An urban drainage pump station monitoring system based on internet of things

Abstract

The application relates to the technical field of urban drainage equipment monitoring, and relates to an urban drainage pump station monitoring system based on the Internet of Things, which comprises the following steps: in a historical monitoring period, the flow water sand particles at the drainage inlet in a historical monitoring time period are analyzed to obtain a micro-cutting degree value, so as to reflect the comprehensive strength of the micro-cutting effect of the sand particles on the surface of a drainage impeller in the drainage process, and help to understand the influence of the sand particles on the impeller in the drainage process; the micro-cutting degrees corresponding to multiple serially-connected drainage impellers in the historical monitoring time period are associated with corresponding surface wear degrees for analysis to obtain a degree dispersion value, so as to reflect the close degree of association between the micro-cutting degree and the surface wear degree and the stable degree of change rule, and help monitoring personnel to understand the wear degree of the surface of the drainage impeller according to the micro-cutting degree, thereby providing reference data for subsequent targeted reduction of the wear degree of the drainage impeller and prolongation of the service life of the drainage impeller.

Description

Technical Field

[0001] This invention relates to the field of urban drainage equipment monitoring technology, and more specifically to an Internet of Things-based urban drainage pumping station monitoring system. Background Technology

[0002] In urban drainage systems, drainage pumping stations, as critical infrastructure, are responsible for discharging urban sewage and rainwater. Their operational efficiency and stability directly affect the city's flood control and drainage capabilities and the quality of life for residents. Within these pumping stations, the drainage pump itself is the core equipment. During long-term operation, the impellers connected in series within the pumping station are subjected to the micro-cutting effect of sand particles in the flowing water, leading to wear on the impeller surface. This wear, in turn, affects drainage efficiency, increases energy consumption, and may even cause equipment failure, impacting the normal operation of the entire drainage pumping station.

[0003] Existing technologies struggle to accurately reflect the comprehensive intensity of the micro-cutting effect of sand particles on the impeller surface during drainage. Furthermore, there is a lack of effective methods to correlate the degree of micro-cutting with the degree of impeller surface wear, making it impossible to accurately reflect the strength of the correlation and the stability of the variation pattern between the degree of micro-cutting and surface wear. This makes it difficult for monitoring personnel to accurately assess the degree of impeller surface wear based on the degree of micro-cutting, thus hindering the provision of reliable data support for subsequent maintenance work.

[0004] Secondly, in drainage pumping stations, among multiple drainage impellers connected in series, there are often high-risk impellers with a high degree of wear. Since existing technology cannot accurately understand the wear degree and location information of the impellers, there is often a lack of scientific basis when formulating drainage strategies. This leads to the impact on the operational stability of the entire drainage pump system when some impellers are excessively worn, and may even trigger a chain reaction, causing premature damage to other components. Summary of the Invention

[0005] The purpose of this invention is to provide an Internet of Things-based urban drainage pumping station monitoring system to solve at least one of the aforementioned problems in the prior art.

[0006] An Internet of Things (IoT) based urban drainage pumping station monitoring system includes:

[0007] Micro-cutting assessment module: During the historical monitoring period, the flow of sand particles in the drainage process of urban drainage pumping stations is analyzed to obtain historical micro-cutting degree values ​​and assess whether the flow of sand particles causes micro-cutting effect on the impeller in the drainage pump.

[0008] Correlation assessment module: Performs correlation analysis between the historical micro-cutting degree values ​​corresponding to multiple series-connected drainage impellers and the historical surface wear degree values ​​to assess whether there is a correlation;

[0009] Sequence induction module: If the correlation is high, the correlation coefficient is obtained, and the current surface wear degree value is obtained based on the current micro-cutting degree of the drainage impeller. The induction is then performed to construct the impeller wear sequence.

[0010] Balanced adjustment module: Obtains the position information of multiple series-connected drainage impellers in the drainage pump within the impeller wear sequence, and combines this information with the screening of excessively worn impellers to formulate the current drainage strategy.

[0011] As a further aspect of the present invention, the process for obtaining historical micro-cutting degree values ​​is as follows:

[0012] The historical monitoring period is divided into several historical monitoring periods. The historical sand particle volume ratio within the historical monitoring period is obtained using a laser particle size analyzer, and the sand particle impact angle within the historical monitoring period is obtained using a particle tracking test algorithm.

[0013] The historical impact angle and the historical impact volume ratio are summed to obtain the unit's historical impact value, and then averaged to output the historical micro-cutting degree value.

[0014] As a further aspect of the present invention, the process for obtaining historical surface wear values ​​is as follows:

[0015] The surface of the drainage impeller is divided into several surface detection areas. The wear value of each surface detection area is obtained according to the ultrasonic propagation model formula, and then averaged to output the historical surface wear value.

[0016] A further aspect of this invention is the analysis of the correlation between the historical micro-cutting degree and the historical surface wear degree of each series-connected drainage impeller, as follows:

[0017] During the historical monitoring period, the historical micro-cutting degree value and historical surface wear degree value corresponding to each drainage impeller are obtained and combined to obtain multiple degree correlation groups, and degree correlation change curves are constructed. The local curves between adjacent coordinate points are used as correlation analysis sub-curves.

[0018] Input the endpoint coordinates of the correlation analysis sub-curve into the slope calculation formula, and the output is the correlation sub-slope;

[0019] The sub-slopes corresponding to each sub-curve of the correlation analysis are sorted according to their positions on the degree correlation change curve to obtain the sub-slope analysis sequence, and the degree discrete value is calculated using the Euclidean distance formula.

[0020] A further aspect of this invention is the assessment of correlation, which is carried out as follows:

[0021] If the degree of dispersion value is greater than the degree of dispersion threshold, a signal with low correlation is generated;

[0022] If the degree of dispersion value is less than or equal to the degree of dispersion threshold, a signal with high correlation is generated.

[0023] As a further aspect of the present invention, the process for obtaining the degree correlation coefficient is as follows:

[0024] If a signal with a high degree of correlation is generated, the slopes of all correlated components are averaged to obtain the degree of correlation coefficient.

[0025] A further aspect of the present invention is as follows: The current surface wear level is obtained based on the current micro-cutting degree of the drainage impeller, as follows:

[0026] Based on the degree correlation coefficient, a wear degree model is constructed, where the wear degree equation is: y ms =K gl ×X+b,K gl The coefficient of correlation is expressed as the degree of correlation, and b is a constant.

[0027] The current sand particle volume ratio is obtained using a laser particle size analyzer during the current monitoring period, and the current sand particle impact angle is obtained using a particle tracking test algorithm during the current monitoring period.

[0028] The current sand particle volume ratio is summed with the current impact angle to output the current impact value of the unit, and then averaged to obtain the current micro-cutting degree value.

[0029] Input the current micro-cutting degree value into the wear degree equation, and output the current surface wear degree value.

[0030] As a further aspect of the present invention, the process for constructing the impeller wear sequence is as follows:

[0031] Extract the current surface wear value corresponding to the current drainage impeller, compare the values, sort the multiple series-connected drainage impellers from largest to smallest, and construct the impeller wear sequence.

[0032] A further aspect of the present invention is: the position information of multiple series-connected drainage impellers in the drainage pump within the impeller wear sequence, the process of which is as follows:

[0033] Extract the coordinates of each drainage impeller in the impeller wear sequence on the two-dimensional model of the drainage inlet, and obtain the distance between the coordinates of each drainage impeller and the coordinates of the origin of the two-dimensional model of the drainage inlet according to the coordinate distance formula. Use this distance as the drainage impeller distance, and sort them in ascending order to obtain the drainage impeller position sequence.

[0034] A further aspect of this invention is: developing a current drainage strategy based on the identification of excessively worn impellers.

[0035] Within the impeller wear sequence, the drainage impeller corresponding to the maximum current surface wear degree is extracted as the over-wear impeller. If the distance between the over-wear impeller and the drainage impeller is the smallest within the drainage impeller position sequence, it is recorded as the first wear impeller in the series. The current speed and current power of the first wear impeller in the series, as well as the current speeds of the other series drainage impellers, are obtained. Based on the similarity law formula, the power that the drainage impeller needs to be adjusted to is obtained.

[0036] Adjustments are made according to the order of the other series-connected drainage impellers in the drainage impeller position sequence until all other series-connected drainage impellers in the drainage impeller position sequence have been adjusted.

[0037] The beneficial effects of this invention are:

[0038] 1. This invention analyzes the flow of sand particles at the drainage inlet during historical monitoring periods to obtain micro-cutting degree values. This reflects the comprehensive intensity of the micro-cutting effect of sand particles on the surface of the drainage impeller during drainage. This not only helps to understand the impact of sand particles on the impeller during drainage, but also provides a reference for in-depth research on the relationship between micro-cutting degree values ​​and impeller wear. By correlating the micro-cutting degree of multiple series-connected drainage impellers with the corresponding surface wear degree during historical monitoring periods, a degree dispersion value is obtained, which reflects the closeness of the correlation and the stability of the change pattern between the micro-cutting degree and the surface wear degree. This helps monitoring personnel understand the wear degree of the drainage impeller surface based on the micro-cutting degree, and provides reference data for subsequent targeted reduction of drainage impeller wear and extension of drainage impeller service life.

[0039] 2. This invention obtains the surface wear degree of multiple series-connected drainage impellers based on the micro-cutting degree corresponding to them within the current monitoring period, and summarizes and integrates this information to construct an impeller wear sequence. This not only helps maintenance personnel prioritize the maintenance of high-risk impellers and quickly locate them, but also reflects the performance degradation degree of each drainage impeller. This helps monitoring personnel assess the drainage capacity of the drainage pumping station. By screening out excessively worn impellers based on the impeller wear sequence and combining the location information of the highly worn impellers in the drainage pump, a current drainage strategy can be formulated. This solves the problem of difficulty in quickly locating worn impellers in traditional maintenance methods, avoids system imbalance caused by excessive wear of a single impeller, reduces the chain reaction caused by impeller failure, and allows for targeted adjustment of the power of other series-connected drainage impellers, ensuring the operational stability of the entire drainage pump system. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of an Internet of Things-based urban drainage pumping station monitoring system according to the present invention;

[0042] Figure 2 This is a flowchart of the steps of an Internet of Things-based urban drainage pumping station monitoring system according to the present invention;

[0043] Figure 3 This is a schematic diagram illustrating the steps of adjusting the power of other drainage impellers based on the first worn impeller in series according to the present invention. Detailed Implementation

[0044] To enable those skilled in the art to better understand the present invention, 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0045] Example 1

[0046] Please see Figures 1-3 This invention provides an IoT-based monitoring system for urban drainage pumping stations. During the drainage process using drainage pumps, the system monitors the wear degree of multiple series-connected drainage impellers within the pump. Because the drainage impellers are subjected to the micro-cutting effect of sand particles in the flowing water during long-term drainage, wear occurs on the impeller surface, affecting the overall drainage efficiency. Therefore, this invention analyzes the correlation between the degree of micro-cutting and the surface wear of the drainage impellers. The specific process is as follows:

[0047] Micro-cutting assessment module: During the historical monitoring period, the flow of sand particles in the drainage process of urban drainage pumping stations is analyzed to obtain historical micro-cutting degree values ​​and assess whether the flow of sand particles causes micro-cutting effect on the impeller in the drainage pump.

[0048] In some embodiments, the historical monitoring period is divided into several historical monitoring periods;

[0049] The historical monitoring period is the drainage time required for each drainage process of the urban drainage pumping station, and the historical monitoring period can be one week, one month or one year.

[0050] The volume of drained sand particles during historical monitoring periods was obtained using a laser particle size analyzer, and the ratio of this volume to the total volume of drained sand particles during historical monitoring periods was calculated to obtain the historical sand particle volume ratio.

[0051] The historical monitoring period is divided into several equal historical monitoring time points;

[0052] It should be noted that the time interval between two adjacent monitoring points is equal;

[0053] The impact angle of sand particles is obtained using a particle tracking test algorithm, as follows:

[0054] For example, the drainage inlet is spatially transformed during the historical monitoring period to obtain a two-dimensional model of the drainage inlet;

[0055] Within the two-dimensional model of the drainage inlet, the spatial coordinates of each sand grain at each historical monitoring point and the coordinates of the drainage impeller are identified to obtain the historical sand grain coordinates and drainage impeller coordinates.

[0056] If the historical sand grain coordinates coincide with the drainage impeller coordinates, it indicates that an impact occurred between the sand grains and the drainage impeller during the historical monitoring period. This is marked as a historical impact sand grain, and the monitoring time point after the overlap is further marked as the historical impact moment.

[0057] If the historical sand grain coordinates do not coincide with the drainage impeller coordinates, it indicates that no impact occurred between the sand grains and the drainage impeller during the historical monitoring period, and these are marked as non-historical impact sand grains.

[0058] The historical sand grain coordinates at the adjacent historical monitoring times before the historical impact time and the historical sand grain coordinates at the historical impact time are extracted, and the historical impact angle is obtained by using trigonometric functions.

[0059] It should be noted that the historical impact angle ranges from 60° to 90°. The larger the historical impact angle, the stronger the micro-cutting effect on the drainage impeller, and the smaller the historical impact angle, the weaker the micro-cutting effect on the drainage impeller.

[0060] The historical impact angle and the historical impact volume ratio are summed to obtain the unit's historical impact value;

[0061] The historical impact values ​​of all historical impact sand grains are averaged to calculate the historical micro-cutting degree value.

[0062] Those skilled in the art will understand that the historical micro-cutting degree value represents the comprehensive intensity of the micro-cutting effect of sand particles on the surface of the drainage impeller during the drainage process. Specifically, the sand particle volume ratio reflects the greater the potential impact and wear risk on the impeller, and the sand particle impact angle reflects the angle at which the sand particles impact the impeller. Different impact angles have different cutting effects on the impeller surface. Measuring the strength of the micro-cutting effect of sand particles on the drainage impeller during the drainage process within the historical monitoring period not only helps to understand the impact of sand particles on the impeller during the drainage process, but also provides a reference for in-depth research on the relationship between the micro-cutting degree value and impeller wear.

[0063] Correlation assessment module: This module performs correlation analysis between the micro-cutting degree of multiple series-connected drainage impellers and the corresponding surface wear degree during historical monitoring periods to assess whether a correlation exists.

[0064] In some embodiments, during the historical monitoring period, the historical micro-cutting degree value and surface wear degree value corresponding to each drainage impeller are obtained and combined to obtain multiple sets of degree association groups.

[0065] The method for obtaining the wear value of the drainage impeller surface is as follows:

[0066] For example, the surface of the drainage impeller is divided into several surface detection areas;

[0067] An ultrasonic sensor is used to reflect sound waves towards a surface detection area, and the reflection time is recorded. Based on the ultrasonic propagation model formula, the area wear value D is obtained. ms ;

[0068] Specifically: Ultrasonic wave propagation model formula: Where V represents the speed at which the ultrasonic wave propagates within the drainage impeller (a known constant determined by the material of the drainage impeller), and t represents the reflection time;

[0069] The wear value of each surface detection area is averaged to output the surface wear degree value.

[0070] Based on multiple sets of degree correlation groups, degree correlation change curves are constructed, where the X-axis represents the historical micro-cutting degree value and the Y-axis represents the surface wear degree value;

[0071] On the degree correlation change curve, the local curves between adjacent coordinate points are used as correlation analysis sub-curves;

[0072] Input the endpoint coordinates of the correlation analysis sub-curve into the slope calculation formula, and the output is the correlation sub-slope;

[0073] The sub-slopes corresponding to each sub-curve of the correlation analysis are sorted according to their positions on the degree of correlation change curve, thus obtaining the sub-slope analysis sequence;

[0074] By inputting adjacent sub-slopes within the sub-slope analysis sequence into the Euclidean distance formula, the degree of dispersion value D is output. s ;

[0075] Specifically, the Euclidean calculation formula is as follows: Where n represents the total number of associated sub-slope values ​​within the sub-slope analysis sequence, and K i-1 Let K be the slope value of the (i-1)th correlated component. i Represented as the slope value of the i-th correlated component;

[0076] It should be noted that the degree of dispersion value represents a comprehensive index used to quantify the degree of correlation and the stability of the change pattern between the degree of micro-cutting and the degree of surface wear. Specifically, the larger the degree of dispersion value, the less stable the correlation between the degree of micro-cutting and the degree of surface wear; the smaller the degree of dispersion value, the more stable the correlation between the degree of micro-cutting and the degree of surface wear.

[0077] The degree of discrete value is compared with the degree of discrete threshold, as follows:

[0078] If the degree of dispersion value is greater than the degree of dispersion threshold, it indicates that the correlation between the micro-cutting degree value and the surface wear degree value is relatively unstable, generating a signal with low correlation.

[0079] If the degree of dispersion value is less than or equal to the degree of dispersion threshold, it indicates that the correlation between the micro-cutting degree value and the surface wear degree value is relatively stable, generating a signal with a high degree of correlation.

[0080] The specific implementation plan of this embodiment is as follows: During the historical monitoring period, the flow sand particles at the drainage inlet during the historical monitoring period are analyzed to obtain the micro-cutting degree value, thereby reflecting the comprehensive intensity of the micro-cutting effect of sand particles on the surface of the drainage impeller during the drainage process. This not only helps to understand the impact of sand particles on the impeller during the drainage process, but also provides a reference for in-depth research on the relationship between the micro-cutting degree value and impeller wear. The micro-cutting degree corresponding to multiple series drainage impellers during the historical monitoring period is correlated with the corresponding surface wear degree to obtain the degree dispersion value, which reflects the degree of correlation and the stability of the change pattern between the micro-cutting degree and the surface wear degree. This helps monitoring personnel understand the wear degree of the drainage impeller surface based on the micro-cutting degree, and provides reference data for subsequent targeted reduction of drainage impeller wear and extension of drainage impeller service life.

[0081] Example 2

[0082] Please see Figures 1-3 The present invention provides an Internet of Things-based urban drainage pumping station monitoring system, which further includes the following steps:

[0083] Sequence summarization module: If the correlation is high, the current surface wear degree of multiple series-connected drainage impellers is obtained based on the current micro-cutting degree of multiple series-connected drainage impellers in the current monitoring cycle, and then summarized and integrated to construct an impeller wear sequence;

[0084] In some embodiments, if the degree of correlation is high, the slopes of all correlated sub-slopes are averaged to output the degree of correlation coefficient.

[0085] Based on the degree correlation coefficient, a wear degree model is constructed, where the wear degree equation is: y ms =K gl ×X+b,K gl The coefficient of correlation is expressed as the degree of correlation, and b is a constant.

[0086] The current monitoring cycle is divided into several current monitoring periods;

[0087] The volume of drained sand particles in the current monitoring period is obtained using a laser particle size analyzer, and the ratio of the volume of drained sand particles in the historical monitoring periods is calculated to obtain the current sand particle volume ratio.

[0088] The current monitoring period is divided equally into several current monitoring time points;

[0089] It should be noted that the time intervals between adjacent current monitoring points are equal;

[0090] The current sand grain impact angle is obtained using a particle tracking test algorithm, as follows:

[0091] For example, the drainage inlet is spatially transformed during the current monitoring period to obtain a two-dimensional model of the drainage inlet;

[0092] Within the two-dimensional model of the drainage inlet, the spatial coordinates of each sand grain at each current monitoring point and the coordinates of the drainage impeller are identified to obtain the current sand grain coordinates and drainage impeller coordinates.

[0093] If the current coordinates of the sand grain coincide with the coordinates of the drainage impeller, it indicates that an impact occurred between the sand grain and the drainage impeller during the current monitoring period. This is marked as the current impacting sand grain, and the current monitoring time point after the overlap is further marked as the current impact time.

[0094] If the current sand grain coordinates do not coincide with the drainage impeller coordinates, it means that no impact occurred between the sand grain and the drainage impeller during the current monitoring period, and it is marked as a non-current impact sand grain.

[0095] Extract the current sand grain coordinates at the current monitoring time adjacent to the current impact time, and the current sand grain coordinates at the impact time, and use trigonometric functions to calculate the current impact angle;

[0096] The current sand particle volume ratio is summed with the current impact angle to output the current impact value of the unit.

[0097] The current impact values ​​of all currently impacting sand particles are averaged to obtain the micro-cutting degree value;

[0098] Input the current micro-cutting degree value into the wear degree equation, and output the current surface wear degree value;

[0099] It is understandable that the current surface wear value means that the current surface wear value is calculated in real time using the wear degree equation by combining the micro-cutting degree value within the current monitoring period (calculated from the current sand particle volume ratio and the current impact angle). This allows monitoring personnel to understand the wear status of the drainage impeller in real time during the current operation, greatly improving the timeliness and accuracy of monitoring. It also enables timely detection of impeller wear problems and the implementation of corresponding measures to avoid impeller failures caused by excessive wear.

[0100] Extract the current surface wear value corresponding to the current drainage impeller, compare the values, sort the multiple series-connected drainage impellers from largest to smallest, and construct the impeller wear sequence;

[0101] It should be noted that the purpose of constructing the impeller wear sequence is:

[0102] Function 1: It can screen out impellers with high surface wear values, which helps maintenance personnel to prioritize the maintenance of high-risk impellers and quickly locate high-risk impellers to prevent the failure of high-risk impellers from affecting the lifespan of adjacent drainage impellers or pump shafts, bearings and other components, thus affecting the drainage work of the entire drainage pumping station.

[0103] Function 2: It can reflect the degree of performance degradation of each drainage impeller, which helps monitoring personnel to assess the drainage capacity of drainage pumping stations and facilitates urban drainage management departments to conduct cross-regional equipment status assessments and identify weak links in management.

[0104] Balanced adjustment module: Obtains the position information of multiple series-connected drainage impellers in the drainage pump within the impeller wear sequence, and combines this information with the screening of excessively worn impellers to formulate the current drainage strategy;

[0105] In some embodiments, the coordinates of each drainage impeller in the impeller wear sequence on the two-dimensional model of the drainage inlet are extracted, and the distance between the coordinates of each drainage impeller and the coordinates of the origin of the two-dimensional model of the drainage inlet is obtained according to the coordinate distance formula, which is used as the drainage impeller distance.

[0106] It should be noted that the origin coordinates of the two-dimensional model of the drainage inlet are at the drainage inlet.

[0107] Based on the order of the distance between the drainage impellers from smallest to largest, each drainage impeller in the impeller wear sequence is sorted to obtain the drainage impeller position sequence;

[0108] Within the impeller wear sequence, the current surface wear value corresponding to the current drainage impeller is compared, and the drainage impeller corresponding to the maximum current surface wear value is extracted as the over-wear impeller.

[0109] Extract the impeller distance of excessively worn impellers within the impeller position sequence;

[0110] If the distance between the excessively worn impeller and the drainage impeller is the largest in the sequence of drainage impeller positions, then the excessively worn impeller is located at the tail position of multiple series drainage impellers, and is denoted as the series tail position worn impeller.

[0111] If the distance between the excessively worn impeller and the drain impeller is neither the maximum nor the minimum within the drain impeller position sequence, then the excessively worn impeller is located in the middle of multiple series-connected drain impellers, and is denoted as the series middle worn impeller.

[0112] If the distance between the excessively worn impeller and the drain impeller is the smallest in the sequence of drain impeller positions, then the excessively worn impeller is located at the first position of multiple series-connected drain impellers, and is referred to as the first worn impeller in the series connection.

[0113] Based on the first worn impeller in the series connection, the current speed and power of the first worn impeller in the series connection, as well as the current speed of the other series drainage impellers, are obtained. According to the similarity law formula (the relationship between speed and power), the power of the other series drainage impellers is adjusted. The process is as follows:

[0114] S1, obtain the current speed and current power of other series-connected drainage impellers;

[0115] S2, according to the similarity law formula: The required power adjustment for the drainage impeller is calculated. in, This represents the current rotational speed of the first and second worn impellers in series. This represents the current power of the first and second worn impellers in series. This represents the current rotational speed of the r-th drainage impeller among the other series-connected drainage impellers;

[0116] Based on the order of the other series-connected drainage impellers in the drainage impeller position sequence, adjust the other series-connected drainage impellers from smallest to largest until all other series-connected drainage impellers in the drainage impeller position sequence have been adjusted.

[0117] The specific implementation plan of this embodiment is as follows: Based on the degree of micro-cutting of multiple series-connected drainage impellers within the current monitoring period, the surface wear degree of multiple series-connected drainage impellers is obtained, and then summarized and integrated to construct an impeller wear sequence. This not only helps maintenance personnel to prioritize the maintenance of high-risk impellers and quickly locate high-risk impellers, but also reflects the performance degradation degree of each drainage impeller, which helps monitoring personnel to assess the drainage capacity of the drainage pumping station. Based on the impeller wear sequence, excessively worn impellers are screened out, and combined with the location information of the highly worn impellers in the drainage pump, the current drainage strategy is formulated. This solves the problem of difficulty in quickly locating worn impellers in traditional maintenance methods, avoids system imbalance caused by excessive wear of a single impeller, reduces the chain reaction caused by impeller failure, and allows for targeted adjustment of the power of other series-connected drainage impellers to ensure the operational stability of the entire drainage pump system.

[0118] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0119] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A monitoring system for urban drainage pumping stations based on the Internet of Things, characterized in that, include: Micro-cutting assessment module: During the historical monitoring period, the flow of sand particles in the drainage process of urban drainage pumping stations is analyzed to obtain historical micro-cutting degree values ​​and assess whether the flow of sand particles causes micro-cutting effect on the impeller in the drainage pump. The process of obtaining historical micro-cutting degree values ​​is as follows: The historical monitoring period is divided into several historical monitoring periods. The volume of drainage sand particles in the historical monitoring period is obtained by using a laser particle size analyzer, and the ratio of the volume of drainage in the historical monitoring period is calculated to obtain the historical sand particle volume ratio. The historical sand grain coordinates at the adjacent historical monitoring times before the historical impact time and the historical sand grain coordinates at the historical impact time are extracted, and the historical impact angle is obtained by using trigonometric functions. The historical impact angle is summed with the historical sand grain volume ratio to obtain the unit historical impact value. The unit historical impact values ​​of all historical impact sand grains are averaged to output the historical micro-cutting degree value. Correlation assessment module: Performs correlation analysis between the historical micro-cutting degree values ​​corresponding to multiple series-connected drainage impellers and the historical surface wear degree values ​​to assess whether there is a correlation; Sequence induction module: If the correlation is high, the correlation coefficient is obtained, and the current surface wear degree value is obtained based on the current micro-cutting degree of the drainage impeller. The induction is then performed to construct the impeller wear sequence. Balanced adjustment module: Obtains the position information of multiple series-connected drainage impellers in the drainage pump within the impeller wear sequence, and combines it with the current surface wear degree value to filter out excessively worn impellers and formulate the current drainage strategy.

2. The urban drainage pumping station monitoring system based on the Internet of Things according to claim 1, characterized in that, The process for obtaining historical surface wear values ​​is as follows: The surface of the drainage impeller is divided into several surface detection areas. The wear value of each surface detection area is obtained according to the ultrasonic propagation model formula, and then averaged to output the historical surface wear value.

3. The urban drainage pumping station monitoring system based on the Internet of Things according to claim 1, characterized in that, The correlation between the historical micro-cutting degree and historical surface wear degree for each series-connected drainage impeller is analyzed as follows: During the historical monitoring period, the historical micro-cutting degree value and historical surface wear degree value corresponding to each drainage impeller are obtained and combined to obtain multiple degree correlation groups, and degree correlation change curves are constructed. The local curves between adjacent coordinate points are used as correlation analysis sub-curves. Input the endpoint coordinates of the correlation analysis sub-curve into the slope calculation formula, and the output is the correlation sub-slope; The sub-slopes corresponding to each sub-curve of the correlation analysis are sorted according to their positions on the degree correlation change curve to obtain the sub-slope analysis sequence, and the degree discrete value is calculated using the Euclidean distance formula.

4. The urban drainage pumping station monitoring system based on the Internet of Things according to claim 1, characterized in that, The process for assessing whether a correlation exists is as follows: If the degree of dispersion value is greater than the degree of dispersion threshold, a signal with low correlation is generated; If the degree of dispersion value is less than or equal to the degree of dispersion threshold, a signal with high correlation is generated.

5. The urban drainage pumping station monitoring system based on the Internet of Things according to claim 1, characterized in that, The process of obtaining the degree correlation coefficient is as follows: If a signal with a high degree of correlation is generated, the slopes of all correlated components are averaged to obtain the degree of correlation coefficient.

6. A monitoring system for urban drainage pumping stations based on the Internet of Things according to claim 5, characterized in that, The current surface wear level is obtained based on the current micro-cutting degree of the drainage impeller, as follows: Based on the degree correlation coefficient, a wear degree model is constructed, wherein the wear degree equation is: in, The coefficient of correlation is expressed as the degree of correlation, and b is a constant. The volume of drainage sand particles in the current monitoring period is obtained using a laser particle size analyzer, and the ratio of the drainage volume in the historical monitoring period is calculated to obtain the current sand particle volume ratio. The current sand particle coordinates at the current monitoring time adjacent to the current impact time and the current sand particle coordinates at the impact time are extracted, and the current impact angle is obtained by using trigonometric functions. The current sand particle volume ratio is summed with the current impact angle to output the current impact value of the unit, and then averaged to obtain the current micro-cutting degree value. Input the current micro-cutting degree value into the wear degree equation, and output the current surface wear degree value.

7. A monitoring system for urban drainage pumping stations based on the Internet of Things according to claim 1, characterized in that, The process of constructing the impeller wear sequence is as follows: Extract the current surface wear value corresponding to the current drainage impeller, compare the values, sort the multiple series-connected drainage impellers from largest to smallest, and construct the impeller wear sequence.

8. A monitoring system for urban drainage pumping stations based on the Internet of Things according to claim 1, characterized in that, The process for obtaining the position information of multiple series-connected drainage impellers in the drainage pump within the impeller wear sequence is as follows: Extract the coordinates of each drainage impeller in the impeller wear sequence on the two-dimensional model of the drainage inlet, and obtain the distance between the coordinates of each drainage impeller and the coordinates of the origin of the two-dimensional model of the drainage inlet according to the coordinate distance formula. Use this distance as the drainage impeller distance, and sort them in ascending order to obtain the drainage impeller position sequence.

9. A monitoring system for urban drainage pumping stations based on the Internet of Things according to claim 8, characterized in that, Based on the current surface wear level, excessively worn impellers are identified, and a current drainage strategy is formulated. The process is as follows: Within the impeller wear sequence, the drainage impeller corresponding to the maximum current surface wear degree is extracted as the over-wear impeller. If the distance between the over-wear impeller and the drainage impeller is the smallest within the drainage impeller position sequence, it is recorded as the first wear impeller in the series. The current speed and current power of the first wear impeller in the series, as well as the current speeds of the other series drainage impellers, are obtained. Based on the similarity law formula, the power that the drainage impeller needs to be adjusted to is obtained. Adjustments are made according to the order of the other series-connected drainage impellers in the drainage impeller position sequence until all other series-connected drainage impellers in the drainage impeller position sequence have been adjusted.

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