Sewage station equipment automatic control system based on artificial intelligence

Abstract

The invention discloses a sewage station equipment automatic control system based on artificial intelligence, and relates to the technical field of sewage treatment monitoring, the sewage station equipment automatic control system comprises a monitoring center, and the monitoring center is in communication and / or electrical connection with a front-end data acquisition module, an intelligent data processing module and an equipment cooperative control module; according to data of sewage to be treated at a water inlet and a water outlet of a sewage station and data of sewage station equipment of each piece of sewage equipment in the sewage station, sewage load and sewage treatment suitability of each piece of sewage equipment participating in a sewage treatment process flow are analyzed; whether the sewage equipment needs to be adjusted or not is judged according to the analysis result, and if the sewage equipment needs to be adjusted, the sewage treatment capacity of the sewage equipment is adjusted according to the sewage inflow and adaptability of the water inlet of the sewage station, so that high-efficiency cooperation between the sewage station equipment is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment monitoring, and specifically to an automatic control system for sewage treatment plant equipment based on artificial intelligence. Background Art

[0002] In cities, wastewater treatment plants are also called sewage treatment plants or sewage works. Those located in factories are often called treatment stations. When the effluent is discharged into the urban drainage pipeline, the treatment station is actually a pretreatment facility. A wastewater treatment plant is a complex system composed of multiple unit processes. The costs and efficiencies of each unit process are interrelated and affect each other, and ultimately determine the cost and efficiency of the entire system.

[0003] During the process of sewage treatment, the sewage treatment capacity of each sewage treatment device in the sewage treatment plant often needs to be adapted to the sewage inflow of the sewage treatment plant. Once there is a mismatch between the devices, it will lead to the situation that the operation of the devices does not meet the sewage treatment requirements or the sewage treatment capacity exceeds the actual needs, resulting in the problem of low collaborative efficiency between sewage treatment devices. How to achieve high-efficiency collaboration between sewage treatment plant devices is the problem we need to solve. For this reason, an automatic control system for sewage treatment plant equipment based on artificial intelligence is provided. Summary of the Invention

[0004] The purpose of the present invention is to provide an automatic control system for sewage treatment plant equipment based on artificial intelligence.

[0005] The purpose of the present invention can be achieved through the following technical solutions: An automatic control system for sewage treatment plant equipment based on artificial intelligence includes a monitoring center, and the monitoring center is communicatively and / or electrically connected to a front-end data acquisition module, an intelligent data processing module, and a device collaborative control module.

[0006] The front-end data acquisition module includes a sewage data acquisition unit and a device data acquisition unit. The sewage data acquisition unit is used to acquire sewage data to be processed, and the device data acquisition unit is used to acquire sewage treatment plant equipment data.

[0007] The intelligent data processing module is used to process the acquired sewage data to be processed and sewage treatment plant equipment data to obtain the sewage treatment load value of the sewage treatment plant equipment.

[0008] The device collaborative control module is used to generate a collaborative control instruction according to the obtained sewage treatment load value.

[0009] Further, the process of the sewage data acquisition unit acquiring sewage data to be processed includes:

[0010] Acquire the number of sewage inlets and outlets in the sewage treatment plant.

[0011] A number of sewage data acquisition units are respectively set at the sewage inlet and outlet of the sewage treatment station, and the sewage data to be processed is acquired in real time through the set sewage data acquisition units. The sewage data to be processed includes the cross-sectional area of the sewage inlet, the sewage flow velocity at the sewage inlet, the cross-sectional area of the sewage outlet, and the sewage flow velocity at the sewage outlet.

[0012] Further, the process of the equipment data acquisition unit acquiring the sewage treatment station equipment data includes:

[0013] According to the sewage treatment process flow, determine the sewage treatment sequence of each sewage treatment station equipment in the sewage treatment process flow, and generate corresponding sewage treatment equipment nodes according to each sewage treatment station equipment;

[0014] Associate each sewage treatment equipment node with a sewage treatment station equipment, and generate an equipment database for the sewage treatment station equipment;

[0015] Set an equipment data acquisition unit in each sewage treatment equipment node, and acquire the sewage treatment station equipment data in real time through the equipment data acquisition unit;

[0016] The sewage treatment station equipment data includes equipment name, equipment water swallowing capacity, water inflow per unit time at the equipment inlet, and water outflow per unit time at the equipment outlet.

[0017] Further, the process of the intelligent data processing module processing the obtained sewage data to be processed and sewage treatment station equipment data to obtain the sewage treatment load value of the sewage treatment station equipment includes:

[0018] Construct a first time coordinate system and a second time coordinate system respectively;

[0019] Generate a first flow velocity change curve according to the obtained sewage flow velocity at the sewage inlet;

[0020] Generate a second flow velocity change curve according to the obtained sewage flow velocity at the sewage outlet;

[0021] Map the obtained first flow velocity change curve and second flow velocity change curve into the first time coordinate system;

[0022] Generate corresponding water inflow rate change curves according to the obtained water inflow per unit time at the inlets of each sewage equipment;

[0023] Generate corresponding water outflow rate change curves according to the obtained water outflow per unit time at the outlets of each sewage equipment;

[0024] Generate corresponding water swallowing capacity change curves according to the obtained water swallowing capacity of each sewage equipment;

[0025] Map the generated curve of the influent flow rate change and the curve of the effluent flow rate change to the second time coordinate system;

[0026] Set a time window;

[0027] According to the obtained first time coordinate system, obtain the total influent volume and the total effluent volume of the sewage treatment plant within the time window;

[0028] According to the obtained second time coordinate system, obtain the equipment load coefficients of each sewage treatment equipment;

[0029] According to the obtained equipment load coefficients of each sewage treatment equipment and the total influent volume and the total effluent volume of the sewage treatment plant, obtain the sewage treatment load value of the sewage treatment equipment in the sewage treatment plant.

[0030] Further, the process that the equipment collaborative control module generates a collaborative control instruction according to the obtained sewage treatment load value includes:

[0031] Set several load gradient threshold intervals, and associate a corresponding sewage treatment load level with each load gradient threshold interval;

[0032] Set different collaborative control instructions for the sewage treatment load levels;

[0033] Match the obtained sewage treatment load value of the sewage treatment plant with each load gradient threshold interval, mark the load gradient threshold interval where the sewage treatment load value falls according to the matching result, and obtain the sewage treatment load level associated with the marked load gradient threshold interval, as well as the collaborative control instruction corresponding to the sewage treatment load level. According to the determined collaborative control instruction, judge whether it is necessary to perform corresponding collaborative control on the sewage treatment equipment.

[0034] Further, if it is necessary to perform collaborative control on the sewage treatment equipment, generate an equipment collaborative matrix composed of the same number of blank matrix units according to the number of sewage treatment equipment;

[0035] Obtain the sewage treatment adaptability between each sewage treatment equipment and the influent volume of the sewage inlet, and according to the obtained sewage treatment equipment adaptability;

[0036] Set an adaptability threshold range, and compare the obtained sewage treatment adaptability corresponding to each sewage treatment equipment with the adaptability threshold range;

[0037] If the sewage treatment adaptability is within the set adaptability threshold range, it means that the sewage treatment equipment does not need to be adjusted;

[0038] If the sewage treatment adaptability is not within the adaptability threshold range, mark the corresponding sewage treatment equipment as the equipment to be adjusted;

[0039] Set corresponding control priorities according to the sewage treatment sequence of each sewage treatment device to be adjusted in the sewage treatment process flow;

[0040] According to the control priorities, sequentially adjust the water inflow per unit time at the water inlet of the sewage treatment device and the water outflow per unit time at the water outlet of the sewage treatment device, so that the sorting of the sewage treatment adaptability corresponding to the sewage treatment device obtained in the device collaboration matrix is consistent with the sewage treatment sequence of the sewage treatment device to be adjusted in the sewage treatment process flow.

[0041] Furthermore, if the water inflow per unit time at the water inlet of the sewage treatment device and the water outflow per unit time at the water outlet of the sewage treatment device are adjusted to the maximum value, and still cannot meet the requirement that the sorting of the sewage treatment adaptability in the device collaboration matrix is consistent with the sewage treatment sequence of the sewage treatment device to be adjusted in the sewage treatment process flow, it means that the sewage treatment device cannot meet the sewage treatment requirements of the sewage treatment station, then generate a device update requirement and send the device update requirement to the monitoring center.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] By analyzing the sewage data to be processed at the water inlet and water outlet of the sewage treatment station, as well as the sewage treatment station device data of each sewage treatment device in the sewage treatment station, and then analyzing the sewage load and sewage treatment adaptability of each sewage treatment device participating in the sewage treatment process flow, and judging whether the sewage treatment device needs to be adjusted according to the analysis results. If adjustment is required, then adaptively adjust the sewage treatment volume of the sewage treatment device according to the sewage inflow volume at the water inlet of the sewage treatment station, so as to achieve high-efficiency collaboration between the sewage treatment station devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings.

[0045] Figure 1 is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] As Figure 1 shown, the sewage treatment station device automatic control system based on artificial intelligence includes a monitoring center, and the monitoring center is communicatively and / or electrically connected to a front-end data acquisition module, an intelligent data processing module, and a device collaboration control module;

[0047] The front-end data acquisition module includes a sewage data acquisition unit and a device data acquisition unit. The sewage data acquisition unit is used to acquire the sewage data to be processed, and the device data acquisition unit is used to acquire the sewage treatment station device data;

[0048] The intelligent data processing module is used to process the obtained sewage data to be processed and the sewage treatment station device data to obtain the sewage treatment load value of the sewage treatment station device;

[0049] The device collaborative control module is used to generate a collaborative control instruction according to the obtained sewage treatment load value.

[0050] It should be further noted that in the specific implementation process, the process of the sewage data acquisition unit acquiring the sewage data to be processed includes:

[0051] Obtain the number of sewage inlets and outlets in the sewage treatment station, record the number of sewage inlets as n, and the number of sewage outlets as m;

[0052] Set a number of sewage data acquisition units for the sewage inlets and outlets of the sewage treatment station respectively, and obtain the sewage data to be processed in real time through the set sewage data acquisition units. The sewage data to be processed includes the cross-sectional area of the sewage inlet, the sewage flow rate of the sewage inlet, the cross-sectional area of the sewage outlet, and the sewage flow rate of the sewage outlet;

[0053] Number each sewage inlet, denoted as i, where i = 1, 2,..., n;

[0054] Number each sewage outlet, denoted as j, where j = 1, 2,..., m;

[0055] Then record the cross-sectional area of the sewage inlet numbered i as SR i , and the sewage flow rate as RV i ;

[0056] Record the cross-sectional area of the sewage outlet numbered j as CR j , and the sewage flow rate as CV j .

[0057] It should be further noted that in the specific implementation process, the process of the device data acquisition unit acquiring the sewage treatment station device data includes:

[0058] According to the sewage treatment process flow, determine the sewage treatment sequence of each sewage treatment station device in the sewage treatment process flow, and generate corresponding sewage treatment device nodes according to each sewage treatment station device;

[0059] Associate each sewage treatment device node with a sewage treatment station device, and generate a device database for the sewage treatment station device;

[0060] An equipment data acquisition unit is set up inside each sewage treatment equipment node, and the sewage treatment plant equipment data is acquired in real time through the equipment data acquisition unit;

[0061] The sewage treatment plant equipment data includes the equipment name, the water swallowing volume of the equipment, the water inflow volume per unit time at the equipment inlet, and the water outflow volume per unit time at the equipment outlet;

[0062] Each sewage treatment plant equipment is numbered according to the sewage treatment sequence in the sewage treatment process, denoted as k, where k = 1, 2,..., s;

[0063] The water swallowing volume of the equipment numbered k is denoted as St k , and the water inflow volume per unit time at the equipment inlet is denoted as SJ k , and the water outflow volume per unit time at the equipment outlet is denoted as SC k .

[0064] It should be further noted that in the specific implementation process, the process of the intelligent data processing module processing the obtained sewage data to be processed and the sewage treatment plant equipment data to obtain the sewage treatment load value of the sewage treatment plant equipment includes:

[0065] Construct a first time coordinate system and a second time coordinate system respectively;

[0066] Generate a first flow rate change curve according to the sewage flow rate at the sewage inlet;

[0067] Generate a second flow rate change curve according to the sewage flow rate at the sewage outlet;

[0068] Map the obtained first flow rate change curve and second flow rate change curve into the first time coordinate system;

[0069] Generate a corresponding water inflow rate change curve according to the water inflow volume per unit time at each sewage equipment inlet;

[0070] Generate a corresponding water outflow rate change curve according to the water outflow volume per unit time at each sewage equipment outlet;

[0071] Generate a corresponding water swallowing volume change curve according to the water swallowing volume of each sewage equipment;

[0072] Map the generated water inflow rate change curve and water outflow rate change curve into the second time coordinate system;

[0073] Set a time window, the initial moment of the time window is t1 = 0, and the end moment is the current moment t2 = t;

[0074] According to the obtained first time coordinate system, obtain the total inflow of the sewage treatment plant within the time window, and record the total inflow of the sewage treatment plant as WJZ, where:

[0075]

[0076] Record the total outflow of the sewage treatment plant as WCZ, where:

[0077]

[0078] where t represents the current moment;

[0079] According to the obtained second time coordinate system, obtain the equipment load factor of each sewage treatment equipment, and record the equipment load factor of the sewage treatment equipment numbered k as SZL k , where:

[0080]

[0081] where a, b, and c are weight coefficients, and a > b > c, and T is the total duration from the initial moment to the current moment t;

[0082] According to the obtained equipment load factor of each sewage treatment equipment, the total inflow and total outflow of the sewage treatment plant, obtain the sewage treatment load value of the sewage treatment equipment in the sewage treatment plant, and record the sewage treatment load value of the sewage treatment equipment in the sewage treatment plant as Wf, where:

[0083] Wf = WJZ × β0 × SZL1 × β1 × SZL2 × …… × β s-1 × SZL s × β s × WCZ;

[0084] where β0 is the influence coefficient of the inlet of the sewage treatment plant on the sewage treatment equipment numbered k = 1, β1 is the influence coefficient of the sewage treatment equipment numbered k = 1 on the sewage treatment equipment numbered k = 2, and so on, β s-1 is the influence coefficient of the sewage treatment equipment numbered k = s - 1 on the sewage treatment equipment numbered k = s, and β s is the influence coefficient of the outlet of the sewage treatment plant on the sewage treatment equipment numbered k = s;

[0085] where β0, β s are constants, and the magnitude of β0 is positively correlated with the total inflow of the inlet of the sewage treatment plant, and β s is inversely correlated with the total outflow of the outlet of the sewage treatment plant;

[0086] β2 = β1 × β0, β3 = β2 × β1, and so on, β s-1 = β s-3 × β s-2 ;

[0087] Upload the sewage treatment load value of the obtained sewage treatment equipment to the equipment collaborative control module.

[0088] It should be further noted that in the specific implementation process, the process of the equipment collaborative control module generating a collaborative control instruction according to the obtained sewage treatment load value includes:

[0089] Set several load gradient threshold intervals, and associate each load gradient threshold interval with a corresponding sewage treatment load level;

[0090] Set different collaborative control instructions for the sewage treatment load levels;

[0091] Match the obtained sewage treatment load value of the sewage treatment station with each load gradient threshold interval, mark the falling load gradient threshold interval of the sewage treatment load value according to the matching result, and obtain the sewage treatment load level associated with the marked load gradient threshold interval, as well as the collaborative control instruction corresponding to the sewage treatment load level. According to the determined collaborative control instruction, judge whether it is necessary to perform corresponding collaborative control on the sewage treatment equipment.

[0092] It should be further noted that in the specific implementation process, if it is necessary to perform collaborative control on the sewage treatment equipment, an equipment collaborative matrix composed of the same number of blank matrix units is generated according to the number of sewage treatment equipment;

[0093] Obtain the sewage treatment adaptability between each sewage treatment equipment and the water inflow volume of the sewage inlet, and according to the obtained sewage treatment equipment adaptability;

[0094] Then the sewage treatment adaptability between the sewage treatment equipment labeled as k and the water inflow volume of the sewage inlet is denoted as WSd k , where:

[0095]

[0096] where, t 单位 represents the unit time;

[0097] Set the adaptability threshold range, and compare the obtained sewage treatment adaptability corresponding to each sewage treatment equipment with the adaptability threshold range;

[0098] If the sewage treatment adaptability is within the set adaptability threshold range, it means that the sewage treatment equipment does not need to be adjusted;

[0099] If the sewage treatment adaptability is not within the adaptability threshold range, mark the corresponding sewage treatment equipment as the equipment to be adjusted;

[0100] Set corresponding control priorities according to the sewage treatment sequence of each sewage treatment device to be adjusted in the sewage treatment process flow;

[0101] According to the control priorities, sequentially adjust the water inflow per unit time at the water inlet of the sewage treatment device and the water outflow per unit time at the water outlet of the sewage treatment device, so that the sorting of the sewage treatment adaptability corresponding to the sewage treatment device obtained in the device collaboration matrix is consistent with the sewage treatment sequence of the sewage treatment device to be adjusted in the sewage treatment process flow. If the water inflow per unit time at the water inlet of the sewage treatment device and the water outflow per unit time at the water outlet of the sewage treatment device are adjusted to the maximum value and still cannot meet the requirement that the sorting of the sewage treatment adaptability in the device collaboration matrix is consistent with the sewage treatment sequence of the sewage treatment device to be adjusted in the sewage treatment process flow, it means that the sewage treatment device cannot meet the sewage treatment requirements of the sewage treatment station. Then generate a device update requirement and send the device update requirement to the monitoring center.

[0102] The above is only a preferred embodiment of the present invention, and it is not intended to limit the present invention in any form. Although the present invention has been disclosed above with a preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments by using the technical content disclosed above within the scope of the technical solution of the present invention. However, as long as it does not depart from the content of the technical solution of the present invention, any modification or equivalent replacement made to the above embodiments based on the technical essence of the present invention still belongs to the scope of the technical solution of the present invention.

Claims

1. An artificial intelligence-based automatic control system for sewage treatment station equipment, including a monitoring center, characterized in that, The monitoring center is communicatively and / or electrically connected to a front-end data acquisition module, an intelligent data processing module, and a device collaborative control module; The front-end data acquisition module includes a sewage data acquisition unit and a device data acquisition unit. The sewage data acquisition unit is used to acquire sewage data to be processed, and the device data acquisition unit is used to acquire sewage treatment station device data; The intelligent data processing module is used to process the obtained sewage data to be processed and sewage treatment station device data to obtain the sewage treatment load value of the sewage treatment station devices; The device collaborative control module is used to generate a collaborative control instruction according to the obtained sewage treatment load value.

2. The automated control system for sewage treatment station equipment based on artificial intelligence according to claim 1, wherein, The process by which the sewage data acquisition unit acquires sewage data to be processed includes: Obtaining the number of sewage inlets and outlets in the sewage treatment station; Setting a number of sewage data acquisition units for the sewage inlets and outlets of the sewage treatment station respectively, and acquiring the sewage data to be processed in real time through the set sewage data acquisition units. The sewage data to be processed includes the cross-sectional area of the sewage inlet, the sewage flow rate of the sewage inlet, the cross-sectional area of the sewage outlet, and the sewage flow rate of the sewage outlet.

3. The automated control system for sewage treatment station equipment based on artificial intelligence according to claim 2, characterized in that The process by which the device data acquisition unit acquires sewage treatment station device data includes: Obtaining the sewage treatment sequence of each sewage treatment station device in the sewage treatment process according to the sewage treatment process flow, and generating corresponding sewage treatment device nodes according to each sewage treatment station device; Associating each sewage treatment device node with a sewage treatment station device, and generating a device database corresponding to the sewage treatment station device; Setting a device data acquisition unit in each sewage treatment device node, and acquiring sewage treatment station device data in real time through the device data acquisition unit; The sewage treatment station device data includes the device name, the device water swallowing capacity, the water inflow rate per unit time at the device inlet, and the water outflow rate per unit time at the device outlet.

4. The automated control system for sewage treatment plant equipment based on artificial intelligence according to claim 3, wherein The process by which the intelligent data processing module processes the obtained sewage data to be processed and sewage treatment station device data to obtain the sewage treatment load value of the sewage treatment station devices includes: Constructing a first time coordinate system and a second time coordinate system respectively; Generating a first flow rate change curve according to the obtained sewage flow rate at the sewage inlet; Generating a second flow rate change curve according to the obtained sewage flow rate at the sewage outlet; Mapping the obtained first flow rate change curve and second flow rate change curve into the first time coordinate system; Generating a corresponding water inflow rate change curve according to the obtained water inflow rate per unit time at each sewage device inlet; Generating a corresponding water outflow rate change curve according to the obtained water outflow rate per unit time at each sewage device outlet; Generating a corresponding water swallowing capacity change curve according to the obtained water swallowing capacity of each sewage device; Mapping the generated water inflow rate change curve and water outflow rate change curve into the second time coordinate system; Setting a time window; Obtaining the total inflow and total outflow of the sewage treatment station within the time window according to the obtained first time coordinate system; Obtaining the device load coefficient of each sewage device according to the obtained second time coordinate system; According to the equipment load coefficients of each sewage treatment device obtained, as well as the total inflow and total outflow of the sewage treatment station, the sewage treatment load value of the sewage treatment devices in the sewage treatment station is obtained.

5. The automated control system for sewage treatment station equipment based on artificial intelligence according to claim 4, characterized in that, The process by which the equipment collaborative control module generates a collaborative control instruction based on the obtained sewage treatment load value includes: Set several load gradient threshold intervals, and associate each load gradient threshold interval with a corresponding sewage treatment load level; Set different collaborative control instructions for different sewage treatment load levels; Match the obtained sewage treatment load value of the sewage treatment station with each load gradient threshold interval, mark the load gradient threshold interval where the sewage treatment load value falls according to the matching result, and obtain the sewage treatment load level associated with the marked load gradient threshold interval, as well as the collaborative control instruction corresponding to this sewage treatment load level. According to the determined collaborative control instruction, judge whether it is necessary to perform corresponding collaborative control on the sewage treatment device.

6. The automated control system for sewage treatment plant equipment based on artificial intelligence according to claim 5, characterized in that, If it is necessary to perform collaborative control on the sewage treatment device, an equipment collaborative matrix composed of the same number of blank matrix units is generated according to the number of sewage treatment devices; Obtain the sewage treatment adaptability between each sewage treatment device and the water inflow of the sewage inlet, and according to the obtained sewage treatment device adaptability; Set an adaptability threshold range, and compare the obtained sewage treatment adaptability corresponding to each sewage treatment device with the adaptability threshold range; If the sewage treatment adaptability is within the set adaptability threshold range, it means that this sewage treatment device does not need to be adjusted; If the sewage treatment adaptability is not within the adaptability threshold range, mark the corresponding sewage treatment device as a device to be adjusted; Set corresponding control priorities according to the sewage treatment sequence of each device to be adjusted in the sewage treatment process; According to the control priority, sequentially adjust the unit time water inflow of the sewage treatment device inlet and the unit time water outflow of the sewage treatment device outlet, so that the sorting of the obtained sewage treatment adaptability corresponding to this sewage treatment device in the equipment collaborative matrix is consistent with the sewage treatment sequence of the device to be adjusted in the sewage treatment process.

7. The automated control system for sewage treatment plant equipment based on artificial intelligence according to claim 6, characterized in that, If the unit time water inflow of the sewage treatment device inlet and the unit time water outflow of the sewage treatment device outlet are adjusted to the maximum value, and still cannot meet the requirement that the sorting of the sewage treatment adaptability in the equipment collaborative matrix is consistent with the sewage treatment sequence of the device to be adjusted in the sewage treatment process, it means that this sewage treatment device cannot meet the sewage treatment requirements of this sewage treatment station, then generate an equipment update requirement and send the equipment update requirement to the monitoring center.

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