Drainage pipe network liquid level monitoring device and method with self-correction function

Abstract

The invention discloses a drainage pipe network liquid level monitoring device and method with a self-correcting function, and belongs to the technical field of metering testing, the drainage pipe network liquid level monitoring device comprises a shell, a capacitance sensor, a circuit control structure and a storage battery are installed in the shell, the capacitance sensor is electrically connected with the circuit control structure, and the circuit control structure is electrically connected with an absolute pressure type sensor through a wire; the circuit control structure is connected with a cloud platform through wireless signals, the capacitive sensor and the absolute pressure type sensor are connected with the storage battery, and the absolute pressure type sensor is fixedly located in a monitoring environment. By means of the mode, the monitoring device can achieve self-correction of the liquid level monitoring sensor without manual participation.

Description

Technical Field

[0001] The present invention relates to the technical field of measurement and testing, and in particular to a drainage pipe network liquid level monitoring device and method with self-correction. Background Art

[0002] As a vital component of urban infrastructure, urban drainage systems are responsible for treating and removing urban sewage and rainwater, and are crucial for ensuring the sustainable and healthy development of cities. To prevent pipe networks from operating at high liquid levels and maximize their water storage capacity, liquid level monitoring is essential.

[0003] With the development of materials science and communication technology, the technologies used in liquid level detection at home and abroad include: gauge type, float type, acoustic wave type, capacitance type, DC electrode type, fiber optic type, induction type, etc. The two most widely used liquid level detection methods are acoustic wave type and gauge type. The acoustic wave level meter is a non-contact measurement method with the characteristics of high accuracy, simple installation, easy maintenance and unaffected by factors such as liquid viscosity and density. However, there is a certain blind spot in the measurement. Once the liquid level rises to the blind spot range of the ultrasonic sensor, the liquid level will not be correctly detected. The differential pressure level meter is a contact measurement method with the advantages of reliable operation, stable quality, long life, simple structure, small size and suitable for most normal temperature and pressure occasions. However, it usually needs to be connected to atmospheric pressure and cannot be used for a long time in humid and submerged environments underground.

[0004] Pressure sensors are widely used. They can operate fully submerged underwater, eliminating the need for vents and meeting the requirements for liquid level monitoring in high-level pipelines. However, pressure-type liquid level monitoring equipment is susceptible to the following factors during long-term operation: cumulative errors caused by zero-point drift of the pressure sensor, sensor sensitivity shifts caused by changes in the composition of the medium within the pipeline, and physical measurement deviations caused by sediment deposition. Therefore, frequent calibration is necessary. Current calibration methods include manual calibration or redundant sensors. However, manual calibration is costly and has a delayed response, while redundant sensor calibration hardware costs double and installation space is limited.

[0005] Based on this, the present invention designs a drainage network liquid level monitoring device and method with self-correction to solve the above problems. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a drainage network liquid level monitoring device and method with self-correction.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] A drainage network liquid level monitoring device with self-correction function, comprising a housing:

[0009] A capacitive sensor, a circuit control structure and a battery are installed in the shell. The capacitive sensor and the circuit control structure are electrically connected. The circuit control structure is electrically connected to an absolute pressure sensor through a wire. The circuit control structure is connected to a cloud platform through a wireless signal. The capacitive sensor and the absolute pressure sensor are connected to the battery, and the absolute pressure sensor is fixed in the monitoring environment.

[0010] Furthermore, the circuit control structure includes a first wireless transceiver module, a control center, a receiving module and an input module. The control center is connected to the first wireless transceiver module, the receiving module and the input module. The control center is connected to the cloud platform through the first wireless transceiver module. The control center is connected to the capacitive sensor and the absolute pressure sensor through the receiving module, and the input module is connected to the absolute pressure sensor.

[0011] Furthermore, the cloud platform includes a computing module, a control terminal, a query module, a second wireless transceiver module and a storage module. The control terminal is connected to the computing module, the query module, the second wireless transceiver module and the storage module. The second wireless transceiver module is wirelessly connected to the first wireless transceiver module. The query module is connected to an external real-time meteorological database.

[0012] Furthermore, the shell is installed on the side wall of the facility to be tested, the absolute pressure sensor is connected to the shell and can extend into the liquid to be tested to detect water pressure and atmospheric pressure, the circuit control structure includes a main board, which is installed in the shell and has data acquisition and wireless communication functions, and the battery is set in the shell to power the monitoring device.

[0013] Furthermore, the pressure data detected by the absolute pressure sensor includes both atmospheric pressure and water pressure. The monitoring device collects the absolute pressure from the absolute pressure sensor and sends it to the cloud platform. The cloud platform then queries the local atmospheric pressure data over the network and subtracts the atmospheric pressure data from the collected absolute pressure data to obtain accurate water pressure data. Furthermore, once the absolute pressure sensor emerges from the water, the sensor can be calibrated using the atmospheric pressure data at the installation site, obtained from the platform, enabling remote self-calibration.

[0014] A calibration method for a drainage network liquid level monitoring device with self-calibration comprises the following steps:

[0015] Step 1: Record the installation height H0 of the absolute pressure sensor and the installation height H1 of the capacitance sensor, and calculate the height difference ΔH;

[0016] Step 2: Absolute pressure sensor measures data Y0;

[0017] Step 3: Send Y0 to the cloud platform;

[0018] Step 4: The cloud platform queries the local air pressure data Y1 at this time, calculates the liquid level monitoring data Y, and determines whether the capacitive sensor is triggered. If it is, it executes step 5; if not, it executes step 9;

[0019] Step 5: Calculate the absolute pressure sensor error ΔE;

[0020] Step 6: Determine whether the absolute pressure sensor error ΔE meets the monitoring requirements. If yes, stop the calibration process. If no, proceed to step 7.

[0021] Step 7: Add the absolute pressure sensor error ΔE to Y0 to obtain a new Y0;

[0022] Step 8: Repeat steps 3-7;

[0023] Step 9: Determine whether the Y0 fluctuation difference of three consecutive data is ≤10mm. If it is determined that the absolute pressure sensor is exposed, go to step 10. If not, the absolute pressure sensor is in water and has not reached the highest water level, so no calibration is required.

[0024] Step 10: Send Y to the cloud platform. The cloud platform queries the local air pressure data Y1 and calculates the liquid level monitoring data Y to determine whether Y meets the set requirements. If so, no calibration is required. If not, replace Y1 with Y0 and input the replaced Y0 into the absolute pressure sensor to complete the calibration.

[0025] Furthermore, ΔH is calculated as follows:

[0026] ΔH=H1-H0.

[0027] Furthermore, Y is calculated as follows:

[0028] Y=Y0-Y1.

[0029] Furthermore, ΔE is calculated as follows:

[0030] ΔE=ΔH-Y.

[0031] Furthermore, whether ΔE meets the monitoring requirement is specifically whether |ΔE| / L is ≤ 0.2%, where L is the measuring range of the absolute pressure sensor.

[0032] Furthermore, whether Y meets the set requirements is specifically whether Y=Y0-Y1≤10mm.

[0033] The liquid level monitoring device of the present application integrates water level, water quality and flow monitoring functions to ensure long-term stable operation under full sewage immersion conditions. It uses corrosion-resistant and highly sealed materials and does not pollute groundwater quality. It has been comprehensively optimized in terms of power supply, protection and long-term stability. It can collect data such as liquid level, pH, conductivity, flow, turbidity and COD in real time, and comprehensively monitor the water level, flow, siltation depth and water quality of the pipeline network.

[0034] The present invention has the following technical effects:

[0035] The liquid level monitoring device of the present application can realize self-calibration of the liquid level monitoring sensor without human intervention, solving the problem of measurement accuracy attenuation caused by environmental changes in traditional liquid level monitoring devices; through error calculation, combined with capacitance sensors and absolute pressure sensors, the process of liquid level monitoring error correction is realized, effectively and timely grasping problems that arise, such as overflow. The application of absolute pressure sensors in liquid level monitoring in drainage networks, and then obtaining actual liquid level data by obtaining local air pressure data, can accurately monitor drainage networks that are in a long-term liquid level situation. In drainage networks that are in a long-term liquid level situation, monitoring devices can be timely reduced, reducing usage costs and avoiding meaningless monitoring.

[0036] The present invention monitors the absolute pressure sensor through a calibration method, and evaluates the quality of absolute pressure sensors of different manufacturers and models through absolute pressure sensor error data analysis, thereby providing a data basis for subsequent absolute pressure sensor selection.

[0037] The absolute pressure sensor in this application does not require external ventilation, thus preventing internal moisture and water ingress. It can operate stably and long-term under drainage pipe networks, extending the life of the equipment and reducing maintenance cycles and costs. Furthermore, remote calibration of the sensor using air pressure data can increase the accuracy of monitoring data and avoid excessive errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0039] Figure 1 This is a structural diagram of a drainage network liquid level monitoring device with self-correction capability according to the present invention;

[0040] Figure 2 This is a flow chart of a calibration method for a drainage network liquid level monitoring device with self-calibration according to the present invention;

[0041] Figure 3 This is a logic diagram of a calibration method for a drainage network liquid level monitoring device with self-calibration according to the present invention;

[0042] Figure 4 This is a schematic diagram of the installation of a drainage network liquid level monitoring device with self-correction according to the present invention.

[0043] The numbers in the figure represent:

[0044] 1. Housing 2. Capacitive sensor 3. Circuit control structure 4. Battery 5. Absolute pressure sensor 6. Cloud platform DETAILED DESCRIPTION

[0045] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0046] The present invention will be further described below with reference to the embodiments.

[0047] The terms “left,” “right,” “front,” “back,” “up,” and “down” mentioned in the following description are oriented in the viewing direction of the front view.

[0048] Example 1

[0049] Please see the attached Figure 1 , a drainage network liquid level monitoring device with self-correction, comprising a housing 1:

[0050] A capacitive sensor 2, a circuit control structure 3 and a battery 4 are installed in the shell 1. The capacitive sensor 2 and the circuit control structure 3 are electrically connected. The circuit control structure 3 is electrically connected to an absolute pressure sensor 5 through a wire. The circuit control structure 3 is connected to a cloud platform 6 through a wireless signal. The capacitive sensor 2 and the absolute pressure sensor 5 are connected to the battery 4, and the absolute pressure sensor 5 is fixed in the monitoring environment.

[0051] The circuit control structure 3 includes a first wireless transceiver module, a control center, a receiving module and an input module. The control center is connected to the first wireless transceiver module, the receiving module and the input module. The control center is connected to the cloud platform 6 through the first wireless transceiver module. The control center is connected to the capacitive sensor 2 and the absolute pressure sensor 5 through the receiving module, and the input module is connected to the absolute pressure sensor 5.

[0052] The cloud platform 6 includes a computing module, a control terminal, a query module, a second wireless transceiver module and a storage module. The control terminal is connected to the computing module, the query module, the second wireless transceiver module and the storage module. The second wireless transceiver module is wirelessly connected to the first wireless transceiver module. The query module is connected to an external real-time meteorological database.

[0053] The capacitance sensor 2 monitors that the water level is at a set height. The capacitance sensor 2 monitors the signal and transmits it to the control center through the receiving module. The absolute pressure sensor 5 measures the data Y0 and transmits it to the control center through the receiving module. The control center transmits Y0 to the second wireless transceiver module of the cloud platform 6 through the first wireless transceiver module. The second wireless transceiver module transmits it to the control terminal. The control terminal controls the query module to query the local air pressure data Y1 at this time. The calculation module then performs calculations and makes judgments, and performs correction processing based on the judgment results.

[0054] The monitoring device enables manual self-calibration of the liquid level monitoring sensor. Through error calculation, combined with the capacitive sensor 2 and the absolute pressure sensor 3, the liquid level monitoring error correction process is implemented, effectively and promptly identifying emerging problems such as overflows. The absolute pressure sensor 3 is used for liquid level monitoring in drainage networks, and actual liquid level data is acquired by acquiring local air pressure data. This allows for accurate monitoring of drainage networks experiencing long-term liquid level fluctuations. In such locations, monitoring devices can be reduced, reducing operational costs and avoiding unnecessary monitoring.

[0055] The absolute pressure sensor 3 is monitored through the calibration method, and the quality of the absolute pressure sensor 3 of different manufacturers and models is evaluated through the error data analysis of the absolute pressure sensor 3, providing a data basis for the subsequent absolute pressure sensor 3 selection.

[0056] In this embodiment, the absolute pressure sensor 3 is also called an absolute pressure sensor, which has a vacuum cavity inside and is used to monitor the pressure difference between the current external environment and the vacuum.

[0057] Please see the attached Figure 2 A method for calibrating a drainage network liquid level monitoring device with self-calibration comprises the following steps:

[0058] Step 1: Record the installation height H0 of the absolute pressure sensor 5 and the installation height H1 of the capacitance sensor 2, and calculate the height difference ΔH;

[0059] Step 2: Absolute pressure sensor 5 measures data Y0;

[0060] Step 3: Send Y0 to the cloud platform 6;

[0061] Step 4: The cloud platform 6 queries the local air pressure data Y1 at this time, calculates the liquid level monitoring data Y, and determines whether the capacitive sensor 2 is triggered. If it is determined to be triggered, step 5 is executed; if not, step 9 is executed;

[0062] Step 5: Calculate the error ΔE of the absolute pressure sensor 5;

[0063] Step 6: Determine whether the error ΔE of the absolute pressure sensor 5 meets the monitoring requirements. If yes, stop the calibration process. If no, proceed to step 7.

[0064] Step 7: Add the error of absolute pressure sensor 5 to Y0 to obtain a new Y0;

[0065] Step 8: Repeat steps 3-7;

[0066] From steps 1 to 8, it can be seen that by calculating the error and then combining it with the capacitance sensor 2 and the absolute pressure sensor 3, the process of liquid level monitoring error correction is realized, and problems such as overflow are effectively and timely grasped.

[0067] Step 9: Determine whether the Y0 fluctuation difference of three consecutive data is ≤10mm. If it is determined that the absolute pressure sensor 5 is exposed, execute step 10. If it is not, the absolute pressure sensor 5 is in the water and has not reached the highest water level, and no calibration is required.

[0068] Step 10: Send Y0 to the cloud platform 6. The cloud platform 6 queries the local air pressure data Y1 at this time and calculates the liquid level monitoring data Y to determine whether Y meets the set requirements. If so, no correction is required. If not, replace Y1 with Y0 and input the replaced Y0 into the absolute pressure sensor 5 to complete the correction.

[0069] Through steps 1-3, 9 and 10, it can be known that the application of absolute pressure sensor 3 in the liquid level monitoring of the drainage network, and then obtaining the actual liquid level data by obtaining the local air pressure data, can accurately monitor the drainage network where the liquid level is constantly changing. In the drainage network where the liquid level is constantly changing, the monitoring device can be reduced in time, the use cost can be reduced, and meaningless monitoring can be avoided. ΔH is calculated as follows:

[0070] ΔH=H1-H0.

[0071] Y is calculated as follows:

[0072] Y=Y0-Y1.

[0073] ΔE is calculated as follows:

[0074] ΔE=ΔH-Y.

[0075] Whether ΔE meets the monitoring requirements is specifically whether |ΔE| / L is ≤0.2%, where L is the 5-range of the absolute pressure sensor.

[0076] Whether Y meets the set requirements, specifically whether Y=Y0-Y1≤10mm.

[0077] The absolute pressure sensor 3 is monitored through the calibration method, and the quality of the absolute pressure sensor 3 of different manufacturers and models is evaluated through the error data analysis of the absolute pressure sensor 3, providing a data basis for the subsequent absolute pressure sensor 3 selection.

[0078] Please see the attached Figure 3 and attached Figure 4 , the detailed steps of this method are as follows:

[0079] S1. Install the equipment and record the installation elevation H0 of the absolute pressure sensor and the elevation H1 of the capacitance sensor on the host. Calculate the elevation difference ΔH: ΔH = H1 - H0.

[0080] S2. When the capacitive sensor on the device is triggered, it collects the current liquid level data Y0 and sends it to the cloud platform;

[0081] S3. The platform calculates the current liquid level monitoring data Y, Y = Y0-Y1;

[0082] S4. Calculate the current sensor error ΔE, ΔE = ΔH - Y = H1 - H0 - Y0 + Y1;

[0083] S5. Determine whether the current error ΔE meets the monitoring requirements (for example, |ΔE| < 2CM). If it does not meet the requirements, issue the error correction value ΔE.

[0084] S6. The device receives ΔE and sends the corrected liquid level data Y0';

[0085] S7. The cloud platform calculates the corrected ΔE′

[0086] ΔE=ΔH-Y′=H1-H0-Y0′+Y1;

[0087] S8. When the error ΔE meets the requirement, stop the calibration. If not, continue the calibration process.

[0088] Among them, the capacitive sensor in the host mentioned in step S1 is only a specific example in this solution. The capacitive sensor is not limited to the host and can be independently placed outside the host. At the same time, the error calculation mentioned in step S4 is only a specific example in this solution. You can also first obtain the current air pressure data from the cloud platform, perform error calculation locally, and upload the error value to the cloud platform.

[0089] The liquid level monitoring device of the present application is developed to meet the water level monitoring needs of the rainwater pipe network / sewage pipe network. It has the characteristics of high waterproof grade, built-in antenna, built-in lithium battery, etc. The monitoring terminal sends the manhole water level data to the drainage monitoring center via Cat.1 wireless communication. The software of the monitoring center calculates the pipe section water level difference data and the water level slope of the pipeline based on the water level data of each drainage manhole and the spatial relationship between each drainage pipe manhole, and obtains the actual operating status of the drainage network from the change of the water level slope of the pipeline.

[0090] The drainage network monitoring method of the present application can realize self-calibration of liquid level monitoring sensors without human intervention by establishing a long-term online self-calibration system without human intervention. At the same time, by adopting an absolute pressure liquid level sensor and combining it with the air pressure data of the equipment location collected by the platform, accurate liquid level monitoring under submerged conditions can be achieved; the process of liquid level monitoring error correction is realized by combining a capacitive sensor and a liquid level sensor; by establishing a historical error database, it can assist in judging the quality of the sensor, evaluate the quality of sensors from different manufacturers and models, and provide a data basis for subsequent sensor selection.

[0091] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A drainage network liquid level monitoring device with self-correction, comprising a housing (1), characterized in that: A capacitive sensor (2), a circuit control structure (3) and a battery (4) are installed in the housing (1); the capacitive sensor (2) and the circuit control structure (3) are electrically connected; the circuit control structure (3) is electrically connected to an absolute pressure sensor (5) via a wire; the circuit control structure (3) is connected to a cloud platform (6) via a wireless signal; the capacitive sensor (2) and the absolute pressure sensor (5) are connected to the battery (4); and the absolute pressure sensor (5) is fixedly located in a monitoring environment.

2. The drainage pipe network liquid level monitoring device with self-correction according to claim 1, characterized in that: The circuit control structure (3) includes a first wireless transceiver module, a control center, a receiving module, and an input module. The control center is connected to the first wireless transceiver module, the receiving module, and the input module. The control center is connected to the cloud platform (6) via the first wireless transceiver module. The control center is connected to the capacitive sensor (2) and the absolute pressure sensor (5) via the receiving module. The input module is connected to the absolute pressure sensor (5).

3. The drainage pipe network liquid level monitoring device with self-correction according to claim 2, characterized in that: The cloud platform (6) includes a computing module, a control terminal, a query module, a second wireless transceiver module and a storage module. The control terminal is connected to the computing module, the query module, the second wireless transceiver module and the storage module. The second wireless transceiver module is wirelessly connected to the first wireless transceiver module. The query module is connected to an external real-time meteorological database.

4. A calibration method for a drainage network liquid level monitoring device with self-calibration according to claim 3, characterized in that: The following steps are involved: Step 1: Record the installation height H0 of the absolute pressure sensor (5) and the installation height H1 of the capacitance sensor (2), and calculate the height difference ΔH; Step 2: The absolute pressure sensor (5) measures data Y0; Step 3: Send Y0 to the cloud platform (6); Step 4: The cloud platform (6) queries the local air pressure data Y1 at this time, calculates the liquid level monitoring data Y, and determines whether the capacitance sensor (2) is triggered. If it is determined to be triggered, step 5 is executed; if it is not triggered, step 9 is executed; Step 5: Calculate the error ΔE of the absolute pressure sensor (5); Step 6: Determine whether the error ΔE of the absolute pressure sensor (5) meets the monitoring requirements. If it is determined to be yes, stop the calibration process. If it is determined to be no, execute step 7. Step 7: Add the error ΔE of the absolute pressure sensor (5) to Y0 to obtain a new Y0; Step 8: Repeat steps 3-7; Step 9: Determine whether the fluctuation difference of three consecutive data Y0 is ≤10mm. If it is determined that the absolute pressure sensor (5) is exposed, execute step 10. If it is determined not, the absolute pressure sensor (5) is in the water and has not reached the highest water level, and no calibration is required. Step 10: Send Y0 to the cloud platform (6). The cloud platform (6) queries the local air pressure data Y1 at this time and calculates the liquid level monitoring data Y to determine whether Y meets the set requirements. If so, no correction is required. If not, Y1 is replaced with Y0, and the replaced Y0 is input into the absolute pressure sensor (5) to complete the correction.

5. The calibration method according to claim 4, wherein: ΔH is calculated as follows: ΔH=H1-H0.

6. The calibration method according to claim 5, wherein: Y is calculated as follows: Y=Y0-Y1.

7. The calibration method according to claim 6, wherein: ΔE is calculated as follows: ΔE=ΔH-Y.

8. The calibration method according to claim 7, wherein: Whether ΔE meets the monitoring requirements is specifically whether |ΔE| / L is ≤ 0.2%, where L is the range of the absolute pressure sensor (5).

9. The calibration method according to claim 4, wherein: Whether Y meets the set requirements, specifically whether Y=Y0-Y1≤10mm.

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