Sewage pipe network data acquisition terminal and monitoring system

Abstract

The invention discloses a sewage pipe network data acquisition terminal and a monitoring system, and belongs to the technical field of monitoring, and the terminal comprises a multi-parameter acquisition unit which is used for acquiring at least one kind of monitoring data at the same time; the multi-parameter acquisition unit is electrically connected with the main control unit and is used for carrying out abnormity monitoring on at least one kind of monitoring data according to a set safety threshold value to obtain a monitoring result; the communication unit is electrically connected with the main control unit and is used for uploading the monitoring data and the monitoring result to a supervision platform or receiving an instruction issued by the supervision platform; the expansion interface unit is electrically connected with the main control unit, and the expansion interface unit is used for being externally connected with expansion equipment. According to the invention, rapid identification and response to potential safety hazards of the sewage pipe network are realized, and the reliability and safety of operation of the pipe network are effectively enhanced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of monitoring, and particularly relates to a sewage pipe network data acquisition terminal and a monitoring system. BACKGROUND

[0002] With the acceleration of urbanization and the improvement of water environment management requirements, the operation state monitoring (such as flow, liquid level, water quality parameters) of the sewage pipe network as the core infrastructure of urban water ecological safety is directly related to the prevention and control of risks such as pipe network siltation, overflow and illegal sewage. However, the existing sewage pipe network monitoring technology has the following bottlenecks:

[0003] The existing monitoring method mainly relies on manual inspection, supplemented by single parameter collection at fixed points, and has the problems of poor real-time performance and limited coverage, which is difficult to meet the dynamic operation requirements of complex pipe networks. SUMMARY

[0004] The purpose of the application is to provide a sewage pipe network data acquisition terminal and a monitoring system to solve the problem that the existing monitoring method mainly relies on manual inspection, supplemented by single parameter collection at fixed points, and has the problems of poor real-time performance and limited coverage.

[0005] In order to achieve the above purpose, the application adopts the following technical solutions:

[0006] In a first aspect, the application provides a sewage pipe network data acquisition terminal, comprising:

[0007] A multi-parameter acquisition unit is configured to simultaneously acquire at least one monitoring data.

[0008] A main control unit is electrically connected to the multi-parameter acquisition unit and configured to perform abnormal monitoring on the at least one monitoring data according to a set safety threshold to obtain a monitoring result.

[0009] A communication unit is electrically connected to the main control unit and configured to upload the monitoring data and the monitoring result to a supervision platform or receive an instruction issued by the supervision platform.

[0010] An expansion interface unit is electrically connected to the main control unit, and the expansion interface unit is configured to externally connect an expansion device.

[0011] Preferably, the multi-parameter acquisition unit comprises a flow sensor, a liquid level sensor and a water quality sensor, and the monitoring data is at least one of flow data, liquid level data and water quality data.

[0012] Preferably, the application further comprises:

[0013] A storage unit is electrically connected to the control unit.

[0014] a display unit electrically connected with the control unit;

[0015] a power supply unit for providing working power for the master control unit, the communication unit, the storage unit, the display unit and the multi-parameter acquisition unit.

[0016] Preferably, further comprising: a shell, an inside of the shell is provided with a mainboard, the master control unit, the multi-parameter acquisition unit, the communication unit and the expansion interface unit are integrated on the mainboard, a side of the shell is detachably connected with a mounting plate, and a slot is arranged on the mounting plate.

[0017] Preferably, an operating panel is arranged on an end surface of the shell.

[0018] In a second aspect, the present application provides a sewage pipe network data monitoring system, the system comprising: a supervision platform, a mobile terminal and a plurality of sewage pipe network data acquisition terminals as described above;

[0019] The mobile terminal is in communication connection with each sewage pipe network data acquisition terminal and the supervision platform respectively, and each sewage pipe network data acquisition terminal is in communication connection with the supervision platform;

[0020] At least one sewage pipe network data acquisition terminal constitutes a monitoring point, each sewage pipe network data acquisition terminal is used for acquiring monitoring data of each monitoring point, and the monitoring data of the monitoring point is monitored for abnormality according to a preset safety threshold; when an abnormality occurs, an abnormality alarm is generated, and the abnormality alarm is sent to the mobile terminal or the supervision platform;

[0021] The supervision platform is used for storing the monitoring data and the monitoring result uploaded by each sewage pipe network data acquisition terminal, and is used for configuring the safety threshold of each monitoring point.

[0022] Preferably, the step of configuring the safety threshold of each monitoring point by the supervision platform is:

[0023] Within a preset configuration period, historical data corresponding to any monitoring data is acquired, and a normal data set corresponding to the monitoring data is constructed according to the historical data;

[0024] An abnormality score of the normal data set is obtained by performing abnormality evaluation on the normal data set based on a pre-constructed data abnormality evaluation model;

[0025] A basic threshold is determined according to the abnormality score;

[0026] A scene type of a future period is acquired, and a scene correction coefficient is matched according to the scene type of the future period;

[0027] The base threshold value is corrected according to a scene correction coefficient to obtain a corrected threshold value, and the corrected threshold value is used as a safety threshold value of the monitoring data in a future period.

[0028] Preferably, the safety threshold value of each monitoring data in a future period is constrained by a preset constraint condition, and the constraint condition includes a safety constraint, a physical constraint and a business constraint.

[0029] Preferably, the data anomaly evaluation model is constructed based on an isolation forest.

[0030] The present application has the following beneficial effects:

[0031] 1. The sewage pipe network data acquisition terminal has a highly integrated multi-parameter acquisition unit, can flexibly support parallel acquisition of single type or multiple types of monitoring data, and significantly improves data acquisition efficiency; the terminal locally deploys a preset safety threshold judgment mechanism, can analyze and compare the acquired monitoring data in real time, triggers an alarm as soon as data anomalies are found, thereby realizing rapid identification and response to potential safety hazards of the sewage pipe network, and effectively enhancing the reliability and safety of pipe network operation;

[0032] 2. The sewage pipe network data acquisition terminal also integrates an extensible interface unit in design, has good external device compatibility and access flexibility, can adapt to various professional monitoring sensors, such as high-precision ultrasonic level meters, radar flow meters and other extension devices; through the comprehensive architecture of “built-in basic monitoring parameters and externally connected extended monitoring parameters”, the terminal realizes all-around and full-coverage real-time monitoring of multiple key parameters of the sewage pipe network, and meets the fine monitoring demand in complex scenarios;

[0033] 3. The data acquisition terminal has a stable and reliable communication module built-in, can efficiently and accurately transmit the real-time monitoring data acquired by each monitoring node and the abnormal conditions obtained through local judgment to the central supervision platform; the supervision platform can uniformly access, data aggregate and centrally manage multiple terminal devices distributed in the pipe network, form a complete monitoring and management closed loop, and significantly improve the intelligent level and response efficiency of sewage pipe network operation and maintenance. BRIEF DESCRIPTION OF DRAWINGS

[0034] The accompanying drawings are included to provide a further understanding of the embodiments of the application, and constitute a part of the specification, and are used together with the following specific embodiments to explain the embodiments of the application, but do not constitute a limitation on the embodiments of the application. In the drawings:

[0035] Figure 1 is a block diagram of a sewage pipe network data acquisition terminal provided by an embodiment of the present application;

[0036] Figure 2is a top view of the sewage pipe network data acquisition terminal provided by an embodiment of the present application;

[0037] Figure 3 is a side view of the sewage pipe network data acquisition terminal provided by an embodiment of the present application;

[0038] Figure 4 is a front view of the sewage pipe network data acquisition terminal provided by an embodiment of the present application;

[0039] Figure 5 is a block diagram of the sewage pipe network data monitoring system provided by an embodiment of the present application.

[0040] Explanation of reference signs:

[0041] 1, shell; 2, mounting plate; 3, slot; 4, operation panel. DETAILED DESCRIPTION

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the present application will be briefly introduced below in combination with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the drawings structure is only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor. It should be noted that the description of these embodiment modes is used to help understand the present application, but does not constitute a limitation on the present application.

[0043] Embodiment one

[0044] Figure 1 is a block diagram of the sewage pipe network data acquisition terminal provided by an embodiment of the present application. As shown in the figure, Figure 1 the present embodiment provides a sewage pipe network data acquisition terminal, which comprises a multi-parameter acquisition unit, a main control unit, a communication unit, an expansion interface unit, a storage unit, a display unit and a power supply unit; wherein the multi-parameter acquisition unit, the communication unit, the expansion interface unit, the storage unit and the display unit are electrically connected with the main control unit.

[0045] In the present embodiment, the multi-parameter acquisition unit is used to simultaneously acquire at least one monitoring data, the multi-parameter acquisition unit of the present embodiment contains a flow sensor, a liquid level sensor and a water quality sensor, and the monitoring data of the present embodiment is at least one of flow data, liquid level data and water quality data; wherein the water quality data includes but is not limited to COD, ammonia nitrogen, PH value and other data.

[0046] In the embodiment, the master control unit is configured to perform abnormality monitoring on at least one monitoring data according to a set safety threshold, and obtain a monitoring result, which includes two cases of data abnormality and data normality. When the monitoring data exceeds the set safety threshold, it indicates that the monitoring data is abnormal, for example, a sudden change in flow data is monitored, and the set safety threshold is configured to identify instantaneous flow surge or sudden drop to prevent the risk of pipe explosion or blockage. For another example, the COD (Chemical Oxygen Demand) concentration exceeds the set range, the ammonia nitrogen content abnormally increases, and the pH value exceeds the set range. When the monitoring data is abnormal, an audible and visual alarm or a remote alarm can be used, that is, an alarm signal is generated and sent to a supervision platform to realize remote alarm.

[0047] Therefore, the sewage pipe network data acquisition terminal in the embodiment has a highly integrated multi-parameter acquisition unit, can flexibly support parallel acquisition of single type or multiple types of monitoring data, and significantly improves data acquisition efficiency. The terminal locally deploys a preset safety threshold judgment mechanism, can analyze and compare the acquired monitoring data in real time, triggers an alarm as soon as data abnormality is found, thereby realizing rapid identification and response to potential safety hazards of the sewage pipe network, and effectively enhancing the reliability and safety of the pipe network operation.

[0048] In the embodiment, the expansion interface unit is configured to externally connect an expansion device, and includes an RS232 / RS485 serial port, a relay output, and the like. The RS232 / RS485 serial port can externally connect an expansion device such as a high-precision ultrasonic water level meter or a radar flowmeter, and the relay output can externally connect a water pump or a valve, so that the water pump and the valve can be controlled. Therefore, the terminal realizes all-around and full-coverage real-time monitoring of multiple key parameters of the sewage pipe network through the comprehensive architecture of “built-in basic monitoring parameters (i.e., flow data, liquid level data, and water quality data) and externally connected expansion monitoring parameters”, and meets the fine monitoring demand in a complex scene.

[0049] In the embodiment, the communication unit is configured to upload the monitoring data and the monitoring result to a supervision platform or receive an instruction issued by the supervision platform. The instruction can be a control instruction of a relay. When the expansion interface unit of the sewage pipe network data acquisition terminal is externally connected to a valve, the control unit can control the valve according to the control instruction.

[0050] The communication unit in the embodiment is compatible with mainstream protocols such as ModbusRTU / TCP, supports connection with industrial software such as KingView, and the control process of the embodiment is as follows:

[0051] ‌Device binding: register the sewage pipe network data acquisition terminal in the embodiment on a cloud platform (i.e., a supervision platform) and obtain an SN number, and complete the binding through an RS485 bus;

[0052] ‌Instruction issuing: Kingview software sends control instructions (such as switch output) through virtual serial port;

[0053] ‌Execution feedback: the RTU drives the relay to act after receiving the instructions, and returns the device state confirmation.

[0054] The communication unit of the embodiment also adopts the following communication methods:

[0055] ‌4G / 5G network: supports high-speed data transmission, suitable for scenarios that require real-time transmission of large amounts of data;

[0056] ‌NB-IoT (Narrow Band Internet of Things): with low power consumption and wide coverage, suitable for remote monitoring points;

[0057] ‌GPRS (General Packet Radio Service): as a supplement to traditional communication methods, it can still be used in areas with poor network coverage.

[0058] The communication unit of the embodiment adopts the following data transmission mechanism: the sewage pipe network data acquisition terminal obtains real-time monitoring data through various sensors, and after preprocessing and format conversion, the data is uploaded to the supervision platform (cloud platform or monitoring center) through the selected wireless communication method, supports breakpoint resume, and ensures data integrity.

[0059] The communication unit of the embodiment adopts the following security mechanism: uses PPP layer heartbeat and TCP heartbeat link detection to ensure communication reliability, supports remote parameter setting and program upgrade, and has fault self-repairing capability.

[0060] Therefore, the communication module of the embodiment can efficiently and accurately transmit the real-time monitoring data obtained by each monitoring node and the abnormal conditions obtained by local judgment to the central supervision platform; the supervision platform can uniformly access, data aggregate and centrally manage multiple terminal devices distributed in the pipe network, forming a complete monitoring and management closed loop, and significantly improving the intelligent level and response efficiency of sewage pipe network operation and maintenance

[0061] In the embodiment, the display unit can be used to display real-time monitoring data, battery capacity of the power supply unit, time and other parameters.

[0062] In the embodiment, the storage unit is used to store monitoring data, monitoring results and safety thresholds.

[0063] In the embodiment, the power supply unit is used to provide working power for the main control unit, the communication unit, the storage unit, the display unit and the multi-parameter acquisition unit. The power supply unit of the embodiment adopts wide voltage input design, i.e. 9-36VDC, and integrates overvoltage / overcurrent protection circuit to prevent overvoltage or overcurrent in the circuit.

[0064] As a further optimization of this embodiment, such as Figure 2 and Figure 3 As shown, the sewage pipe network data acquisition terminal of this embodiment also includes: a housing 1. The housing 1 of this embodiment adopts multiple waterproof designs such as sealing rings and waterproof coatings, and is not afraid of extreme harsh environments, such as year-round manhole moisture and long-term underwater immersion; the housing 1 of this embodiment has a motherboard inside, and the main control unit, multi-parameter acquisition unit, communication unit and expansion interface unit are all integrated on the motherboard. A mounting plate 2 is detachably connected to one side of the housing 1. The mounting plate 2 has slots 3, such as... Figure 4 As shown.

[0065] In this embodiment, the mounting plate 2 can be bolted to the side wall of the outer casing 1. The mounting plate 2 is provided with slotted holes 3. At this time, the mounting plate 2 can be installed in the manhole cover, the inner wall of the pipe, etc. by bolts, binding and other methods. Therefore, the sewage network data acquisition terminal of this embodiment will not damage the original structure of the network pipes, equipment, facilities and other structures during installation. It can be directly installed at the valve well interface of water supply, drainage and gas pipelines, and has strong maintainability.

[0066] As a further optimization of this embodiment, an operation panel 4 is provided on the end face of the outer casing 1. The operation panel 4 includes a display screen and buttons of the display unit.

[0067] Example 2

[0068] Figure 5 This is a block diagram of a sewage pipe network data monitoring system provided in one embodiment of the present invention. Figure 5 As shown, this embodiment provides a sewage pipe network data monitoring system. The system includes: a monitoring platform, a mobile terminal, and several sewage pipe network data acquisition terminals as described in Embodiment 1. The mobile terminal is communicatively connected to each sewage pipe network data acquisition terminal and the monitoring platform, and each sewage pipe network data acquisition terminal is communicatively connected to the monitoring platform.

[0069] In this embodiment, at least one sewage pipe network data acquisition terminal constitutes a monitoring point, that is, each monitoring point is equipped with at least one sewage pipe network data acquisition terminal. Each sewage pipe network data acquisition terminal is used to collect monitoring data from each monitoring point and to perform anomaly monitoring on the monitoring data of the monitoring point according to a preset safety threshold. When an anomaly occurs, an anomaly alarm is generated and sent to a mobile terminal or a monitoring platform. The monitoring platform is used to store the monitoring data and monitoring results uploaded by each sewage pipe network data acquisition terminal and to configure the safety thresholds for each monitoring point.

[0070] In the present embodiment, due to different normal data fluctuations under different scenarios (season, weather, pipe network type, etc.), for example, "early peak sewage discharge, low flow at night" of the domestic sewage pipe network, the required safety threshold is also different. The current safety threshold often uses a fixed value, which is difficult to meet the dynamic demand, resulting in high false positive rate and false negative rate. In order to solve this problem, the safety threshold of each monitoring point is configured on the supervision platform in the present embodiment. This configuration is dynamic to adapt to changes in the pipe network (such as the addition of a sewage outlet or changes in flow patterns after pipe maintenance), without the need for frequent manual intervention in the threshold, thereby reducing the false positive rate and false negative rate.

[0071] Specifically, the specific steps of the supervision platform configuring the safety threshold of each monitoring point are as follows:

[0072] First, within a preset configuration period, the historical data corresponding to any monitoring data is obtained, and a normal data set corresponding to the monitoring data is constructed according to the historical data.

[0073] The preset configuration period of the present embodiment is 0:00~0:30 every day, and the configuration task is performed within this period, usually starting at the initial time (0:00).

[0074] The historical data of the present embodiment is the monitoring data of each monitoring point in the past month, which includes flow data, liquid level data, water quality data, etc. Then, the monitoring data of each monitoring point in the past month is filtered, and normal data is selected. Data with abnormalities is not selected, and all normal data is used as a normal data set.

[0075] Next, the normal data set is evaluated based on a pre-constructed data anomaly evaluation model to obtain an anomaly score of the normal data set; and a basic threshold is determined according to the anomaly score.

[0076] In the present embodiment, the data anomaly evaluation model is constructed based on an isolation forest. In the present embodiment, sample data is obtained, the sample data is labeled to construct a training set and a test set, the isolation forest is trained using the training set, and the trained isolation forest is tested using the test set. Finally, a trained isolation forest is obtained, which is used as a data anomaly evaluation model.

[0077] The sample data of the present embodiment includes the following data:

[0078] The monitoring data collected by the sewage pipe network data collection terminal, such as flow, liquid level, COD, ammonia nitrogen, pH value, etc.

[0079] Environmental auxiliary data, such as rainfall, temperature, humidity, weather type (sunny / rainy / snowy), etc.

[0080] Pipe network static data, such as: pipe network type (industrial / living / rain and sewage separation), pipe diameter (D), material (PE / steel pipe / concrete), design flow upper limit (Q_max), monitoring point type (inspection well / discharge port / pump station) and the like;

[0081] Device state data, such as: sensor communication state (normal / timeout), power voltage, terminal internal temperature, storage usage rate and the like;

[0082] Operation and maintenance history data, such as: desilting time (T_clean), pipe repair record (T_repair), sensor calibration record (T_calib), historical alarm verification result (label: normal / false alarm / missed alarm) and the like.

[0083] The above sample data is cleaned and standardized, and then a feature set is constructed, which is used as the input of the isolation forest.

[0084] The feature set of the embodiment includes the following features:

[0085] 1. Time series statistical features, used to capture the parameter's own fluctuation law, based on the standardized time series data, the statistical quantities in the sliding window are calculated, and the window size is set as "collection frequency x n" (n=3, 7, 24, corresponding to different time granularity);

[0086] The time series statistical features include:

[0087] Rolling mean, rolling standard deviation, rolling maximum / minimum value;

[0088] Coefficient of variation: the ratio of rolling standard deviation to rolling mean;

[0089] Cumulative value: the cumulative sum of the last 24 collection data, such as flow cumulative = total discharge, COD cumulative = total pollution load;

[0090] Same period deviation rate: (current rolling mean - last 7 days rolling mean of the same period) / last 7 days rolling mean of the same period x 100%).

[0091] 2. Scene interaction features, used to fuse the environment and pipe network attributes, distinguish normal fluctuation and abnormality, and capture the correlation law of "parameter-environment-pipe network" through feature cross (such as rain day flow increase is normal, no rain day flow increase is abnormal);

[0092] The scene interaction features include:

[0093] Rainfall-flow interaction: rainfall x standardized flow value;

[0094] Period-flow weight: Period weight (0-24 hours) x normalized flow value, weight setting: morning peak (7-9 am) = 1.5, evening peak (18-20 pm) = 1.3, night (0-6 am) = 0.8;

[0095] Pipe network type-COD adaptation: Pipe network type weight (industry = 1.2, life = 1.0, rain and sewage separation = 0.9) x normalized COD value;

[0096] Temperature-pH correction: air temperature x normalized pH value;

[0097] Device status-data reliability: sensor communication status (normal = 1, abnormal = 0) x power voltage normalized value (0-1).

[0098] 3、Multi-parameter fusion feature, used to capture cross-parameter correlation anomaly, based on the internal logic of sewage pipe network parameters (such as COD and turbidity positively correlated, flow and liquid level positively correlated), construct fusion features, identify joint anomalies that cannot be found by single parameter;

[0099] Multi-parameter fusion features include:

[0100] Water quality comprehensive index: weighted on normalized flow, liquid level, COD, ammonia nitrogen and pH value to obtain water quality comprehensive index;

[0101] Flow-liquid level consistency: calculate the Pearson correlation coefficient of flow and liquid level collected in the last 10 times (normal should be positively correlated, r> 0.6), r< 0.3 is an abnormal feature;

[0102] Pollution load index: the product of flow and COD.

[0103] 4、Trend feature, used to capture parameter gradual change anomaly, for slow deterioration anomaly (such as pipe siltation leading to gradual decrease of flow, sewage pollution leading to slow rise of COD), construct trend feature;

[0104] Trend features include:

[0105] First-order difference: current data-last 1 collected data;

[0106] Change slope: current data-last 6 collected data) / (6x collection period, unit: h)

[0107] Trend consistency: statistics of first-order difference sign (positive = 1, negative =-1) collected in the last 12 times, if consecutive ≥8 times sign is the same, it represents stable trend;

[0108] Mutation intensity: (current data-last 3 rolling mean) / last 3 rolling standard deviation, if the absolute value of the calculation result > 2, the mutation intensity is strong mutation.

[0109] In this embodiment, the model output values of the training set are sorted, and the quantile is calculated, for example: the 95th quantile of the Isolation Forest anomaly score = 0.8, then 0.8 is taken as the basic threshold to ensure that more than 95% of the normal data will not trigger the early warning.

[0110] Then, the scene type of the future period is obtained, and the scene correction coefficient is matched according to the scene type of the future period; the future period of this embodiment is 24 hours in the future, and the scene type of this embodiment includes: meteorological scene, date type, pipe network type, period feature and pipe network state.

[0111] The scene correction coefficient of this embodiment is as follows:

[0112] 1. Meteorological scene: in rainy days, the scene correction coefficient is 1.1, which is suitable for monitoring data such as flow and liquid level;

[0113] 2. Meteorological scene: in sunny days, the scene correction coefficient is 1.0, which is suitable for all monitoring data;

[0114] 3. Date type: on holidays or weekends, the scene correction coefficient is 0.9, which is suitable for monitoring data such as flow and COD;

[0115] 4. Date type: on weekdays, the scene correction coefficient is 1.0, which is suitable for all monitoring data;

[0116] 5. Pipe network type: for industrial sewage pipe network, the scene correction coefficient is 1.2, which is suitable for monitoring data such as COD and ammonia nitrogen;

[0117] 6. Pipe network type: for domestic sewage pipe network, the scene correction coefficient is 1.0, which is suitable for all monitoring data;

[0118] 7. Period feature: at night (0-6 o'clock), the scene correction coefficient is 0.8, which is suitable for monitoring data such as flow and COD;

[0119] 8. Pipe network state: there is recent dredging (within 7 days), the scene correction coefficient is 1.05, which is suitable for monitoring data such as flow and liquid level;

[0120] 9. Pipe network state: there is pipe repair (on the same day), the scene correction coefficient is 0.95, which is suitable for all monitoring data.

[0121] Finally, the basic threshold is corrected according to the scene correction coefficient to obtain the corrected threshold, and the corrected threshold is taken as the safety threshold of the monitoring data in the future period.

[0122] The expression of the corrected threshold of this embodiment is:

[0123] ;

[0124] wherein, is the revised threshold value, is the base threshold value, k i is the i-th scene revision coefficient, N is the total number of scene revision coefficients, N = 9 in the present embodiment, and k1 = 1.1 (i.e., corresponding to the weather scene: in rainy weather, the scene revision coefficient is 1.1).

[0125] As a further optimization of the present embodiment, the safety threshold value of each monitoring data in the future period is constrained by a preset constraint condition, which includes a safety constraint, a physical constraint, and a business constraint.

[0126] In the present embodiment, the scene-revised threshold value can have unreasonable cases (such as exceeding the sensor range or being lower than the national emission standard), which need to be revised by multi-layer constraint verification to ensure the safety and practicality of the threshold value.

[0127] The safety constraint is that the safety threshold value cannot be lower than the national / local emission standard, for example: COD: the actual value corresponding to the threshold value ≥ 50 mg / L, ammonia nitrogen: the actual value corresponding to the threshold value ≥ 15 mg / L; pH: the actual value corresponding to the threshold value ∈ [6.5, 8.5].

[0128] The physical constraint is that the safety threshold value cannot exceed the physical range of the parameter, for example: flow: threshold value ≤ pipe design upper limit Qmax × 1.5;

[0129] The business constraint is that the safety threshold value cannot deviate too much from the historical optimal threshold value (such as ≤ ± 20%), to avoid sudden changes in the threshold value on a single day.

[0130] The present embodiment can automatically learn the normal data fluctuation patterns under different scenes (seasons, weather, pipe network types) (such as the "morning peak sewage discharge" and "night low flow" rules of domestic sewage pipe networks); by dynamically adjusting the safety threshold value (rather than a fixed ± 20% or a fixed numerical value), the false alarm rate is reduced by more than 30%, the missed alarm rate is controlled within 5%, and it can also adapt to changes in the pipe network (such as the addition of a sewage outlet or changes in the flow pattern after pipe maintenance), without the need for frequent manual intervention in the threshold value.

[0131] The above is only an embodiment of the present application and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.

Claims

1. A sewage pipe network data acquisition terminal, characterized in that, include: A multi-parameter acquisition unit, wherein the multi-parameter acquisition unit is used to simultaneously acquire at least one type of monitoring data; The main control unit, wherein the multi-parameter acquisition unit is electrically connected to the main control unit, is used to perform anomaly monitoring on at least one monitoring data according to a set safety threshold, and obtain monitoring results; A communication unit, which is electrically connected to the main control unit, is used to upload monitoring data and monitoring results to the monitoring platform or receive instructions issued by the monitoring platform. An expansion interface unit is electrically connected to the main control unit and is used to connect external expansion devices.

2. The sewage pipe network data acquisition terminal according to claim 1, characterized in that, The multi-parameter acquisition unit includes a flow sensor, a liquid level sensor, and a water quality sensor, and the monitoring data is at least one of flow data, liquid level data, and water quality data.

3. The sewage pipe network data acquisition terminal according to claim 1, characterized in that, Also includes: Storage unit, which is electrically connected to control unit; The display unit is electrically connected to the control unit; The power supply unit provides operating power to the main control unit, communication unit, storage unit, display unit, and multi-parameter acquisition unit.

4. The sewage pipe network data acquisition terminal according to claim 1, characterized in that, Also includes: The housing has a motherboard inside, on which the main control unit, multi-parameter acquisition unit, communication unit and expansion interface unit are all integrated. A mounting plate is detachably connected to one side of the housing, and the mounting plate has slots.

5. The sewage pipe network data acquisition terminal according to claim 4, characterized in that, An operation panel is provided on the end face of the outer casing.

6. A sewage pipe network data monitoring system, characterized in that, The system includes: a monitoring platform, a mobile terminal, and several sewage pipe network data acquisition terminals as described in any one of claims 1-5; The mobile terminal is connected to each sewage pipe network data acquisition terminal and the monitoring platform, and each sewage pipe network data acquisition terminal is connected to the monitoring platform. At least one sewage pipe network data acquisition terminal constitutes a monitoring point. Each sewage pipe network data acquisition terminal is used to collect monitoring data from each monitoring point and to perform abnormal monitoring of the monitoring data of the monitoring point according to a preset safety threshold. When an abnormality occurs, an abnormal alarm is generated and sent to a mobile terminal or a monitoring platform. The monitoring platform is used to store the monitoring data and results uploaded by the data acquisition terminals of each sewage pipe network, and to configure the safety thresholds of each monitoring point.

7. The sewage pipe network data monitoring system according to claim 6, characterized in that, The steps for configuring the safety thresholds for each monitoring point on the monitoring platform are as follows: Within a preset time period, acquire historical data corresponding to any monitoring data, and construct a normal dataset corresponding to the monitoring data based on the historical data; Anomaly assessment of normal datasets is performed based on a pre-built data anomaly assessment model to obtain anomaly scores for normal datasets; Determine the baseline threshold based on the anomaly scores; Obtain the scene type for the future time period, and match the scene correction coefficient according to the scene type for the future time period; The base threshold is corrected based on the scenario correction factor to obtain the corrected threshold, which is then used as the safety threshold for the monitoring data in the future period.

8. The sewage pipe network data monitoring system according to claim 7, characterized in that, The safety thresholds for each monitoring data point in the future are constrained by preset constraints, which include security constraints, physical constraints, and business constraints.

9. The sewage pipe network data monitoring system according to claim 7, characterized in that, The data anomaly assessment model is based on an isolated forest.

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