Drainage pipe network overflow collaborative control method and system based on zoning hierarchical perception

Abstract

The application discloses a drainage pipe network overflow collaborative control method and system based on zoning and grading perception and belongs to the field of urban drainage pipe network operation control. The drainage pipe network overflow collaborative control method based on zoning and grading perception comprises the following steps: S1, deploying corresponding types of perception terminals in each zone to collect corresponding physical quantity parameters; S2, receiving physical quantity parameters uploaded by each perception terminal through a corresponding zone measurement and control terminal; S3, determining and matching a current abnormal scene through logical combination operation; S4, outputting a differentiated control instruction according to the matched abnormal scene; and S5, generating a reset signal to restore normal operation. The application does not require a complex deep learning algorithm, realizes real-time response based on pure hardware and hard logic, and reduces the deployment threshold. The application discards the dependence on complex algorithms such as neural networks and deep learning, designs differentiated control strategies according to the physical topology differences of upstream, midstream and downstream sections, and realizes precise disposal.

Description

Technical Field

[0001] This invention relates to the field of urban drainage network operation and control technology, and in particular to a drainage network overflow collaborative control method and system based on zoned and hierarchical sensing. Background Technology

[0002] With the increasing demands for improving the quality and efficiency of urban drainage systems in my country, "integrated plant and network" has become an industry consensus. However, most urban drainage systems in China still adhere to the construction and management model of "emphasizing plants over networks and separating plants from networks." Wastewater treatment plants, municipal pipe networks, and booster pumping stations are operated and maintained independently by different entities. Daily operation and maintenance rely on manual on-site inspections, lacking a unified digital sensing and data collection channel. Pipeline water quality, liquid level, and operation and maintenance work order data are scattered and isolated, lacking a unified top-level design and collaborative linkage mechanism, resulting in an overall imbalance in facility operation.

[0003] Currently, some drainage management units have begun to explore the construction of online monitoring and early warning systems for drainage pipe networks, but these systems generally suffer from the following technical defects: First, the deployment of sensing terminals in existing monitoring systems lacks differentiated design for different hydraulic characteristics. Typically, a uniform type of sensor (such as deploying only level gauges) and uniform deployment density are used throughout the entire pipeline network. This makes it impossible to conduct targeted monitoring based on the physical characteristics of different sections, such as upstream industrial impacts, midstream confluence overflows, and downstream transportation bottlenecks, resulting in a mismatch between monitoring data and scheduling needs.

[0004] Second, most existing early warning systems rely on manual experience or complex algorithm models. For example, the published Chinese patent application CN113902161A discloses a method for intelligent analysis of overflow early warning in drainage pipe networks. This method preprocesses historical liquid level time series data by performing box plot outlier detection, moving median filtering interpolation, and Box-Cox transformation, and then constructs a multi-layer superimposed LSTM network (with one-dimensional convolutional layers, batch normalization layers, and dropout layers). Based on the liquid level data of the previous two hours, it predicts the liquid level change trend of the next hour to achieve overflow early warning.

[0005] This technical solution has achieved certain results in terms of the accuracy of liquid level time-series prediction; however, it still has the following shortcomings: (1) This method relies heavily on a large amount of historical data for model training. The LSTM network contains complex gate control structures such as forget gate, update gate, and output gate, as well as a large number of trainable parameters. It has high requirements for computing power (GPU or high-performance CPU) and storage resources in the deployment environment, making it difficult to promote and apply in scenarios with limited edge computing resources, such as rural drainage facilities. (2) This method only predicts the liquid level at a single point and does not have the ability to comprehensively perceive and integrate multiple heterogeneous physical quantities such as water quality anomalies (such as COD / pH impact caused by industrial illegal discharge) and the degree of rainwater and sewage mixing (such as sudden change in conductivity). It is difficult to distinguish the specific causes of the overflow and is prone to false alarms. (3) The output of this method is only a warning signal, without any linkage control logic with pumping stations, sewage treatment plants and other actuators. After the warning is issued, manual judgment and dispatching instructions are still required, resulting in a large response delay and failure to form an automated closed-loop system of "perception, judgment, execution and verification".

[0006] Third, existing technologies lack differentiated scheduling strategies for three abnormal scenarios with drastically different physical characteristics: "upstream industrial illegal discharge impact," "midstream rainwater mixing and overflow," and "downstream inverted siphon blockage." For example, when there is a midstream overflow, the pumping station frequency needs to be reduced to reduce pressure, while when there is a blockage in the downstream inverted siphon, blindly increasing the pumping station frequency will exacerbate the blockage. Existing systems often use a single logic of "alarm when the liquid level is too high" or "record when the water quality exceeds the standard" to handle the situation, without realizing that different sections have conflicting needs for coordinated scheduling instructions, leading to misjudgment or invalidation of scheduling instructions. Summary of the Invention

[0007] The purpose of this invention is to solve the problems existing in the prior art, and to propose a collaborative control method and system for overflow of drainage pipe network based on zoned and hierarchical sensing.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: The drainage network overflow collaborative control method based on zoned and hierarchical sensing includes the following steps: S1: Divide the drainage network into multiple independent zones based on the physical topology and hydraulic characteristics, and deploy corresponding sensing terminals in each zone to collect corresponding physical parameters. S2: The data processing unit receives the physical quantity parameters uploaded by each sensing terminal through the corresponding partition's measurement and control terminal; S3: The data processing unit compares each physical quantity parameter with a preset fixed threshold, and determines and matches the current abnormal scenario through logical combination operations; The abnormal scenarios include at least the bottleneck scenario of pipe blockage; S4: The data processing unit outputs differentiated control instructions based on the matched abnormal scenarios; Among them, when the abnormal scenario is a bottleneck scenario of pipe blockage, only the dredging instruction is pushed to the field terminal, and the control instruction is prohibited from being sent to the pumping station and sewage treatment facility. S5: The data processing unit continuously monitors the feedback parameters. When the parameters fall back to each safety threshold and continue for a preset duration, a reset signal is generated to restore normal operation.

[0009] Preferably, the zones include an upstream industrial emission zone, a midstream combined sewer overflow zone, and a downstream river-crossing bottleneck zone, with corresponding deployment of a first sensing terminal, a second sensing terminal, and a third sensing terminal: The first sensing terminal is deployed in the upstream industrial discharge area to collect water quality chemical parameters; The second sensing terminal is deployed in the overflow area of ​​the midstream confluence main stream to collect hydraulic mixing parameters; The third sensing terminal is deployed in the bottleneck area of ​​downstream river crossing transportation to collect water level parameters.

[0010] Furthermore, in step S3, the preset fixed thresholds include trigger thresholds that match the parameters collected by the first sensing terminal, the second sensing terminal, and the third sensing terminal, respectively. The water level parameter determination corresponding to the third sensing terminal is also configured with a duration threshold. The water quality parameter trigger thresholds of the first sensing terminal include the COD shock warning threshold and the pH abnormal deviation threshold range; The trigger thresholds for hydraulic mixing parameters of the second sensing terminal include the conductivity discrimination threshold for rainwater and sewage mixing and the instantaneous flow surge threshold. The third sensing terminal triggers water level parameters, including critical sludge level threshold and duration threshold.

[0011] Furthermore, three types of abnormal scenarios are identified through logical combination operations: If the COD value collected by the first sensing terminal reaches the COD impact warning threshold, or the pH value exceeds the pH abnormal deviation threshold range, it is matched as an industrial illegal discharge impact scenario. If the conductivity value collected by the second sensing terminal is lower than the conductivity discrimination threshold for rainwater and sewage mixing, and the instantaneous flow value is higher than the instantaneous flow surge threshold, it is matched as a rainwater mixing overflow scenario; If the liquid level value collected by the third sensing terminal is higher than the critical sludge level threshold, and the duration of the state where the liquid level value is higher than the critical sludge level threshold exceeds the duration threshold, it is matched as a pipe section sludge bottleneck scenario.

[0012] Furthermore, when the scenario is matched to an industrial illegal discharge impact scenario, a process impact resistance electrical signal is sent to the pretreatment section of the sewage treatment facility, and a source tracing and location command is pushed to the field terminal.

[0013] Furthermore, when the scenario involves rainwater mixing with the overflow, a frequency reduction and capacity reduction drive signal is sent to the pumping station, a capacity evacuation and opening signal is sent to the sewage treatment facility's regulating tank, and an emergency dredging command for the overflow outlet is pushed to the field terminal.

[0014] Furthermore, when the scenario is a bottleneck due to pipe blockage, the system only pushes directional dredging coordinate instructions to the field terminal responsible for the corresponding zone, while simultaneously cutting off the control signal output of the pump station and sewage treatment facilities through hardware-level locking logic.

[0015] Furthermore, in step S5, the conditions for generating the reset signal are set according to the abnormal scenario as follows: In the scenario of industrial illegal discharge, when the water quality chemical parameters fall back to the corresponding safety threshold range, the reset judgment condition is met; In the case of rainwater mixing into the overflow, the reset judgment condition is met when the conductivity rises above the corresponding safety threshold and the flow rate falls below the corresponding safety threshold. In the case of a bottleneck in the pipeline, the reset judgment condition is met when the liquid level steadily drops below the normal level and the duration is longer than the preset duration, or when a dredging completion signal is received from the field terminal and the liquid level shows a downward trend.

[0016] Preferably, a preset fixed threshold is stored in the non-volatile memory of the data processing unit in the form of a fixed value; The response time for a single scene matching and command output does not exceed 500ms; When the sensing terminals deployed in each zone connect to the corresponding zone's measurement and control terminal, the data is aggregated and then independently uploaded to the data processing unit via wireless communication; The sensing and data acquisition links and data transmission links between each zone are physically isolated, forming independent subnets.

[0017] A drainage network overflow collaborative control system based on zoned and hierarchical sensing includes: The partitioned IoT sensing layer includes a first sensing terminal, a second sensing terminal, and a third sensing terminal deployed in each independent partition, used to collect physical quantity parameters of the corresponding partition. The signal processing layer is used to convert the signals output by the sensing terminal into processable digital electrical signals. The hard logic scene matching layer, built into the data processing unit, includes a multi-channel comparator module with preset fixed thresholds and a logic gate operation module, which is used to output scene identification electrical signals based on the comparison results between parameters and thresholds. The differentiated instruction generation layer includes a multi-channel selection switch, which is used to select the corresponding control loop according to the scenario identifier electrical signal. The multi-channel selection switch is configured to lock the output of the control loop corresponding to the pump station and the sewage treatment facility when matching the bottleneck scenario of pipe blockage.

[0018] Compared with existing technologies, this invention provides a collaborative control method for overflow in drainage pipe networks based on zoned and hierarchical sensing, which has the following beneficial effects: 1. This drainage network overflow collaborative control method based on partitioned and hierarchical perception does not require complex deep learning algorithms. It achieves real-time response based on pure hardware logic, reducing the deployment threshold. It abandons the dependence on complex algorithms such as neural networks and deep learning. All decision logic is implemented based on basic digital logic circuits such as comparators, AND gates, OR gates, and timing units. It can be directly embedded and run in data processing units or embedded microcontrollers. The response time for a single scene matching does not exceed 500 milliseconds. It does not rely on historical data training. It is especially suitable for scenarios with limited computing resources and maintenance personnel expertise, such as rural drainage facilities, thus lowering the technology promotion threshold.

[0019] 2. This drainage network overflow collaborative control method based on zoned and hierarchical perception uses zoned and hierarchical differentiated scheduling to avoid command conflicts. According to the physical topology differences of the upstream, midstream and downstream sections, differentiated control strategies are designed for three mutually exclusive scenarios: "industrial illegal discharge impact", "rainwater mixing into overflow", and "pipeline blockage bottleneck". In particular, when the pipeline blockage bottleneck scenario is identified, the system actively prohibits the sending of frequency modulation signals to the pumping station, avoiding erroneous intervention under the traditional unified logic and achieving precise handling.

[0020] 3. This drainage network overflow collaborative control method based on zoned and hierarchical perception transforms the traditional post-rain overflow emergency response mode into a systematic prevention and control mode of proactive interception, buffering, and dredging before or during rain by using early warning of industrial source COD or pH value, dual-factor linkage of midstream overflow outlets, and continuous monitoring of downstream inverted siphon liquid level. This reduces the risk of combined sewer overflow pollution during the flood season from a systems engineering perspective.

[0021] 4. The drainage network overflow collaborative control method based on zoned and hierarchical sensing uses spectral COD sensors, radar level gauges, ultrasonic Doppler flow meters, digital pH electrodes, and conductivity electrodes, all of which are standard industrial-grade sensors available on the market. Combined with a waterproof multi-parameter measurement and control terminal, it can achieve modular and rapid deployment. The spatial topology logic of the three typical points is common to most township drainage systems, and it has good cross-regional replication and promotion value.

[0022] 5. This drainage network overflow collaborative control method based on zoned and hierarchical perception achieves closed-loop management of the entire chain from early warning, handling, verification, and recovery through continuous monitoring and automatic reset mechanisms after the execution of control commands. This avoids secondary problems caused by maintaining special control states indefinitely. Since this invention uses hard logic judgment of the data processing unit, the scene matching response time is only limited by the scanning cycle of the data processing unit. Compared with the traditional mode that relies on manual inspection or complex model reasoning, the response speed is improved by orders of magnitude. Attached Figure Description

[0023] Figure 1This is a schematic diagram of the hard logic scene matching circuit topology of the present invention; Figure 2 This is a schematic diagram of the network topology for partitioned sensing and transmission according to the present invention. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0025] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0026] Example 1: Refer to Figures 1-2 A collaborative control method for overflow in drainage pipe networks based on zoned and hierarchical sensing includes the following steps; Step 1: Divide the drainage network into multiple independent zones based on its physical topology and hydraulic characteristics. Deploy corresponding types of sensing terminals in each zone to collect corresponding physical parameters.

[0027] The zones include the upstream industrial discharge zone, the midstream combined sewer overflow zone, and the downstream river transport bottleneck zone. The first, second, and third sensing terminals are deployed accordingly. The second sensing terminal is deployed in the midstream combined sewer overflow zone to collect hydraulic mixing parameters.

[0028] Specifically, the physical deployment method of the sensing terminal is as follows: the main overflow inspection well at the intersection of the town government in the middle reaches of a certain town is selected as the monitoring object. An integrated monitoring terminal is fixedly installed on the downstream outlet pipe wall of the inspection well. The terminal uses a waterproof multi-parameter measurement and control terminal as the data aggregation core. The measurement and control terminal is powered by a DC14.4V 114AH battery, has an IP68 protection rating, NB-IoT wireless transmission function, and is equipped with 3 sensor interfaces, which can simultaneously connect up to 6 MODBUS RS485 digital sensors.

[0029] It should be noted that the main overflow inspection well is the preferred location in this embodiment. Other inspection wells with overflow risk characteristics of the combined main pipe section can also be selected in the midstream area, as long as it is convenient to deploy flow and conductivity sensors.

[0030] Two sensors are deployed in the main overflow inspection well. One is an ultrasonic Doppler flow meter with the probe facing the direction of water flow at the bottom of the pipe. The flow meter has a range of -10 m / s to +10.000 m / s, a resolution of 0.001 m / s, and uses RS485 digital output. The flow meter has a baud rate of 9600, 8, N, 1, a device address of 10, an IP68 waterproof rating, and is equipped with a breather valve and waterproof connector. The flow meter is used to collect instantaneous flow and liquid level in real time. The flow meter can simultaneously calculate the liquid level value through the Doppler frequency shift principle. That is, one sensor outputs two physical quantities, flow and liquid level, at the same time, and has the hardware capability to measure liquid level. The second type is a digital conductivity electrode, which is immersed 0.5 meters below the surface of the main liquid. Its measurement range is 10 μS / cm to 200 mS / cm, and it uses RS485 digital output. The digital conductivity electrode has a baud rate of 9600, 8, N, 1, a device address of 2, and is equipped with an IP68 waterproof connector and a 10-meter cable. This digital conductivity electrode is used for continuous monitoring of the conductivity of wastewater. The digital signals from the ultrasonic Doppler flowmeter and the digital conductivity electrode are aggregated via an RS485 bus to a waterproof multi-parameter measurement and control terminal. After being packaged by the MCU inside the waterproof multi-parameter measurement and control terminal, they are transmitted to the data server of the regional control center via the NB-IoT wireless network for retrieval by the data processing unit.

[0031] Step 2: The data processing unit receives the physical quantity parameters uploaded by each sensing terminal through the corresponding zone's measurement and control terminal.

[0032] The preset fixed threshold is stored in the non-volatile memory of the data processing unit in the form of a fixed value, and is configured with a power-off retention attribute to remain constant during operation; the response time of a single scene matching and command output does not exceed 500ms.

[0033] When the sensing terminals deployed in each zone connect to the corresponding zone's measurement and control terminal, the data is aggregated and independently uploaded to the data processing unit via wireless communication; the sensing acquisition links and data transmission links between each zone are physically isolated, each forming an independent subnet.

[0034] Step 3: The data processing unit compares each physical quantity parameter with a preset fixed threshold, and determines and matches the current abnormal scenario through logical combination operations.

[0035] The preset fixed thresholds include trigger thresholds that match the parameters collected by the first sensing terminal, the second sensing terminal, and the third sensing terminal, respectively; the hydraulic mixing parameter trigger thresholds of the second sensing terminal include the stormwater and sewage mixing conductivity discrimination threshold C0 and the instantaneous flow surge threshold Q0.

[0036] Based on the design and operation parameters of the pipe section where the inspection well is located and the engineering operation experience, the baseline operating parameters under clear weather conditions are first determined. The conductivity fluctuation range of the upstream water inflow under stable operating conditions is taken as the baseline conductivity range, and the water flow fluctuation range under the corresponding conditions is taken as the baseline flow range. The statistical average values ​​of the two ranges are taken to obtain the baseline conductivity average value and the baseline flow average value, which are used as the baseline values ​​for subsequent threshold calculation.

[0037] The conductivity threshold C0 for rainwater and sewage mixing is set at 65% of the average baseline conductivity. The principle behind this setting is that the dissolved ion content in rainwater runoff is much lower than that in domestic sewage, and the overall conductivity of sewage will decrease significantly after rainwater mixes in. This value can identify the risk of rainwater mixing in advance before the water level in the pipe network rises significantly, and can also effectively filter out false triggers caused by normal water quality fluctuations.

[0038] The threshold Q0 for instantaneous flow surge is set at 250% of the average flow rate under clear weather conditions. The principle behind this setting is that when the flow rate increases to twice or more of the baseline value in a short period of time, it is determined that the flow rate is concentrated in the pipe network by rainfall runoff. At this time, the flow rate has exceeded the normal range of fluctuations in residents' daily water use. This value can accurately distinguish between normal flow fluctuations and overflow risk flow rates, taking into account both detection sensitivity and anti-interference ability.

[0039] The two types of thresholds mentioned above are written into the fixed threshold register of the non-volatile memory inside the data processing unit in the form of double-precision floating-point numbers, and the power-off retention attribute is configured to ensure that the threshold remains constant during system operation.

[0040] If the conductivity value collected by the second sensing terminal is lower than the conductivity discrimination threshold C0 for mixed rainwater and sewage, and the instantaneous flow value is higher than the instantaneous flow surge threshold Q0, it is matched as a rainwater mixing overflow scenario. At this time, the data processing unit sends a frequency reduction and flow reduction drive signal to the pumping station, causing the pumping station's operating frequency to be reduced by 10% to 20%. The data processing unit also sends a capacity vacating signal to the sewage treatment facility's regulating tank and pushes an emergency dredging command for the overflow outlet to the field terminal.

[0041] Specifically, the data processing unit has a built-in logic judgment program based on comparator instructions that directly reads two register values ​​reported from the measurement and control terminal: instantaneous flow rate Q and conductivity C. It should be noted that although the Doppler flow meter in this embodiment has the hardware capability to synchronously output liquid level values, the overflow determination in this scenario only relies on two physical quantities: conductivity and flow rate, and does not use liquid level as the determination input. The reason is that the response speed of conductivity to rainwater mixing is significantly better than the response speed of liquid level rise. The overflow determination method in this scenario can identify the overflow risk in advance through the rapid response characteristics of conductivity before the liquid level in the pipeline network rises significantly, thus gaining a valuable time window for downstream coordinated scheduling.

[0042] The data processing unit has two sets of independent fixed threshold registers, which store the conductivity discrimination threshold C0 for mixed rainwater and sewage and the instantaneous flow surge threshold Q0, respectively. The data processing unit distinguishes and calls the two types of thresholds independently through different register addresses. For example, the conductivity discrimination threshold C0 is stored in address unit DB1.DBD0, and the flow surge threshold Q0 is stored in address unit DB1.DBD4. When the program runs, it reads and calls the thresholds separately through address addressing, and the two types of thresholds do not interfere with each other and will not be confused.

[0043] In this embodiment, the conductivity discrimination threshold C0 for rainwater and sewage mixing is set at 65% of the average conductivity of normal domestic sewage in sunny weather. The basis for this setting is that rainwater runoff contains almost no dissolved ions, and the ion concentration of sewage is diluted after rainwater mixes in, resulting in a significant decrease in conductivity. This value can identify rainwater mixing in advance before the liquid level rises significantly, and can also filter out false alarms caused by normal water quality fluctuations.

[0044] In this embodiment, the instantaneous flow surge threshold Q0 is selected as 250% of the baseline flow rate in clear weather; To address the need for determining whether rainwater is mixed with overflow in this zone, the data processing unit is configured with two independent numerical comparator function blocks, connected to comparator one and comparator two respectively: Comparator 1: It can read the conductivity value C in real time. If C ≤ C0 in the comparator, then comparator 1 outputs a high-level signal "Flag_1". Comparator 2: It can read the instantaneous flow rate Q in real time. If Q in comparator 2 is greater than or equal to Q0, then comparator 2 outputs a high-level signal "Flag_2".

[0045] The data processing unit has a "dual-input AND gate" logic circuit unit. It determines that the current scenario is a rainwater overflow scenario caused by a large amount of rainwater mixing in, which leads to pipe flow overload, only when Flag_1 and Flag_2 are both high.

[0046] Step 4: The data processing unit outputs differentiated control instructions based on the matched abnormal scenarios.

[0047] The moment the AND gate outputs a high level, the data processing unit triggers a scene interrupt response and, based on the internally stored linkage address mapping table, outputs three control signals in parallel within ≤500ms: Pump station control signal: A 15% frequency reduction analog electrical signal is sent to the frequency converter controller of the midstream booster pump station via the ModbusTCP protocol to forcibly reduce the instantaneous pumping capacity of the pump station and prevent the overload of the pipeline network caused by pressurization from further deteriorating. Wastewater treatment plant control signal: Send a switching signal to the electric inlet valve of the emergency regulating tank in the pretreatment section of the wastewater treatment plant through a hard-wired dry contact to increase the valve opening to 100%, thereby forcibly opening the regulating tank to buffer peak wastewater. Field terminal signal: The IoT communication module pushes a structured data packet to the handheld terminal of the field personnel, which includes instructions such as "overflow warning and emergency dredging", the precise GPS coordinates of the inspection well and a list of rainwater and sewage mixing points within a 500-meter range upstream and downstream; the handheld terminal is a specific terminal with a dedicated operation and maintenance APP pre-installed, which supports structured data packet parsing, GPS coordinate display, work order feedback and other information reception and transmission.

[0048] Step 5: The data processing unit continuously monitors the feedback parameters. When the parameters fall back to the respective safety thresholds and remain there for the preset duration, a reset signal is generated to restore normal operation.

[0049] After the linkage control is executed, the data processing unit continuously monitors the real-time conductivity and flow data. When the conductivity rises to more than 80% of the average baseline conductivity and the flow rate falls to less than 150% of the average baseline flow rate for a period of 30 minutes, it is determined that the pipeline's overflow capacity has been restored. A reset electrical signal is then generated, the pump station frequency converter returns to the normal frequency band, the sewage treatment plant regulating valve resets to the normally closed state, and a "handling completed, warning lifted" instruction is pushed to the field terminal, ending the intervention operation process.

[0050] If the alarm is not restored within the preset time, the data processing unit maintains the control command and triggers the alarm status register to continuously output an alarm signal.

[0051] By using the above-mentioned deterministic hard logic judgment process, which uses two physical parameters, conductivity and instantaneous flow rate, as inputs and compares preset fixed threshold values ​​and performs AND gate logic operations, this invention enables the early identification of midstream overflow risks and efficient collaborative intervention operation of multiple equipment positions, including pumping stations, sewage treatment facilities, and field terminals, without relying on any complex algorithm models.

[0052] Example 2: Refer to Figures 1-2 This embodiment will elaborate on the specific application of the present invention in an industrial cluster area upstream of the drainage pipeline. This area usually contains potentially high-pollution emission enterprises such as food processing, electroplating or chemical industries. If the high-concentration wastewater discharged instantaneously by these enterprises is mixed into the pipeline, it will not only be transported downstream to impact the biological treatment system of the sewage treatment plant, but will also cause serious pollution after being superimposed with rainwater during the flood season.

[0053] The specific application of this invention in the industrial cluster area upstream of the drainage pipeline includes the following steps: Step 1: Divide the drainage pipeline into multiple independent zones according to the physical topology and hydraulic characteristics, deploy corresponding types of sensing terminals in each zone, and collect corresponding physical quantity parameters. The zones include the upstream industrial discharge zone, the midstream combined sewer overflow zone, and the downstream river transport bottleneck zone. The first, second, and third sensing terminals are deployed accordingly. The first sensing terminal is deployed in the upstream industrial discharge zone to collect water quality chemical parameters.

[0054] In this embodiment, the inspection well before the main discharge outlet of the upstream food processing plant in the town connects to the municipal sewage pipe network is selected as the key monitoring target. A monitoring terminal is installed in the inspection well. The core component of the monitoring terminal is a waterproof multi-parameter measurement and control terminal. Specifically, the waterproof multi-parameter measurement and control terminal is equipped with a DC14.4V 114AH battery, a waterproof rating of IP68, narrowband IoT NB-IoT, 3 sensor interfaces, and supports 6-channel MODBUS RS485 accessories.

[0055] The monitoring and control terminal is equipped with the following two sensors: One type is a spectroscopic COD sensor, which is fixedly installed in the stable mainstream area inside the inspection well. The measurement principle is ultraviolet absorption spectroscopy. The COD range of this sensor is 0-1000 mg / L, the turbidity range is 10-1000 NTU, and the COD measurement accuracy is ±5%. These parameters of the spectroscopic COD sensor are measured using KHP standard solution as the reference solution. The spectroscopic COD sensor has RS485 digital output, baud rate 9600, 8, N, 1, and the device address is set to 7. It is equipped with an IP68 waterproof connector and a 10-meter cable.

[0056] The second is a digital pH electrode sensor: This digital pH electrode sensor is installed side by side next to the spectroscopic COD sensor; the pH range of this digital pH electrode sensor is 0 to 14, supports RS485 digital output, baud rate 9600, 8, N, 1; the device address of this digital pH electrode sensor is set to 1, and it is equipped with an IP68 waterproof connector and a 10-meter cable. The spectroscopic COD sensor and the digital pH electrode sensor are installed side by side in the mainstream stable area inside the inspection well, which can ensure that the water sample monitored is representative of the same area.

[0057] The measured values ​​from the spectroscopic COD sensor and the digital pH electrode sensor can be aggregated to a waterproof multi-parameter measurement and control terminal via an RS485 bus. After being packaged by the waterproof multi-parameter measurement and control terminal, the data is uploaded to the independent register of the data processing unit via NB-IoT. The data processing unit can read the measured values ​​of the corresponding sensors through different addresses.

[0058] Step 2: The data processing unit receives the physical quantity parameters uploaded by each sensing terminal through the corresponding zone's measurement and control terminal; the preset fixed threshold is stored in the non-volatile memory of the data processing unit in the form of a fixed value. When the preset fixed threshold is stored in the memory, the memory is configured to retain the preset fixed threshold when power is off. During the operation of the memory, the preset fixed threshold remains constant. The response time for a single scene matching and command output does not exceed 500ms.

[0059] When the sensing terminals deployed in each zone connect to the corresponding zone's measurement and control terminal, the measurement and control terminal aggregates the data and then independently uploads it to the data processing unit via wireless communication; the sensing acquisition links and data transmission links between each zone are physically isolated; the sensing acquisition links and data transmission links between each zone can each form an independent subnet.

[0060] Step 3: The data processing unit compares each physical quantity parameter with a preset fixed threshold, and determines and matches the current abnormal scenario through logical combination operations.

[0061] The preset fixed thresholds include trigger thresholds that match the parameters collected by the first sensing terminal, the second sensing terminal, and the third sensing terminal, respectively. The first sensing terminal is deployed in the upstream industrial discharge area to collect water quality chemical parameters.

[0062] The data processing unit has two independent numerical comparator function blocks, which are used to receive the real-time COD value and the real-time pH value from the register, respectively.

[0063] The data processing unit has a set of preset thresholds, namely the COD shock warning threshold and the pH abnormal deviation threshold. In this embodiment, the COD shock warning threshold is set to 450 mg / L. The pH abnormal deviation threshold ranges from 5.5 to 9.0. When the real-time pH value is lower than 5.5 or higher than 9.0, it is determined that strong acid or strong alkali wastewater has been mixed in. The pH of normal municipal sewage is usually maintained between 6.5 and 8.5. A safety margin transition zone is reserved between the above-mentioned thresholds and the normal water quality range, which serves as a buffer boundary for abnormal judgment. The above thresholds are written into the non-volatile memory in the data processing unit as double-precision floating-point numbers, and the memory is configured to retain the preset fixed thresholds unchanged when power is off.

[0064] To address the need for determining the impact of industrial illegal discharge in this zone, the data processing unit is configured with two independent numerical comparator function blocks; the comparators connected to these two independent numerical comparator function blocks are comparator three and comparator four, respectively: Comparator 3: It can read the COD register value in real time. If C_COD in comparator 3 is greater than or equal to 450mg / L, it will output a high-level signal "Flag_COD"; if C_COD in comparator 3 is less than 450mg / L, it will output a low-level signal and set Flag_COD to 0. Comparator 4: It can read the pH register value in real time. If P_H < 5.5 or P_H > 9.0 in comparator 4, it outputs a high-level signal "Flag_pH". If the real-time pH value in comparator 4 is within the range of 5.5 to 9.0, it outputs a low-level signal, and Flag_pH is set to 0. When both Flag_pH and Flag_COD are low, the OR gate outputs a low level, and the industrial illegal discharge impact scenario judgment is not triggered. The control system of this invention maintains continuous real-time monitoring and normal operation. The data processing unit has a binary input OR gate logic circuit unit. When either Flag_COD or Flag_pH is high, the system determines that the current scenario is an industrial illegal discharge impact scenario.

[0065] The inspection well before the main discharge outlet of the upstream food processing plant in the town connects to the municipal sewage network was selected as the key monitoring target. Based on the design influent water quality standards of the upstream sewage treatment plant and industry specifications, the normal COD concentration range and normal pH fluctuation range of the water in the inspection well were determined. The shock warning threshold for the COD concentration of the water in the inspection well was 450 mg / L, which is based on the fact that the design influent COD concentration of a typical sewage treatment plant is about 500 mg / L as specified in the "Discharge Standard of Pollutants for Urban Wastewater Treatment Plants" GB18918-2002. 90% of the design concentration can be taken as the shock warning value. The pH value of the water in this inspection well deviates abnormally from the threshold range of 5.5 to 9.0. When the real-time pH value is lower than 5.5 or higher than 9.0, it is determined that the pH value of the water in the inspection well is abnormal. At this time, the pH value can be used as the real-time pH value of the mixed sewage in the inspection well of the upstream industrial discharge area. Under normal circumstances, the pH value of normal municipal sewage is in the range of 6.5 to 8.5. Therefore, it is reasonable to set the deviation threshold range of abnormal pH value to 5.5 to 9.0. The COD threshold and pH abnormal deviation range of the water in the aforementioned inspection well are written into the fixed threshold register of the non-volatile memory inside the data processing unit in the form of double-precision floating-point numbers. The register is configured to retain the preset threshold unchanged when power is off, so as to ensure that the threshold remains constant during operation.

[0066] Step four: The data processing unit outputs differentiated control instructions based on the matched abnormal scenarios; The moment the "binary input OR gate" outputs a high level, the data processing unit immediately triggers the "impact response interrupt program" and, within ≤1 second, issues advance control commands to the two downstream actuators and their corresponding supporting hardware: Among them, the first control command signal is sent to the dosing or aeration controller of the pretreatment section of the sewage treatment plant. The command "advanced warning and process pre-adjustment" is sent to the precision dosing system and aeration blower frequency converter at the inlet of the sewage treatment plant via industrial Ethernet. The instantaneous value of the coagulant dosage ratio in the precision dosing system is increased by 20% based on the original normal coagulant dosage in the precision dosing system, and the air supply of the corresponding aeration blower is increased at the same time. The instantaneous value of the coagulant dosage ratio in the precision dosing system is increased by 20% based on the original normal coagulant dosage in the precision dosing system. This is an optimal value based on engineering experience. The increase ratio of the coagulant dosage can be adjusted within the range of 15% to 30%, and the specific amount is determined by the wastewater treatment plant process personnel based on the preset impact intensity and the actual situation as predicted. For example, in a typical township wastewater treatment plant with a treatment capacity of 500–2000 m³ / d, when encountering a sudden surge in the COD concentration of the wastewater to above 450 mg / L, the instantaneous value of the coagulant dosage in the precision dosing system corresponding to the wastewater treatment at that location will be increased by 20% from the normal dosage in the same system. This can rapidly enhance the flocculation effect of the wastewater treatment without wasting coagulant, and can also mitigate the impact load of the wastewater on the biochemical system of the township wastewater treatment plant; simultaneously, the corresponding aeration... The air supply of the aeration blower can be increased by increasing the operating frequency of the aeration blower. For example, the operating frequency of the corresponding aeration blower can be increased by 10% to 20% compared to the original normal operating frequency of the corresponding aeration blower; or the number of operating corresponding aeration blowers can be increased to increase the supply of dissolved oxygen to the water body. The specific increase is determined by the township sewage treatment plant based on the impact intensity of the sewage body and the real-time measurement value of dissolved oxygen in the corresponding pool. The data processing unit only sends a switch or analog control signal for "increase air supply", which is executed by the corresponding aeration control system of the township sewage treatment plant.

[0067] The second control command signal is sent to the mobile terminal of the field law enforcement / inspection personnel, or pushed to the PDA mobile terminal of the pipeline inspection personnel through the Internet of Things communication module. The "Industrial Source Traceability and Investigation Order" with a red highlight is pushed. The control command signal contains the precise latitude and longitude coordinates of the detection point, the COD concentration of the water body when the alarm is triggered, and the specific pH value of the water body.

[0068] The precise latitude and longitude coordinates of the detection point are collected by a handheld GPS surveying instrument or RTK positioning device during the initialization of the control system of this invention, and are written as a fixed attribute into the metadata field of the point in the address mapping table of the data processing unit. When an alarm is encountered, the data processing unit directly calls the pre-stored coordinates and embeds the pre-stored coordinates into the data packet for push / send, without the need for real-time positioning. The manhole cover numbers of the inspection wells before the main discharge outlet of the food processing plant upstream of the town connects to the municipal sewage pipe network are manually arranged and entered according to the rule of "administrative division-road name-manhole number".

[0069] Step 5: The data processing unit continuously monitors the feedback parameters. When the parameters fall back to each safety threshold and remain there for a preset duration, a reset signal is generated to restore normal operation.

[0070] After the linkage control is executed, the data processing unit of the control system of the present invention continuously monitors the COD concentration and real-time pH value of the water at the upstream monitoring point. If, within a preset 1-hour period, the real-time COD concentration of the water at the monitored point drops below 380 mg / L, and the pH value of the water at the monitored point simultaneously recovers to the range of 6.0 to 8.5, the data processing unit determines that the impact of industrial pollution on the water at the monitored point has been effectively diluted or blocked. 380 mg / L is approximately 84% of 450 mg / L, and the COD concentration of 380 mg / L at the monitored point is used as the safety margin value for the impact to recede. When the real-time COD concentration of the monitored water body is 380 mg / L, it indicates that the high-concentration industrial wastewater has been effectively diluted or blocked. The relevant process control personnel of this invention's control system can also adjust the real-time COD concentration of the monitored water body to 400–420 mg / L based on the actual process conditions of the water body being treated. Specifically, when the real-time COD concentration of the monitored water body drops back to 380 mg / L, 380 mg / L is used as a preferred reset threshold, ensuring that the impact of the high-concentration industrial wastewater has fully subsided when the COD concentration of the monitored water body drops back to this value and completes the reset. The pH value reset threshold range of the monitored water body is 6.0 to 8.5, which is slightly wider than the normal pH range of municipal sewage (6.5 to 8.5). A hysteresis margin is reserved between the trigger threshold and the normal water quality range, which can avoid frequent reset jitter of the control system of the present invention caused by water quality fluctuations near the boundary value, thus ensuring the operational stability of the control system of the present invention.

[0071] When the control system of the present invention responds to the above-mentioned determination, the data processing unit therein can automatically generate reset logic, cancel the "advanced warning" state, and push a "tracing task completed" confirmation command to the mobile terminal.

[0072] Example 3: Refer to Figures 1-2This embodiment will elaborate on the specific application of the present invention in the bottleneck area of ​​the cross-river inverted siphon transportation in the downstream of the drainage pipe network. This area is a key bottleneck section of the pipe network's hydraulic transportation, and usually has problems such as limited flow capacity, high water level during the flood season, and siltation. If the upstream water flow is superimposed with rainfall runoff, resulting in a sudden increase in flow, it will not only cause the inverted siphon section to overflow and pollute the river water quality, but also cause the downstream sewage treatment plant's influent load to fluctuate drastically, affecting the stable operation of the treatment system.

[0073] The specific application of this invention in the bottleneck area of ​​the cross-river inverted siphon transportation in the downstream of the drainage pipe network includes the following steps: Step 1: Divide the drainage pipe network into multiple independent zones according to the physical topology and hydraulic characteristics, deploy corresponding types of sensing terminals in each zone, and collect corresponding physical quantity parameters.

[0074] The zones include the upstream industrial discharge zone, the midstream combined sewer overflow zone, and the downstream river transport bottleneck zone. The first, second, and third sensing terminals are deployed accordingly. The third sensing terminal is deployed in the downstream river transport bottleneck zone to collect water level parameters.

[0075] In this embodiment, the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant is selected as the key monitoring point; a radar level gauge is installed on the top of the inner wall of the inspection well. The radar level gauge adopts the non-contact radar wave measurement principle, and the probe of the radar level gauge is vertically oriented towards the water surface. The key technical parameters of this radar level gauge are: measuring range 0-5m, accuracy ±0.25% or ±10mm (whichever is greater), resolution 1mm, and waterproof rating IP68. The measurement data from the radar level gauge is output to a waterproof multi-parameter monitoring and control terminal connected near the wellhead via an RS485 digital interface. After being packaged by the waterproof multi-parameter monitoring and control terminal, it is sent to the dedicated register of the data processing unit in the regional control center via the NB-IoT network. It should be noted that in this embodiment, the level value occupies one register with the address DB3.DBD0, which is used for storing and retrieving level data and comparing thresholds. The number of registers in the data processing unit is limited by the hardware model, and this system uses only a small number of registers, far below the upper limit.

[0076] It should be noted that the sensing terminal in this embodiment is in a completely independent subnet in terms of pipeline topology from the sensing terminal in the aforementioned midstream main overflow pipe section. The water intake of the inverted siphon well comes only from the Hexi area and does not receive water from the main pipeline of the Hedong Town Government, which provides a physical isolation premise for the implementation of "zoned control".

[0077] Step 2: The data processing unit receives the physical parameters uploaded by each sensing terminal through the corresponding monitoring and control terminal in the zone; the zone includes the upstream industrial discharge zone, the midstream combined sewer overflow zone, and the downstream river crossing bottleneck zone, and deploys the first sensing terminal, the second sensing terminal, and the third sensing terminal accordingly; the third sensing terminal is deployed in the downstream river crossing bottleneck zone to collect water level parameters.

[0078] Reference Figure 2 The upstream industrial emission zone, the midstream combined sewer overflow zone, and the downstream river-crossing bottleneck zone each form an independent subnet. Sensors in each zone transmit data to a waterproof multi-parameter monitoring and control terminal via an RS485 bus and wirelessly to the data processing unit. This achieves physical isolation, ensuring that the sensors and communication links in each subnet are completely independent and do not affect each other. A single point of failure will not affect other zones. Furthermore, each zone's thresholds and parameters can be independently configured, set, and maintained, so that when expanding to add new monitoring zones, there is no need to modify the existing subnet architecture.

[0079] Step 3: The data processing unit compares each physical quantity parameter with a preset fixed threshold, and determines and matches the current abnormal scenario through logical combination operation. The preset fixed thresholds include trigger thresholds that match the parameters collected by the first sensing terminal, the second sensing terminal, and the third sensing terminal respectively. Among them, the water level parameter determination corresponding to the third sensing terminal is also configured with a duration threshold. The water level parameter trigger threshold of the third sensing terminal includes a critical siltation level threshold and a duration threshold.

[0080] The data processing unit has two sets of independent register thresholds for key monitoring points, namely the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant. These two sets of independent register thresholds are the liquid level threshold and the duration threshold. The liquid level threshold includes the normal water conveyance liquid level reference value L_n of the U-tube and the critical blockage liquid level alarm threshold L_d of the U-tube. In this embodiment, the normal water conveyance liquid level reference value L_n of the U-tube is taken as the radar liquid level gauge reading corresponding to 1.5m below the pipe top elevation; the critical blockage liquid level alarm threshold L_d of the U-tube is the radar liquid level gauge reading corresponding to 0.2m below the pipe top elevation; the duration threshold is implemented by a timer set inside the data processing unit to determine the duration of the abnormal liquid level state.

[0081] To address the need for determining the sludge blockage scenario in the inverted siphon inlet inspection well connecting the Hexi area to the Hedong sewage treatment plant as a key monitoring point, the corresponding data processing unit is configured with two independent numerical comparator function blocks. These two independent numerical comparator function blocks are connected to comparator five and comparator six, respectively. Comparator 5: It can continuously compare the real-time reading L of the radar level gauge with the critical sludge level alarm threshold L_d of the U-tube. When L≥L_d, the output level signal of comparator 5 drives the timer to start accumulating from zero. Comparator 6: When the cumulative value of the timer continuously exceeds the preset duration threshold, the current scenario is determined to be a pipe blockage bottleneck scenario. Specifically, the pipe blockage bottleneck scenario is a transportation bottleneck scenario in which the bottom of the inverted siphon U-shaped pipe is substantially blocked. In this embodiment, the value range of the duration threshold is 10 to 15 minutes. This value range of the duration threshold can filter out short-term liquid level fluctuations, such as short-term liquid level fluctuations caused by external factors such as temporary obstruction by large floating objects or fluctuations in pump station start-up and shutdown, thus avoiding false alarms. The reason for setting the time duration threshold to a range of 10 to 15 minutes is that if the time duration threshold is too short, it will cause short-term liquid level fluctuations caused by external factors, thus inducing false alarms; if the time duration threshold is too long, it will delay the opportunity to deal with the blockage. Among them, 15 minutes is the preferred time for rural drainage systems, which can take into account both the sensitivity and anti-interference of the control system of this invention.

[0082] In this embodiment, based on the design parameters and top elevation of the inverted siphon U-shaped pipe, the liquid level reference under normal water conveyance conditions is determined. The specific method is as follows: take the normal water conveyance liquid level reference value L_n, where L_n is the radar level gauge reading corresponding to 1.5m below the top elevation of the pipe; take the critical sludge level alarm threshold L_d, where L_d is the radar level gauge reading corresponding to 0.2m below the top elevation of the pipe; and take 15 minutes as the duration threshold for this time. The critical sludge level alarm threshold and the duration threshold are written into the fixed threshold register of the non-volatile memory inside the data processing unit in the form of double-precision floating-point numbers. The register is configured to retain the preset threshold unchanged when power is off, so as to ensure that the threshold remains constant during operation.

[0083] Step 4: The data processing unit outputs differentiated control instructions based on the matched abnormal scenario; when the matched scenario is a pipe blockage bottleneck, it only pushes directional dredging coordinate instructions to the field terminal responsible for the corresponding zone, and at the same time cuts off the control signal output of the pumping station and sewage treatment facilities through hardware-level locking logic.

[0084] Unlike the midstream overflow scenario in Example 1, when the pipe blockage bottleneck scenario in this example is triggered, the data processing unit actively prohibits sending any control signals to the pumping station or sewage treatment plant, and only executes the following single precise field operation instruction. Furthermore, the data processing unit pushes an "emergency targeted clearing work order" blockage alarm instruction data packet to all handheld terminals in the pipeline maintenance team within its jurisdiction through the built-in IoT module. This data packet contains the following dedicated data packet fields: Task type: Marked as "U-shaped inverted siphon special dredging", its priority is the highest level; The working coordinates are the GPS coordinates and manhole cover numbers of the inverted siphon intake wells on the west bank of the Hexi area. The GPS coordinates of these inverted siphon intake wells on the west bank are collected by surveying equipment and pre-stored in the metadata of the address mapping table of the data processing unit during the initialization of the control system of this invention. The data processing unit does not embed a GPS positioning program, but only calls the pre-stored coordinates. The manhole cover numbers are manually arranged and entered into the system according to the rule of "administrative division code-road abbreviation-manhole number". The accompanying operating data in the control system of this embodiment includes: automatically reported real-time liquid level value and duration of continuous exceedance at the point. The real-time liquid level value is the real-time reading L of the radar liquid level gauge read by the data processing unit from the corresponding liquid level register; the duration of continuous exceedance is the cumulative value of the timer inside the data processing unit. The real-time liquid level value and duration of continuous exceedance can be automatically attached to the siltation alarm command data packet and pushed without manual intervention.

[0085] Unlike the midstream overflow scenario in Example 1, which requires immediate coordinated intervention from the pumping station and wastewater treatment plant, this example proactively prohibits sending any control signals to the pumping station and wastewater treatment plant when the pipe section is identified as a bottleneck due to blockage. The reason is that blockage in the inverted siphon U-shaped pipe section is a physical narrowing or blockage. Sending frequency-increasing or flow-increasing signals to the pumping station according to conventional logic would not only fail to flush and clear the blockage but would also cause a rapid rise in the water level of the inverted siphon inlet well due to increased upstream water pressure, exacerbating the risk of overflow from the upstream inspection well. Similarly, sending control signals to the wastewater treatment plant according to conventional scheduling logic would not address the root cause of the blockage. Therefore, this example employs a no-action and precise dredging field command as the optimal differentiated control strategy for this specific scenario, avoiding misjudgments of commands under traditional unified scheduling logic. The no-action aspect refers to prohibiting control.

[0086] Step 5: The data processing unit continuously monitors the feedback parameters. When the parameters fall back to each safety threshold and reach the preset duration, a reset signal is generated to restore normal operation. It should be noted that the safety threshold in this invention is set separately for the three different abnormal scenarios, and is a reset judgment threshold with a safety margin compared to the trigger threshold; the time duration threshold is the shortest time that the corresponding time parameter needs to be maintained continuously after falling back to the safety threshold; the above safety threshold and time duration threshold are used together to confirm the stable recovery of the working condition and avoid false resets caused by boundary fluctuations in the value range.

[0087] In this embodiment, a reset decision is made when any of the following conditions are met in the scenario of a bottleneck caused by pipe blockage: Condition 1: The liquid level of the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant stably drops below the normal liquid level, and the duration reaches the preset time duration threshold. Condition 2: The field terminal receives a signal indicating that the dredging is complete, and the liquid level in the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant shows a continuous downward trend.

[0088] If, within the preset 4-hour monitoring window after the dredging command is issued, or after the "Dredging Completed" button is manually clicked on the terminal, the real-time reading L of the radar level gauge of the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant gradually decreases and stabilizes at a level less than or equal to the normal water level reference value L_n of the U-shaped pipe, and the duration of this stable state reaches the preset time duration threshold, i.e., 15 minutes, then the reset is determined to be successful.

[0089] When the control system of the present invention responds to the above-mentioned reset judgment, the corresponding data processing unit in the control system of the present invention automatically resets the siltation alarm status of the point corresponding to the inverted siphon inlet inspection well connecting the Hexi area to the Hedong sewage treatment plant using a register, and pushes a confirmation message of "liquid level has returned to normal" to all mobile terminals of the team members responsible for the operation and maintenance management of the pipeline network in this area that are pre-installed with a dedicated operation and maintenance APP. At the same time, it automatically generates a "siltation effect verification" record and stores it in the historical archive.

[0090] In this invention, the data processing unit in the control system continuously issues alarms and repeatedly pushes work orders every 30 minutes. If the liquid level does not recover after 4 hours, the alarm is upgraded to the upper-level management platform, such as the district / county-level drainage supervision platform, and manual intervention is required. At the same time, the data processing unit maintains a safe state that prohibits pump station control. The historical archives refer to the historical database of the host computer or the historical archiving module of the SCADA system connected to the data processing unit via industrial Ethernet.

[0091] Specifically, the data processing unit in the control system of this invention can be operated by a main control PLC.

[0092] In this application, Example 1 focuses on the combined sewer main pipe section in the middle reaches of urban drainage pipe networks where overflows are frequent during the flood season. The main overflow inspection well is the preferred location in this example. Other inspection wells with overflow risk characteristics of combined sewer main pipe sections can also be selected in the middle reaches. The application fully verifies the dual-factor AND gate hard logic judgment method of conductivity and instantaneous flow in the main overflow inspection well under the condition of rainwater mixing and overflow, as well as the multi-subject collaborative linkage control strategy of frequency reduction and pressure reduction of the corresponding pumping station connected to the main overflow inspection well, sewage treatment plant reservoir emptying and buffering, and field point dredging. At the same time, it also verifies the closed-loop reset mechanism based on real-time hydraulic parameter feedback, which solves the technical problems of traditional middle reaches overflow monitoring relying solely on liquid level warning with lag, lack of linkage between plant and network pumping stations, and slow response speed. It fully demonstrates the technical practicality and use value of this invention in the scenario of combined sewer main pipe overflow prevention and control.

[0093] Example 2: Targeting the source of illegal discharge of high-concentration industrial wastewater from an industrial cluster upstream of the drainage network, the inspection well before the main discharge outlet of a food processing plant upstream of the town connects to the municipal sewage network was selected as the key monitoring target. A monitoring terminal was installed in this inspection well. The core component of this monitoring terminal is a waterproof multi-parameter measurement and control terminal, which is equipped with two sensors: a spectroscopic COD sensor and a digital pH electrode sensor. Both sensors are fixedly installed in the stable mainstream area inside the inspection well. The reliability of the COD and pH dual-parameter OR gate hard logic judgment method was verified, as well as the source impact proactive linkage control strategy of wastewater treatment plant process advance adjustment and field tracing and location. At the same time, the closed-loop reset logic based on water quality parameter feedback was verified, solving the problem that traditional systems cannot identify industrial water quality impacts in advance and wastewater treatment plants passively respond, leading to overload of the biochemical system. This demonstrates the accurate identification and proactive prevention and control capabilities of this invention for upstream water quality anomalies.

[0094] Example 3: Addressing the physical blockage of the downstream cross-river inverted siphon transport bottleneck in the drainage network, the inverted siphon intake inspection well connecting the Hexi area to the Hedong sewage treatment plant was selected as a key monitoring point. A radar level gauge was installed on the top of the inner wall of this inspection well. The accuracy of the time-series logic method for determining the level threshold and duration was verified, as well as the differentiated control strategy of precise dredging only by field personnel and prohibiting pump station and sewage treatment plant regulation. Simultaneously, the network architecture of physically isolated independent subnets and the single-variable closed-loop reset mechanism were verified. This solved the problems of misjudging downstream blockage scenarios and blindly increasing pressure, which exacerbates the risk of upstream backflow and overflow, as with traditional unified scheduling logic. This highlights the core advantages of this invention: differentiated scheduling and avoidance of command conflicts.

[0095] The three embodiments correspond to three typical functional sections of the pipeline network—midstream, upstream, and downstream—and three abnormal operating conditions with vastly different physical characteristics. They also correspond to three different hard logic judgment modes—AND gate, OR gate, and sequential logic—and respectively verify the three differentiated collaborative control strategies. From the three dimensions of scenario coverage, logic support, and strategy verification, they jointly support the core inventive concept of this invention: partitioned and hierarchical perception, hard logic judgment, and differentiated collaborative control, and fully cover the typical operating conditions of the entire pipeline network from source to end.

[0096] Example 4: This application also provides a drainage network overflow collaborative control system based on zoned and hierarchical sensing, including a zoned IoT sensing layer, a signal processing layer, a hard logic scene matching layer, and a differentiated instruction generation layer. The zoned IoT sensing layer includes a first sensing terminal, a second sensing terminal, and a third sensing terminal deployed in each independent zone, used to collect physical quantity parameters of the corresponding zone; the signal processing layer is used to convert the signals output by the sensing terminals into processable digital electrical signals; the hard logic scene matching layer is built into the data processing unit and includes a multi-channel comparator module with preset fixed thresholds and a logic gate operation module, used to output scene identification electrical signals according to the comparison results of parameters and thresholds; the differentiated instruction generation layer includes a multi-channel selection switch, used to select the corresponding control loop according to the scene identification electrical signal; the multi-channel selection switch is configured to lock the control loop output corresponding to the pump station and sewage treatment facility when matching a bottleneck scenario of pipe segment blockage.

[0097] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for coordinated control of overflow in drainage pipe networks based on zoned and hierarchical sensing, characterized in that, The following control steps are included: S1: Divide the drainage network into multiple independent zones based on the physical topology and hydraulic characteristics, and deploy corresponding sensing terminals in each zone to collect corresponding physical parameters. S2: The data processing unit receives the physical quantity parameters uploaded by each sensing terminal through the corresponding partition's measurement and control terminal; S3: The data processing unit compares each physical quantity parameter with a preset fixed threshold, and determines and matches the current abnormal scenario through logical combination operations. The abnormal scenarios include at least the bottleneck scenario of pipe blockage; S4: The data processing unit outputs differentiated control instructions based on the matched abnormal scenarios; When the abnormal scenario is a bottleneck scenario of pipe blockage, only the dredging command is pushed to the field terminal, and the control command is prohibited from being sent to the pumping station and sewage treatment facility. S5: The data processing unit continuously monitors the feedback parameters. When the parameters fall back to each safety threshold and continue for a preset duration, a reset signal is generated to restore normal operation.

2. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 1, characterized in that, The zones are divided into an upstream industrial emission zone, a midstream combined sewer overflow zone, and a downstream river-crossing bottleneck zone, with corresponding deployment of first, second, and third sensing terminals: The first sensing terminal is deployed in the upstream industrial discharge area to collect water quality chemical parameters; The second sensing terminal is deployed in the overflow area of ​​the midstream confluence main stream to collect hydraulic mixing parameters; The third sensing terminal is deployed in the bottleneck area of ​​downstream river crossing transportation to collect water level parameters.

3. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 2, characterized in that, In step S3, the preset fixed thresholds include trigger thresholds that match the parameters collected by the first sensing terminal, the second sensing terminal, and the third sensing terminal, respectively. The water level parameter determination corresponding to the third sensing terminal also includes a duration threshold. The water quality parameter trigger thresholds of the first sensing terminal include the COD shock warning threshold and the pH abnormal deviation threshold range; The trigger thresholds for hydraulic mixing parameters of the second sensing terminal include the conductivity discrimination threshold for rainwater and sewage mixing and the instantaneous flow surge threshold. The third sensing terminal triggers water level parameters, including critical sludge level threshold and duration threshold.

4. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 3, characterized in that, Three types of abnormal scenarios were identified through logical combination operations: If the COD value collected by the first sensing terminal reaches the COD impact warning threshold, or the pH value exceeds the pH abnormal deviation threshold range, it is matched as an industrial illegal discharge impact scenario. If the conductivity value collected by the second sensing terminal is lower than the conductivity discrimination threshold for rainwater and sewage mixing, and the instantaneous flow value is higher than the instantaneous flow surge threshold, it is matched as a rainwater mixing overflow scenario; If the liquid level value collected by the third sensing terminal is higher than the critical sludge level threshold, and the duration of the state where the liquid level value is higher than the critical sludge level threshold exceeds the duration threshold, it is matched as a pipe section sludge bottleneck scenario.

5. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 4, characterized in that, When the scenario is matched to an industrial illegal discharge impact scenario, a process impact resistance electrical signal is sent to the pretreatment section of the sewage treatment facility, and a source tracing and location command is pushed to the field terminal.

6. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 4, characterized in that, When the scenario is rainwater mixing into the overflow, a frequency reduction and capacity reduction drive signal is sent to the pumping station, a capacity evacuation and opening signal is sent to the sewage treatment facility's regulating tank, and an emergency dredging command for the overflow outlet is pushed to the field terminal.

7. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 4, characterized in that, When the matching scenario is a bottleneck due to pipe blockage, the system only pushes directional dredging coordinate instructions to the field terminal responsible for the corresponding zone, and at the same time cuts off the control signal output of the pump station and sewage treatment facilities through hardware-level locking logic.

8. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 4, characterized in that, In step S5, the conditions for generating a reset signal are set according to the abnormal scenario as follows: In the scenario of industrial illegal discharge, when the water quality chemical parameters fall back to the corresponding safety threshold range, the reset judgment condition is met; In the case of rainwater mixing into the overflow, the reset judgment condition is met when the conductivity rises above the corresponding safety threshold and the flow rate falls below the corresponding safety threshold. In the case of a bottleneck in the pipeline, the reset judgment condition is met when the liquid level steadily drops below the normal level and the duration is longer than the preset duration, or when a dredging completion signal is received from the field terminal and the liquid level shows a downward trend.

9. The drainage network overflow collaborative control method based on zoned and hierarchical sensing according to claim 1, characterized in that, A preset fixed threshold is stored in the non-volatile memory of the data processing unit in the form of a fixed value; The response time for a single scene matching and command output does not exceed 500ms; When the sensing terminals deployed in each zone connect to the corresponding zone's measurement and control terminal, the data is aggregated and then independently uploaded to the data processing unit via wireless communication; The sensing and data acquisition links and data transmission links between each zone are physically isolated, forming independent subnets.

10. A drainage network overflow collaborative control system based on zoned and hierarchical sensing, employing the drainage network overflow collaborative control method based on zoned and hierarchical sensing as described in any one of claims 1-9, characterized in that, include: The partitioned IoT sensing layer includes a first sensing terminal, a second sensing terminal, and a third sensing terminal deployed in each independent partition, used to collect physical quantity parameters of the corresponding partition. The signal processing layer is used to convert the signals output by the sensing terminal into processable digital electrical signals. The hard logic scene matching layer, built into the data processing unit, includes a multi-channel comparator module with preset fixed thresholds and a logic gate operation module, which is used to output scene identification electrical signals based on the comparison results between parameters and thresholds. The differentiated instruction generation layer includes a multi-channel selection switch, which is used to select the corresponding control loop according to the scenario identifier electrical signal. The multi-channel selection switch is configured to lock the output of the control loop corresponding to the pump station and the sewage treatment facility when matching the bottleneck scenario of pipe blockage.

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