Differential pressure diagnosis and alarm method and equipment based on pressure type waterlogging and ponding monitoring

Abstract

The invention discloses a differential pressure diagnosis and alarm method and equipment based on pressure type waterlogging and ponding monitoring, two pressure type water level gauges are respectively installed at different height positions in a high-low manner, a high-level pressure type water level gauge and a low-level pressure type water level gauge are respectively formed, and the height difference between the two pressure type water level gauges is kettle D; a dynamic differential pressure analysis algorithm and an intelligent diagnosis model are adopted for analysis and judgment, whether data are reasonable or not is judged by comparing water level data of the two pressure type water level gauges so as to diagnose and judge whether the equipment is abnormal or not, alarm information is sent to a platform server according to the abnormal condition, and operation and maintenance personnel are reminded to carry out precise operation and maintenance. Therefore, the real-time diagnosis of the deposition fault of the pressure type water level sensor of the monitoring equipment can be realized, the reliability and accuracy of an accumulated water depth measurement result and the accurate operation and maintenance triggering of the fault are ensured, and the accuracy of urban waterlogging monitoring data and the accurate operation and maintenance efficiency of the equipment are improved.

Description

Technical Field

[0001] This invention relates to the field of urban flood monitoring technology, and in particular to a fault diagnosis and alarm method for urban flood pressure monitoring equipment. Background Technology

[0002] With the continued acceleration of urbanization in my country, urban flooding has become an increasingly prominent problem, affecting urban safety and residents' quality of life. This places higher demands on the accuracy of urban drainage and flood control systems. Currently, pressure-type flood monitoring equipment is widely used in the field of urban flood monitoring. Its core principle is to sense the water pressure generated by the floodwater through pressure sensors, and then calculate the water depth data, providing basic support for flood early warning and response.

[0003] However, in practical applications, these devices suffer from significant reliability issues due to limitations imposed by installation scenarios and operating environments. Specific problems include: Urban flood-prone areas are often located in low-lying sections, underpass entrances, culverts, and other challenging locations. These areas are not only spatially dispersed but also have poor accessibility for daily personnel, making efficient and timely on-site maintenance (especially cleaning operations) of pressure monitoring equipment difficult. During flooding, the silt, fallen leaves, and household waste carried by the floodwater accumulate in large quantities at the pressure sensor ports at the bottom of the equipment after the water recedes. Due to delayed maintenance, the accumulated material continuously blocks the pressure ports and interferes with water pressure transmission, directly causing a significant decrease in the measurement accuracy of the bottom pressure sensor, or even data failure (such as displaying that the water level has not receded, the depth is falsely high, or there is no response). This fails to accurately reflect the on-site flood situation and severely impacts the accurate assessment of the flooding situation by the backend system.

[0004] Meanwhile, existing monitoring solutions rely solely on data output from a single pressure sensor, lacking an effective mechanism to determine the sensor's operational status. This is because the backend system cannot distinguish between genuine feedback from normal water accumulation and erroneous signals caused by sensor malfunctions due to siltation. This can lead to false alarms or missed warnings for flooding, and also fails to provide maintenance personnel with accurate fault location information, further exacerbating the problems of low equipment maintenance efficiency and insufficient reliability of monitoring data. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies by providing a differential pressure diagnosis and alarm method based on pressure-type urban flooding monitoring. This method effectively solves the problem that sensor measurement errors caused by siltation at the pressure port of pressure-type urban flooding monitoring equipment lead to inconsistencies, and that the back-end system cannot distinguish between normal flooding data and equipment malfunction data.

[0006] To solve the above technical problems, the present invention adopts the following technical solution: a differential pressure diagnosis and alarm method based on a pressure-type urban flooding monitoring device, wherein two pressure level gauges, one high and one low, are installed at different heights. The pressure level gauge at the higher position forms a high-level pressure level gauge, and the pressure level gauge at the lower position forms a low-level pressure level gauge, with a height difference of ▲D between the two pressure level gauges; a dynamic differential pressure analysis algorithm and an intelligent diagnostic model are used for analysis and judgment. By comparing the water level data of the two pressure level gauges, the reasonableness of the data is determined, thereby diagnosing whether the equipment is abnormal. In case of abnormality, an alarm message is sent to the platform server to remind maintenance personnel to perform precise maintenance; specifically including the following steps:

[0007] S1: After the equipment is started, the water level reading of the high-level pressure water level gauge is collected as L1, and the water level reading of the low-level pressure water level gauge is collected as L2; ​​as the input of the algorithm, the dynamic differential pressure analysis algorithm and the intelligent diagnostic model are run synchronously.

[0008] S2: By running the dynamic differential pressure analysis algorithm and intelligent diagnostic model, calculate the difference between the water level reading L1 of the high-level pressure water level gauge and the water level reading L2 of the low-level pressure water level gauge. Based on the water level readings and differences of the two pressure water level gauges, analyze and determine the collected values ​​and the sensor status of each pressure water level gauge, and output the current water depth value and equipment alarm information.

[0009] S3: Output the current water depth value. If there is an alarm, report it to remind maintenance personnel to carry out precise maintenance.

[0010] The dynamic differential pressure analysis algorithm and intelligent diagnostic model specifically include:

[0011] ▲D = Installation height of high-pressure water level gauge – Installation height of low-pressure water level gauge;

[0012] Water level pressure difference value L3 = Water level reading L2 of low-pressure water level gauge - Water level reading L1 of high-pressure water level gauge;

[0013] The water level pressure difference value L3 deviates significantly from ▲D when the absolute value of the deviation exceeds ▲D / 2.

[0014] Water level remains stable for an extended period: the current water depth remains unchanged for 2 consecutive hours;

[0015] Based on our experience in the operation and maintenance of IoT devices for urban flood monitoring, the specific algorithm model designed is as follows:

[0016] S01. When there is no data for water level reading L1 and water level reading L2 < ▲D, report the current water depth value = water level reading L1. If the current water level remains stable for a long time, the equipment alarms and repairs: the data of water level reading L2 may be abnormal, the current water depth value does not change for a long time, and the sensor of the low-pressure water level gauge may be faulty.

[0017] S02. When there is no data for water level reading L1 and water level reading L2 > ▲D, the equipment alarms and repairs are triggered: the data of water level reading L1 or water level reading L2 may be abnormal; the sensor of the high-pressure water level gauge and / or low-pressure water level gauge may be faulty.

[0018] S03. When the water level reading L1 > 0, the current water depth value = water level reading L1 + ▲D; if the water level pressure difference value L3 deviates significantly from ▲D, the equipment alarms and maintenance is required: the sensor of the high-pressure water level gauge and / or the low-pressure water level gauge may be faulty; if the current water level remains stable for a long time, the equipment alarms and maintenance is required: the data of the water level reading L1 may be abnormal, the current water depth value does not change for a long time, and the sensor of the high-pressure water level gauge may be faulty.

[0019] The high-pressure water level gauges and low-pressure water level gauges are installed in high-risk areas, including but not limited to important urban roads / sites, historical urban flooding points, high-risk waterlogging sections, low-lying areas, underpasses, tunnels, culverts, riverside backflow points, and / or underground parking garages with potential water immersion hazards.

[0020] A differential pressure diagnosis and alarm device based on pressure-type urban flooding monitoring includes a built-in microcontroller, a power control module, a communication module, and two pressure level gauges. The communication module enables communication with a platform server. The two pressure level gauges are installed at different heights within the device, one at a higher position and the other at a lower position, forming a high-level pressure level gauge and a low-level pressure level gauge, with a height difference of ▲D between them. The microcontroller incorporates the dynamic differential pressure analysis algorithm and intelligent diagnostic model described in claim 1 or 2. The microcontroller executes programs to implement the steps of the differential pressure diagnosis and alarm method described in claim 1 or 2.

[0021] In addition, it also includes a display module, which is connected to the microcontroller and is used to display data such as water level, network status, and power status.

[0022] This invention employs a dual-pressure sensor redundancy architecture and, based on accumulated experience in on-site IoT operation and maintenance of urban flooding monitoring and backend data analysis, designs a dynamic differential pressure analysis algorithm and an intelligent diagnostic model. It achieves the following technical effects: 1) Real-time diagnosis of siltation faults in the pressure level sensors of monitoring equipment; 2) Ensuring the reliability and accuracy of water depth measurement results; 3) Precise operation and maintenance triggering for pressure level sensor faults; 4) Improving the installation location of key pressure level sensors for detecting severe flooding, effectively reducing the failure rate of critical sensors. This significantly improves the accuracy of urban flooding monitoring data and enhances the efficiency of precise operation and maintenance of urban flooding monitoring IoT equipment. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the dual pressure sensor redundancy architecture of the present invention;

[0024] Figure 2 This is a schematic diagram of the system architecture of the waterlogging monitoring equipment of the present invention;

[0025] Figure 3 This is a flowchart of the diagnostic process of the present invention;

[0026] Figure 4 This is a flowchart of the workflow of the present invention. Detailed Implementation

[0027] The present invention will be further illustrated below through specific embodiments:

[0028] like Figures 1-4 As shown, this differential pressure diagnostic alarm device incorporates a microcontroller, power control module, communication module, display module, and two pressure level gauges. The microcontroller integrates a dynamic differential pressure analysis algorithm and an intelligent diagnostic model. The two pressure level gauges, one high and one low, are installed at different heights. The higher-positioned gauge forms the high-level pressure level gauge, and the lower-positioned gauge forms the low-level pressure level gauge. The height difference between the two gauges is ▲D. The device uses a dynamic differential pressure analysis algorithm and an intelligent diagnostic model to analyze and judge the data. By comparing the water level data from the two gauges, it determines whether the data is reasonable, thereby diagnosing whether the equipment is malfunctioning. If an anomaly is detected, an alarm message is sent to the platform server to remind maintenance personnel to perform precise maintenance. The basic process is as follows:

[0029] S1: After the equipment is started, the water level reading of the high-level pressure water level gauge is collected as L1, and the water level reading of the low-level pressure water level gauge is collected as L2; ​​as the input of the algorithm, the dynamic differential pressure analysis algorithm and the intelligent diagnostic model are run synchronously.

[0030] S2: By running the dynamic differential pressure analysis algorithm and intelligent diagnostic model, calculate the difference between the water level reading L1 of the high-level pressure water level gauge and the water level reading L2 of the low-level pressure water level gauge. Based on the water level readings and differences of the two pressure water level gauges, analyze and determine the collected values ​​and the sensor status of each pressure water level gauge, and output the current water depth value and equipment alarm information.

[0031] S3: Output the current water depth value. If there is an alarm, report it to remind maintenance personnel to carry out precise maintenance.

[0032] The dynamic differential pressure analysis algorithm and intelligent diagnostic model specifically include:

[0033] ▲D = Installation height of high-pressure water level gauge – Installation height of low-pressure water level gauge;

[0034] Water level pressure difference value L3 = Water level reading L2 of low-pressure water level gauge - Water level reading L1 of high-pressure water level gauge;

[0035] The water level pressure difference value L3 deviates significantly from ▲D when the absolute value of the deviation exceeds ▲D / 2.

[0036] Water level remains stable for a long period of time: The current water depth remains unchanged for 2 consecutive hours.

[0037] The specific implementation process is as follows:

[0038] 1. Installation and deployment of dual-pressure water level gauges for urban flood monitoring

[0039] To ensure the accuracy of waterlogging monitoring data, this monitoring equipment can be installed in high-risk areas such as important urban roads and locations, historical urban flooding sites, high-risk waterlogging sections, low-lying areas, underpasses, tunnels, culverts, riverside backflow points, and underground parking garages with potential water intrusion hazards. In this embodiment, the equipment is installed on the curb of roads prone to flooding in open areas to facilitate quick installation and maintenance.

[0040] 2. Reporting of water level monitoring data and equipment alarm data.

[0041] The equipment starts collecting data on accumulated water from urban flooding, and runs dynamic differential pressure analysis and intelligent diagnostic model algorithms. The specific steps are as follows:

[0042] (1) When there is no data for water level reading L1 and water level reading L2 < ▲D, the current water depth value is reported as = water level reading L2; if the current water depth value does not change for a long time, the equipment alarms for maintenance: the data of water level reading L2 may be abnormal, the current water depth value does not change for a long time; the sensor of the low-pressure water level gauge may be faulty. For example, ▲D=4cm, water level reading L1=0cm, water level reading L2=3cm, the equipment reports the current water depth as 3cm. If the current water depth value remains unchanged at 3cm for 3 hours, the equipment alarms: the data of water level reading L2 may be abnormal, the current water depth value does not change for a long time; the sensor of the low-pressure water level gauge may be faulty.

[0043] (2) When there is no data for water level reading L1 and water level reading L2 > ▲D, the equipment alarms for maintenance: the data of water level reading L1 or water level reading L2 may be abnormal; the sensor of the high-pressure water level gauge and / or the low-pressure water level gauge may be faulty. For example, if ▲D=4cm, water level reading L1=0cm, water level reading L2=8cm, the dual-pressure water level gauge for urban flooding monitoring will report an equipment alarm: the data of water level reading L1 or water level reading L2 may be abnormal; the sensor of the high-pressure water level gauge and / or the low-pressure water level gauge may be faulty.

[0044] (3) When the water level reading L1>0, the current water depth value = water level reading L1+▲D; if the current water level remains stable for a long time, the equipment alarms for maintenance: the data of the water level reading L1 may be abnormal, the current water depth value does not change for a long time, and the sensor of the high-pressure water level gauge may be faulty. For example, ▲D=4cm, water level reading L1=4cm, water level reading L2=11cm, water level pressure difference value L3=water level reading L2-water level reading L1=7cm, the equipment reports an equipment alarm: the water level deviation is serious, and the sensor of the water level gauge may be faulty.

[0045] When IoT maintenance personnel receive alarm data, they check the equipment's reporting status based on the information and initiate equipment maintenance work. For example, if IoT maintenance personnel receive the following equipment alarm message: Equipment alarm: Water level reading L2 may be abnormal. The current water depth value has not changed for an extended period; the sensor of the low-level pressure water level gauge may be faulty. They will check the equipment data and dispatch personnel to the equipment installation site to initiate equipment maintenance.

[0046] The present invention has been described in detail above. The above description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of this application. All equivalent changes and modifications made in accordance with the scope of this application should still fall within the scope of the present invention.

Claims

1. A differential pressure diagnosis and alarm method based on pressure-type urban flooding monitoring, characterized in that: Two pressure level gauges are installed at different heights, one higher and one lower. The higher gauge forms the high-level pressure level gauge, and the lower gauge forms the low-level pressure level gauge. The height difference between the two gauges is ▲D. A dynamic differential pressure analysis algorithm and an intelligent diagnostic model are used for analysis and judgment. By comparing the water level data from the two gauges, the reasonableness of the data is determined, thereby diagnosing whether the equipment is malfunctioning. If an anomaly occurs, an alarm message is sent to the platform server to remind maintenance personnel to perform precise maintenance. The specific steps include: S1: After the equipment is started, the water level reading of the high-level pressure water level gauge is collected as L1, and the water level reading of the low-level pressure water level gauge is collected as L2; ​​as the input of the algorithm, the dynamic differential pressure analysis algorithm and the intelligent diagnostic model are run synchronously. S2: By running the dynamic differential pressure analysis algorithm and intelligent diagnostic model, calculate the difference between the water level reading L1 of the high-level pressure water level gauge and the water level reading L2 of the low-level pressure water level gauge. Based on the water level readings and differences of the two pressure water level gauges, analyze and determine the collected values ​​and the sensor status of each pressure water level gauge, and output the current water depth value and equipment alarm information. S3: Output the current water depth value. If there is an alarm, report it to remind maintenance personnel to carry out precise maintenance.

2. The differential pressure diagnosis and alarm method based on pressure-type urban flooding monitoring according to claim 1, characterized in that: The dynamic differential pressure analysis algorithm and intelligent diagnostic model specifically include: ▲D = Installation height of high-pressure water level gauge – Installation height of low-pressure water level gauge; Water level pressure difference value L3 = Water level reading L2 of low-pressure water level gauge - Water level reading L1 of high-pressure water level gauge; The water level pressure difference value L3 deviates significantly from ▲D when the absolute value of the deviation exceeds ▲D / 2. Water level remains stable for an extended period: the current water depth remains unchanged for 2 consecutive hours; Based on our experience in the operation and maintenance of IoT devices for urban flood monitoring, the specific algorithm model designed is as follows: S01. When there is no data for water level reading L1 and water level reading L2 < ▲D, report the current water depth value = water level reading L1. If the current water level remains stable for a long time, the equipment alarms and repairs: the data of water level reading L2 may be abnormal, the current water depth value does not change for a long time, and the sensor of the low-pressure water level gauge may be faulty. S02. When there is no data for water level reading L1 and water level reading L2 > ▲D, the equipment alarms and repairs are triggered: the data of water level reading L1 or water level reading L2 may be abnormal; the sensor of the high-pressure water level gauge and / or low-pressure water level gauge may be faulty. S03. When the water level reading L1 > 0, the current water depth value = water level reading L1 + ▲D; if the water level pressure difference value L3 deviates significantly from ▲D, the equipment alarms and maintenance is required: the sensor of the high-pressure water level gauge and / or the low-pressure water level gauge may be faulty; if the current water level remains stable for a long time, the equipment alarms and maintenance is required: the data of the water level reading L1 may be abnormal, the current water depth value does not change for a long time, and the sensor of the high-pressure water level gauge may be faulty.

3. The differential pressure diagnosis and alarm method based on pressure-type urban flooding monitoring according to claim 1, characterized in that: The high-pressure water level gauges and low-pressure water level gauges are installed in high-risk areas, including important urban roads / sites, historical urban flooding points, high-risk waterlogging sections, low-lying areas, underpasses, tunnels, culverts, riverside backflow points, and / or underground parking garages with potential water immersion hazards.

4. A differential pressure diagnostic alarm device based on pressure-type urban flooding monitoring, comprising a built-in microcontroller, a power control module, a communication module, and two pressure-type water level gauges, which communicates with a platform server via the communication module, characterized in that: Two pressure level gauges are installed at different heights in the equipment, one high and one low. The pressure level gauge at the higher position forms a high-level pressure level gauge, and the pressure level gauge at the lower position forms a low-level pressure level gauge. The height difference between the two pressure level gauges is ▲D. The microcontroller has a built-in dynamic differential pressure analysis algorithm and intelligent diagnostic model as described in claim 1 or 2, and the steps of the differential pressure diagnosis and alarm method as described in claim 1 or 2 are implemented by executing the program through the microcontroller.

5. The differential pressure diagnostic alarm device based on pressure-type urban flooding monitoring as described in claim 4, characterized in that: It also includes a display module, which is connected to the microcontroller.

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