A flood control and drainage water pump unit management and control system based on big data

Abstract

The application discloses a kind of based on big data's flood control and drainage water pump unit with management and control system, it is related to water pump unit management and control technical field, solve the technical problem that real-time management and control cannot be carried out to water pump unit in each region in prior art, the water pump unit in each region is carried out management and control analysis, improve the work efficiency of each regional water pump unit to complete drainage, reduce drainage failure and the risk of uneven resource distribution;Each drainage area is analyzed, the drainage intensity of each drainage area is judged, so as to improve the operation efficiency of each drainage area, reduce the corresponding area appears waterlogging to influence the daily operation in the corresponding area that each drainage area cannot complete drainage;Real-time management and control the operation efficiency of water pump unit, prevent water pump unit low-efficiency operation to cause drainage work to be unable to complete in time, prevent water pump unit from running under abnormal condition to cause equipment natural abrasion to increase simultaneously, reduce the service life of equipment.

Description

Technical Field

[0001] This invention relates to the field of water pump unit control technology, specifically a big data-based control system for flood control and drainage water pump units. Background Technology

[0002] With the rapid development of science and technology, modern industrial production machinery and equipment are developing towards larger scale, greater complexity, higher speed, automation, and higher power. The production efficiency of the equipment is getting higher and higher, the mechanical structure is becoming more and more complex, and the interrelationship and coupling between different parts of the equipment are becoming closer. A failure of one component will cause the entire production process to be interrupted. In the process of water pump maintenance, fault diagnosis is a key and indispensable link. From practical work, we can see that many common faults will occur during water pump testing. Therefore, we must take targeted measures based on practice to eliminate them and improve the operating efficiency of water pumps.

[0003] However, with existing technology, it is impossible to monitor and control the water pump units in each area in real time. While ensuring the normal operation of the water pump units, it is also impossible to analyze the operating efficiency of the water pump units in a timely manner, resulting in low-efficiency operation of the water pump units, which increases the risk of regional flooding and the risk of natural wear and tear on the water pump equipment.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to address the problem by proposing a big data-based management and control system for flood control and drainage pump units. This system manages and analyzes pump units in various areas, improving their drainage efficiency and reducing the risks of drainage failures and uneven resource distribution. It analyzes areas requiring drainage, determining their drainage intensity to improve operational efficiency and reduce the risk of flooding in areas that cannot complete drainage, thus impacting daily operations. Furthermore, it analyzes the operational intensity of pumps in similar areas, filtering them based on this intensity to improve accuracy and efficiency in area comparison and pump diagnostics within each analyzed area. This effectively prevents pump malfunctions during operation and reduces overall drainage efficiency.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A big data-based flood control and drainage pump unit management and control system includes a pump unit management and control platform, which is equipped with a server. The server is connected to a regional analysis unit, an intensity analysis unit, a regional comparison unit, an influencing factor acquisition unit, and a real-time control unit.

[0008] The pump unit management platform is used to manage and analyze pump units in various areas. The server generates area analysis signals and sends them to the area analysis unit, which analyzes each area requiring drainage. After analysis, the server generates intensity analysis signals and sends them to the intensity analysis unit. The intensity analysis unit analyzes the operating intensity of pumps in similar areas, selects pairs of selected areas, and sends these pairs to the server. Upon receiving the pairs of selected areas, the server generates area comparison signals and sends them to the area comparison unit. The area comparison unit compares the pairs of selected areas, obtaining high-efficiency characteristics, low-efficiency characteristics, and fault characteristics of the pump units, and sends these characteristics to the real-time control unit. The influencing factor acquisition unit acquires the influencing factors for the selected areas corresponding to the high-efficiency, low-efficiency, and fault characteristics, and the real-time control unit manages the pump units operating in real time.

[0009] As a preferred embodiment of the present invention, the region analysis process of the region analysis unit is as follows:

[0010] Each area requiring drainage is marked as an analysis area, and the analysis area is labeled with a number i, where i is a natural number greater than 1. The rainfall frequency and maximum rainfall in each analysis area are collected and labeled as PLi and JYi, respectively. The maximum difference in terrain in each analysis area is collected and labeled as DSi.

[0011] By analyzing and obtaining the demand analysis coefficient Xi for each analysis region, the demand analysis coefficient for each analysis region is compared with the threshold range of the demand analysis coefficient:

[0012] If the demand analysis coefficients of two analysis regions are within the same demand analysis coefficient threshold range, the two corresponding analysis regions are marked as similar regions and bound together, and the number of bound similar regions is not two; if the demand analysis coefficients of two analysis regions are not within the same demand analysis coefficient threshold range, the two corresponding analysis regions are marked as dissimilar regions and bound together, and the number of bound dissimilar regions is not two; the bound similar and dissimilar regions are then sent to the server.

[0013] In a preferred embodiment of the present invention, the strength analysis process of the strength analysis unit is as follows:

[0014] Similar areas are labeled with the number 'o', where 'o' is a natural number greater than 1. The average water accumulation rate and drainage rate of each similar area are collected, and the ratio of the average water accumulation rate and drainage rate of each similar area is calculated to obtain the operating intensity ratio of each similar area. The operating intensity ratio of the similar areas is marked as BZo. The ratio of the maintenance cycle to the operating cycle of the water pumps in each similar area is collected and marked as ZQo.

[0015] The ratio of operating intensity (BZo) corresponding to the bound similar regions and the ratio of pump maintenance cycle to operating cycle (ZQo) are compared with the threshold range of operating intensity ratio and the threshold range of corresponding cycle ratio, respectively:

[0016] If the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as selected regions, and the selected regions are grouped in pairs. If the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are not both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as unselected regions, and the number of unselected regions is not two. The selected regions grouped in pairs are then sent to the server.

[0017] In a preferred embodiment of the present invention, the region comparison process of the region comparison unit is as follows:

[0018] The pump units corresponding to each selected area are analyzed. The working time and corresponding drainage volume of the pump units in the same selected area at the same operating time are collected. The working time and drainage volume of the pump units in the two selected areas are calculated to obtain the difference in working time and drainage volume between the two selected areas. If the difference in working time and drainage volume are both within the corresponding difference threshold range, the operating efficiency of the selected area is determined to be normal. If the difference in working time and drainage volume are not within the corresponding difference threshold range, the operating efficiency of the selected area is determined to be abnormal. The selected areas corresponding to abnormal operating efficiency are analyzed proportionally. In the selected areas of the group, the working time of the selected area with a larger drainage volume is lower than that of the selected area with a smaller drainage volume. The former is marked as a high-efficiency selected area, and the latter is marked as a low-efficiency selected area.

[0019] The system compares the operating time of the high-efficiency and low-efficiency selected areas at the same running time. If the operating time of the high-efficiency and low-efficiency selected areas does not exceed the operating time threshold, the pump unit in the high-efficiency selected area is marked as a high-efficiency feature, and the pump unit in the low-efficiency selected area is marked as a low-efficiency feature. If the operating time of the high-efficiency and low-efficiency selected areas exceeds the operating time threshold, the pump unit in the corresponding low-efficiency selected area is marked as a fault feature. The high-efficiency feature, low-efficiency feature, fault feature, and the total drainage volume at the corresponding running time are sent to the server.

[0020] In a preferred embodiment of the present invention, the process of acquiring influencing factors by the influencing factor acquisition unit is as follows:

[0021] Set an operation monitoring period, collect environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to high efficiency characteristics, low efficiency characteristics, and fault characteristics during the operation monitoring period. Compare the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to high efficiency characteristics and low efficiency characteristics. If the environmental parameters, operating parameters, and human parameters are inconsistent, mark the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to low efficiency characteristics as low efficiency environmental influencing factors, low efficiency operating influencing factors, and low efficiency human influencing factors, respectively.

[0022] The environmental parameters, operating parameters, and human parameters of the pump units within the selected area corresponding to the high efficiency feature and the fault efficiency feature are compared. If the environmental parameters, operating parameters, and human parameters are inconsistent, the environmental parameters, operating parameters, and human parameters of the pump units within the selected area corresponding to the fault efficiency feature are marked as fault environmental influencing factors, fault operating influencing factors, and fault human influencing factors, respectively. The low efficiency environmental influencing factors, low efficiency operating influencing factors, and low efficiency human influencing factors are sent to the server along with the fault environmental influencing factors, fault operating influencing factors, and fault human influencing factors.

[0023] In a preferred embodiment of the present invention, the real-time control process of the real-time control unit is as follows:

[0024] The pump units in each analysis area are monitored in real time. If the pump units in the corresponding analysis area show low efficiency or fault characteristics, the environmental factors affecting low efficiency, the operational factors affecting low efficiency, and the human factors affecting low efficiency, or the environmental factors affecting faults, the operational factors affecting faults, and the human factors affecting faults are marked as rectification parameters. At the same time, a rectification signal is generated and the rectification signal and rectification parameters are sent to the mobile terminal of the unit management personnel.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] 1. In this invention, the pump units in each area are controlled and analyzed, which improves the efficiency of the pump units in completing drainage and reduces the risk of drainage failures and uneven resource distribution. The analysis of each area requiring drainage determines the drainage intensity, thereby improving the operational efficiency of each area and reducing the risk of flooding in areas that cannot complete drainage, which would affect daily operations. Furthermore, the analysis of the operating intensity of pumps in similar areas allows for the screening of similar areas based on their operating intensity. This screening improves the accuracy of similar areas, increases the efficiency of area comparison, and enhances the efficiency of pump diagnosis within each analyzed area, effectively preventing pump failures during operation and reducing the overall drainage efficiency of the area.

[0027] 2. In this invention, the operating efficiency of water pumps in selected areas are determined in pairs, thereby identifying pumps with substandard efficiency through comparison. Simultaneously, the characteristics of the corresponding pumps are collected, and preventative measures are taken based on these characteristics. This allows for accurate screening of substandard pumps within an area, timely maintenance, and effective improvement of pump operating efficiency. The invention also analyzes the influencing factors that generate high-efficiency, low-efficiency, and fault characteristics, accurately identifying the influencing factors of the pump units. This improves the efficiency of abnormally operating pump units by restoring them to normal operation and reduces the impact of pump unit malfunctions on regional drainage efficiency. Furthermore, the invention manages and controls the real-time operation of the pump units, preventing inefficient operation that could hinder timely drainage and increasing wear and tear under abnormal conditions, thus reducing equipment lifespan. Attached Figure Description

[0028] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0029] Figure 1 This is a schematic diagram of the principle of the present invention. Detailed Implementation

[0030] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. 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 are within the scope of protection of the present invention.

[0031] Please see Figure 1As shown, a big data-based flood control and drainage pump unit management and control system includes a pump unit management and control platform. The pump unit management and control platform is equipped with a server. The server is connected to a regional analysis unit, an intensity analysis unit, a regional comparison unit, an influencing factor acquisition unit, and a real-time control unit. The server is bidirectionally connected to the regional analysis unit, the intensity analysis unit, the regional comparison unit, the influencing factor acquisition unit, and the real-time control unit.

[0032] The pump unit management platform is used to manage and analyze pump units in various areas, improving the efficiency of drainage operations and reducing the risks of drainage failures and uneven resource distribution. The server generates regional analysis signals and sends them to the regional analysis unit, which analyzes each area requiring drainage, determining the drainage intensity. This improves the operational efficiency of each area and reduces the risk of flooding due to drainage failures, impacting daily operations. The specific regional analysis process is as follows:

[0033] Each area requiring drainage is marked as an analysis area, and the analysis area is labeled with a number i, where i is a natural number greater than 1. The rainfall frequency and maximum rainfall in each analysis area are collected and labeled as PLi and JYi, respectively. The maximum difference in terrain in each analysis area is collected and labeled as DSi.

[0034] Through formula Obtain the demand analysis coefficients Xi for each analysis region, where a1, a2, and a3 are preset proportional coefficients, and a1 > a2 > a3 > 0; compare the demand analysis coefficients of each analysis region with the threshold range of the demand analysis coefficients:

[0035] If the demand analysis coefficients of two analysis regions are within the same demand analysis coefficient threshold range, the two corresponding analysis regions will be marked as similar regions and bound together, and the number of similar regions bound together will not be two; if the demand analysis coefficients of two analysis regions are not within the same demand analysis coefficient threshold range, the two corresponding analysis regions will be marked as dissimilar regions and bound together, and the number of dissimilar regions bound together will not be two.

[0036] The bound similar and dissimilar regions are sent to the server; after receiving the bound similar and dissimilar regions, the server generates an intensity analysis signal and sends the intensity analysis signal to the intensity analysis unit.

[0037] The intensity analysis unit is used to analyze the operating intensity of water pumps in similar areas, thereby screening similar areas based on the operating intensity of the water pumps. This screening improves the accuracy of similar areas, increases the accuracy and efficiency of area comparison, and enhances the diagnostic efficiency of water pumps in each analysis area. It effectively prevents water pump failures during operation and reduces the drainage efficiency of the area. The specific intensity analysis process is as follows:

[0038] Similar areas are labeled with the number 'o', where 'o' is a natural number greater than 1. The average water accumulation rate and drainage rate of each similar area are collected, and the ratio of the average water accumulation rate and drainage rate of each similar area is calculated to obtain the operating intensity ratio of each similar area. The operating intensity ratio of the similar areas is marked as BZo. The ratio of the maintenance cycle to the operating cycle of the water pumps in each similar area is collected and marked as ZQo.

[0039] The ratio of operating intensity (BZo) corresponding to the bound similar regions and the ratio of pump maintenance cycle to operating cycle (ZQo) are compared with the threshold range of operating intensity ratio and the threshold range of corresponding cycle ratio, respectively:

[0040] If the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as selected regions, and the selected regions are grouped in pairs. If there are more than two similar regions with the same corresponding ratio, the one with the closest corresponding values ​​of operating intensity ratio and maintenance cycle to operating cycle ratio will be used. If the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are not both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as unselected regions, and the number of unselected regions is not two.

[0041] The selected regions are sent to the server in pairs. Upon receiving the selected regions, the server generates a region comparison signal and sends it to the region comparison unit. The region comparison unit compares the selected regions in pairs to determine the operating efficiency of the water pumps within each pair. This comparison identifies pumps with substandard efficiency and collects characteristics of the corresponding pumps. Based on these characteristics, preventative measures are implemented, enabling accurate screening of substandard pumps within a region and timely maintenance to effectively improve pump operating efficiency. The specific region comparison process is as follows:

[0042] The pump units corresponding to each selected area are analyzed. The working time and corresponding drainage volume of the pump units in the same selected area at the same operating time are collected. The working time and drainage volume of the pump units in the two selected areas are calculated to obtain the difference in working time and drainage volume between the two selected areas. If the difference in working time and drainage volume are both within the corresponding difference threshold range, the operating efficiency of the selected area is determined to be normal. If the difference in working time and drainage volume are not within the corresponding difference threshold range, the operating efficiency of the selected area is determined to be abnormal. The selected areas corresponding to abnormal operating efficiency are analyzed proportionally. In the selected areas of the group, the working time of the selected area with a larger drainage volume is lower than that of the selected area with a smaller drainage volume. The former is marked as a high-efficiency selected area, and the latter is marked as a low-efficiency selected area.

[0043] The system compares the operating time of the high-efficiency and low-efficiency selected regions at the same running time. If the operating time of the high-efficiency and low-efficiency selected regions does not exceed the operating time threshold, the characteristics of the pump units in the high-efficiency selected region are marked as high-efficiency characteristics, and the characteristics of the pump units in the low-efficiency selected region are marked as low-efficiency characteristics. If the operating time of the high-efficiency and low-efficiency selected regions exceeds the operating time threshold, the characteristics of the pump units in the corresponding low-efficiency selected region are marked as fault characteristics. The characteristics of the pump units are represented by parameters related to the operation of the pump units, such as the operating time and operating power.

[0044] The system sends high-efficiency characteristics, low-efficiency characteristics, fault characteristics, and the corresponding total drainage volume at the time of operation to the server. The server then sends these characteristics to the real-time control unit, simultaneously generating an influencing factor acquisition signal and sending it to the influencing factor acquisition unit. This unit acquires influencing factors for the selected areas corresponding to the high-efficiency, low-efficiency, and fault characteristics, analyzing the factors that generate these characteristics. This accurately identifies the influencing factors of the pump unit, improving the efficiency of restoring normal operation of abnormally operating pump units and reducing the impact of pump unit malfunctions on regional drainage efficiency. The specific influencing factor acquisition process is as follows:

[0045] Set the operation monitoring period and collect the environmental parameters, operating parameters and human parameters of the water pump unit in the selected area corresponding to the high efficiency characteristics, low efficiency characteristics and fault characteristics during the operation monitoring period. The environmental parameters include the temperature fluctuation value and humidity fluctuation value in the surrounding environment of the water pump unit. The operating parameters include the continuous running time of the water pump unit and the interval between adjacent runs. The human parameters include the frequency of erroneous operation of the water pump unit and the average maintenance time.

[0046] The environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to the high-efficiency and low-efficiency characteristics are compared. If the environmental parameters, operating parameters, and human parameters are inconsistent, the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to the low-efficiency characteristics are marked as low-efficiency environmental influencing factors, low-efficiency operating influencing factors, and low-efficiency human influencing factors, respectively.

[0047] The environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to the high efficiency feature and the fault efficiency feature are compared. If the environmental parameters, operating parameters, and human parameters are inconsistent, the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to the fault efficiency feature are marked as fault environmental influencing factors, fault operating influencing factors, and fault human influencing factors, respectively.

[0048] The factors affecting inefficiency, including environmental factors, operational factors, and human factors, are sent to the server along with the factors affecting failure, operational factors, and human factors. The server then forwards these factors to the real-time control unit.

[0049] After receiving data on inefficiency environmental factors, inefficiency operational factors, inefficiency human factors, fault environmental factors, fault operational factors, fault human factors, high-efficiency characteristics, low-efficiency characteristics, and fault characteristics, the real-time control unit manages the real-time operation of the water pump unit. This real-time monitoring of the water pump unit's operating efficiency prevents inefficient operation from hindering timely drainage and also prevents abnormal operation from increasing natural wear and tear and reducing equipment lifespan. The specific real-time control process is as follows:

[0050] The pump units in each analysis area are monitored in real time. If the pump units in the corresponding analysis area show low efficiency or fault characteristics, the environmental factors affecting low efficiency, the operational factors affecting low efficiency, and the human factors affecting low efficiency, or the environmental factors affecting faults, the operational factors affecting faults, and the human factors affecting faults are marked as rectification parameters. At the same time, a rectification signal is generated and the rectification signal and rectification parameters are sent to the mobile terminal of the unit management personnel.

[0051] The above formulas are all derived from software simulation using a large amount of data, and are selected to be close to the true values. The coefficients in the formulas are set by those skilled in the art based on the actual situation.

[0052] In use, this invention manages and analyzes water pump units in various areas through a water pump unit management platform. The regional analysis unit analyzes each area requiring drainage; the intensity analysis unit analyzes the operating intensity of water pumps in similar areas, selecting pairs of areas and sending these pairs to a server; the regional comparison unit compares these pairs, obtaining high-efficiency, low-efficiency, and fault characteristics of the water pump units, which are then transmitted to the real-time control unit; the influencing factor acquisition unit acquires the influencing factors for the selected areas corresponding to the high-efficiency, low-efficiency, and fault characteristics; and the real-time control unit manages and controls the water pump units operating in real-time.

[0053] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A big data-based control system for flood control and drainage pump units, characterized in that, It includes a water pump unit management and control platform, which is equipped with a server. The server is connected to a regional analysis unit, an intensity analysis unit, a regional comparison unit, an influencing factor acquisition unit, and a real-time control unit. The pump unit management platform is used to manage and analyze pump units in various areas. The server generates area analysis signals and sends them to the area analysis unit, which then analyzes each area requiring drainage. The area analysis process of the area analysis unit is as follows: Each area requiring drainage is marked as an analysis area, and the analysis area is labeled with a number i, where i is a natural number greater than 1. The rainfall frequency and maximum rainfall in each analysis area are collected and labeled as PLi and JYi, respectively. The maximum difference in terrain in each analysis area is collected and labeled as DSi. By analyzing and obtaining the demand analysis coefficient Xi for each analysis region, the demand analysis coefficient for each analysis region is compared with the threshold range of the demand analysis coefficient: If the demand analysis coefficients of two analysis regions are within the same demand analysis coefficient threshold range, the two corresponding analysis regions are marked as similar regions and bound together, with the number of bound similar regions being no more than two; if the demand analysis coefficients of two analysis regions are not within the same demand analysis coefficient threshold range, the two corresponding analysis regions are marked as dissimilar regions and bound together, with the number of bound dissimilar regions being no more than two; the bound similar and dissimilar regions are then sent to the server. The analysis server generates intensity analysis signals and sends them to the intensity analysis unit. The intensity analysis unit analyzes the operating intensity of pumps in similar areas, selects pairs of regions based on the intensity analysis, and sends these pairs of selected regions back to the server. The intensity analysis process of the intensity analysis unit is as follows: Similar areas are labeled with the number 'o', where 'o' is a natural number greater than 1. The average water accumulation rate and drainage rate of each similar area are collected, and the ratio of the average water accumulation rate and drainage rate of each similar area is calculated to obtain the operating intensity ratio of each similar area. The operating intensity ratio of the similar areas is marked as BZo. The ratio of the maintenance cycle to the operating cycle of the water pumps in each similar area is collected and marked as ZQo. The ratio of operating intensity (BZo) corresponding to the bound similar regions and the ratio of pump maintenance cycle to operating cycle (ZQo) are compared with the threshold range of operating intensity ratio and the threshold range of corresponding cycle ratio, respectively: If the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as selected regions, and the selected regions are grouped in pairs; if the ratio of operating intensity BZo to the ratio of maintenance cycle to operating cycle ZQo of two similar regions are not both within the same operating intensity ratio threshold range and the same corresponding cycle ratio threshold range, then the two similar regions are marked as unselected regions, and the number of unselected regions is not two; the selected regions grouped in pairs are sent to the server. After receiving the selected regions in pairs, the server generates a region comparison signal and sends it to the region comparison unit. The region comparison unit compares the selected regions in pairs and obtains the high-efficiency characteristics, low-efficiency characteristics, and fault characteristics of the water pump unit through the selected region comparison. The high-efficiency characteristics, low-efficiency characteristics, and fault characteristics are then sent to the real-time control unit. The influencing factor acquisition unit obtains the influencing factors of the selected regions corresponding to the high-efficiency characteristics, low-efficiency characteristics, and fault characteristics. The real-time control unit then manages and controls the water pump unit that is running in real time.

2. The big data-based flood control and drainage pump unit control system according to claim 1, characterized in that, The region comparison process of the region comparison unit is as follows: The pump units corresponding to each selected area are analyzed. The working time and corresponding drainage volume of the pump units in the same selected area at the same operating time are collected. The working time and corresponding drainage volume of the pump units in the two selected areas are calculated to obtain the difference in working time and drainage volume between the two selected areas. If the difference in working time and drainage volume are both within the corresponding difference threshold range, the operating efficiency of the selected area is determined to be normal. If the difference in working time and the difference in total drainage volume are both outside the corresponding difference threshold range, the operating efficiency of the selected area in this group is determined to be abnormal. The selected areas corresponding to the abnormal operating efficiency are then analyzed proportionally. In this group of selected areas, the working time corresponding to the selected area with a large total drainage volume is lower than the working time corresponding to the selected area with a small total drainage volume. The former is marked as a high-efficiency selected area, and the latter is marked as a low-efficiency selected area. The system compares the operating time of the high-efficiency and low-efficiency selected areas at the same running time. If the operating time of the high-efficiency and low-efficiency selected areas does not exceed the operating time threshold, the pump unit in the high-efficiency selected area is marked as a high-efficiency feature, and the pump unit in the low-efficiency selected area is marked as a low-efficiency feature. If the operating time of the high-efficiency and low-efficiency selected areas exceeds the operating time threshold, the pump unit in the corresponding low-efficiency selected area is marked as a fault feature. The high-efficiency feature, low-efficiency feature, fault feature, and the total drainage volume at the corresponding running time are sent to the server.

3. The big data-based flood control and drainage pump unit control system according to claim 1, characterized in that, The process of obtaining the influencing factors for the influencing factor acquisition unit is as follows: Set an operation monitoring period, collect environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to high efficiency characteristics, low efficiency characteristics, and fault characteristics during the operation monitoring period. Compare the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to high efficiency characteristics and low efficiency characteristics. If the environmental parameters, operating parameters, and human parameters are inconsistent, mark the environmental parameters, operating parameters, and human parameters of the pump units in the selected area corresponding to low efficiency characteristics as low efficiency environmental influencing factors, low efficiency operating influencing factors, and low efficiency human influencing factors, respectively. The environmental parameters, operating parameters, and human parameters of the pump units within the selected area corresponding to the high efficiency feature and the fault efficiency feature are compared. If the environmental parameters, operating parameters, and human parameters are inconsistent, the environmental parameters, operating parameters, and human parameters of the pump units within the selected area corresponding to the fault efficiency feature are marked as fault environmental influencing factors, fault operating influencing factors, and fault human influencing factors, respectively. The low efficiency environmental influencing factors, low efficiency operating influencing factors, and low efficiency human influencing factors are sent to the server along with the fault environmental influencing factors, fault operating influencing factors, and fault human influencing factors.

4. The big data-based control system for flood control and drainage pump units according to claim 1, characterized in that, The real-time control process of the real-time control unit is as follows: The pump units in each analysis area are monitored in real time. If the pump units in the corresponding analysis area show low efficiency or fault characteristics, the environmental factors affecting low efficiency, the operational factors affecting low efficiency, and the human factors affecting low efficiency, or the environmental factors affecting faults, the operational factors affecting faults, and the human factors affecting faults are marked as rectification parameters. At the same time, a rectification signal is generated and the rectification signal and rectification parameters are sent to the mobile terminal of the unit management personnel.

Images