Water supply energy-saving safe scheduling and purifying intelligent control equipment

Abstract

The invention relates to the technical field of water supply control, in particular to water supply energy-saving safe scheduling and purifying intelligent control equipment. Through a three-level architecture of distributed sensing, edge calculation and joint scheduling, regional-level anomaly detection response time is compressed, local rapid control such as water pump rotating speed adjustment and standby equipment starting is supported, meanwhile, cross-regional resource dynamic allocation is achieved through a priority scheduling algorithm, compared with a traditional centralized system, water supply delay and energy consumption waste are reduced, and the system has the advantages of high reliability and high reliability. The water supply stability and the energy utilization efficiency are improved; manual scheduling instructions are verified in real time through an intelligent contract through a transaction chain, unauthorized operation and non-compliance modification are intercepted, and the abnormal operation interception rate is increased; the data chain allocates a unique digital identity for the sensor and manual operation, so that data sources are traceable, the modification process is verifiable, the problems of data tampering risk and unclear operation responsibility in the prior art are solved, and a reliable data basis is provided for safe scheduling of a water supply system.

Description

Technical Field

[0001] The present invention relates to the technical field of water supply control, and in particular to intelligent control equipment for water supply energy saving, safety scheduling and purification. Background Art

[0002] In the current field of water supply scheduling and intelligent control, the centralized processing model dominates. Under this model, a large amount of data such as water pressure, water quality, flow, and energy consumption needs to be transmitted to the central processing system for analysis and regulation. However, this model has many drawbacks: First, it is difficult to meet real-time requirements. Due to delays in data transmission and centralized processing, it is impossible to respond effectively in time when faced with emergencies such as peak water consumption and pipeline failures, resulting in unstable water supply and even affecting users' normal water use. Second, the cost of cross-regional data transmission is high, including network bandwidth fees, data center storage and processing costs, which greatly increases the operating costs of the water supply system. In addition, existing technologies are also insufficient in ensuring data credibility. Data is easily interfered with and tampered with during transmission and processing, affecting the accuracy of scheduling and control decisions. Summary of the Invention

[0003] The present invention provides a water supply energy-saving and safe scheduling and purification intelligent control equipment for solving the above-mentioned technical problems.

[0004] The first aspect of the present invention provides a water supply energy-saving and safe scheduling and purification intelligent control equipment, including: a distributed perception layer, an edge computing processing module, a joint scheduling module, a data transmission network module and a blockchain evidence protection module.

[0005] The distributed perception layer divides the water supply area into multiple water supply blocks according to the pre-designed zoning information, deploys a block monitoring terminal in each water supply block, and obtains an analysis data packet by collecting water use data, water quality data, and energy consumption data from the multimodal sensor group deployed in the corresponding water supply block through the block monitoring terminal; the block monitoring terminal of each water supply block transmits the analysis data packet to the edge computing processing module.

[0006] The edge computing processing module includes a local analysis server and a local control unit pre-deployed corresponding to each water supply block. The local analysis server receives the analysis data packet and performs edge computing analysis on the analysis data packet to obtain the regional analysis results, and transmits the regional analysis results to the joint scheduling module; the local control unit generates corresponding primary judgment information based on the regional analysis results of the water supply block and receives macro-control information, and executes according to the primary judgment information or macro-control information. When the primary judgment information and macro-control information are detected at the same time, the macro-control information is executed first.

[0007] As a further improvement of the present invention, edge computing analysis is performed on the analysis data packet, and its specific execution content is as follows:

[0008] Water use data, water quality data and energy consumption data are obtained based on the analysis data packet; edge computing analysis includes regional water use analysis unit, regional water quality analysis unit and regional energy consumption analysis unit; the water use data is analyzed by the regional water use analysis unit to obtain the regional water use status; the water quality data is analyzed by the regional water quality analysis unit to obtain the regional water quality status; the energy consumption data is analyzed by the regional energy consumption analysis unit to obtain the regional energy consumption status; the regional water use status, regional water quality status and regional energy consumption status of each water supply block are combined to obtain the regional analysis results.

[0009] The water use data is analyzed through the regional water use analysis unit, specifically:

[0010] Based on the water consumption data of each water supply area, the regional real-time flow data and regional real-time water pressure data of the water supply area corresponding to the current moment are obtained: based on the current moment, multiple corresponding historical flow averages are obtained, and the multiple historical flow averages corresponding to the current moment are predicted and analyzed using a pre-deployed water demand prediction model to obtain the predicted water demand at the current moment. The difference between the regional real-time flow data of the water supply area and the predicted water demand is calculated to obtain the water demand mutation. When the water demand mutation is greater than a preset threshold, a flow anomaly signal is generated;

[0011] Based on the real-time water pressure data of the region, the household water pressure of each user in the corresponding water supply area is obtained, and the standard user demand water pressure is obtained based on the regional database. When the user's household water pressure is lower than the standard user demand water pressure, the corresponding user is marked as a water pressure abnormal user, and the number of users with water pressure abnormality is obtained by counting. The water pressure abnormality ratio is calculated by the ratio of the number of users with water pressure abnormality to the total number of users in the water supply area. When the water pressure abnormality ratio is greater than the pre-set water pressure abnormality ratio warning value, a water pressure abnormality signal is generated; the flow abnormality signal and the water pressure abnormality signal are monitored by a signal divider. When either the flow abnormality signal or the water pressure abnormality signal is triggered, a water use abnormality signal is generated, and the water use abnormality signal is used as the corresponding regional water use status.

[0012] The water quality data is analyzed through the regional water quality analysis unit, specifically:

[0013] According to the water quality data corresponding to the water supply area, the water quality macro-indicators are obtained. The water quality macro-indicators include physical indicators, chemical indicators, pollutant indicators and microbial indicators. The corresponding indicator signals are set for each water quality macro-indicator, namely the physical indicator signal, chemical indicator signal, pollutant indicator signal and microbial indicator signal, and are respectively recorded as T phy 、T che 、T pol 、T mic , the indicators are combined to obtain the water quality signal set (T phy , Tche , T pol , T mic ); based on each water quality macro-indicator, the corresponding sub-indicator is obtained, and the pre-deployed single-indicator threshold warning mechanism is used to warn the sub-indicator of each water quality macro-indicator to generate a corresponding sub-indicator warning signal. The single-indicator threshold warning mechanism compares each sub-indicator of the physical indicator with the corresponding preset sub-indicator threshold. When the sub-indicator is greater than the corresponding sub-indicator threshold, a sub-indicator warning signal is generated, and the indicator signal of the physical indicator includes the warning signals of each sub-indicator; similarly, the sub-indicators of the chemical indicator, the pollutant indicator and the microbial indicator are warned through the single-indicator threshold warning mechanism to generate corresponding sub-indicator warning signals;

[0014] Monitor the early warning signals of the sub-indicators of each water quality macro-indicator. When any one or more early warning signals of sub-indicators appear, the corresponding water quality signal set (T phy , T che , T pol , T mic ), and the corresponding regional water quality status is generated as abnormal water quality.

[0015] The sub-indicators of physical indicators are turbidity, temperature, conductivity, and color; the sub-indicators of chemical indicators are pH value, residual chlorine, total dissolved solids, and hardness; the sub-indicators of pollutant indicators are heavy metals, organic matter, ammonia nitrogen, and nitrate; the sub-indicators of microbial indicators are total colony count, total coliform bacteria, and heat-resistant coliform bacteria.

[0016] The energy consumption data is analyzed through the regional energy consumption analysis unit as follows:

[0017] According to the energy consumption data, the real-time power and cumulative power consumption of each water supply equipment in the water supply area are obtained; the real-time power of each water supply equipment and the rated power corresponding to the equipment are loaded and calculated to obtain the equipment load rate. When the equipment load rate exceeds the preset optimal load range, the corresponding water supply equipment is marked as a power abnormality equipment; according to the accumulated power, the accumulated power consumption of each power supply equipment in the preset unit time is obtained, and the accumulated power consumption of each power supply equipment corresponding to the preset unit time is calculated and summed to obtain the total power consumption. Based on the regional database, the historical average power consumption corresponding to each historical unit time is obtained, and the difference between the total power consumption and the historical average power consumption is calculated to obtain the power consumption difference. When the power consumption is greater than the preset power consumption difference threshold, the corresponding power consumption difference is recorded as an abnormal power consumption value.

[0018] Based on the Dirichlet series improved model, the number of power abnormal devices and abnormal power consumption values ​​are analyzed to obtain the abnormal value of equipment energy consumption; the number of power abnormal devices and abnormal power consumption values ​​are normalized and their values ​​are taken; the Dirichlet series improved model is used The abnormal energy consumption value of the equipment f(Py, Pe) is calculated; where Py and Pe represent the number of power-abnormal equipment and the abnormal power consumption value, respectively; α is the convergence control parameter, and α>β×Py+γ×Pe; β and γ are both variable weights, and both β and γ are greater than zero; when the abnormal energy consumption value of the equipment is greater than the preset threshold, an abnormal energy consumption signal is triggered, and the abnormal energy consumption signal is used as the corresponding regional energy consumption status.

[0019] The joint scheduling module receives the regional analysis results of each water supply block through the pre-deployed master control server, performs joint scheduling analysis based on the regional analysis results of each water supply block to obtain macro control information, and transmits the macro control information back to the edge computing processing module.

[0020] As a further improvement of the present invention, a joint scheduling analysis is performed based on the regional analysis results of each water supply block. The specific analysis is as follows:

[0021] Based on the regional analysis results, the regional water use status, regional water quality status, and regional energy consumption status of each water supply block are obtained. The regional water use status, regional water quality status, and regional energy consumption status of the water supply block are identified. When the regional water use status corresponds to a water use abnormality signal, a priority signal is generated; similarly, when the regional water quality status corresponds to a water quality abnormality, a priority signal is generated; when the regional energy consumption status corresponds to an energy consumption abnormality signal, a priority signal is generated. The number of priority signals of each water supply block is counted and recorded as XI;

[0022] When XI=0, it means that the water supply area has no permanent state, and the corresponding regional priority is generated as none;

[0023] When XI=1, it means that the water supply area has an abnormal state, and the corresponding regional priority is generated as low priority;

[0024] When XI=2, it means that the water supply area has two abnormal states, and the corresponding regional priority is medium priority;

[0025] When XI=3, it means that the water supply area has three abnormal states, and the corresponding regional priority is generated as high priority;

[0026] Obtain the regional priority of each water supply block, and obtain the generation time of the regional priority and record it as the priority timestamp; sort the water supply blocks based on the regional priority and the order of the priority timestamp to obtain the water supply block priority number, divide the scheduling computing power based on the water supply block priority number, and coordinate the macro control information of each water supply block for each water supply area through the pre-deployed comprehensive linkage scheduling model.

[0027] The data transmission network module includes a cloud database, a data transmission map and a data transmission channel. It obtains the coordinate information of each water supply block and marks it on the data transmission map to obtain the transmission map signal punctuation. Each transmission signal punctuation point is connected to the local analysis server of the corresponding water supply block through the data transmission channel. The regional analysis results of each water supply block are stored in the cloud database and connected to the master control server through the data transmission channel.

[0028] The blockchain evidence protection module includes the transaction chain and the data chain;

[0029] The transaction chain is used to record manual scheduling instructions and execution results, and conduct compliance verification analysis on the operation data to obtain preliminary modification judgment information. When the preliminary modification judgment information corresponds to compliance, the pre-set modifiable personnel are obtained, and the operation information of the modifiable personnel is packaged to obtain evidence data. The evidence data includes the portrait image before the modification and the modification timestamp;

[0030] The data link is used to obtain data access information, and obtain the source information corresponding to each data based on the access information. The source information includes manual modification and sensor collection; assign a unique digital identity to the sensor of each water supply block, and assign a digital identity to the data collected by each sensor; obtain the evidence data of the modifiable personnel corresponding to the manual modification, time-sequentially number the evidence data to obtain the evidence digital identity, and associate the evidence data with the evidence digital identity.

[0031] As a further improvement of the present invention, compliance verification analysis of operation data is performed specifically as follows: each manual scheduling instruction is identified through a pre-deployed data verification smart contract. When the manual scheduling instruction exceeds the set warning rules, modification judgment information is generated as abnormal; otherwise, modification judgment information is generated as compliant; warning rules include but are not limited to modifying data in an abnormal range, modifying data beyond a preset range, unauthorized operation judgment, and high-frequency operations during non-working hours.

[0032] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0033] 1. This invention uses a three-level architecture of distributed perception, edge computing, and joint scheduling to compress the response time of regional anomaly detection, support local rapid control such as water pump speed adjustment and backup equipment startup, and realize dynamic cross-regional resource allocation through a priority scheduling algorithm. Compared with traditional centralized systems, it reduces water supply delays and energy waste, and improves water supply stability and energy utilization efficiency.

[0034] 2. The present invention verifies manual scheduling instructions in real time through smart contracts via the transaction chain, intercepts unauthorized operations and non-compliant modifications, and improves the interception rate of abnormal operations; the data chain assigns unique digital identities to sensors and manual operations, making the data source traceable and the modification process verifiable, solving the existing data tampering risks and unclear operational responsibilities, and providing a reliable data basis for the safe scheduling of the water supply system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present application.

[0036] Figure 1 It is a principle block diagram of the present invention;

[0037] Figure 2 This is a flow chart of the data transmission network module of the present invention. DETAILED DESCRIPTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1-2 In an embodiment of the present invention, an embodiment of a water supply energy-saving safety scheduling and purification intelligent control equipment includes:

[0040] The distributed perception layer divides the water supply area into multiple water supply blocks according to the pre-designed zoning information, deploys a block monitoring terminal in each water supply block, and obtains an analysis data packet by collecting water use data, water quality data, and energy consumption data from the multimodal sensor group deployed in the corresponding water supply block through the block monitoring terminal; the block monitoring terminal of each water supply block transmits the analysis data packet to the edge computing processing module.

[0041] Water use data includes water pressure data and flow data; water pressure data includes but is not limited to water pressure at regional pipe network nodes, water pressure at user entrances, and water pressure at water plants; flow data includes but is not limited to regional trunk flow, branch network flow, and user water consumption; water quality data includes but is not limited to pH value, residual chlorine content, turbidity, heavy metal ion concentration, and microbial indicators; energy consumption data includes but is not limited to electricity consumption, equipment operating hours, and pump unit power of water supply facilities such as water pumps and purification equipment;

[0042] Through a multimodal sensor group, we can achieve refined division and differentiated monitoring of water supply areas, and deploy customized sensors for different functional areas such as residents, industry, and commerce to improve the pertinence and comprehensiveness of data collection; the block monitoring terminal packages and transmits data in real time, ensuring that the edge computing module obtains high-precision, spatiotemporally labeled raw data, providing a reliable foundation for subsequent analysis.

[0043] The edge computing processing module includes a pre-deployed local analysis server and a local control unit corresponding to each water supply block. The local analysis server receives the analysis data packet and performs edge computing analysis on the analysis data packet to obtain the regional analysis results, and transmits the regional analysis results to the joint scheduling module;

[0044] The local control unit generates corresponding primary judgment information based on the regional analysis results of the water supply block and receives macro control information, and executes according to the primary judgment information or macro control information. When the primary judgment information and macro control information are detected at the same time, the macro control information is executed first.

[0045] Perform edge computing analysis on the analysis data packets. The specific execution content is as follows:

[0046] Water use data, water quality data and energy consumption data are obtained based on the analysis data packet; edge computing analysis includes regional water use analysis unit, regional water quality analysis unit and regional energy consumption analysis unit; the water use data is analyzed by the regional water use analysis unit to obtain the regional water use status; the water quality data is analyzed by the regional water quality analysis unit to obtain the regional water quality status; the energy consumption data is analyzed by the regional energy consumption analysis unit to obtain the regional energy consumption status; the regional water use status, regional water quality status and regional energy consumption status of each water supply block are combined to obtain the regional analysis results; the local analysis server controls the regional data analysis response time at a low level through parallel processing of three units.

[0047] Furthermore, the water use data is analyzed by the regional water use analysis unit as follows:

[0048] Based on the water consumption data of each water supply area, the regional real-time flow data and regional real-time water pressure data of the water supply area corresponding to the current moment are obtained: based on the current moment, multiple corresponding historical flow averages are obtained, and the multiple historical flow averages corresponding to the current moment are predicted and analyzed using a pre-deployed water demand prediction model to obtain the predicted water demand at the current moment. The difference between the regional real-time flow data of the water supply area and the predicted water demand is calculated to obtain the water demand mutation. When the water demand mutation is greater than a preset threshold, a flow anomaly signal is generated;

[0049] Based on the real-time water pressure data of the region, the household water pressure of each user in the corresponding water supply area is obtained, and the standard user demand water pressure is obtained based on the regional database. When the user's household water pressure is lower than the standard user demand water pressure, the corresponding user is marked as a water pressure abnormal user, and the number of users with water pressure abnormality is obtained by counting. The water pressure abnormality ratio is calculated by the ratio of the number of users with water pressure abnormality to the total number of users in the water supply area. When the water pressure abnormality ratio is greater than the pre-set water pressure abnormality ratio warning value, a water pressure abnormality signal is generated; the flow abnormality signal and the water pressure abnormality signal are monitored by a signal divider. When either the flow abnormality signal or the water pressure abnormality signal is triggered, a water use abnormality signal is generated, and the water use abnormality signal is used as the corresponding regional water use status.

[0050] Taking a residential area as an example, the water demand prediction model is trained by using the morning peak flow data of the past 7 days. When the real-time flow (300m 3 / h) and predicted water demand (200m 3 / h) of water demand mutation (100m 3 / h) exceeds the preset threshold (80m 3 / h), a flow abnormality signal is generated; at the same time, if the household water pressure (0.15MPa) of 10% of the users in the community (exceeding the water pressure abnormality warning value of 5%) is lower than the standard demand water pressure (0.2MPa), a water pressure abnormality signal is generated, and finally a water use abnormality signal is triggered.

[0051] Furthermore, the water quality data is analyzed by the regional water quality analysis unit as follows:

[0052] According to the water quality data corresponding to the water supply area, the water quality macro-indicators are obtained. The water quality macro-indicators include physical indicators, chemical indicators, pollutant indicators and microbial indicators. The corresponding indicator signals are set for each water quality macro-indicator, namely the physical indicator signal, chemical indicator signal, pollutant indicator signal and microbial indicator signal, and are respectively recorded as T phy 、T che 、T pol 、T mic , the indicators are combined to obtain the water quality signal set (T phy , T che , T pol , T mic); based on each water quality macro-indicator, the corresponding sub-indicator is obtained, and the pre-deployed single-indicator threshold warning mechanism is used to warn the sub-indicator of each water quality macro-indicator to generate a corresponding sub-indicator warning signal. The single-indicator threshold warning mechanism compares each sub-indicator of the physical indicator with the corresponding preset sub-indicator threshold. When the sub-indicator is greater than the corresponding sub-indicator threshold, a sub-indicator warning signal is generated, and the indicator signal of the physical indicator includes the warning signals of each sub-indicator; similarly, the sub-indicators of the chemical indicator, the pollutant indicator and the microbial indicator are warned through the single-indicator threshold warning mechanism to generate corresponding sub-indicator warning signals;

[0053] Monitor the early warning signals of the sub-indicators of each water quality macro-indicator. When any one or more early warning signals of sub-indicators appear, the corresponding water quality signal set (T phy , T che , T pol , T mic ), and the corresponding regional water quality status is generated as abnormal water quality.

[0054] The sub-indicators of physical indicators are turbidity, temperature, conductivity, and color; the sub-indicators of chemical indicators are pH value, residual chlorine, total dissolved solids, and hardness; the sub-indicators of pollutant indicators are heavy metals, organic matter, ammonia nitrogen, and nitrate; the sub-indicators of microbial indicators are total colony count, total coliform bacteria, and heat-resistant coliform bacteria; for example, in a certain surface water supply block, when the turbidity exceeds the sub-threshold of the physical indicator and the residual chlorine content is lower than the sub-threshold of the chemical indicator, the sub-indicator warning signals are generated respectively, triggering the water quality signal set (T phy , T che ), and judged that the water quality status of the area was abnormal.

[0055] Furthermore, the energy consumption data is analyzed by the regional energy consumption analysis unit as follows:

[0056] According to the energy consumption data, the real-time power and cumulative power consumption of each water supply equipment in the water supply area are obtained; the real-time power of each water supply equipment and the rated power corresponding to the equipment are loaded and calculated to obtain the equipment load rate. When the equipment load rate exceeds the preset optimal load range, the corresponding water supply equipment is marked as a power abnormality equipment; according to the accumulated power, the accumulated power consumption of each power supply equipment in the preset unit time is obtained, and the accumulated power consumption of each power supply equipment corresponding to the preset unit time is calculated and summed to obtain the total power consumption. Based on the regional database, the historical average power consumption corresponding to each historical unit time is obtained, and the difference between the total power consumption and the historical average power consumption is calculated to obtain the power consumption difference. When the power consumption is greater than the preset power consumption difference threshold, the corresponding power consumption difference is recorded as an abnormal power consumption value.

[0057] Based on the Dirichlet series improved model, the number of power abnormal devices and abnormal power consumption values ​​are analyzed to obtain the abnormal value of equipment energy consumption; the number of power abnormal devices and abnormal power consumption values ​​are normalized and their values ​​are taken; the Dirichlet series improved model is used The abnormal energy consumption value of the equipment f(Py, Pe) is calculated; where Py and Pe represent the number of power-abnormal equipment and the abnormal power consumption value, respectively; α is the convergence control parameter, and α>β×Py+γ×Pe; β and γ are both variable weights, and both β and γ are greater than zero; when the abnormal energy consumption value of the equipment is greater than the preset threshold, an abnormal energy consumption signal is triggered, and the abnormal energy consumption signal is used as the corresponding regional energy consumption status.

[0058] The joint scheduling module receives the regional analysis results of each water supply block through the pre-deployed master control server, performs joint scheduling analysis based on the regional analysis results of each water supply block to obtain macro control information, and transmits the macro control information back to the edge computing processing module.

[0059] The joint scheduling analysis is conducted based on the regional analysis results of each water supply block. The specific analysis is as follows: the regional water use status, regional water quality status, and regional energy consumption status of each water supply block are obtained based on the regional analysis results. The regional water use status, regional water quality status, and regional energy consumption status of the water supply block are identified. When the regional water use status corresponds to an abnormal water use signal, a priority signal is generated; similarly, when the regional water quality status corresponds to an abnormal water quality signal, a priority signal is generated; when the regional energy consumption status corresponds to an abnormal energy consumption signal, a priority signal is generated. The number of priority signals of each water supply block is counted and recorded as XI;

[0060] When XI=0, it means that the water supply area has no permanent state, and the corresponding regional priority is generated as none;

[0061] When XI=1, it means that the water supply area has an abnormal state, and the corresponding regional priority is generated as low priority;

[0062] When XI=2, it means that the water supply area has two abnormal states, and the corresponding regional priority is medium priority;

[0063] When XI=3, it means that the water supply area has three abnormal states, and the corresponding regional priority is generated as high priority;

[0064] Obtain the regional priority of each water supply block, and obtain the generation time of the regional priority and record it as the priority timestamp; sort the water supply blocks based on the regional priority and the order of the priority timestamp to obtain the water supply block priority number, divide the scheduling computing power based on the water supply block priority number, and coordinate the macro control information of each water supply block for each water supply area through the pre-deployed comprehensive linkage scheduling model.

[0065] The data transmission network module includes a cloud database, a data transmission map and a data transmission channel. It obtains the coordinate information of each water supply block and marks it on the data transmission map to obtain the transmission map signal punctuation. Each transmission signal punctuation point is connected to the local analysis server of the corresponding water supply block through the data transmission channel. The regional analysis results of each water supply block are stored in the cloud database and connected to the master control server through the data transmission channel.

[0066] Example 2: The blockchain evidence protection module includes a transaction chain and a data chain;

[0067] The transaction chain is used to record manual scheduling instructions and execution results, and conduct compliance verification analysis on the operation data to obtain preliminary modification judgment information. When the preliminary modification judgment information corresponds to compliance, the pre-set modifiable personnel are obtained, and the operation information of the modifiable personnel is packaged to obtain evidence data. The evidence data includes the portrait capture image before the modification and the modification timestamp.

[0068] Compliance verification and analysis of operational data is specifically carried out as follows: each manual scheduling instruction is identified through a pre-deployed data verification smart contract. When a manual scheduling instruction exceeds the set warning rules, a modification judgment information is generated as abnormal; otherwise, a modification judgment information is generated as compliant; warning rules include but are not limited to modifying data in an abnormal range, modifying data beyond a preset range, unauthorized operation judgment, and high-frequency operations during non-working hours.

[0069] The data link is used to obtain data access information, and obtain the source information corresponding to each data based on the access information. The source information includes manual modification and sensor collection; assign a unique digital identity to the sensor of each water supply block, and assign a digital identity to the data collected by each sensor; obtain the evidence data of the modifiable personnel corresponding to the manual modification, time-sequentially number the evidence data to obtain the evidence digital identity, and associate the evidence data with the evidence digital identity.

[0070] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A water supply energy-saving, safe scheduling and purification intelligent control equipment, characterized in that: include: The edge computing processing module includes a pre-deployed local analysis server and a local control unit corresponding to each water supply block. The local analysis server receives the analysis data packet and performs edge computing analysis on the analysis data packet to obtain the regional analysis results, and transmits the regional analysis results to the joint scheduling module; The local control unit generates corresponding primary determination information based on the regional analysis results of the water supply block and receives macro control information, and executes according to the primary determination information or the macro control information. When the primary determination information and the macro control information are detected at the same time, the macro control information is executed first; The joint scheduling module receives the regional analysis results of each water supply block through the pre-deployed master control server, performs joint scheduling analysis based on the regional analysis results of each water supply block to obtain macro control information, and transmits the macro control information back to the edge computing processing module; The data transmission network module includes a cloud database, a data transmission map and a data transmission channel. It obtains the coordinate information of each water supply block and marks it on the data transmission map to obtain the transmission map signal punctuation. Each transmission signal punctuation point is connected to the local analysis server of the corresponding water supply block through the data transmission channel. The regional analysis results of each water supply block are stored in the cloud database and connected to the master control server through the data transmission channel.

2. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 1 is characterized in that: It also includes a blockchain evidence protection module, which includes a transaction chain and a data chain; The transaction chain is used to record manual scheduling instructions and execution results, and conduct compliance verification and analysis on operation data: each manual scheduling instruction is identified through a pre-deployed data verification smart contract. When a manual scheduling instruction exceeds the set warning rules, a modification judgment information is generated as abnormal; otherwise, a modification judgment information is generated as compliant. When the preliminary modification judgment information corresponds to compliance, the pre-set modifiable personnel are obtained, and the operation information of the modifiable personnel is packaged to obtain evidence data. The evidence data includes the portrait image before the modification and the modification timestamp; The data link is used to obtain data access information, and obtain the source information corresponding to each data based on the access information. The source information includes manual modification and sensor collection; assign a unique digital identity to the sensor of each water supply block, and assign a digital identity to the data collected by each sensor; obtain the evidence data of the modifiable personnel corresponding to the manual modification, time-sequentially number the evidence data to obtain the evidence digital identity, and associate the evidence data with the evidence digital identity.

3. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 1 is characterized in that: It also includes a distributed perception layer, which divides the water supply area into multiple water supply blocks according to pre-designed zoning information, deploys block monitoring terminals in each water supply block, and obtains analysis data packets by collecting water use data, water quality data and energy consumption data from the multimodal sensor group deployed in the corresponding water supply block through the block monitoring terminal; the block monitoring terminal of each water supply block transmits the analysis data packet to the edge computing processing module.

4. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 1 is characterized in that: The edge computing analysis of the analysis data packet is specifically performed as follows: Water use data, water quality data and energy consumption data are obtained based on the analysis data packet; edge computing analysis includes regional water use analysis unit, regional water quality analysis unit and regional energy consumption analysis unit; the water use data is analyzed by the regional water use analysis unit to obtain the regional water use status; the water quality data is analyzed by the regional water quality analysis unit to obtain the regional water quality status; the energy consumption data is analyzed by the regional energy consumption analysis unit to obtain the regional energy consumption status; the regional water use status, regional water quality status and regional energy consumption status of each water supply block are combined to obtain the regional analysis results.

5. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 4 is characterized in that: The specific implementation method of the regional water use analysis unit is: Based on the water consumption data of each water supply area, the regional real-time flow data and regional real-time water pressure data of the water supply area corresponding to the current moment are obtained: based on the current moment, multiple corresponding historical flow averages are obtained, and the multiple historical flow averages corresponding to the current moment are predicted and analyzed using a pre-deployed water demand prediction model to obtain the predicted water demand at the current moment. The difference between the regional real-time flow data of the water supply area and the predicted water demand is calculated to obtain the water demand mutation. When the water demand mutation is greater than a preset threshold, a flow anomaly signal is generated; Based on the real-time water pressure data of the region, the household water pressure of each user in the corresponding water supply area is obtained, and the standard user demand water pressure is obtained based on the regional database. When the user's household water pressure is lower than the standard user demand water pressure, the corresponding user is marked as a water pressure abnormal user, and the number of users with water pressure abnormality is obtained by counting. The water pressure abnormality ratio is calculated by the ratio of the number of users with water pressure abnormality to the total number of users in the water supply area. When the water pressure abnormality ratio is greater than the pre-set water pressure abnormality ratio warning value, a water pressure abnormality signal is generated; the flow abnormality signal and the water pressure abnormality signal are monitored by a signal divider. When either the flow abnormality signal or the water pressure abnormality signal is triggered, a water use abnormality signal is generated, and the water use abnormality signal is used as the corresponding regional water use status.

6. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 4 is characterized in that: The specific implementation method of the regional water quality analysis unit is: Based on the water quality data corresponding to the water supply area, macro-indicators of water quality are obtained. Macro-indicators of water quality include physical indicators, chemical indicators, pollutant indicators, and microbial indicators. Corresponding indicator signals, namely physical indicator signals, chemical indicator signals, pollutant indicator signals, and microbial indicator signals, are assigned to each macro-indicator, and each indicator signal is aggregated to obtain a water quality signal set. Based on each macro-indicator, corresponding sub-indicators are obtained. A pre-deployed single-indicator threshold warning mechanism is used to issue warnings for the sub-indicators of each macro-indicator, generating corresponding sub-indicator warning signals. The single-indicator threshold warning mechanism compares each sub-indicator of the physical indicator with the corresponding preset sub-indicator threshold. When the sub-indicator exceeds the corresponding sub-indicator threshold, a sub-indicator warning signal is generated. The indicator signal of the physical indicator includes each sub-indicator warning signal. Similarly, the single-indicator threshold warning mechanism is used to issue warnings for the sub-indicators of the chemical indicator, pollutant indicator, and microbial indicator, generating corresponding sub-indicator warning signals. The sub-indicator warning signals of each macro-indicator are monitored. When any one or more sub-indicator warning signals appear, the corresponding water quality signal set is triggered, and the corresponding regional water quality status is generated as abnormal water quality.

7. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 4 is characterized in that: The specific execution method of the regional energy consumption analysis unit is: Based on the energy consumption data, the real-time power and cumulative power consumption of each water supply device in the water supply area are obtained; the real-time power of each water supply device is calculated with the rated power of the device to obtain the device load rate. When the device load rate exceeds the preset optimal load range, the corresponding water supply device is marked as a power abnormality device; The accumulated power consumption of each power supply device within a preset unit time is obtained based on the accumulated power consumption. The accumulated power consumption of each power supply device corresponding to the preset unit time is calculated and summed to obtain the total power consumption. The historical average power consumption corresponding to each unit time is obtained based on the regional database. The total power consumption is calculated as a difference from the historical average power consumption to obtain a power consumption difference. When the power consumption is greater than a preset power consumption difference threshold, the corresponding power consumption difference is recorded as an abnormal power consumption value. Based on the improved Dirichlet series model, the number of power-abnormal devices and abnormal power consumption values ​​are analyzed to obtain the abnormal energy consumption value of the equipment. When the abnormal energy consumption value of the equipment is greater than the preset threshold, an abnormal energy consumption signal is triggered, and the abnormal energy consumption signal is used as the corresponding regional energy consumption status.

8. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 7 is characterized in that: The analysis of the number of abnormal power devices and abnormal power consumption values ​​based on the improved Dirichlet series model specifically includes: normalizing the number of abnormal power devices and abnormal power consumption values ​​and obtaining their numerical values; Improve the model using Dirichlet series The abnormal value of equipment energy consumption f(Py, Pe) is calculated; where Py and Pe represent the number of abnormal power devices and abnormal power consumption values, respectively; α is the convergence control parameter, and α>β×Py+γ×Pe; β and γ are both variable weights, and both β and γ are greater than zero.

9. The water supply energy-saving, safe scheduling and purification intelligent control equipment according to claim 1 is characterized in that: The specific analysis of the joint scheduling analysis based on the regional analysis results of each water supply block is as follows: According to the regional analysis results, the regional water use status, regional water quality status and regional energy consumption status of each water supply block are obtained, and the regional water use status, regional water quality status and regional energy consumption status of the water supply block are identified. When the regional water use status corresponds to an abnormal water use signal, a priority signal is generated; similarly, when the regional water quality status corresponds to an abnormal water quality, a priority signal is generated; when the regional energy consumption status corresponds to an abnormal energy consumption signal, a priority signal is generated. The number of priority signals of each water supply block is counted, and the regional priority corresponding to each water supply block is obtained according to the number of priority signals. The regional priority includes none, low priority, medium priority and high priority. Obtain the regional priority of each water supply block, and obtain the generation time of the regional priority and record it as the priority timestamp; sort the water supply blocks based on the regional priority and the order of the priority timestamp to obtain the water supply block priority number, divide the scheduling computing power based on the water supply block priority number, and coordinate the macro control information of each water supply block for each water supply area through the pre-deployed comprehensive linkage scheduling model.

Images