Inspection standard construction method, construction device, inspection method, inspection device, apparatus, and program

Abstract

The invention discloses a construction method, a construction device, an inspection method, an inspection device, equipment and a program of an inspection standard. According to the construction method, a plurality of target water consumption curves of any specified equipment are statistically analyzed to judge whether water consumption characteristics of the specified equipment at different moments are consistent with theoretical statistical characteristics of the specified equipment or not, namely whether the specified equipment has reproducibility or not. And if the target water consumption curve has reproducibility, determining the target water consumption curve as a standard water consumption curve of the specified equipment. According to the construction method, single fluctuation or accidental interference can be effectively eliminated, and the representativeness and reliability of the inspection standard are ensured. Therefore, in practical application, the water consumption data is checked through the standard water consumption curve, and the operation states of different water consumption equipment can be judged. Especially, the operation state of the user water meter is judged, the difficulty of current user water meter detection can be broken through, and low-cost, efficient, real-time and accurate user water meter quality detection is achieved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent water affairs, and particularly relates to a construction method and a construction device of a verification standard, a verification method and a verification device, equipment and a program. BACKGROUND

[0002] According to relevant regulations, user water meters need to be regularly tested for accuracy during use to ensure the accuracy of measurement. The existing testing method is usually to regularly disassemble the water meters installed at the user end, and send them back to the standard testing room of the water department for detection and calibration. Although this method can meet the compliance requirements of regulations, it will bring huge detection pressure after large-scale use of user water meters.

[0003] Firstly, the large-scale disassembly, transportation, calibration and reinstallation of water meters require a large amount of manpower and resources, and the workload is huge, which brings a great burden to the management and operation of the water department. Secondly, during the disassembly and replacement of water meters, water supply is easily interrupted, affecting the normal water use experience of users. In addition, due to the time interval of periodic testing, the accumulation of measurement errors during the interval may cause economic losses or user disputes.

[0004] Therefore, how to reduce the detection cost, reduce the manual workload, and improve the efficiency and real-time performance of detection under the premise of meeting the regulatory requirements has become a technical problem to be solved at present. SUMMARY

[0005] The application provides a construction method and a construction device of a verification standard, a verification method and a verification device, equipment and a program, which can break through the current predicament of user water meter detection, realize low-cost, less-labor, efficient, real-time and accurate quality detection of user water meters under the premise of meeting the regulatory requirements.

[0006] In a first aspect, the application provides a construction method of water consumption data verification standard, comprising: determining whether the water consumption characteristics of the specified device have reproducibility based on a specified number of target water consumption curves; the target water consumption curve is a standard water consumption curve corresponding to the specified device, and the water consumption characteristics have theoretical statistical stability; In the case where the water consumption characteristics have reproducibility, each target water consumption curve is determined as a standard water consumption curve for testing water consumption data.

[0007] Further, before determining whether the water consumption characteristics of the specified device have reproducibility based on a specified number of target water consumption curves, the construction method further comprises: cyclically performing the following operations until a specified number of target water consumption curves is obtained: acquire first water consumption data collected by a target user water meter, to obtain a first water consumption curve based on the first water consumption data; the target user water meter is installed for less than a preset installation duration threshold; a sampling frequency of the first water consumption data ranges from 1 Hz to 8 Hz; determine a candidate water consumption curve corresponding to the specified device from each first water consumption curve; determine a target water consumption curve from the candidate water consumption curve based on a preset condition.

[0008] Further, based on a specified number of target water consumption curves, determine whether the water consumption feature of the specified device has reproducibility, comprising: extract digital feature values of each target water consumption curve; determine whether each digital feature value is consistent; In the case where each digital feature value is consistent, determine whether the water consumption feature has reproducibility.

[0009] Further, the digital feature value includes a global feature value, the specified device includes a flushing device of a sanitary fixture and a washing machine, and correspondingly, the target water consumption curve is a target trapezoidal pulse; the global feature value includes a total water injection amount and a total water injection duration; extracting the digital feature value of each target water consumption curve, comprising: integrating each target trapezoidal pulse to obtain a corresponding total water injection amount; determining a pulse duration corresponding to each target trapezoidal pulse as a corresponding total water injection duration.

[0010] Further, the digital feature value includes a stage feature value, and the stage corresponding to the stage feature value includes a change stage of instantaneous flow rate / unit time water consumption and a stable stage; extracting the digital feature value of each target water consumption curve, comprising: for the change stage, determining a change duration and a dynamic change feature value of a corresponding change curve; for the stable stage, determining a peak value, an average value and a mean square error of a corresponding stable curve.

[0011] Further, determining the change duration and the dynamic change feature value of the corresponding change curve, comprising: based on boundary clipping of the change curve, obtaining an effective change curve; based on the effective change curve, determining the change duration and the dynamic change feature value; wherein the effective change curve is linear, and the dynamic change feature value is a slope; the effective change curve is nonlinear, and the dynamic change feature value is an instantaneous flow rate / unit time water consumption decay time constant.

[0012] Further, the digital feature includes a global feature value and a stage feature value, and determining whether each digital feature value is consistent, comprising: Based on the similarity measurement method, the global feature values and the stage feature values are analyzed respectively to determine whether the global feature values have relative consistency and whether the stage features have relative consistency. Correspondingly, in the case that the global feature values have relative consistency and the stage features have relative consistency, it is determined that the digital feature values are consistent.

[0013] Further, the digital features include global feature values and stage feature values, and determining whether the digital feature values are consistent includes: determining whether the global feature values fall within a preset first deviation range; determining whether the stage feature values fall within a preset second deviation range; in the case that the global feature values fall within the first deviation range and the stage feature values fall within the second deviation range, it is determined that the digital feature values are consistent.

[0014] Further, the candidate water consumption curve is a candidate trapezoidal pulse; determining the candidate water consumption curve corresponding to the specified device from the first water consumption curves includes: filtering independent trapezoidal pulses from the first water consumption curves; the pulse intervals of the independent trapezoidal pulses are greater than a preset time length; deleting independent trapezoidal pulses in which the stable stage contains a sudden change in instantaneous flow rate / unit time water consumption, to obtain suspected candidate trapezoidal pulses; calculating the total water consumption of each suspected candidate trapezoidal pulse; determining the suspected candidate trapezoidal pulse whose total water consumption reaches the standard total water consumption of the specified device as the candidate trapezoidal pulse.

[0015] Further, the preset condition includes a preset anomaly; determining the target trapezoidal pulse from the candidate trapezoidal pulses based on the preset condition includes: determining an abnormal trapezoidal pulse from the candidate trapezoidal pulses based on an abnormal feature corresponding to the preset anomaly; filtering the abnormal trapezoidal pulse from the candidate trapezoidal pulses to obtain the target trapezoidal pulse.

[0016] Further, the specified device includes a flushing device of sanitary wares; determining the abnormal trapezoidal pulse from the candidate trapezoidal pulses based on the abnormal feature corresponding to the preset anomaly includes: for each candidate trapezoidal pulse, in the case that it is determined that the stable stage and / or the change stage of the candidate trapezoidal pulse contains an anomaly, the corresponding candidate trapezoidal pulse is determined as the abnormal trapezoidal pulse.

[0017] Further, determining that the stable stage and / or the change stage of the candidate trapezoidal pulse contains an anomaly includes: In a case where a difference between the attribute value of the stable phase and / or the change phase of the candidate trapezoidal pulse and the normal attribute value is greater than a preset threshold value, it is determined that the stable phase and / or the change phase of the candidate trapezoidal pulse is abnormal.

[0018] Further, the abnormal trapezoidal pulse is determined from each candidate trapezoidal pulse based on an abnormal feature corresponding to a preset abnormality, comprising: In a case where there are a plurality of candidate trapezoidal pulses with approximately continuous pulse intervals, each corresponding candidate trapezoidal pulse is determined as an abnormal trapezoidal pulse.

[0019] Further, after each target water curve is determined as a standard water curve of the test water data, further comprising: A device aging model is constructed based on each trapezoidal pulse corresponding to the second water data; An adjustment value is determined based on the device aging model; The standard water curve is optimized based on the adjustment value.

[0020] Further, after each target water curve is determined as a standard water curve of the test water data, further comprising: A seasonal identifier of the standard water curve is determined based on a first season to which the first water data belongs; A new standard water curve is constructed based on the water data of a second season, and a corresponding seasonal identifier is determined; the second season is a season other than the first season; In the process of water data testing, a target standard water curve is determined from the constructed standard water curves based on a third season corresponding to the water data to be detected, and water testing is performed; the seasonal identifier of the target standard water curve matches the third season.

[0021] Further, the first water curve is obtained based on the first water data, comprising: Curve fitting is performed based on the first water data to obtain each fitting curve; The fitting curve is denoised by a preset method to obtain the first water curve.

[0022] In a second aspect, the application provides a water data detection method, comprising: After the standard water curve is constructed, third water data is obtained; the standard water curve is obtained based on any construction method in the first aspect; A third water curve is obtained based on the third water data; A to-be-detected water curve corresponding to a specified device is determined from each third water curve; The to-be-detected water curve is tested based on the standard water curve, and water service is provided to a user based on the obtained water detection result.

[0023] Further, the water service includes in-use quality inspection monitoring of the user water meter, the detected water curve is checked based on the standard water curve, and the water service is provided for the user based on the obtained water detection result, including: determining whether the detected water curve is similar to the standard water curve; in the case that the detected water curve is similar to the standard water curve, determining that the in-use quality inspection monitoring of the user water meter is qualified.

[0024] Further, the water curve corresponding to the specified device is a trapezoidal pulse; the detected water curve is a detected trapezoidal pulse; the standard water curve is a standard trapezoidal pulse; the trapezoidal pulse includes a stable stage; determining whether the detected water curve is similar to the standard water curve, including: extracting a detected digital feature of the detected trapezoidal pulse; comparing the detected digital feature with a standard digital feature of the standard trapezoidal pulse; and / or, in the stable stage, determining a plurality of difference values between the instantaneous flow rate / unit time water consumption of the detected trapezoidal pulse corresponding to a plurality of specified time intervals and the instantaneous flow rate / unit time water consumption of the standard trapezoidal pulse corresponding to the plurality of specified time intervals; in the case that the detected digital feature is consistent with the standard digital feature, and / or, the plurality of difference values all fall within a preset difference value range; or, in the case that the detected digital feature is consistent with the standard digital feature, and / or, the root mean square error or the average absolute difference corresponding to the plurality of difference values is less than a preset threshold, determining that the detected trapezoidal pulse is similar to the standard trapezoidal pulse.

[0025] Further, the detected water curve is checked based on the standard water curve, and the water service is provided for the user based on the obtained water detection result, including: in the case that the detected water curve is not similar to the standard water curve, determining whether the detected water curve has an abnormal feature; in the case that it is determined that the detected water curve does not have an abnormal feature, determining that the user water meter is faulty.

[0026] Further, the water service further includes an abnormal alarm service, the detected water curve is checked based on the standard water curve, and the water service is provided for the user based on the obtained water detection result, including: in the case that it is determined that the detected water curve has an abnormal feature, providing an abnormal alarm service for the user based on fault information corresponding to the abnormal feature.

[0027] In a third aspect, the present application provides a water data inspection standard construction device, including: a first determination module configured to determine whether the water feature of the specified device has reproducibility based on a specified number of target water curves; the target water curve is a standard water curve corresponding to the specified device, and the water feature has theoretical statistical stability; a construction module configured to determine each target water consumption curve as a standard water consumption curve for testing the water consumption data, in a case where the water consumption feature of the designated device is recurrent.

[0028] Further, the construction apparatus further comprises a screening module configured to: Before determining whether the water consumption feature of the designated device is recurrent based on the specified number of target water consumption curves, the following operations are performed in a loop until the specified number of target water consumption curves is obtained: obtain first water consumption data collected by a target user water meter, to obtain a first water consumption curve based on the first water consumption data; the target user water meter is installed for less than a preset installation duration threshold; a sampling frequency of the first water consumption data is in a value range of [1 Hz, 8 Hz]; determine a candidate water consumption curve corresponding to the designated device from each first water consumption curve; determine a target water consumption curve from the candidate water consumption curves based on a preset condition.

[0029] Further, the first determination module comprises: an extraction unit configured to extract a digital feature value of each target water consumption curve; a determination unit configured to determine whether each digital feature value is consistent; in a case where each digital feature value is consistent, determine whether the water consumption feature is recurrent.

[0030] Further, the digital feature value comprises a global feature value, the designated device comprises a flushing device of a sanitary ware and a washing machine, and correspondingly, the target water consumption curve is a target trapezoidal pulse; the global feature value comprises a total water injection amount and a total water injection duration; the extraction unit is specifically configured to: integrate each target trapezoidal pulse to obtain a corresponding total water injection amount; determine a pulse duration corresponding to each target trapezoidal pulse as a corresponding total water injection duration.

[0031] Further, the digital feature value comprises a stage feature value, and a stage corresponding to the stage feature value comprises a change stage of instantaneous flow rate / unit time water consumption and a stable stage; the extraction unit is specifically configured to: for the change stage, determine a change duration of a corresponding change curve and a dynamic change feature value; for the stable stage, determine a peak value, an average value, and a mean square error of a corresponding stable curve.

[0032] Further, for the stable stage, the determination unit is more specifically configured to: based on boundary clipping of the change curve, obtain an effective change curve; based on the effective change curve, determine the change duration and the dynamic change feature value. wherein the effective change curve is linear, and the dynamic change characteristic value is a slope; the effective change curve is nonlinear, and the dynamic change characteristic value is an attenuation time constant of the instantaneous flow rate / unit time water consumption.

[0033] Further, the digitized features include global feature values and stage feature values, and the determination unit is specifically configured to: analyze the global feature values and the stage feature values respectively based on a similarity measurement method to determine whether the global feature values have relative consistency and whether the stage features have relative consistency; Correspondingly, in the case that the global feature values have relative consistency and the stage features have relative consistency, it is determined that the digitized feature values are consistent.

[0034] Further, the digitized features include global feature values and stage feature values, and the determination unit is specifically configured to: determine whether the global feature values fall within a preset first deviation range; determine whether the stage feature values fall within a preset second deviation range; In the case that the global feature values fall within the first deviation range and the stage feature values fall within the second deviation range, it is determined that the digitized feature values are consistent.

[0035] Further, the selected water consumption curve is a candidate trapezoidal pulse; the screening module includes a first screening unit, and the first screening unit is configured to: screen independent trapezoidal pulses from the first water consumption curve; the pulse intervals of the independent trapezoidal pulses are greater than a preset time length; delete independent trapezoidal pulses in which the stable stage contains a sudden change in instantaneous flow rate / unit time water consumption, to obtain suspected candidate trapezoidal pulses; calculate total water consumption of the suspected candidate trapezoidal pulses; determine the suspected candidate trapezoidal pulses whose total water consumption reaches a standard total water consumption of a specified device as candidate trapezoidal pulses.

[0036] Further, the preset condition includes a preset anomaly; the screening module further includes a second screening unit, and the second screening unit is configured to: determine an abnormal trapezoidal pulse from the candidate trapezoidal pulses based on an abnormal feature corresponding to the preset anomaly; filter the abnormal trapezoidal pulse in the candidate trapezoidal pulses to obtain a target trapezoidal pulse.

[0037] Further, the specified device includes a flushing device of a sanitary fixture; the second screening unit includes: The abnormal trapezoidal pulse screening subunit is configured to determine each candidate trapezoidal pulse as an abnormal trapezoidal pulse if the stable phase and / or the change phase of the candidate trapezoidal pulse is determined to be abnormal.

[0038] Further, the abnormal trapezoidal pulse screening subunit is specifically configured to: determine that the stable phase and / or the change phase of the candidate trapezoidal pulse is abnormal if the difference between the attribute value of the stable phase and / or the change phase of the candidate trapezoidal pulse and the normal attribute value is greater than a preset threshold.

[0039] Further, the abnormal trapezoidal pulse screening subunit is specifically configured to: determine each candidate trapezoidal pulse as an abnormal trapezoidal pulse if there are multiple candidate trapezoidal pulses with similar pulse intervals.

[0040] Further, the construction device further comprises a first optimization module, and the first optimization module is configured to: after determining each target water consumption curve as a standard water consumption curve of the test water consumption data, construct a device aging model based on each water consumption curve corresponding to the second water consumption data; determine an adjustment value based on the device aging model; optimize the standard water consumption curve based on the adjustment value.

[0041] Further, the construction device further comprises a second optimization module, and the second optimization module is configured to: after determining each target water consumption curve as a standard water consumption curve of the test water consumption data, determine a seasonal identifier of the standard water consumption curve based on a first season to which the first water consumption data belongs; construct a new standard water consumption curve based on water consumption data of a second season, and determine a corresponding seasonal identifier; the second season is a season other than the first season; in the process of water consumption data testing, determine a target standard water consumption curve from the constructed standard water consumption curves based on a third season corresponding to the water consumption data to be tested, and perform water consumption testing; the seasonal identifier of the target standard water consumption curve matches the third season.

[0042] Further, the construction device further comprises a preprocessing module, and the screening module comprises a preprocessing unit, and the preprocessing unit is configured to: perform curve fitting based on the first water consumption data to obtain each fitting curve; perform noise reduction processing on the fitting curve by a preset method to obtain the first water consumption curve.

[0043] In a fourth aspect, the present application provides a water consumption data testing device, comprising: The acquisition module is configured to acquire third water consumption data after the standard water consumption curve is constructed, and the standard water consumption curve is obtained based on any of the construction methods in the first aspect; The fitting module is configured to obtain a third water consumption curve based on the third water consumption data. The second determination module is configured to determine, from the third water consumption curves, a to-be-detected water consumption curve corresponding to the specified device. The inspection service module is configured to inspect the to-be-detected water consumption curve based on the standard water consumption curve, and provide water service for the user based on a water consumption detection result obtained.

[0044] Further, the water service includes user water meter quality inspection, and the inspection service module is specifically configured to: determine whether the to-be-detected water consumption curve is similar to the standard water consumption curve; in a case where the to-be-detected water consumption curve is similar to the standard water consumption curve, determine that the user water meter quality inspection is monitored to be qualified in use.

[0045] Further, the water consumption curve corresponding to the specified device is a trapezoidal pulse, the to-be-detected water consumption curve is a to-be-detected trapezoidal pulse, the standard water consumption curve is a standard trapezoidal pulse, and the trapezoidal pulse includes a stable stage; the inspection service module is specifically configured to: extract a to-be-detected digital feature of the to-be-detected trapezoidal pulse; compare the to-be-detected digital feature with a standard digital feature of the standard trapezoidal pulse; and / or, in the stable stage, determine a plurality of difference values between an instantaneous flow rate / unit time water consumption of the to-be-detected trapezoidal pulse corresponding to a plurality of specified time intervals and an instantaneous flow rate / unit time water consumption of the standard trapezoidal pulse corresponding to the plurality of specified time intervals; in a case where the to-be-detected digital feature is consistent with the standard digital feature, and / or, the plurality of difference values all fall within a preset difference value range; or, in a case where the to-be-detected digital feature is consistent with the standard digital feature, and / or, a root mean square error or a mean absolute difference corresponding to the plurality of difference values is less than a preset threshold, determine that the to-be-detected trapezoidal pulse is similar to the standard trapezoidal pulse.

[0046] Further, the inspection service module is specifically configured to: in a case where the to-be-detected water consumption curve is not similar to the standard water consumption curve, determine whether the to-be-detected water consumption curve has an abnormal feature; in a case where it is determined that the to-be-detected water consumption curve has no abnormal feature, determine that the user water meter is faulty.

[0047] Further, the water service further includes an abnormal alarm service, and the inspection service module is specifically configured to: in a case where it is determined that the to-be-detected water consumption curve has an abnormal feature, provide an abnormal alarm service for the user based on fault information corresponding to the abnormal feature.

[0048] Fifthly, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the methods described in the first or second aspect above.

[0049] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the methods described in the first or second aspect above.

[0050] Fifthly, this application provides a computer program product comprising a computer program that, when executed by one or more processors, implements the steps of the method described in the first aspect.

[0051] The first advantage of this application compared to existing technologies is that the water usage characteristics of specified equipment theoretically possess statistical stability, meaning that under normal operating conditions, water usage behavior remains statistically stable and similar, exhibiting reproducibility. However, in actual data collection, water usage curves may be affected not only by external factors such as environmental changes, pipeline pressure fluctuations, or measurement errors, but also by deviations caused by issues such as performance degradation, component aging, or structural abnormalities within the equipment itself. Without verifying reproducibility, abnormal curves may be incorporated into the standard construction process, leading to distortion of the established standard and reducing its representativeness and reliability.

[0052] Therefore, by statistically analyzing multiple target water usage curves of designated equipment, the reproducibility of its water usage characteristics can be verified. This effectively identifies and eliminates abnormal curves caused by external sporadic interference or equipment malfunctions, ensuring that standards are established solely based on stable and repeatable data. The validated standard water usage curves not only possess statistical representativeness and engineering reliability but also provide a reliable benchmark for subsequent water usage data testing, especially for the quality testing of user water meters. Quality testing based on this benchmark enables low-cost, high-efficiency, and real-time monitoring and quality assessment of user water meter status.

[0053] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is a flowchart illustrating a method for constructing a water usage data verification standard provided in an embodiment of this application; Figure 2 This is a schematic diagram of the toilet water usage curve during the stable phase provided in this application embodiment, showing a sudden change in flow rate. Figure 3 This is a schematic diagram of a toilet trapezoidal pulse with different stages provided in the embodiments of this application; Figure 4 This is a schematic diagram of the trapezoidal pulse of a toilet when there is a minor leak in other devices provided in this application embodiment; Figure 5 This is a schematic diagram of the trapezoidal pulse when a toilet is clogged, provided in an embodiment of this application. Figure 6 This is a schematic diagram illustrating the process of verifying water usage data using an electronic device provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of the device for constructing water data verification standards provided in the embodiments of this application; Figure 8 This is a schematic diagram of the structure of the water usage data verification device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0056] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0057] In related technologies, the large-scale dismantling, transportation, calibration, and reinstallation of water meters require significant manpower and resources, resulting in a huge workload and placing a heavy burden on water companies' management and maintenance. Secondly, the dismantling and replacement of water meters can easily cause water supply interruptions, affecting users' normal water usage experience. Furthermore, the time intervals between periodic calibrations can lead to the accumulation of metering errors during these intervals, potentially causing economic losses or user disputes.

[0058] Therefore, how to reduce testing costs, decrease manual workload, and improve testing efficiency and real-time performance while meeting regulatory requirements has become an urgent technical problem to be solved.

[0059] To address this issue, this application proposes a method for constructing water usage data verification standards. By building precise verification standards, user water usage data can be verified, providing users with big data-based water services, especially online quality inspection services for water meters. This quality inspection method can perform testing without disassembling the water meter, avoiding the high manpower and material costs and heavy workload caused by large-scale disassembly, transportation, calibration, and reinstallation in traditional methods, thus reducing the burden on water companies in terms of management and maintenance. Simultaneously, the online verification process does not affect the continuity of water supply, enabling real-time detection and anomaly warnings, reducing economic losses or user disputes caused by metering errors. In other words, the construction of water usage verification standards can help achieve low-cost, high-efficiency, uninterrupted, and high-precision water meter quality testing, thereby improving water service capabilities. The control method proposed in this application will be described below through specific embodiments.

[0060] The method for constructing water data verification standards provided in this application can be applied to electronic devices such as mobile phones, tablets, in-vehicle devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). This application does not impose any restrictions on the specific type of electronic device.

[0061] To illustrate the technical solutions proposed in this application, the following description will use an electronic device as the execution subject to illustrate various embodiments.

[0062] Figure 1 A schematic flowchart illustrating the method for constructing water use data verification standards provided in this application is shown. The method for constructing water use data verification standards includes: Step 110: The electronic device determines whether the water usage characteristics of the specified device are reproducible based on a specified number of target water usage curves.

[0063] Designated equipment typically refers to devices whose water usage characteristics are theoretically statistically stable, meaning that their water usage behavior remains statistically similar across different time periods and can be stably and repeatedly observed, exhibiting good reproducibility. Typical examples include flushing devices in sanitary ware (such as toilets or squat toilets) and washing machines (whose water usage characteristics are basically consistent under the same washing mode). Therefore, testing standards can be constructed based on the typical water usage curves of these devices.

[0064] It is important to note that while washing machines offer a degree of stability in fixed modes, their complete washing process typically involves multiple water injections, and the water volume fluctuates depending on the weight and material of the clothes. This makes establishing a standard water usage curve difficult and complex in practice. Therefore, this application designates a toilet flushing device as the preferred option; and a washing machine is considered a secondary option when a stable toilet flushing curve cannot be obtained or suitable flushing devices are unavailable. Consequently, subsequent examples will primarily use a toilet as an example.

[0065] However, in actual operation, factors such as fluctuations in pipeline pressure, environmental changes, or the degradation of equipment performance may still affect its water usage characteristics, leading to deviations. Therefore, it is considered that the specified equipment is only theoretically reproducible. To ensure the accuracy and reliability of the testing standard, statistical analysis can be performed on multiple target water usage curves of the specified equipment to verify whether its actual water usage characteristics are consistent with its theoretical characteristics, thereby determining whether the testing standard should be constructed based on its water usage curves.

[0066] In practical applications, in order to ensure the stability and representativeness of the statistical analysis results, a specified number of target water use curve samples can be set according to actual needs. The number range can be 20 to 40, for example, 20, 30 or 40.

[0067] It should be noted that the selected target water usage curve should not only originate from the specified equipment but also meet certain quality requirements. For example, the curve should be complete, and its trend should be consistent with the theoretical trend of the specified equipment. Through appropriate screening and verification, it can be ensured that the data involved in the standard construction has sufficient representativeness and statistical reliability, thereby helping to establish a stable, accurate, and reusable testing standard.

[0068] Step 120: When the water usage characteristics are reproducible, the electronic device determines each target water usage curve as the standard water usage curve for verifying the water usage data.

[0069] If statistical analysis verifies that the water usage characteristics of a specified device exhibit repeatability across different time periods, then the device's water usage behavior can be considered statistically stable, both theoretically and practically, and its corresponding target water usage curve can represent the device's normal operating state. A standard water usage curve constructed based on this characteristic can serve as a benchmark for subsequent testing, identifying equipment operational deviations or metering anomalies, thereby enabling relevant water services, especially online inspection and status monitoring of user water meters.

[0070] In this embodiment, the electronic device performs statistical analysis on multiple target water usage curves of any specified device to determine whether the device's water usage characteristics at different times are consistent with its theoretical statistical characteristics, thereby determining its reproducibility. If the analysis results show that the water usage characteristics of the specified device are reproducible, it means that its water usage behavior can be stably reproduced in a statistical sense, and is predictable and representative. At this time, establishing these target water usage curves as the standard water usage curves of the specified device can ensure that the standard is based on a real, stable, and repeatable water usage pattern, avoiding deviations caused by single fluctuations or occasional anomalies, thereby improving the reliability and universality of the standard.

[0071] Based on this standard's construction logic, standard water usage curves can be used to verify the actual collected water usage data to determine the operating status of different water-using devices. Especially in user water meter testing scenarios, this method can effectively replace the traditional disassembly and offline testing process, achieving low-cost, high-efficiency, real-time, and accurate online water meter quality testing.

[0072] In some embodiments, to ensure that the established standard water consumption curves accurately reflect the stable operating characteristics of the equipment and have effective verification significance, target water consumption curves under the specified equipment compliance state must be selected as the basis. Therefore, before the electronic device determines whether the water consumption characteristics of the specified equipment are reproducible based on a specified number of target water consumption curves, the electronic device performs the following operations cyclically until the specified number of target water consumption curves are obtained: Step A1: The electronic device acquires the first water usage data collected after the target user's water meter is installed, and obtains the first water usage curve based on the first water usage data.

[0073] The failure time of user water meters typically occurs after a certain number of years of installation (this varies by region, and is also affected by specific equipment and management methods, e.g., 6 years). Therefore, user water meters installed for a certain period (e.g., less than 3 years) usually do not have metering deviations. Based on this, an installation time threshold can be preset, and user water meters with high metering reliability can be selected as target user water meters based on this threshold. The electronic device acquires the first water usage data collected by the target user water meter, ensuring the accuracy and reliability of the obtained data, meaning that the data is less likely to be affected by abnormal factors of the water meter. Subsequently, the electronic device can generate a first water usage curve based on the acquired first water usage data. With the accuracy of the data guaranteed, the water usage inspection standard constructed based on this first water usage curve can be used as a reliable reverse verification for the quality of water-using equipment, especially user water meters, based on the water usage inspection standard, thereby facilitating the provision of corresponding water services to users.

[0074] The initial water usage data is collected and uploaded by the user's water meter according to regulations. To accurately identify the water usage characteristics of designated devices, a high sampling frequency is required, ranging from [1 Hz, 8 Hz], i.e., data acquisition at the second or even millisecond level. This high-frequency sampling can capture subtle changes during water usage, forming the basis for accurately reflecting the dynamic characteristics of the equipment and achieving water usage characteristic identification.

[0075] Understandably, although electronic devices typically use instantaneous flow rate or water consumption per unit time as the primary basis for water usage characteristic analysis, the water usage measurement parameters in the initial water usage data are not limited to being instantaneous flow rate or instantaneous velocity. They can also be related physical quantities whose values ​​can be calculated and converted to these values, such as water consumption per unit time. In practical applications, due to factors such as equipment cost, sensor structure, and measurement accuracy, instantaneous flow rate or water consumption per unit time is preferred as the water usage measurement parameter. This simplifies the conversion process and improves overall analysis efficiency while ensuring data accuracy.

[0076] The frequency at which electronic devices acquire data can be flexibly set according to actual needs. It can acquire the latest data uploaded by the user's water meter in real time, or it can acquire the first set of water usage data uploaded by the water meter in a time period, thereby ensuring the completeness and timeliness of the analysis.

[0077] It should be noted that this application is based on the assumption that the user's water meter can operate normally according to the established sampling frequency, accuracy, and data upload requirements. In other words, the electronic device constructs, compares, and analyzes water usage curves based on the qualified sampling data provided by the water meter to achieve water usage characteristic identification and anomaly detection for the specified device. How the user's water meter implements underlying functions such as data acquisition, signal processing, and communication upload is not the focus of this application. The innovation of this application lies in the implementation of feature extraction, standard curve construction, and intelligent verification logic based on the acquired water usage data.

[0078] Step A2: The electronic device determines the candidate water use curve corresponding to the specified device from each of the first water use curves.

[0079] It is understandable that the water usage curve generated based on the initial water usage data may include water usage curves from various different devices, such as toilets, washing machines, faucets, and water heaters. To obtain the target water usage curve for a specific device, it is necessary to filter out candidate water usage curves corresponding to that device from the initial water usage curves. Assuming the specified device is a toilet, we can first identify curve segments from the overall water usage curves that match the toilet's usage pattern as candidate objects, providing basic data for subsequent statistical analysis and the construction of standard water usage curves.

[0080] Step A3: The electronic device determines the target water use curve from the candidate water use curves based on preset conditions.

[0081] As can be seen from the foregoing, relying solely on candidate water usage curves from designated equipment is insufficient to construct a stable and reliable testing standard. Therefore, preset conditions can be set according to relevant quality requirements, and target water usage curves that meet the requirements can be selected from candidate water usage curves based on these preset conditions to ensure that the selected curves are representative and reliable.

[0082] It is understandable that if the amount of initial water usage data obtained in a single instance is large enough and the data quality is excellent, steps A1 to A3 above can be completed after one execution. However, to ensure the reliability of the standard construction, the screening requirements are usually quite strict. In most cases, the initial water usage data from a single batch may not be able to obtain the specified number of target water usage curves. Therefore, the above steps can also be executed cyclically, using the cumulative screening of multiple batches of data to finally obtain the target water usage curves that meet the conditions.

[0083] In this embodiment, the electronic device extracts candidate water use curves from the initial first water use curve through hierarchical screening, and then further filters the candidate water use curves to select the target water use curve. By performing this screening process in one or more batches, progressive identification and refinement are achieved, ensuring that the finally selected target water use curve has sufficient representativeness and reliability, providing a solid foundation for building stable and accurate testing standards.

[0084] In some embodiments, in order to obtain a first water usage curve with high accuracy, the electronic device may perform the following operations: Step A11: The electronic device performs curve fitting based on the first water usage data to obtain various fitted curves.

[0085] The electronic equipment first performs curve fitting based on the collected initial water usage data (the fitting of other water usage curves, such as the third water usage curve, is done in the same way, and will not be elaborated further). Specifically, methods such as polynomial fitting, spline interpolation, or moving average can be used to transform discrete water usage data points into continuous fitted curves. For example, when the collected initial water usage data includes flow changes during stages such as water usage, water outages, and subsequent flushing, the fitted curve can more intuitively reflect these trends.

[0086] Step A12: The electronic device performs noise reduction processing on the fitted curve using a preset method to obtain the first water usage curve.

[0087] To eliminate potential noise interference during data acquisition, the electronic equipment can smooth the fitted curve using preset noise reduction methods. Specifically, it can address specific disturbances that may occur at different stages of the data acquisition process. For example, high-frequency vibration noise may be caused by the valve closing during the start and / or end of water filling in a toilet, or periodic disturbances caused by fluctuations in pipe network pressure during the stable water filling phase. The electronic equipment can employ methods such as low-pass filtering, moving average, and wavelet noise reduction for targeted processing. This targeted noise reduction and smoothing process effectively reduces instantaneous spikes and periodic disturbances, making the curve more stable and smoother, and accurately reflecting the actual water usage characteristics of the specified equipment.

[0088] In this embodiment, the electronic device can effectively filter out the discreteness and noise components in the original data by performing curve fitting on the original water use data and denoising the fitting results, thus achieving a smooth transformation from "original data" to "analyzable curve". This lays a more accurate, stable and reliable data foundation for subsequent water use feature extraction and the construction of testing standards.

[0089] In some embodiments, assuming that the water usage curve of a specified device is a trapezoidal pulse, then the candidate water usage curves are candidate trapezoidal pulses. To filter candidate trapezoidal pulses from each of the first water usage curves, the following steps can be used: Step B1: The electronic device filters out independent trapezoidal pulses from the first water curve.

[0090] The initial water usage data acquired by electronic devices is at least second-level instantaneous flow rate / water consumption per unit time, typically including water usage processes from multiple devices at different time periods. Therefore, water usage curves from different devices may partially overlap in time, forming superimposed composite curves. Furthermore, the same device may be triggered consecutively within a short period; for example, a toilet might flush again before completing a single flush, blurring the boundaries between adjacent pulses. Both of these scenarios make it difficult to accurately separate the water usage curve corresponding to a specific device from the overall water usage curve, thus placing higher demands on the subsequent screening and feature extraction of candidate water usage curves.

[0091] Since designated devices are frequently triggered independently in daily life, and their water usage typically exhibits a trapezoidal pulse pattern—comprising distinct rising, stabilizing, and falling phases on the timeline—this characteristic can be leveraged to reduce the complexity of candidate water usage curve selection. Specifically, electronic devices can filter out independent trapezoidal pulses from the first water usage curve based on the trapezoidal pulse morphology and the requirement that adjacent pulse intervals exceed a preset duration. By filtering these independent trapezoidal pulses, the processing of complex, superimposed water usage data can be bypassed, allowing for the efficient and accurate extraction of the water usage curve corresponding to the designated device.

[0092] Step B2: The electronic device deletes independent trapezoidal pulses in the stable phase that contain sudden changes in instantaneous flow rate / water consumption per unit time, and obtains suspected candidate trapezoidal pulses.

[0093] In actual water use, even if the curve obtained through independent trapezoidal pulse screening is generally complete, there may still be sudden changes in instantaneous flow rate / water consumption per unit time during the stable phase, for example, see [reference needed]. Figure 2 Short-term fluctuations in water usage or pipeline pressure from other equipment can cause interference. To eliminate these interferences and improve the reliability of subsequent analysis, the electronic equipment can examine each individual trapezoidal pulse, deleting those containing anomalous instantaneous flow / water consumption abrupt changes during the stable phase, thus obtaining potential candidate trapezoidal pulses. These potential candidate pulses are morphologically closer to the ideal water usage characteristics of the specified equipment, providing cleaner and more reliable data for subsequent target water usage curve screening and standard construction.

[0094] Step B3: The electronic device calculates the total water consumption of each suspected candidate trapezoidal pulse.

[0095] Step B4: Identify the suspected candidate trapezoidal pulses whose total water consumption reaches the standard total water consumption of the specified equipment as candidate trapezoidal pulses.

[0096] Since potential candidate trapezoidal pulses may still contain some interfering pulses, such as water usage from non-designated equipment, it is difficult to completely determine whether they belong to the designated equipment based solely on morphological characteristics. Therefore, the electronic device first calculates the total water consumption corresponding to each potential candidate trapezoidal pulse to quantify the actual water flow characteristics of the pulse. Subsequently, pulses with total water consumption reaching the standard range of the designated equipment are filtered out and identified as candidate trapezoidal pulses. By limiting the total water consumption, not only can pulses with abnormal total water consumption be eliminated, but it also ensures that the remaining candidate pulses conform to the actual water consumption characteristics of the designated equipment in both morphology and magnitude, providing a reliable foundation for the subsequent extraction of target water consumption curves and the construction of standards.

[0097] Given that the specifications of the specified equipment are usually quite uniform—for example, the capacity of a toilet typically ranges from 4 to 8 liters—the standard total water consumption used for verification can be determined based on this capacity range. Of course, if a more precise standard total water consumption can be obtained from the relevant information of the specified equipment, the accuracy of the verification results can be further improved.

[0098] In this embodiment, through the screening of independent trapezoidal pulses, the identification of suspected candidate trapezoidal pulses, and the final screening of candidate trapezoidal pulses, the electronic device can progressively eliminate composite pulses, abnormal spikes, and pulses with abnormal total water consumption. This allows for the efficient extraction of water consumption curves that highly match the specified device from complex water consumption data. This hierarchical screening process not only ensures that the extracted pulses conform to the characteristics of the specified device in terms of both morphology and total water consumption, but also effectively reduces the impact of interference factors on subsequent feature analysis and standard construction, providing a solid data foundation for building stable, reliable, and representative testing standards.

[0099] In some embodiments, the preset conditions include preset anomalies; thus, in order to further improve the quality of the target trapezoidal pulse, the electronic device may also perform the following operations: Step C1: The electronic device determines the abnormal trapezoidal pulse from each candidate trapezoidal pulse based on the abnormal characteristics corresponding to the preset abnormality.

[0100] Step C2: The electronic device filters out abnormal trapezoidal pulses from each candidate trapezoidal pulse to obtain the target trapezoidal pulse.

[0101] Although steps A12-A13 described above can reduce noise in some abnormal features caused by environmental changes, some abnormal features may still remain. To further ensure the accuracy of the target trapezoidal pulse determination, the electronic equipment can preset abnormality types, including equipment failure, equipment anomaly, environmental anomaly, and data anomaly. Among these, data anomaly refers to abnormal data features caused by data acquisition, transmission, or processing. These anomalies may be caused by equipment or environmental anomalies or may exist independently. In practical applications, anomalies caused by equipment failure are common.

[0102] Equipment failures include at least leaks from other equipment and various other possible failure types for the specified equipment. By extracting the abnormal features corresponding to these preset anomalies, these features can be understood as curve characteristics that cause abnormal changes in the trapezoidal pulse shape of the specified equipment after a failure occurs. Based on this, electronic equipment can use these abnormal features to identify and eliminate abnormal trapezoidal pulses from candidate trapezoidal pulses, thereby obtaining the target trapezoidal pulse free from fault interference. This provides more accurate data for subsequent water usage characteristic analysis and health status assessment.

[0103] In some embodiments, when the designated device includes a flushing device for sanitary ware, specifically taking a toilet as an example, the determination of abnormal trapezoidal pulses is achieved through the following steps: Step C11: For each candidate trapezoidal pulse, if the electronic device determines that there is an abnormality in the stable phase and / or changing phase of the candidate trapezoidal pulse, the corresponding candidate trapezoidal pulse is identified as an abnormal trapezoidal pulse.

[0104] SeeFigure 3 The trapezoidal pulse of a toilet typically consists of a changing phase and a stable phase (including rising and falling phases). Different types of faults will affect the curve characteristics of different phases. For example, a slight leak in other equipment may cause abnormal fluctuations in the amplitude of instantaneous flow rate / water consumption per unit time during the stable phase, while an aging toilet valve may prolong the duration of the changing phase. For these cases exhibiting abnormal characteristics in different phases, the electronic equipment can identify the corresponding candidate trapezoidal pulses as abnormal trapezoidal pulses, thereby achieving effective identification and differentiation of fault states.

[0105] In some embodiments, in order to accurately determine whether there are anomalies in different stages of a candidate trapezoidal pulse, the electronic device may perform the following operations: Step C111: If the difference between the attribute value in the stable phase and the normal attribute value is greater than a preset threshold, the electronic device determines that there is an anomaly in the stable phase and / or changing phase of the candidate trapezoidal pulse.

[0106] During the analysis of candidate trapezoidal pulses, different types of faults will have specific effects on different stages of the trapezoidal pulses and their attribute values. By analyzing these patterns of change, electronic devices can accurately identify and eliminate abnormal pulses based on reasonable inferences rather than empirical judgments, thereby ensuring that the data used for feature analysis and standard construction is purer and more reliable.

[0107] For example, the impact of minor leaks in other equipment or slight water leakage in the specified equipment itself is mainly reflected in the steady-state phase of the trapezoidal pulse. Under normal circumstances, the steady-state phase should be characterized by stable flow rate, small variance, and constant amplitude. However, when a leak is present, the instantaneous flow rate / water consumption per unit time before and after water injection may not return to zero, resulting in continuous small flow values ​​during the pulse intervals, while the average flow rate during the steady-state phase will decrease slightly.

[0108] For example, see Figure 4 If the pulse start point is not zero and the actual steady-state flow amplitude is lower than the theoretical steady-state flow amplitude (e.g., by about 5%), it indicates that leakage flow persists, and a minor leak can be considered to exist. Although this type of anomaly does not significantly disrupt the pulse pattern, it can lead to distortion of energy consumption statistics and standard samples, and therefore should be identified as an abnormal trapezoidal pulse.

[0109] For example, if slight flow fluctuations, repetitive small pulses, or irregular intervals occur during the steady-state phase, it may indicate a malfunction in the toilet control mechanism. In this case, the standard deviation of the data during the steady-state phase often increases beyond a certain threshold, such as exceeding 50% in severe cases. This confirms an abnormal response from the valve or control signal. Similarly, when the valve seat is worn or the float is misaligned, the duration of the steady-state phase of the pulse will be significantly prolonged, even resulting in prolonged water flow. This anomaly will cause the entire water usage process to no longer conform to the time-domain characteristics of an independent trapezoidal pulse, and should also be considered an abnormal trapezoidal pulse and discarded.

[0110] For example, when a blockage occurs, the rise phase of the pulse response becomes slow. Because the water flow is obstructed, the process of increasing flow velocity is prolonged, resulting in a significantly longer rise time and a reduced slope. See, for example, [reference needed]. Figure 5 When the duration of the rising phase increases (assuming an increase of 30%) and the steady-state average flow amplitude decreases (assuming a decrease of 30%), it can be considered that there is a blockage problem in the pipeline. Although such pulses still retain their complete form, their amplitude is reduced and the flow rate is insufficient, so they do not have the flow characteristics of the standard specified equipment.

[0111] For example, valve aging typically manifests as a prolonged response time during the rising or falling phase, while the flow amplitude change during the steady phase is not significant. Even if the peak flow rate remains normal, the lag in valve action will lengthen the change phase time at both ends of the pulse, such as increasing the rise time from 0.3 seconds to 1.5 seconds. Although the overall shape of such pulses is intact, their dynamic response characteristics have deviated from the standard and will be discarded as abnormal trapezoidal pulses of the "valve aging" category.

[0112] As illustrated by the examples above, faults such as minor leaks, control malfunctions, blockages, and valve aging can be visually represented by altering the attribute values ​​of each stage of the trapezoidal pulse. For the stable stage, attributes include the amplitude, standard deviation, and duration of instantaneous flow rate / water consumption per unit time; for the changing stage, attributes include the slope and duration of the flow rate change. Alternatively, a comprehensive judgment can be made by combining the attribute values ​​that may change in both stages. These attributes are then compared with pre-calibrated or estimated (based on statistically derived relevant characteristics) normal attribute values. When the attribute difference in any stage exceeds a preset threshold, it indicates that the water consumption characteristics of that stage have deviated from the normal pattern. The electronic equipment thus determines that there is an anomaly in the corresponding stage of the candidate trapezoidal pulse, providing a basis for identifying the fault type.

[0113] In this embodiment, by analyzing the impact of different fault types on the attribute values ​​of each stage (stable stage and / or changing stage) of a trapezoidal pulse, a correspondence between faults and stage-specific attribute changes can be established. Based on this, the electronic device can utilize the characteristic changes caused by these faults to compare with calibrated / estimated normal attribute values, achieving verifiable anomaly identification from a data perspective. For example, the electronic device can calculate the amplitude, standard deviation, and duration of the stable stage, and the rising slope and duration of the changing stage, and perform difference analysis with normal attribute values ​​to determine whether the pulse is abnormal. If the attribute deviation of any stage exceeds a preset threshold, the pulse can be identified as being affected by a fault and deleted. Through this method, the electronic device can remove unrepresentative abnormal pulses from the overall data, retaining only the target trapezoidal pulses that meet the stability and integrity requirements, thereby making fault determination more verifiable and data-driven, significantly reducing the false positive rate, and improving the reliability and accuracy of subsequent feature extraction and verification standard construction.

[0114] In some embodiments, it is important to note that different types of faults have varying degrees of impact on the water usage curve: some faults only affect a single, independent trapezoidal pulse, such as valve aging or blockage altering the pattern of a single water injection cycle; while other faults span multiple pulses, manifesting as abnormal intervals between adjacent trapezoidal pulses. For the latter, the electronic device may perform the following operations: Step C12: In the case of multiple consecutive candidate trapezoidal pulses with approximately the same pulse interval, the electronic device determines each candidate trapezoidal pulse as an abnormal trapezoidal pulse.

[0115] For intermittent water injection faults caused by poor valve body sealing, the fault will span multiple pulses, manifesting as abnormal intervals between adjacent trapezoidal pulses.

[0116] Taking a toilet as an example, when the control valve malfunctions and seals poorly, even without user intervention, the water level will drop, automatically triggering water replenishment and creating multiple regularly repeating trapezoidal pulses on the water usage curve. For instance, every 10-15 minutes, a trapezoidal pulse representing a complete process of rising, stabilizing, and falling phases will appear on the curve. If there is no other water usage between pulses, such regular pulse intervals will occur. Since users typically use the toilet irregularly with longer intervals, this situation can be considered an abnormal pattern in the device's automatic water replenishment. Furthermore, a sustained low-flow tail, such as 0.05-0.2 L / s, may appear after each drop, manifesting as a non-zero baseline deviating from zero. Based on this, electronic equipment can identify and determine these abnormal trapezoidal pulses by detecting multiple candidate trapezoidal pulses with approximately similar intervals, thus effectively distinguishing intermittent water filling caused by poor valve sealing.

[0117] In this embodiment, in addition to focusing on independent faults affecting a single trapezoidal pulse, a global perspective is also taken into account correlated faults affecting multiple trapezoidal pulse intervals, enabling the fault detection logic to cover a wider range of anomaly types. By considering both types of anomaly characteristics, the electronic device can not only promptly identify local inaccuracies caused by abnormal single pulse morphology, but also capture latent equipment faults reflected by rhythmic disturbances between pulse sequences, thereby significantly improving the comprehensiveness and accuracy of abnormal trapezoidal pulse filtering.

[0118] In some embodiments, after obtaining a sufficient number of accurate and reliable target water usage curves, the electronic device may perform the following steps: Step D1: The electronic device extracts the digital feature values ​​of the water use curves of each target.

[0119] After obtaining a sufficient number of accurate and reliable target water usage curves, the electronic equipment first digitizes these curves, extracting digital feature values ​​for each curve, such as peak value, average flow rate, slope, duration, and standard deviation. Through digitization, the originally continuous and complex flow curves are transformed into quantifiable and comparable numerical features, standardizing comparisons between different curves and improving operability, thereby providing an objective basis for subsequent consistency judgments.

[0120] Step D2: The electronic device determines whether each digital feature value is consistent.

[0121] After extracting the digital features, the electronic device further determines whether the values ​​of each digital feature are consistent. The quantitative nature of the digital features allows for the accurate assessment of differences in water usage curves for different targets through statistical analysis, error measurement, or threshold judgment, thereby effectively identifying abnormal pulses or single fluctuations and ensuring the reliability and scientific validity of the comparison results.

[0122] Step D3: When all digital feature values ​​are consistent, the electronic device determines whether the water usage characteristics are reproducible.

[0123] Once all digital characteristic values ​​are confirmed to be consistent, the electronic device can further determine whether the water usage characteristics of the specified device are reproducible. Through digital analysis, not only can the impact of occasional anomalies or short-term fluctuations be eliminated, but the stability and repeatability of water usage characteristics over different time periods can also be ensured, providing a solid basis for constructing standard water usage curves.

[0124] In this embodiment, the electronic device, through digital processing and subsequent comparison and reproducibility determination, enables the entire process to achieve high-precision, quantifiable and automated analysis from the original curve to a reliable standard. This ensures that the standard water usage curve can not only truly reflect the water usage behavior of the equipment, but also guarantee the accuracy and reliability of subsequent user water meter detection.

[0125] In some embodiments, the digital characteristic values ​​include global characteristic values. When the specified device is defined as a flushing device for sanitary ware such as a toilet, its water usage curve exhibits a trapezoidal pulse shape. Specifically, the global characteristic values ​​include the total water injection volume and the total water injection duration. In this case, the electronic device will perform the following operations: Step D111: The electronic device performs an integration operation on each target trapezoidal pulse to obtain the corresponding total water injection volume.

[0126] Step D112: The electronic device determines the pulse duration corresponding to each target trapezoidal pulse as the corresponding total water injection duration.

[0127] The electronic device first performs an integration operation on each target trapezoidal pulse to calculate the total water injection volume for each pulse. This integration operation transforms the continuously varying instantaneous flow rate / water consumption per unit time curve into a single numerical feature, quantifying the water consumption per unit time for each injection process and providing a directly quantifiable basis for comparing different pulses. Subsequently, the electronic device extracts the duration of each target trapezoidal pulse, determining it as the total injection duration for each pulse. The statistical analysis of duration also transforms the continuous time-dimensional curve information into a quantifiable feature, allowing for direct comparison and analysis of the durations of different pulses, thereby further supporting the assessment of consistency and stability.

[0128] In this embodiment, the electronic device can transform the originally complex and continuous instantaneous flow rate / water consumption per unit time curve into quantifiable digital global features, including total water injection volume and total water injection duration. This digital processing not only facilitates comparison between different trapezoidal pulses, but also provides a reliable quantitative basis for subsequent judgment of the consistency and reproducibility of water consumption characteristics, thereby ensuring that the constructed standard water consumption curve can accurately and stably reflect the real water consumption characteristics of the specified device.

[0129] In some embodiments, the digital feature value includes a stage feature value, and the stage corresponding to the stage feature value includes a change stage and a stable stage for instantaneous flow rate / water consumption per unit time; at this time, the electronic device will perform the following operations: Step D121: For the change phase, the electronic device determines the change duration and dynamic change characteristic value of the corresponding change curve.

[0130] Step D122: For the stable phase, the electronic device determines the peak value, average value, and root mean square error of the corresponding stable curve.

[0131] For each trapezoidal pulse, the electronic device extracts corresponding stage feature values ​​for different stages. Specifically, for the changing stage, the electronic device first analyzes the change curve of instantaneous flow rate / water consumption per unit time, calculates its change duration, and further extracts feature values ​​reflecting dynamic changes, such as slope or exponential change parameters, to quantify the water consumption dynamics of the rising and falling stages. For the stable stage, the electronic device analyzes each instantaneous flow rate / water consumption per unit time to extract peak values ​​and calculates features such as average value and root mean square error to describe the amplitude level and fluctuation of the stable water injection stage, thereby fully characterizing the behavioral characteristics of the stable stage.

[0132] In this embodiment, by extracting stage feature values ​​for the changing and stable stages respectively, the electronic device can decompose the continuous instantaneous flow rate / water consumption per unit time curve into quantifiable stage indicators. This not only facilitates the comparison of differences between different trapezoidal pulses in each stage, but also provides a more detailed and reliable data foundation for subsequent judgment of the reproducibility of water consumption characteristics, thereby improving the accuracy and representativeness of the standard water consumption curve construction.

[0133] In some embodiments, during the change phase, in order to effectively reduce interference from irrelevant factors and obtain highly accurate digital feature values, the electronic device may perform the following operations: Step D1211: The electronic device obtains an effective change curve by performing boundary clipping on the change curve.

[0134] Step D1212: The electronic device determines the duration of change and the dynamic change characteristic value based on the effective change curve.

[0135] To effectively reduce the interference of irrelevant factors in the calculation of digital feature values, electronic equipment first performs boundary clipping on the curves when processing curves during the change phase. Boundary clipping is necessary because at the beginning and end of the change phase, the curve is often susceptible to various non-target factors, such as sensor jitter, instantaneous pressure fluctuations in the pipe network, short-term rises or falls in other water-using equipment, and instantaneous anomalies during data acquisition. These anomalies may cause spikes, abrupt changes, or tailing in the instantaneous flow / water consumption per unit time curve, thus affecting the duration of change and the accuracy of dynamic feature values. Directly using the untrimmed, complete curve to calculate digital feature values ​​may introduce noise, causing the feature values ​​to deviate from the actual water consumption characteristics, reducing their stability and repeatability.

[0136] After removing the disturbed start and end segments through boundary trimming, the resulting effective variation curve more accurately reflects the dynamic water usage characteristics of the specified equipment during actual use. On this effective curve, if the variation curve exhibits a linear change, its dynamic variation characteristic value can be represented by the slope; if the variation curve exhibits a non-linear change (such as exponential growth or decay), the dynamic variation characteristic value is represented by the decay time constant of instantaneous flow rate / water consumption per unit time.

[0137] In this embodiment, by clipping the boundary of the change curve and distinguishing the type of change curve, the electronic device can obtain more stable, accurate and statistically significant digital feature values, providing a reliable data foundation for subsequent water use feature identification, inspection standard construction and fault detection, while reducing the possibility of misjudgment and improving the accuracy and robustness of the entire detection system.

[0138] In some embodiments, the digital features include global feature values ​​and stage feature values. Based on this, the electronic device determines whether the individual digital feature values ​​are consistent through the following steps: Step D211: The electronic device analyzes each global feature value and each stage feature value based on the similarity measurement method to determine whether each global feature value has relative consistency and whether each stage feature value has relative consistency.

[0139] In the process of analyzing digital feature values, when standard data is lacking as an absolute reference—for example, when the aforementioned standard total water consumption is determined based on conventional capacity or normal attribute values ​​are estimated based on relevant data—electronic devices can use similarity measurement methods to determine whether the feature values ​​are consistent. Specifically, for global and stage feature values, electronic devices can use statistical feature clustering to group feature values ​​with similar characteristics into one category to determine whether there is a significant deviation; they can also use relative deviation comparison to compare each feature value with the overall mean or median to assess its degree of deviation; and they can construct consistency indices to integrate the fluctuation range, standard deviation, or correlation of each feature value into a numerical indicator to determine whether the feature values ​​are generally consistent. Through these similarity measurement methods, even in the absence of standard reference data, the consistency between digital feature values ​​can be objectively assessed, thus providing a basis for reproducibility judgment.

[0140] It is worth noting that global characteristic values ​​are typically used as absolute standards to reflect the overall water usage behavior of a specified device, such as total water injection volume and total injection duration. Stage characteristic values, on the other hand, involve more parameters, including extreme points, inflection points, slopes, mean, and standard deviations, and are used to characterize the detailed features of the water usage curve at each stage. When the amount of data for stage characteristic values ​​is large or the range of variation is wide, directly comparing all parameters strictly to the standard may lead to an overly stringent standard, easily excluding legitimate water usage curves within the normal fluctuation range.

[0141] To balance this issue, the consistency of characteristic values ​​at each stage can be comprehensively evaluated by setting reasonable tolerance ranges, weight allocations, or employing statistical methods (such as confidence intervals, standardized deviations, and cluster analysis). This ensures that the digital characteristic values ​​reflect real water use behavior overall while also taking into account the normal range of periodic fluctuations, thereby ensuring that the established water use characteristic standards are both scientifically reliable and have practical application value.

[0142] Accordingly, when all global feature values ​​are relatively consistent and the features at each stage are relatively consistent, the electronic device can determine that all digital feature values ​​are consistent.

[0143] In this embodiment, when standard data is lacking, the electronic device uses a similarity measurement method to determine the consistency of stage / global feature values, thereby obtaining stable, reliable, and statistically significant feature information. This not only reduces the impact of noise and occasional anomalies on the results but also ensures the reproducibility of the final water usage characteristics, providing a solid data foundation for subsequent standard water usage curve construction, fault identification, and water meter testing, thus achieving efficient, accurate, and verifiable user water meter quality monitoring.

[0144] In some embodiments, the digital features include global feature values ​​and stage feature values. If a reference standard value can be quantified by acquiring the attribute information of a specified device, then the electronic device can perform the following steps: Step D221: The electronic device determines whether each global feature value falls within the preset first deviation range.

[0145] Step D222: The electronic device determines whether the characteristic values ​​of each stage fall within the preset second deviation range.

[0146] Step D223: When all global feature values ​​fall within the first deviation range and all stage feature values ​​fall within the second deviation range, the electronic device determines that all digital feature values ​​are consistent.

[0147] After obtaining the attribute information of the specified device, the electronic device can further quantify the reference standard value, that is, the standard range corresponding to the data to be judged, so as to achieve accurate comparison of digital feature values.

[0148] Specifically, for global feature values, the electronic device determines whether they fall within a preset first deviation range, verifying whether overall parameters such as total water injection volume and total injection duration are consistent with the corresponding standard range, thereby ensuring the rationality of overall water usage behavior. Next, for stage feature values, the electronic device determines whether they fall within a preset second deviation range. This range is used to assess the detailed differences between the changing and stable stages, such as whether the slope, peak value, and root mean square error are within normal fluctuation ranges, to ensure the stability and integrity of the curve shape. Finally, if both global and stage feature values ​​meet their respective deviation range requirements, the electronic device can determine that all digitized feature values ​​are consistent.

[0149] In this embodiment, the electronic device achieves feature comparison at both the macro and micro levels: ensuring the conformity of the overall water use characteristics while also taking into account the accurate matching of local changes. Thus, without relying on a large amount of manual calibration, it obtains a highly reliable identification result of the water use curve of the specified device, thereby significantly improving the automation and accuracy of the standard judgment.

[0150] In some embodiments, as the specified equipment is used over time, its internal components inevitably experience varying degrees of performance degradation or aging. However, when the degree of aging has not yet reached the threshold requiring replacement, the water usage characteristics of the equipment may have already shown a slight shift. In order to extend the service life of the specified equipment, how to enable the existing inspection standards to dynamically adapt to changes in the equipment's condition becomes a key issue in standard maintenance and long-term application.

[0151] To address this issue, after determining the target water usage curves as the standard water usage curves for verifying water usage data, the electronic device can perform the following steps: Step E1: The electronic equipment constructs an aging model based on the water usage curves corresponding to the second water usage data.

[0152] First, the electronic equipment collects secondary water usage data under different usage cycles and extracts the corresponding water usage curves to construct an equipment aging model. This model can reflect the characteristic change trends of the equipment at different aging stages, such as a decrease in the flow amplitude during the steady-state stage due to a decline in valve sealing performance, or a prolonged rise time caused by a slow float response.

[0153] Step E2: The electronic device determines the adjustment value based on the device aging model.

[0154] Subsequently, the electronic equipment will determine adjustment values ​​based on the equipment aging model, which are parameters reflecting the degree of deviation in water usage characteristics. For example, when the average flow rate during the stable phase decreases by 5% compared to the standard curve, the electronic equipment can automatically calculate the corresponding correction factor.

[0155] Step E3: The electronic device optimizes the standard water usage curve based on the adjustment value.

[0156] Finally, the electronic equipment uses this adjustment value to optimize the existing standard water usage curve, so that the standard curve can be dynamically corrected as the equipment ages.

[0157] In this embodiment, based on the construction of a specified equipment aging model, the inspection standard not only has adaptability, but also maintains inspection accuracy when the equipment is aged but still usable, avoiding misjudgment or omission due to aging, thereby extending the effective service life of the equipment and improving the overall intelligence level of the water system.

[0158] In some embodiments, the pressure of the water supply network typically fluctuates across different seasons due to factors such as temperature changes, peak water usage, or regional scheduling. These pressure variations directly affect the amplitude and duration of the water usage curve, leading to distorted test results. To ensure the accuracy and consistency of water usage data testing, the electronic equipment can perform the following steps: Step F1: The electronic device determines the seasonal identifier of the standard water use curve based on the first season to which the first water use data belongs.

[0159] Step F2: The electronic device constructs a new standard water usage curve based on the water usage data of the second season and determines the corresponding seasonal identifier.

[0160] When performing water usage data verification, the electronic device first determines the corresponding seasonal identifier based on the season in which the water usage data was collected. For example, if the electronic device detects that a set of water usage data was collected in January, it will automatically determine that it belongs to winter and select or establish a corresponding winter verification standard accordingly. Subsequently, the electronic device will also construct a standard water usage curve based on historical water usage data from other seasons (such as summer, autumn, or spring), assigning an independent seasonal identifier to each season. This ensures that the electronic device has a water usage reference model that adapts to different climatic conditions throughout the year. For example, the summer curve may reflect the peak water usage trend caused by rising temperatures and increased water demand.

[0161] Step F3: During the water usage data verification process, the electronic device determines the target standard water usage curve from the constructed standard water usage curves based on the third season corresponding to the water usage data to be tested; the seasonal identifier of the target standard water usage curve matches the third season. Based on seasonal indicators, the testing standards are established. During actual testing, electronic equipment can automatically match the target standard water consumption curve corresponding to the seasonal indicator of the water consumption data to be tested for comparative analysis. By dynamically matching standards according to the season, the electronic equipment can avoid misjudgments caused by directly comparing low water consumption in winter with high water consumption in summer, thus achieving more accurate testing.

[0162] In summary, the dynamic verification mechanism based on seasonal characteristics can effectively offset seasonal fluctuations caused by climate change or differences in user water usage habits, significantly improve the accuracy and reliability of water usage data verification, and provide more robust data support for subsequent work such as anomaly detection, leak identification, and billing verification.

[0163] In this embodiment, the electronic device can dynamically adjust water usage inspection standards according to seasonal changes, enabling precise seasonal inspection of water usage data. This effectively eliminates the impact of seasonal fluctuations caused by differences in climate, temperature, or user behavior on the inspection results, significantly improving the accuracy and reliability of water usage data inspection. This provides a more credible basis for applications such as anomaly detection, leak analysis, or billing verification.

[0164] In some embodiments, it is understandable that during the process of verifying the reproducibility of each target water consumption curve, some target water consumption curves may fail to be reproducible due to occasional equipment failures or other accidental interference factors. In such cases, if a majority (e.g., more than 60%) of the target water consumption curves still meet the reproducibility requirements, curves that are not reproducible can be preferentially removed, and the process of acquiring the target water consumption curves can be returned to supplement new data samples. If the reproducibility rate further improves in the supplemented samples (e.g., reaching 80%), this process can continue to be repeated until all target water consumption curves reach a stable and consistent reproducibility standard. Through this dynamic screening and cyclic correction mechanism, the construction of standard water consumption curves can be gradually improved while ensuring data reliability, ensuring that the final standard has high representativeness and repeatability.

[0165] Based on the operations described in the foregoing embodiments, reproducible target water usage data can be obtained. This target water usage curve not only accurately reflects the typical water usage characteristics of a specified device under normal operating conditions but also serves as a core benchmark for subsequent water usage data comparison and verification. Based on this, after the electronic device determines these target water usage data as the standard curve for water usage data, it can then perform real-time verification of the user's water usage data and provide corresponding water services.

[0166] It should be understood that the water usage data verification method described in this application is not limited to being performed by electronic devices. For some detection steps with relatively low computational load, they can also be directly implemented by the user's water meter, thereby reducing the system's computational load and improving overall operating efficiency while meeting the detection accuracy requirements.

[0167] In some embodiments, Figure 6 This is a flowchart illustrating the process of electronic equipment verifying water usage data, specifically including: Step 610: After the standard water usage curve is constructed, the electronic device acquires the third-party water usage data.

[0168] Step 620: The electronic device obtains the third water use curve based on the third water use data.

[0169] Step 630: The electronic device determines the water usage curve to be tested corresponding to the designated device from each of the third water usage curves.

[0170] After constructing the standard water usage curve, the electronic device acquires new water usage data, i.e., third-party water usage data, and generates a third-party water usage curve based on this data. Subsequently, the water usage curve to be tested corresponding to the specified device is selected from the third-party water usage curves for subsequent water usage detection and analysis.

[0171] The method for acquiring the water usage curve to be tested can be flexibly selected according to management needs and application scenarios. For example, if acquisition is carried out periodically according to management requirements, the electronic device can collect third-party water usage data from user water meters within a preset period, such as collecting water usage data for one week consecutively every month as third-party water usage data, and then generate the corresponding third-party water usage curve to determine the water usage curve to be tested. For example, if a real-time acquisition method is used, user water meters can upload the real-time collected water usage data as third-party water usage data to the electronic device. Upon receiving the data, the electronic device immediately processes it to generate a third-party water usage curve and extracts the water usage curve to be tested when available.

[0172] Whether periodic or real-time data collection is used, as long as the water usage curve to be tested can be obtained, it can be used as input for subsequent analysis. Specifically, the third-party water usage curve drawn by electronic devices based on third-party water usage data can reflect the time-varying trend of actual water usage, and at least one water usage curve corresponding to a specified device can be selected from multiple third-party water usage curves as the water usage curve to be tested. For example, when the specified device is a toilet, at least one toilet water usage curve will be selected as the water usage curve to be tested for subsequent targeted analysis and identification.

[0173] It is understood that the water usage curve to be tested should at least be a complete and independent water usage curve, equivalent to the aforementioned candidate water usage curve. This requirement helps ensure that, during inspection and comparison, non-standard water usage curves of the designated equipment that may be affected by interference or abnormal operation are effectively distinguished from standard water usage curves of the designated equipment that conform to normal usage characteristics. By using a complete and independent water usage curve as the comparison object, electronic equipment can more accurately identify whether water usage characteristics meet preset standards, thereby improving the accuracy and reliability of anomaly detection, while avoiding misjudgments caused by superimposed water usage or incomplete water usage processes.

[0174] Step 640: The electronic device verifies the water usage curve to be tested based on the standard water usage curve, and provides water services to the user based on the obtained water usage test results.

[0175] After obtaining the water usage curve to be tested, the electronic device compares it with the previously constructed standard water usage curve. By analyzing the differences between the two in key characteristics such as peak value, flow rate variation period, volatility, and duration, the electronic device can derive the corresponding water usage detection result. This result can be either a one-to-one comparison between each water usage curve to be tested and each standard water usage curve, or an overall matching result between the water usage curve to be tested and a comprehensive reference curve obtained by fusing multiple standard curves. This not only addresses the variability of individual water usage behaviors but also improves the stability and robustness of the detection in complex or variable water usage environments, making the detection results more representative and reliable. Finally, the electronic device can provide users with corresponding water services based on the detection results, such as push notifications for leaks, water usage optimization suggestions, abnormal bill alerts, and detection and recovery of suspected faulty water meters.

[0176] In this embodiment, based on the establishment of an accurate and stable standard, the electronic device achieves a complete closed loop from data acquisition, curve generation, feature matching to result feedback. Through automatic verification based on the standard water usage curve, the electronic device can not only continuously monitor the water usage status of the equipment, but also dynamically discover potential problems, significantly improving the intelligence level and refinement of water management, and providing strong support for users to save water resources and improve the safety of equipment use.

[0177] In some embodiments, water services may include user water meter quality inspection services, and accordingly, electronic devices may obtain inspection results through the following operations: Step G1: The electronic device determines whether the water usage curve to be tested is similar to the standard water usage curve.

[0178] Step G2: If the water usage curve to be tested is similar to the standard water usage curve, the electronic device determines that the user's water meter has passed the quality inspection during use.

[0179] During this process, the electronic equipment first performs a similarity analysis between the water consumption curve to be tested and a pre-constructed standard water consumption curve. This analysis can employ various methods, such as graphical similarity comparison, which measures the degree of matching by calculating the deviation of the instantaneous flow rate / water consumption per unit time on the time axis between the two curves; comparison of basic characteristic values, such as total injection volume, injection duration, and the mean, peak value, and slope of characteristic values ​​at each stage; and indicators representing the correlation between basic characteristic values, such as the slope relationship or time ratio between the changing and stable stages. Of course, a comprehensive assessment of the similarity between the water consumption curve to be tested and the standard curve can also be used to provide a quantitative basis for subsequent judgments.

[0180] Assume the electronic device extracts relevant feature values ​​based on the target water usage curve of the toilet. For the water usage curve to be detected, the electronic device first compares each feature value with the mean ± 3σ range of historical qualified data to determine if any anomalies exist.

[0181] For example, during analysis, graphical similarity comparison can be performed, such as by calculating the correlation coefficient or dynamic time warping (DTW) distance between the curve to be detected and the standard curve. If the similarity is lower than a preset threshold, it is marked as an anomaly. Secondly, for global feature values, such as total injection volume and injection duration, if any one of them exceeds the mean ± 3σ range, it is marked as an anomaly. Thirdly, considering the differences between stage eigenvalues, such as the ratio of the slope of the rising stage to the flow rate of the steady stage, or the proportional relationship between features of each stage, if the relationship with the standard curve deviates from the set threshold, it will also be marked as an anomaly.

[0182] In other words, through multi-dimensional comparison, electronic devices can not only detect abnormalities in individual parameters, but also discover inconsistencies in the overall water usage curve shape or the relationship between features, thereby more accurately identifying potential toilet malfunctions or abnormal water usage, providing a reliable basis for subsequent water management.

[0183] If the water usage curve to be tested is confirmed to be similar to the standard water usage curve, it indicates that any equipment is working properly. At this point, the electronic equipment can determine that the user's water meter has passed the quality inspection during use.

[0184] In this embodiment, the advantage of this inspection process is that it can quantitatively compare and verify actual water usage data in real time based on a reliable standard curve, thereby accurately identifying whether the water meter has any abnormalities or malfunctions, significantly improving the accuracy and efficiency of quality inspection, and providing a scientific and quantifiable basis for water management.

[0185] In some embodiments, the water usage curve corresponding to the specified device is a trapezoidal pulse; the water usage curve to be tested is a trapezoidal pulse to be tested; the standard water usage curve is a standard trapezoidal pulse; the trapezoidal pulse includes a stable phase; determining whether the water usage curve to be tested is similar to the standard water usage curve includes: Step H1: The electronic device extracts the digital features to be detected from the trapezoidal pulse to be detected; compares the digital features to be detected with the standard digital features of the standard trapezoidal pulse; and / or, in the stabilization phase, determines multiple differences between the instantaneous flow rate / water consumption per unit time of the trapezoidal pulse to be detected corresponding to multiple specified time intervals and the instantaneous flow rate / water consumption per unit time of the corresponding standard trapezoidal pulse.

[0186] Similar to the method of extracting and comparing digital features of standard trapezoidal pulses in the standard construction phase, in this embodiment, the electronic device can extract corresponding digital features from the trapezoidal pulse to be detected. These digital features include global features (e.g., total water consumption, water usage duration) and stage-specific features (e.g., duration of stable and changing stages, root mean square error of the stable stage, attribute values ​​of the changing stage). By extracting and quantifying these features, the morphological characteristics and dynamic changes of the trapezoidal pulse to be detected can be fully characterized. Subsequently, the electronic device can compare the trapezoidal pulse to be detected with the standard trapezoidal pulse item by item based on each digital feature, determining whether they are consistent or whether their differences are within a preset allowable range, thereby achieving an accurate assessment of the similarity between the curve to be detected and the standard curve.

[0187] Besides comparing digital features, a judgment can also be made by comparing the differences in data during stable phases. Specifically, electronic devices at multiple specified time intervals... Compare instantaneous flow rate or total water consumption. For example, the formula for calculating the difference in instantaneous flow rate is: When calculating total water consumption using an integral method, it can be expressed as:

[0188] The resulting difference sequence This reflects the difference distribution between the curve to be detected and the standard curve during the stable phase. Through this step, the electronic device converts the continuous curve data into quantitative features and numerical differences, providing a basis for subsequent similarity determination.

[0189] It is understandable that the above two methods can be used individually or in combination to improve the reliability and robustness of the judgment results. When the two methods are used in combination, electronic devices can first perform preliminary screening based on feature consistency, and then perform secondary verification through difference or error statistics, thereby improving the accuracy and stability of the comparison results while ensuring computational efficiency. This combined judgment mechanism can take into account both local features and overall errors, ensuring that the similarity judgment is both sensitive and anti-interference, and is more suitable for water use curve consistency detection under different operating environments.

[0190] Step H2: If the digitized feature to be detected is consistent with the standard digitized feature, and / or multiple differences fall within the preset difference range; or if the digitized feature to be detected is consistent with the standard digitized feature, and / or the root mean square error or mean absolute difference corresponding to multiple differences is less than the preset threshold, determine that the trapezoidal pulse to be detected is similar to the standard trapezoidal pulse.

[0191] By comparing various digital features, if the comparison results are consistent, then when only digital features are used to compare the curve to be tested and the standard curve, it can be concluded that the water use curve to be tested is similar to the standard water use curve.

[0192] However, if the comparison is based on the difference series of instantaneous flow rate or water consumption per unit time under steady-state conditions, it can be achieved in two ways. That is, the root mean square error (RMSE) or mean absolute difference (MAE) can be used as a similarity measure, and the specific calculation formula is as follows:

[0193]

[0194] Accordingly, if only the difference sequence of instantaneous flow rate or water consumption per unit time under steady-state conditions is used for comparison, then when or When the overall deviation between the test curve and the standard curve is considered to be small and the consistency is good, it can be concluded that the test water curve and the standard water curve are similar.

[0195] However, if both schemes are considered comprehensively, the comparison results of various digital features need to be consistent, and when or Only then was it concluded that the water usage curve under test was similar to the standard water usage curve.

[0196] In this application embodiment, the electronic device provides diverse methods for curve similarity testing. Among them, the advantage of digital feature comparison lies in its ability to parameterize and structure the complex water use curve morphology. By extracting global features (such as total water consumption and water use duration) and stage features (such as the duration of the stable stage, the root mean square error, and attribute values ​​of the changing stage), it is possible to accurately depict the overall trend and local changes of the curve. This method can preserve the macroscopic morphological information of the curve, facilitating the rapid identification of structural deviations.

[0197] In contrast, the difference calculation during the steady-state phase focuses more on fine-grained quantitative comparison. By calculating the difference between the test curve and the standard curve at multiple time intervals in terms of instantaneous flow rate or cumulative water consumption, subtle differences between the two in a steady state can be effectively reflected, thus enabling high-resolution detection of measurement consistency. This method can capture local variation characteristics under statistical fluctuations or random noise, providing a more sensitive basis for anomaly identification.

[0198] When used in combination, these two methods can both ensure overall morphological consistency through digital feature comparison and verify local steady-state accuracy through difference calculation. By combining threshold determination and statistical error analysis, a comprehensive assessment of systematic deviations and random errors can be achieved. This composite testing method, while ensuring detection sensitivity and accuracy, possesses good robustness and versatility, effectively addressing signal fluctuations and equipment differences under varying operating environments, thereby significantly improving the overall reliability and engineering application value of the detection.

[0199] In some embodiments, the water usage curve to be tested is tested based on the standard water usage curve, so as to provide water services to users based on the obtained water usage test results, including: Step H1: When the water usage curve to be tested is not similar to the standard water usage curve, the electronic device determines whether there are abnormal characteristics in the water usage curve to be tested.

[0200] Under normal circumstances, the water usage curve under test is similar to the standard water usage curve. However, when an anomaly occurs, the test result will show that the water usage curve under test is dissimilar to the standard water usage curve. In this case, the electronic equipment first analyzes whether the curve contains abnormal features to determine whether it reflects a potential fault in the specified equipment. These abnormal features can be based on the comparison between the target water usage curve and the standard curve, including abnormal amplitude in the stable phase, standard deviation exceeding a threshold, abnormal slope in the changing phase, or regular changes in pulse intervals. For example, for a toilet, if the curve under test shows a continuous low flow tail in the stable phase or a significantly prolonged water filling rise phase, the electronic equipment can identify abnormal features such as valve aging or blockage.

[0201] Step I2: If the water usage curve to be tested does not show any abnormal characteristics, the electronic device determines that the user's water meter is faulty.

[0202] When no significant abnormalities are found in the water usage curve to be tested after abnormal feature analysis, it can be considered that conventional abnormal factors other than the water meter's own malfunction or abnormality have been eliminated. That is, by the elimination method, it can be considered that the water meter currently in use has malfunctioned or is abnormal.

[0203] Common anomalies can include characteristic changes or deviations caused by equipment failure, equipment malfunction, data anomalies, environmental fluctuations, changes in pipeline pressure, sampling interference, or anomalies in instantaneous water usage patterns. After ruling out common anomalies, the source of the anomaly can be further determined to be the user's water meter itself. These anomalies may manifest as metering anomalies (such as deviations in water consumption per unit time, or sluggish flow response), sensor damage (such as drift of the detection element, or distortion of the output signal), or data upload anomalies (such as communication interruptions, upload delays, or data packet loss).

[0204] In this embodiment, the electronic device achieves accurate diagnosis based on the process of elimination by precisely distinguishing between common routine abnormalities and genuine water meter malfunctions. This enables the electronic device to effectively eliminate interference from non-water meter factors in the detection results within complex and ever-changing water usage environments, triggering quality inspection or maintenance processes only when there is a high probability of determining a water meter malfunction or abnormality, thereby significantly reducing the frequency of water meter disassembly and inspection. Compared with existing methods that rely on manual disassembly and inspection for judgment, this application can achieve automated and non-disruptive intelligent quality inspection, which not only greatly reduces manpower input and lowers the false judgment rate, but also can detect potential fault trends in advance, thereby achieving accurate monitoring and predictive maintenance of user water meters, improving the overall operational efficiency of the water system and the user service experience.

[0205] In some embodiments, the water service further includes an anomaly alarm service, which, after determining whether the water usage curve to be detected exhibits abnormal characteristics, also includes: Step I2: If it is determined that there are abnormal characteristics in the water usage curve to be tested, the electronic device provides an abnormal alarm service to the user based on the fault information corresponding to the abnormal characteristics.

[0206] In actual operation, there are many types of abnormal situations, some of which do not require triggering anomaly alarm services. For example, environmental anomalies caused by environmental changes may cause the water consumption curve under test to deviate from the standard curve, but this is not caused by equipment failure. Environmental anomalies refer to short-term or localized fluctuations in the water consumption curve caused by changes in external conditions, rather than abnormalities in the performance of the metering device itself.

[0207] For example, under non-seasonal conditions, local pipeline pressure may fluctuate momentarily, causing slight tremors or short-term low flow peaks in the instantaneous flow / water consumption per unit time curve. Similarly, during peak water usage periods, frequent starting and stopping of nearby users' water-using appliances (such as washing machines and toilets) may cause a temporary drop in pipeline pressure, thus affecting the water filling stability of the monitored water meter. While such environmental disturbances may alter the shape of local curves, they generally do not affect the normal operation of the equipment.

[0208] Electronic devices can identify and label environmental impact characteristics by comparing the overall trend, local fluctuations, and periodic features of the target standard water consumption curve with the water consumption curve under test. For identified environmental anomalies, the electronic devices can upload the results to the water management platform, allowing the water company to analyze large-scale data samples and statistically identify regional or periodic environmental fluctuation patterns. This optimizes water supply pressure control at different times of the year, improves user experience, and reduces false alarms and ineffective maintenance operations caused by non-equipment factors.

[0209] If abnormal situations that do not require triggering alarms to users are ruled out, for abnormal situations that require triggering alarm services to users, such as equipment failure or abnormal water usage, once the electronic device confirms that the water usage curve to be detected has abnormal characteristics based on the analysis results of the water usage curve, it can generate and push the corresponding alarm service information to the user's electronic device according to the abnormality type corresponding to the abnormal characteristics.

[0210] For example, when a persistent leakage characteristic related to valve seat wear is detected, the electronic device can determine that the valve sealing performance has deteriorated, and then push a prompt message to the user, suggesting that the user check or repair the valve; when an abnormal characteristic related to pipe blockage is identified, the electronic device can prompt the user to clean the pipe or check the drain passage to prevent poor drainage; if an anomaly related to data acquisition or communication is identified, such as data upload interruption, signal loss or abnormal drift, the electronic device can prompt the user to check the communication module or contact maintenance personnel for handling.

[0211] In this embodiment, through the aforementioned anomaly alarm mechanism, the electronic device can achieve closed-loop processing from anomaly identification to alarm push after anomaly detection. This mechanism can not only provide users with timely and targeted maintenance suggestions, reducing water waste and potential losses, but also improve the intelligence level of water meter management and the safety and reliability of system operation.

[0212] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0213] Corresponding to the method for constructing water data verification standards in the above embodiments, Figure 7 A structural block diagram of the water data verification standard construction device 7 provided in the embodiments of this application is shown. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0214] Reference Figure 7 The apparatus 7 for constructing the water data verification standard includes: The first determining module 71 is used to determine whether the water use characteristics of a specified device are reproducible based on a specified number of target water use curves; the target water use curves are the compliant water use curves corresponding to the specified devices, and the water use characteristics have theoretical statistical stability. Module 72 is used to determine each target water use curve as a standard water use curve for verifying water use data, provided that the water use characteristics are reproducible.

[0215] Furthermore, the construction apparatus also includes a screening module, which is used for: Before determining whether the water usage characteristics of a specified device are reproducible based on a specified number of target water usage curves, perform the following operations repeatedly until a specified number of target water usage curves are obtained: The first water usage data collected after the installation of a new user's water meter is obtained, and the first water usage curve is obtained based on the first water usage data; the sampling frequency of the first water usage data is in the range of [1Hz, 8Hz]; From each of the first water usage curves, determine the candidate water usage curve corresponding to the specified equipment; The target water use curve is determined from the candidate water use curves based on preset conditions.

[0216] Furthermore, the first determining module 71 includes: The extraction unit is used to extract the digital feature values ​​of each target water use curve; The determining unit is used to determine whether the determinations of each digitized feature value are consistent. Given that all digital feature values ​​are consistent, determine whether the water usage characteristics are reproducible.

[0217] Furthermore, the digital feature values ​​include global feature values, the specified devices include flushing devices for sanitary ware and washing machines, and correspondingly, the target water usage curve is a target trapezoidal pulse; the global feature values ​​include total water injection volume and total water injection duration; the extraction unit is specifically used for: Integrate the trapezoidal pulses for each target to obtain the corresponding total water injection volume; The pulse duration corresponding to each target trapezoidal pulse is determined as the corresponding total water injection duration.

[0218] Furthermore, the digitized feature values ​​include stage feature values, and the stages corresponding to the stage feature values ​​include the change stage and the stable stage of instantaneous flow rate / water consumption per unit time; the extraction unit is specifically used for: For each stage of change, determine the duration of the change curve and the dynamic characteristic values ​​of the change. For the stable phase, determine the peak value, average value, and root mean square error of the corresponding stable curve.

[0219] Furthermore, for the stable phase, the unit is defined more specifically for: The effective curve is obtained by clipping the boundary of the change curve; Determine the duration of change and dynamic change characteristic values ​​based on the effective change curve; Among them, the effective change curve is linear, and the dynamic change characteristic value is the slope; the effective change curve is nonlinear, and the dynamic change characteristic value is the decay time constant of instantaneous flow rate / water consumption per unit time.

[0220] Furthermore, the digitization features include global feature values ​​and stage feature values, which determine the specific use of the unit: Based on similarity measurement methods, we analyze each global feature value and each stage feature value to determine whether each global feature value has relative consistency and whether each stage feature value has relative consistency. Accordingly, given that all global feature values ​​are relatively consistent and all stage features are relatively consistent, the consistency of each digitized feature value is determined.

[0221] Furthermore, the digital features include global feature values ​​and stage feature values, and the determining unit is specifically used for: Determine whether each global feature value falls within a preset first deviation range; Determine whether the characteristic values ​​of each stage fall within the preset second deviation range; If all global feature values ​​fall within the first deviation range and all stage feature values ​​fall within the second deviation range, then the consistency of each digitized feature value is determined.

[0222] Furthermore, the water curve is selected as the candidate trapezoidal pulse; the screening module includes a first screening unit, which is used for: Independent trapezoidal pulses are selected from the first water usage curve; the pulse interval of each independent trapezoidal pulse is greater than the preset duration; Remove independent trapezoidal pulses whose stable phase contains sudden changes in instantaneous flow rate / water consumption per unit time, and obtain suspected candidate trapezoidal pulses; Calculate the total water consumption for each suspected candidate trapezoidal pulse; Suspected candidate trapezoidal pulses whose total water consumption reaches the standard total water consumption of the specified equipment are identified as candidate trapezoidal pulses.

[0223] Furthermore, the preset conditions include preset anomalies; the filtering module also includes a second filtering unit, which is used for: Based on the abnormal characteristics corresponding to the preset abnormality, the abnormal trapezoidal pulse is determined from each candidate trapezoidal pulse; Abnormal trapezoidal pulses are filtered out from each candidate trapezoidal pulse to obtain the target trapezoidal pulse.

[0224] Furthermore, the designated equipment includes flushing devices for sanitary ware; the second screening unit includes: The abnormal trapezoidal pulse screening subunit is used to identify the corresponding candidate trapezoidal pulse as an abnormal trapezoidal pulse if an anomaly is found in the stable phase and / or changing phase of the candidate trapezoidal pulse.

[0225] Furthermore, the abnormal trapezoidal pulse screening subunit is specifically used for: If the difference between the attribute value and the normal attribute value of the stable phase and / or changing phase of the candidate trapezoidal pulse is greater than a preset threshold, it is determined that there is an anomaly in the stable phase and / or changing phase of the candidate trapezoidal pulse.

[0226] Furthermore, the abnormal trapezoidal pulse screening subunit is specifically used for: In the case of multiple candidate trapezoidal pulses with approximately the same pulse interval, each candidate trapezoidal pulse is identified as an abnormal trapezoidal pulse.

[0227] Furthermore, the construction apparatus also includes a first optimization module, which is used for: After determining each target water usage curve as the standard water usage curve for testing water usage data, an equipment aging model is constructed based on each water usage curve corresponding to the second water usage data. Adjustment values ​​are determined based on equipment aging models; Optimize the standard water use curve based on the adjustment value.

[0228] Furthermore, the construction apparatus also includes a second optimization module, which is used for: After determining each target water use curve as the standard water use curve for verifying water use data, the seasonal identifier of the standard water use curve is determined based on the first season to which the first water use data belongs. A new standard water use curve is constructed based on water use data from the second season, and the corresponding seasonal identifier is determined; the second season is any season other than the first season. During the water use data verification process, a target standard water use curve is determined from the established standard water use curves based on the third season corresponding to the water use data to be tested; the seasonal identifier of the target standard water use curve is matched with the third season.

[0229] Furthermore, the construction apparatus also includes a preprocessing module, and the screening module includes a preprocessing unit, which is used for: Curve fitting was performed based on the first water usage data to obtain various fitted curves; The first water usage curve is obtained by denoising the fitted curve using a preset method.

[0230] Corresponding to the water usage data verification method in the above embodiment, Figure 8 The diagram shows a structural block diagram of the water usage data verification device 8 provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0231] Reference Figure 8 The water usage data verification device 8 includes: The acquisition module 81 is used to acquire third water use data after the standard water use curve standard is constructed; the standard water use curve is obtained based on the embodiment of the above-mentioned method for constructing the standard for verifying arbitrary water use data. Fitting module 82 is used to obtain the third water use curve based on the third water use data; The second determining module 83 is used to determine the water usage curve to be tested corresponding to the specified equipment from each of the third water usage curves; The inspection service module 84 is used to inspect the water use curve to be tested based on the standard water use curve, and to provide water services to users based on the obtained water use test results.

[0232] Furthermore, water services include user water meter quality inspection, and the inspection service module 84 is specifically used for: Determine whether the water usage curve to be tested is similar to the standard water usage curve; If the water usage curve to be tested is similar to the standard water usage curve, the user's water meter is deemed to have passed the quality inspection during use.

[0233] Furthermore, the water usage curve corresponding to the specified equipment is a trapezoidal pulse; the water usage curve to be tested is a trapezoidal pulse to be tested; the standard water usage curve is a standard trapezoidal pulse; the trapezoidal pulse includes a stable phase; the inspection service module 84 is specifically used for: Extract the digital features to be detected from the trapezoidal pulse to be detected; compare the digital features to be detected with the standard digital features of the standard trapezoidal pulse; and / or, in the stabilization phase, determine multiple differences between the instantaneous flow rate / water consumption per unit time of the trapezoidal pulse to be detected corresponding to multiple specified time intervals and the instantaneous flow rate / water consumption per unit time of the corresponding standard trapezoidal pulse; If the digitized feature to be detected is consistent with the standard digitized feature, and / or multiple differences fall within the preset difference range; or if the digitized feature to be detected is consistent with the standard digitized feature, and / or the root mean square error or mean absolute difference corresponding to multiple differences is less than the preset threshold, the trapezoidal pulse to be detected is determined to be similar to the standard trapezoidal pulse.

[0234] Furthermore, the inspection service module 84 is specifically used for: When the water usage curve to be tested is not similar to the standard water usage curve, determine whether the water usage curve to be tested has abnormal characteristics; If the water usage curve under test does not show any abnormal characteristics, the user's water meter is determined to be faulty.

[0235] Furthermore, the water services also include anomaly alarm services, and the inspection service module 84 is specifically used for: If the water usage curve to be tested is found to have abnormal characteristics, an anomaly alarm service is provided to the user based on the fault information corresponding to the abnormal characteristics.

[0236] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0237] Figure 9 This is a schematic diagram of the physical layer structure of an electronic device provided in an embodiment of this application. Figure 9 As shown, the electronic device 9 of this embodiment includes: at least one processor 90 ( Figure 9 Only one processor is shown in the diagram, along with a memory 91 and a computer program 92 stored in the memory 91 and executable on at least one processor 90. When the processor 90 executes the computer program 92, it implements the steps described in the embodiment of the method for constructing any water data verification standard, for example... Figure 1 Steps 110-120 are shown.

[0238] The processor 90 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0239] In some embodiments, memory 91 may be an internal storage unit of electronic device 9, such as a hard disk or memory of electronic device 9. In other embodiments, memory 91 may also be an external storage device of electronic device 9, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on electronic device 9.

[0240] Furthermore, the memory 91 may include both internal storage units and external storage devices of the electronic device 9. The memory 91 is used to store operating devices, application programs, bootloaders, data, and other programs, such as program code for computer programs. The memory 91 can also be used to temporarily store data that has been output or will be output.

[0241] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the above device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0242] 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.

[0243] This application provides a computer program product that, when run on an electronic device, enables the electronic device to perform the steps described in the various method embodiments above.

[0244] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographic device / electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, such as a USB flash drive, a portable hard drive, a magnetic disk, or an optical disk.

[0245] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0246] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0247] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some water usage curves may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0248] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0249] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical solutions using water curves. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for constructing a water usage data verification standard, characterized in that, include: Based on a specified number of target water usage curves, determine whether the water usage characteristics of a specified device are reproducible; the target water usage curves are the compliant water usage curves corresponding to the specified device, and the water usage characteristics have theoretical statistical stability. When the water use characteristics possess the reproducibility, each of the target water use curves is determined as the standard water use curve for verifying the water use data.

2. The construction method as described in claim 1, characterized in that, The determination of whether the water usage characteristics of a specified device are reproducible based on a specified number of target water usage curves includes: Extract the digital feature values ​​of each of the target water use curves; Determine whether the determinations of each of the aforementioned digital feature values ​​are consistent; If all the digital feature values ​​are consistent, determine whether the water usage feature is reproducible.

3. The construction method as described in claim 2, characterized in that, The digital feature values ​​include global feature values, the designated devices include flushing devices for sanitary ware and washing machines, and correspondingly, the target water usage curve is a target trapezoidal pulse; The global feature values ​​include the total water injection volume and the total water injection duration; The extraction of digital feature values ​​from each of the target water usage curves includes: Integrate each of the target trapezoidal pulses to obtain the corresponding total water injection volume; The pulse duration corresponding to each of the target trapezoidal pulses is determined as the corresponding total water injection duration.

4. The construction method as described in claim 3, characterized in that, The digital feature values ​​include stage feature values, and the stages corresponding to the stage feature values ​​include the change stage of instantaneous flow rate / water consumption per unit time and the stable stage. The extraction of digital feature values ​​from each of the target water usage curves includes: For each stage of change, determine the duration of the change curve and the dynamic characteristic values ​​of the change. For the stable phase, determine the peak value, average value, and root mean square error of the corresponding stable curve.

5. The construction method as described in claim 4, characterized in that, The determination of the duration of change and dynamic change characteristic value of the corresponding change curve includes: The effective change curve is obtained by clipping the boundary of the change curve; The duration of change and the dynamic change characteristic value are determined based on the effective change curve; Wherein, the effective change curve is linear, and the dynamic change characteristic value is the slope; the effective change curve is nonlinear, and the dynamic change characteristic value is the decay time constant of instantaneous flow rate / water consumption per unit time.

6. The construction method according to any one of claims 2 to 5, characterized in that, The digital features include global feature values ​​and stage feature values. Determining whether the determinations of each of the digital feature values ​​are consistent includes: Based on the similarity measurement method, the global feature values ​​and the stage feature values ​​are analyzed to determine whether the global feature values ​​and the stage features have relative consistency. Accordingly, when all the global feature values ​​are relatively consistent and all the stage features are relatively consistent, it is determined that all the digital feature values ​​are consistent.

7. The construction method according to any one of claims 2 to 5, characterized in that, The digital features include global feature values ​​and stage feature values. Determining whether the determinations of each of the digital feature values ​​are consistent includes: Determine whether each of the global feature values ​​falls within a preset first deviation range; Determine whether the characteristic values ​​of each stage fall within a preset second deviation range; If each of the global feature values ​​falls within the first deviation range and each of the stage feature values ​​falls within the second deviation range, then the digitized feature values ​​are determined to be consistent.

8. The construction method according to any one of claims 1 to 5, characterized in that, Before determining whether the water usage characteristics of a specified device are reproducible based on a specified number of target water usage curves, the construction method further includes: Repeat the following operations until the specified number of the target water usage curves are obtained: The first water usage data collected by the target user's water meter is obtained, and a first water usage curve is obtained based on the first water usage data; the installation time of the target user's water meter is less than a preset installation time threshold; the sampling frequency of the first water usage data is in the range of [1Hz, 8Hz]; Determine the candidate water usage curve corresponding to the designated device from each of the first water usage curves; The target water use curve is determined from the candidate water use curves based on preset conditions.

9. The construction method as described in claim 8, characterized in that, The candidate water usage curve is a candidate trapezoidal pulse; determining the candidate water usage curve corresponding to the designated device from each of the first water usage curves includes: Independent trapezoidal pulses are selected from the first water usage curve; the pulse interval of each independent trapezoidal pulse is greater than a preset duration; Delete the independent trapezoidal pulses in the stable phase of each of the independent trapezoidal pulses that contain sudden changes in instantaneous flow rate / water consumption per unit time, and obtain the suspected candidate trapezoidal pulses; Calculate the total water consumption for each of the suspected candidate trapezoidal pulses; The suspected candidate trapezoidal pulses whose total water consumption reaches the standard total water consumption of the specified equipment are identified as candidate trapezoidal pulses.

10. The construction method as described in claim 9, characterized in that, The preset conditions include preset anomalies; The target water usage curve is a target trapezoidal pulse; the step of determining the target water usage curve from the candidate water usage curves based on preset conditions includes: Based on the abnormal characteristics corresponding to the preset abnormality, an abnormal trapezoidal pulse is determined from each candidate trapezoidal pulse; The abnormal trapezoidal pulses among the candidate trapezoidal pulses are filtered to obtain the target trapezoidal pulse.

11. The construction method as described in claim 10, characterized in that, The designated equipment includes the flushing device of sanitary ware; the step of determining the abnormal trapezoidal pulse from each candidate trapezoidal pulse based on the abnormal characteristics corresponding to the preset abnormality includes: For each candidate trapezoidal pulse, if it is determined that there is an anomaly in the stable phase and / or changing phase of the candidate trapezoidal pulse, the corresponding candidate trapezoidal pulse is identified as the abnormal trapezoidal pulse.

12. The construction method as described in claim 11, characterized in that, The determination that there are anomalies in the stable phase and / or changing phase of the candidate trapezoidal pulse includes: If the difference between the attribute value and the normal attribute value of the stable phase and / or changing phase of the candidate trapezoidal pulse is greater than a preset threshold, it is determined that there is an anomaly in the stable phase and / or changing phase of the candidate trapezoidal pulse.

13. The construction method as described in claim 10, characterized in that, The step of determining the abnormal trapezoidal pulse from each candidate trapezoidal pulse based on the abnormal features corresponding to the preset abnormality includes: In the presence of multiple consecutive candidate trapezoidal pulses with approximately the same pulse interval, each of the corresponding candidate trapezoidal pulses is identified as the abnormal trapezoidal pulse.

14. The construction method according to any one of claims 1 to 5, characterized in that, After determining each of the target water use curves as the standard water use curves for verifying water use data, the method further includes: An equipment aging model is constructed based on each trapezoidal pulse corresponding to the second water usage data. The adjustment value is determined based on the equipment aging model. The standard water usage curve is optimized based on the adjustment value.

15. The construction method as described in claim 8, characterized in that, After determining each of the target water use curves as the standard water use curves for verifying water use data, the method further includes: The seasonal identifier of the standard water use curve is determined based on the first season to which the first water use data belongs; A new standard water usage curve is constructed based on water usage data from the second season, and the corresponding seasonal identifier is determined; the second season is any season other than the first season. During the water usage data verification process, a target standard water usage curve is determined from the established standard water usage curves based on the third season corresponding to the water usage data to be tested; the seasonal identifier of the target standard water usage curve is matched with the third season.

16. The construction method as described in claim 8, characterized in that, The process of obtaining the first water usage curve based on the first water usage data includes: Curve fitting was performed based on the first water usage data to obtain various fitted curves; The first water usage curve is obtained by denoising the fitted curve using a preset method.

17. A method for detecting water usage data, characterized in that, include: After the standard water use curve is constructed, third-party water use data are obtained; the standard water use curve is obtained based on the construction method described in any one of claims 1-16; The third-party water use curve is obtained based on the third-party water use data; Determine the water usage curve to be tested for the specified equipment from each of the third water usage curves; The water usage curve to be tested is verified based on the standard water usage curve, so as to provide water services to users based on the obtained water usage test results.

18. The detection method as described in claim 17, characterized in that, The water service includes user water meter quality inspection, and the step of testing the water usage curve to be tested based on the standard water usage curve, and providing water services to users based on the obtained water usage test results, includes: Determine whether the water usage curve to be tested is similar to the standard water usage curve; If the water usage curve to be tested is similar to the standard water usage curve, the user's water meter is deemed to have passed the quality inspection during use.

19. The detection method as described in claim 18, characterized in that, The water usage curve corresponding to the designated device is a trapezoidal pulse; the water usage curve to be tested is a trapezoidal pulse to be tested; the standard water usage curve is a standard trapezoidal pulse; the trapezoidal pulse includes a stable phase; determining whether the water usage curve to be tested is similar to the standard water usage curve includes: Extract the digitized features of the trapezoidal pulse to be detected; compare the digitized features to be detected with the standard digitized features of the standard trapezoidal pulse; and / or, in the stabilization phase, determine multiple differences between the instantaneous flow rate / water consumption per unit time of the trapezoidal pulse to be detected corresponding to multiple specified time intervals and the instantaneous flow rate / water consumption per unit time of the corresponding standard trapezoidal pulse; When the digitized feature to be detected is consistent with the standard digitized feature, and / or multiple differences fall within a preset difference range; or when the digitized feature to be detected is consistent with the standard digitized feature, and / or the root mean square error or mean absolute difference corresponding to multiple differences is less than a preset threshold, the trapezoidal pulse to be detected is determined to be similar to the standard trapezoidal pulse.

20. The detection method as described in claim 18, characterized in that, The process of testing the water usage curve to be tested based on the standard water usage curve, and providing water services to users based on the obtained water usage test results, includes: If the water usage curve to be tested is not similar to the standard water usage curve, determine whether the water usage curve to be tested has any abnormal characteristics; If the water usage curve to be tested does not show any abnormal characteristics, the user's water meter is determined to be faulty.

21. The detection method as described in claim 20, characterized in that, The water service also includes an anomaly alarm service, which verifies the water usage curve to be tested based on the standard water usage curve, and provides water services to users based on the obtained water usage detection results, including: If it is determined that the water usage curve to be tested has abnormal characteristics, an abnormal alarm service is provided to the user based on the fault information corresponding to the abnormal characteristics.

22. A device for constructing a water data verification standard, characterized in that, include; The first determining module is used to determine whether the water use characteristics of a specified device are reproducible based on a specified number of target water use curves; the target water use curves are the compliant water use curves corresponding to the specified device, and the water use characteristics have theoretical statistical stability. A construction module is used to determine each of the target water use curves as the standard water use curves for verifying water use data, provided that the water use characteristics have the reproducibility.

23. A device for verifying water usage data, characterized in that, include: The acquisition module is used to acquire third-party water use data after the standard water use curve is constructed; the standard water use curve is obtained based on the construction method described in any one of claims 1-16; The fitting module is used to obtain the third-party water use curve based on the third-party water use data; The second determining module is used to determine the water usage curve to be tested corresponding to the specified device from each of the third water usage curves; The testing service module is used to test the water use curve to be tested based on the standard water use curve, so as to provide water services to users based on the obtained water use test results.

24. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for constructing a water use data verification standard as described in any one of claims 1 to 16, or the method for detecting water use data as described in any one of claims 17 to 21.

25. A computer program product, the computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for constructing a water use data verification standard as described in any one of claims 1 to 16, or the method for detecting water use data as described in any one of claims 17 to 21.

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