penalty calibration for slight fluctuations. The calibrated values ​​are then standardized to ensure that they can accurately reflect the actual impact of slight water pressure fluctuations, while maintaining a consistent quantification standard with the water pressure fault parameter variables. Finally, multiple water pressure fault parameter variables are calculated, taking into account the impact of slight fluctuations while avoiding their interference with fault location accuracy.

[0061] By setting the above steps, the severity of faults is highlighted by weighting those that meet the standards, while those that do not meet the standards are penalized and calibrated using a preset water pressure fault parameter penalty factor. This enhances the relevance and accuracy of the water pressure fault parameter variable calculation, effectively avoiding interference from slight water pressure fluctuations on fault location results. At the same time, the preset water pressure fault parameter identification weight information highlights the impact of severe faults, enabling the subsequent fault location model to more accurately identify core faults. This significantly improves the accuracy and reliability of fault location in the water system, providing strong support for the accurate investigation and timely handling of water system faults.

[0062] Furthermore, the pump operating status parameter information includes pump speed parameter information, pump power parameter information, pump vibration frequency parameter information, and pump inlet and outlet pressure difference parameter information; step 304 specifically includes: like Figure 6As shown, in step 601, the multiple pump speed parameters, multiple pump power parameters, multiple pump vibration frequency parameters, and multiple pump inlet and outlet pressure difference parameters are normalized to obtain normalized information of multiple pump speed parameters, multiple pump power parameters, multiple pump vibration frequency parameters, and multiple pump inlet and outlet pressure difference parameters.

[0063] First, extract the maximum and minimum values ​​from multiple pump speed parameters, multiple pump power parameters, multiple pump vibration frequency parameters, and multiple pump inlet / outlet pressure difference parameters to determine the value ranges for each type of parameter. For each type of parameter, subtract the minimum value of the corresponding range from each parameter value, and then divide by the difference between the maximum and minimum values ​​of that range to complete the normalization conversion of a single parameter. Verify the converted parameter values, eliminate abnormal normalization results, and correct them to generate multiple normalized information for pump speed parameters, multiple normalized information for pump power parameters, multiple normalized information for pump vibration frequency parameters, and multiple normalized information for pump inlet / outlet pressure difference parameters with uniform values ​​and no abnormalities. All types of normalized information correspond one-to-one with the original pump operating status parameters, preserving the fault characteristic correlation of the original parameters.

[0064] Step 602: Based on the preset water pump operation fault parameter identification weight information, the normalized information of multiple water pump speed parameters, multiple water pump power parameters, multiple water pump vibration frequency parameters, and multiple water pump inlet and outlet pressure difference parameters are weighted and summed to calculate multiple water pump operation fault discrimination variables.

[0065] The preset water pump operation fault parameter identification weight information is set according to the degree of influence of various water pump operation status parameters on water pump faults. Among them, the water pump vibration frequency parameter and the water pump inlet and outlet pressure difference parameter are more sensitive to faults and have a more direct impact, so they are set with higher identification weights. The water pump speed parameter and the water pump power parameter are set with relatively lower identification weights to ensure that the core influencing parameters are highlighted in the fault identification process.

[0066] First, clearly define the weight coefficients of various normalized parameters in the preset water pump operation fault parameter identification weight information, ensuring that the sum of the weight coefficients is one. For a set of normalized parameter information corresponding to each water node, multiply the normalized information of the water pump speed parameter by the corresponding weight coefficient, the normalized information of the water pump power parameter by the corresponding weight coefficient, the normalized information of the water pump vibration frequency parameter by the corresponding weight coefficient, and the normalized information of the water pump inlet and outlet pressure difference parameter by the corresponding weight coefficient. Add the four weighted results to complete the weighted summation calculation of a single set of parameters. Summarize and organize the weighted summation results corresponding to all water nodes, eliminate calculation errors and correct them, thereby calculating multiple water pump operation fault discrimination variables that can comprehensively reflect the risk of water pump operation faults. Each water pump operation fault discrimination variable corresponds to the comprehensive operation status of the water pump of a water node.

[0067] Step 603: Calculate the difference based on multiple pump operation fault discrimination variables and preset pump operation fault parameter threshold information to obtain multiple pump fault parameter variables.

[0068] The preset water pump operation fault parameter threshold information is the critical standard for distinguishing between normal operation and fault operation of water pumps. It is divided into normal threshold range and fault threshold range, and the fault critical value corresponding to the water pump operation fault discrimination variable is clearly defined.

[0069] First, multiple pump operation fault discrimination variables are compared with preset pump operation fault parameter threshold information to determine the threshold range of each discrimination variable. For each pump operation fault discrimination variable, the difference between it and the critical value in the preset pump operation fault parameter threshold information is calculated. If the discrimination variable is greater than the critical value, the difference is positive, and the larger the difference, the more severe the fault. If the discrimination variable is less than or equal to the critical value, the difference is negative or zero, indicating that the pump is operating normally and there is no obvious fault. The calculated difference is standardized and calibrated to make its quantification range adapt to the input requirements of the subsequent fault location model, thereby generating multiple pump fault parameter variables that can accurately quantify the severity of pump faults. A positive fault parameter variable indicates the presence of a pump fault, and the larger the value, the more severe the fault. A negative or zero value indicates that the pump is operating normally.

[0070] These steps ensure the fairness and accuracy of the water system fault identification process, highlight the impact of core fault parameters, achieve comprehensive identification of pump operating status, accurately quantify the severity of pump faults, thereby improving the accuracy of pump fault parameter variables. This provides high-quality parameter support for the subsequent fusion analysis of water system fault location models, effectively optimizes the identification efficiency and accuracy of pump faults, and enhances the performance of water system fault location.

[0071] Following step 103, the following steps are also included: like Figure 7As shown, in step 701, feature extraction processing is performed on the fault location information of multiple water systems to obtain fault feature information of multiple water systems.

[0072] First, the fault location information of multiple water systems is classified and organized to distinguish the location information corresponding to water pressure faults, water quantity faults, water quality faults, and water pump faults. Then, for each type of fault location information, key features such as fault type, fault location, fault severity, fault development trend, and fault duration are extracted. Among them, fault severity and fault development trend are the core features to be extracted. Then, the extracted feature information is standardized and described, and the quantitative standards and classification specifications of feature parameters are clarified. The feature information is deduplicated and noise-reduced to remove invalid and duplicate features, thereby generating multiple water system fault feature information that is clear, non-redundant, and highly targeted. Each water system fault feature information corresponds one-to-one with the original water system fault location information, and the core attributes of the fault are completely preserved.

[0073] Step 702: Based on the preset mapping relationship between water system fault feature information and water system fault early warning level, generate multiple water system fault early warning level information according to multiple water system fault feature information.

[0074] This mapping relationship is constructed based on the severity, development trend, and scope of impact of water system failures. It is divided into three levels: Level 1 warning, Level 2 warning, and Level 3 warning. Level 1 warning corresponds to minor failures with no risk of spread, Level 2 warning corresponds to moderate failures with a slight risk of spread, and Level 3 warning corresponds to severe failures with a high risk of spread, affecting the normal operation of the water system.

[0075] First, the rules for determining the warning level corresponding to various fault characteristics in the preset mapping relationship are clarified. For example, a minor fault with a stable development trend corresponds to a Level 1 warning, a moderate fault with an upward development trend corresponds to a Level 2 warning, and a severe fault with a rapidly spreading development trend corresponds to a Level 3 warning. Then, for each water system fault characteristic, the corresponding water system fault warning level is determined by referring to the rules in the mapping relationship. The determination results are then verified to ensure that the warning level matches the fault characteristics. The verified warning levels are then standardized and labeled, thereby generating multiple accurate and clearly defined water system fault warning level information. Each water system fault warning level information corresponds one-to-one with the water system fault characteristic information, intuitively reflecting the urgency of the fault.

[0076] Step 703: Based on the preset mapping relationship between water system fault characteristic information and water system fault handling strategies, multiple water system fault handling strategy information is generated according to multiple water system fault characteristic information. This mapping relationship formulates targeted handling procedures, handling methods and division of responsibilities for different fault types, different fault severity, and different fault development trends, ensuring that fault handling work is carried out in a standardized and efficient manner.

[0077] First, the fault type, severity, location, and development trend are extracted from the fault characteristic information of each water system. Then, the corresponding fault handling strategies are matched against the preset mapping relationship. For example, for water quality abnormality faults, mild severity corresponds to water quality sampling and testing, and local pipeline flushing; for severe pump faults, emergency shutdown, repair and replacement of parts, and startup of backup pumps are corresponding to the handling strategies; and for water pressure faults, pipeline inspection and pressure regulation are corresponding to the handling strategies. Then, the matched handling strategies are refined and supplemented, clarifying the handling steps, handling time limits, required equipment, and responsible personnel. The refined handling strategies are reviewed, unreasonable handling steps are eliminated, and improvements are made. This generates multiple water system fault handling strategy information with clear processes, strong targeting, and implementability. Each water system fault handling strategy information is accurately matched with the water system fault characteristic information to ensure that faults can be handled accurately.

[0078] Step 704: Generate multiple water system fault handling information based on multiple water system fault warning level information and multiple water system fault handling strategy information.

[0079] First, multiple water system fault warning levels are correlated and matched with multiple water system fault handling strategies to ensure that each warning level corresponds to a specific handling strategy. For each correlation combination, the warning level and urgency from the water system fault warning information are integrated with the handling steps, time limits, responsible personnel, and required equipment from the water system fault handling strategy information, supplementing basic information such as fault location and fault type. Then, the integrated information is standardized and formatted, clarifying the presentation order and highlighting the warning level and core handling steps. Subsequently, the integrated information is verified to ensure that it is complete, consistent, and executable, thereby generating multiple complete, standardized, clear, and directly applicable water system fault handling information sets. Each water system fault handling information set corresponds to a specific water system fault, providing comprehensive guidance for operation and maintenance personnel in handling faults.

[0080] The above method can achieve full-process coverage from fault location to fault early warning and fault handling, solve the problem of lack of standardized early warning and targeted handling guidelines after fault location in existing technologies, improve the efficiency and standardization of fault handling in water systems, facilitate operation and maintenance personnel to distinguish the urgency of faults, prioritize the handling of severe faults, reduce the losses caused by the spread of faults, and provide comprehensive and powerful technical support for the stable and safe operation of water systems.

[0081] Example 2: A water system fault location device is provided, which can be the execution subject of the water system fault location method provided in Example 1 above.

[0082] Reference Figure 8 The water system fault location device includes: The water affairs node operation status monitoring information acquisition module 810 is used to acquire the operation status monitoring information of multiple water affairs nodes; The water affairs operation status parameter information generation module 820 is used to calculate multiple water affairs operation status parameter information based on the multiple water affairs node operation status monitoring information and multiple preset water affairs operation status parameter calculation models; The water system fault location information generation module 830 is used to obtain multiple water system fault location information by filtering and analyzing multiple water system operation status parameter information based on a preset water system fault location model.

[0083] The water system fault location method provided in this application embodiment can be applied to terminal devices such as mobile phones, tablets, wearable devices, vehicle-mounted devices, laptops, and netbooks. This application embodiment does not impose any restrictions on the specific type of terminal device.

[0084] like Figure 9 As shown, the terminal device 9 of this embodiment includes: at least one processor 90 ( Figure 9 (Only one is shown in the image) A memory 91 stores a computer program 92 that can run on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the various water system fault location method embodiments described above, for example... Figure 1 Steps S101 to S103 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 8 The functions of modules 810 to 830 are shown.

[0085] The terminal device 9 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will understand that... Figure 9This is merely an example of terminal device 9 and does not constitute a limitation on terminal device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input transmission devices, network access devices, buses, etc.

[0086] The processor 90 can be a central processing unit, or it can be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0087] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as a hard disk or memory of the terminal device 9. The memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc., equipped on the terminal device 9. Furthermore, the memory 91 may include both internal and external storage units of the terminal device 9. The memory 91 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 91 can also be used to temporarily store data that has been sent or will be sent.

[0088] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0089] This application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, it causes the terminal device to implement the steps in any of the above method embodiments.

[0090] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0091] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the above-described method embodiments.

[0092] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for locating faults in a water system, characterized in that, Includes the following steps: Obtain operational status monitoring information from multiple water management nodes; Based on the monitoring information of the operation status of multiple water affairs nodes and multiple preset calculation models of water affairs operation status parameters, multiple water affairs operation status parameter information are calculated. Based on a pre-set water system fault location model, multiple water system fault location information is obtained by filtering and analyzing multiple water system operation status parameters.

2. The water system fault location method according to claim 1, characterized in that, The water node operation status monitoring information includes one-to-one corresponding water node monitoring spatial identification information, water node monitoring time identification information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information; Based on the water node operation status feature extraction rules, spatiotemporal features are extracted according to the water node monitoring spatial identifier information, water node monitoring time identifier information, water pressure status monitoring information, water quantity status monitoring information, water quality status monitoring information, and water pump operation status monitoring information to generate water pressure status feature information, water quantity status feature information, water quality status feature information, and water pump operation status feature information. Based on the generated water pressure status characteristic information, water quantity status characteristic information, water quality status characteristic information, water pump operation status characteristic information, and the water operation status parameter calculation model, the water operation status parameter information is calculated.

3. The water system fault location method according to claim 1, characterized in that, The water supply operation status parameters include water pressure status parameters, water quantity status parameters, water quality status parameters, and water pump operation status parameters. The steps for calculating fault location information in a water system include: fitting a coordinate system based on preset water system fault parameters. Based on the water pressure status parameter information, the preset water pressure fault parameter threshold information, and the preset water pressure fault parameter identification weight information, the water pressure fault parameter variable is calculated. Based on the water volume status parameter information, the preset water volume fault parameter threshold information, and the preset water volume fault parameter identification weight information, the water volume fault parameter variable is calculated. Based on the water quality status parameter information, the preset water quality anomaly parameter threshold information, and the preset water quality anomaly parameter identification weight information, the water quality anomaly parameter variable is calculated. Based on the pump operating status parameter information, the preset pump operating fault parameter threshold information, and the preset pump operating fault parameter identification weight information, the pump fault parameter variables are obtained. Based on the water system fault location model, the water system fault location information is calculated according to the water pressure fault parameter variables, the water quantity fault parameter variables, the water quality anomaly parameter variables, and the water pump fault parameter variables.

4. The water system fault location method according to claim 3, characterized in that, The specific steps for calculating water pressure fault parameters include: Based on the coordinate system fitted to the fault parameters of the water system, a time-series fitting calculation is performed according to the water pressure state parameter information to generate a water pressure state parameter change curve. Based on the water pressure state parameter change curve and the preset water pressure fault parameter benchmark fitting straight line, the intersection information of the water pressure state parameter curve is obtained; The difference between the intersection points of the water pressure state parameter curves is calculated to obtain the water pressure fault representation variable; The water pressure fault parameter variable is calculated based on the water pressure fault representation variable, the water pressure fault parameter threshold information, and the water pressure fault parameter identification weight information.

5. The water system fault location method according to claim 4, characterized in that, Based on the water pressure fault representation variables and the preset water pressure fault parameter benchmark values, water pressure fault parameter judgment information is calculated. Determine whether the water pressure fault parameter determination information is greater than or equal to the preset water pressure fault parameter threshold information; If so, the water pressure fault parameter identification weight information is used to weight the water pressure state parameter information corresponding to the water pressure fault parameter determination information to calculate the water pressure fault parameter variable. If not, the water pressure fault parameter penalty value information is calculated based on the water pressure state parameter information, water pressure fault parameter threshold information, and preset water pressure fault parameter penalty factor corresponding to the water pressure fault parameter judgment information. Based on the water pressure state parameter information, water pressure fault parameter penalty value information, and preset water pressure fault parameter identification weight information corresponding to the water pressure fault parameter determination information, the water pressure fault parameter variable is calculated.

6. The water system fault location method according to claim 3, characterized in that, The pump operating status parameters include pump speed parameters, pump power parameters, pump vibration frequency parameters, and pump inlet and outlet pressure difference parameters. The specific steps for calculating the parameters of a water pump failure include: The pump speed parameter information, pump power parameter information, pump vibration frequency parameter information, and pump inlet and outlet pressure difference parameter information are normalized to obtain normalized information of each parameter. Based on the identified weight information of the pump operation fault parameters, these normalized information are weighted and summed to calculate the pump operation fault discrimination variable. The pump fault parameter variables are obtained by calculating the difference between the pump operation fault discrimination variable and the pump operation fault parameter threshold information.

7. The water system fault location method according to claim 1, characterized in that, After obtaining multiple water system fault location information steps, the process also includes: The water system fault location information is processed by feature extraction to obtain water system fault feature information; Based on the preset mapping relationship between water system fault characteristic information and water system fault early warning level, water system fault early warning level information is generated according to the obtained water system fault characteristic information. Based on the pre-defined mapping relationship between water system fault characteristic information and water system fault handling strategies, water system fault handling strategy information is generated according to the obtained water system fault characteristic information. Based on the water system fault warning level information and the water system fault handling strategy information, water system fault handling information is generated.

8. A water system fault location device, used to implement the water system fault location method as described in any one of claims 1 to 7, characterized in that, include: The water affairs node operation status monitoring information acquisition module is used to acquire the operation status monitoring information of multiple water affairs nodes; The water affairs operation status parameter information generation module is used to calculate multiple water affairs operation status parameter information based on the operation status monitoring information of multiple water affairs nodes and multiple preset water affairs operation status parameter calculation models; The water system fault location information generation module is used to obtain multiple water system fault location information by filtering and analyzing multiple water system operation status parameters based on a preset water system fault location model.

9. An electronic device, characterized in that, The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the water system fault location method as described in any one of claims 1 to 7.

10. A computer-readable storage medium comprising a stored program, characterized in that, When the program is executed by the processor, it implements the water system fault location method as described in any one of claims 1 to 7.

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