CN111708339A - Artificial intelligence control system and method for sewage plant and application of artificial intelligence control system - Google Patents
Artificial intelligence control system and method for sewage plant and application of artificial intelligence control system Download PDFInfo
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- CN111708339A CN111708339A CN202010571336.9A CN202010571336A CN111708339A CN 111708339 A CN111708339 A CN 111708339A CN 202010571336 A CN202010571336 A CN 202010571336A CN 111708339 A CN111708339 A CN 111708339A
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- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 69
- 239000010865 sewage Substances 0.000 title claims abstract description 61
- 238000000034 method Methods 0.000 title claims description 14
- 238000012544 monitoring process Methods 0.000 claims abstract description 14
- 238000004171 remote diagnosis Methods 0.000 claims abstract description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 46
- 238000003745 diagnosis Methods 0.000 claims description 16
- 238000012423 maintenance Methods 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000012549 training Methods 0.000 claims description 10
- 238000004891 communication Methods 0.000 claims description 9
- 238000012545 processing Methods 0.000 claims description 6
- 238000007405 data analysis Methods 0.000 claims description 4
- 239000012528 membrane Substances 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 3
- 238000013024 troubleshooting Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 description 24
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 12
- 239000007788 liquid Substances 0.000 description 7
- 239000010802 sludge Substances 0.000 description 7
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 6
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 6
- 229910052757 nitrogen Inorganic materials 0.000 description 6
- 229910052698 phosphorus Inorganic materials 0.000 description 6
- 239000011574 phosphorus Substances 0.000 description 6
- 230000008439 repair process Effects 0.000 description 4
- 238000005273 aeration Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000009434 installation Methods 0.000 description 3
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000001276 controlling effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
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- 229910052760 oxygen Inorganic materials 0.000 description 2
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- 230000001105 regulatory effect Effects 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 238000011144 upstream manufacturing Methods 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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- 239000000284 extract Substances 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
- G05B19/4186—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication by protocol, e.g. MAP, TOP
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention discloses an artificial intelligence control system of a sewage plant, which relates to the technical field of sewage treatment and comprises a remote central data acquisition and control system, an artificial intelligence system, a data acquisition system and an automatic control system, wherein: the data acquisition system comprises at least one data acquisition unit and at least one database; the artificial intelligence system establishes an operation mode model by receiving data of the data acquisition system and recommends an optimal operation scheme for the remote central data acquisition and control system; the automatic control system is used for executing the instruction issued by the artificial intelligence system and controlling the field device to automatically operate; the remote central data acquisition and control system is also in wireless connection with a monitoring center and a PC (personal computer) end or a mobile monitoring system for remote diagnosis. The invention can realize stable and effective control of sewage treatment and can realize intelligent management and control of sewage treatment control.
Description
Technical Field
The invention belongs to the technical field of sewage treatment, and particularly relates to an artificial intelligent control system and method for a sewage plant and application thereof.
Background
The sewage treatment is widely applied to various fields of industry, agriculture, medical treatment and the like, the development of economy causes serious pollution to the environment along with a large amount of production sewage and domestic sewage, and the sewage treatment becomes the only way for changing the environment at the present stage along with the continuous increase of the country for environmental protection.
At present, in order to better effectively treat sewage, a sewage plant purchases or constructs a large amount of sewage treatment equipment, however, the sewage treatment equipment often needs manual field supervision and operation debugging, so that the sewage treatment production process is difficult to realize stable and effective control, and the intellectualization of sewage treatment control cannot be realized.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides an artificial intelligent control system for a sewage plant.
In order to achieve the purpose, the invention adopts the following technical scheme:
an artificial intelligence control system, a method and an application of a sewage plant are designed, the artificial intelligence control system comprises a remote central data acquisition and control system, an artificial intelligence system, a data acquisition system and an automatic control system, wherein:
the data acquisition system comprises at least one data acquisition unit for acquiring water quality parameters after field sewage treatment, and at least one database for integrating data in the data acquisition system;
the data acquisition system is in wireless communication connection with the artificial intelligence system through the gateway of the Internet of things and is used for sending the integrated data information to the artificial intelligence system;
the artificial intelligence system establishes an operation mode model through the received data and recommends an optimal operation scheme for the remote central data acquisition and control system, and the remote central data acquisition and control system and the artificial intelligence system establish wireless communication connection through a wireless network;
the automatic control system is used for executing an instruction issued by the artificial intelligence system and controlling the field device to automatically operate, data uploading or downloading is carried out between the automatic control system and the artificial intelligence system through the internet of things gateway, and wireless communication connection is established;
the remote central data acquisition and control system is also in wireless connection with a monitoring center for monitoring the sewage treatment water quality parameters through a large screen and a PC (personal computer) end or a mobile monitoring system for remote diagnosis.
Furthermore, the data acquisition unit comprises a sensor, an instrument and an instrument which are used for acquiring the parameters of the quality of the treated sewage.
Further, the database at least comprises a daily operation data set, a maintenance data set, a system debugging data set, various working condition simulation and operation parameter sets and an on/off data set.
Further, the operation mode model at least establishes a conventional operation model, an energy-saving operation model and an emergency operation model according to a plurality of groups of data information in the database, wherein the conventional operation model comprises the following steps: the equipment automatically operates according to the design scheme and the operation and debugging parameters, and when the water quality slightly changes, the system automatically adjusts the operation condition of the equipment; an energy-saving operation model: when the actual water inflow reaches the designed water inflow, the running state of the equipment can be adjusted, even part of the equipment can be stopped to achieve an energy-saving effect by taking the purpose of ensuring the qualified water quality of the outlet water; an emergency operation model: when some equipment in the system breaks down and the measurement of the instrument is not accurate, the system can automatically balance the running state of the equipment and carry out local adjustment so as to ensure that the quality of the outlet water reaches the standard.
Furthermore, an actual operation parameter module, a system stability requirement module and an optimal operation scheme recommendation module for data training are arranged in the artificial intelligence system, and the artificial intelligence system is trained by combining historical data analysis and comparison according to the operation mode model and is used for training a stable operation scheme of the system.
Furthermore, an alarm emergency processing module and a manual diagnosis and analysis module are also arranged in the artificial intelligence system, and when the artificial intelligence system recommends a scheme with problems, manual intervention can be performed, and repaired parameters are input into the system, so that the system can reanalyze and recommend an operation scheme.
Furthermore, an expert diagnosis module, an equipment manufacturer online diagnosis module and an operation and maintenance expert online analysis and diagnosis module for troubleshooting equipment faults and repairing the program BUG are arranged in the PC end or the mobile monitoring system.
The invention also provides a control method of the artificial intelligent control system of the sewage plant, which comprises the following steps:
(1) collecting daily operation data and integrating the data into groups;
(2) establishing an operation mode model according to the data, and analyzing and comparing the operation mode model with historical data;
(3) establishing a maintenance data file;
(4) collecting system debugging data;
(5) simulating various limit working conditions;
(6) and training to obtain an optimal starting and stopping operation data scheme.
The invention also provides an application of the artificial intelligent control system of the sewage plant in MBR membrane sewage treatment.
The artificial intelligence control system, the method and the application of the sewage plant have the beneficial effects that:
(1) the intelligent control of the sewage treatment in the sewage plant can be realized, the optimal operation scheme is established for the sewage treatment in an artificial intelligence mode through the Internet of things and the application of big data of the Internet of things, the working condition mode can be adjusted according to the change of water quality parameters, the operation state of the equipment is balanced automatically, and local adjustment is carried out, so that the quality of the outlet water reaches the standard.
(2) The method extracts daily operation data through establishing the operation mode model, and can automatically recommend the optimal system operation scheme of the system based on big data and artificial intelligence.
(3) The invention introduces experts, equipment manufacturers and operation and maintenance experts to perform online analysis and diagnosis by using the Internet of things, troubleshoots equipment faults and repairs program BUG, and further improves the remote controllability of sewage treatment.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a system block diagram of an artificial intelligence control system of a sewage plant according to the present invention;
FIG. 2 is a block diagram of the flow of the artificial intelligence control method of the sewage plant of the present invention;
FIG. 3 is a schematic structural diagram of an artificial intelligence control system of a sewage plant applied to MBR membrane sewage treatment.
Labeled as: a raw water pipe 1, an adjusting tank 2, a first water outlet pipe 21, an MBR tank 3, a facultative tank 31, a sludge pump 33, a second water outlet pipe 34, a fan 4, an aeration component 41, a dosing tank 5, a dosing pump 51, a first electromagnetic flow meter 52, a first direct-connection electromagnetic valve 53, a first self-priming pump 61, a second electromagnetic flow meter 63, a second self-priming pump 64, a third electromagnetic flow meter 66, a second direct-connection electromagnetic valve 67, a first detection pipe 7, a first COD (chemical oxygen demand) amount detection sensor 71, a first ammonia nitrogen amount detection sensor 72, a first total nitrogen, a total phosphorus amount detection sensor 73, a second detection pipe 8, a second COD amount detection sensor 81, a second ammonia nitrogen amount detection sensor 82, a second total nitrogen, a total phosphorus amount detection sensor 83, a third detection pipe 9, a third COD amount detection sensor 91, a third ammonia nitrogen amount detection sensor 92, a third total nitrogen, a total phosphorus amount detection sensor 93, a first liquid level meter 10, A second level gauge 11.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. These examples are intended to illustrate the invention and are not intended to limit the scope of the invention. In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted", "provided" and "connected" are to be interpreted broadly, e.g. as a fixed connection, a detachable connection or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The structural features of the present invention will now be described in detail with reference to the accompanying drawings.
Referring to fig. 1, an artificial intelligence control system, method and application thereof for a sewage plant include a remote central data acquisition and control system, an artificial intelligence system, a data acquisition system and an automatic control system, wherein:
the data acquisition system comprises at least one data acquisition unit, and the data acquisition unit comprises a sensor, an instrument and an instrument which are used for acquiring parameters of the quality of the treated sewage. The system comprises a water quality monitoring system, at least one database and a control system, wherein the water quality monitoring system is used for collecting water quality parameters after field sewage treatment, the database is used for integrating data in a data collection system, and the database at least comprises a daily operation data group, a maintenance data group, a system debugging data group, various working condition simulation and operation parameter groups and a start-up/shut-down data group.
The data acquisition system is in wireless communication connection with the artificial intelligence system through the gateway of the Internet of things and used for sending the integrated data information to the artificial intelligence system.
The artificial intelligence system establishes an operation mode model through the received data, and the operation mode model at least establishes a conventional operation model, an energy-saving operation model and an emergency operation model according to a plurality of groups of data information in the database, wherein the conventional operation model comprises the following steps: the equipment automatically operates according to the design scheme and the operation and debugging parameters, and when the water quality slightly changes, the system automatically adjusts the operation condition of the equipment; an energy-saving operation model: when the actual water inflow reaches the designed water inflow, the running state of the equipment can be adjusted, even part of the equipment can be stopped to achieve an energy-saving effect by taking the purpose of ensuring the qualified water quality of the outlet water; an emergency operation model: when some equipment in the system breaks down and the measurement of the instrument is not accurate, the system can automatically balance the running state of the equipment and carry out local adjustment so as to ensure that the quality of the outlet water reaches the standard. And recommending an optimal operation scheme for the remote central data acquisition and control system, wherein the remote central data acquisition and control system and the artificial intelligence system are in wireless communication connection through a wireless network.
The artificial intelligence system is internally provided with an actual operation parameter module for data training, a system stability requirement module and an optimal operation scheme recommendation module, the optimal operation method of the equipment is extracted according to the summary of the times, the method and the experience of equipment inspection and maintenance, a reasonable maintenance plan is proposed, and the long-term and efficient service system of the equipment is ensured. And performing system artificial intelligence training by combining historical data analysis and comparison according to the operation mode model, and training a relatively stable operation scheme of the system.
The automatic control system is used for executing instructions issued by the artificial intelligence system and controlling the field device to automatically operate, data uploading or downloading is carried out between the automatic control system and the artificial intelligence system through the internet of things gateway, and wireless communication connection is established.
The remote central data acquisition and control system is also in wireless connection with a monitoring center for monitoring the sewage treatment water quality parameters through a large screen and a PC (personal computer) end or a mobile monitoring system for remote diagnosis.
An alarm emergency processing module and an artificial diagnosis and analysis module are also arranged in the artificial intelligence system, and are used for carrying out artificial intervention when the artificial intelligence system recommends a scheme with problems, inputting repaired parameters into the system, and enabling the system to reanalyze and recommend an operation scheme. When the fluctuation of the water quality parameters is large, whether the instrument is in fault or the water quality is greatly changed is judged based on big data and artificial intelligence, and misoperation of the system is avoided.
An expert diagnosis module for troubleshooting equipment faults and repairing a program BUG, an equipment manufacturer online diagnosis module and an operation and maintenance expert online analysis and diagnosis module are arranged in the PC end or the mobile monitoring system. An expert mode is added by the Internet of things, equipment manufacturers diagnose and troubleshoot equipment faults on line and repair programs BUG, and operation and maintenance experts analyze and diagnose the system on line.
The artificial intelligent control system of the sewage plant can realize the intelligent control of the sewage plant on sewage treatment, and through the application of the Internet of things and big data thereof, the sewage treatment establishes an optimal operation scheme in an artificial intelligent mode, and can adjust the working condition mode according to the change of water quality parameters, automatically balance the operation state of equipment and perform local adjustment so as to ensure that the quality of effluent water reaches the standard; extracting daily operation data through establishing an operation mode model, and automatically recommending an optimal system operation scheme of the system based on big data and artificial intelligence; and the Internet of things is utilized to introduce experts, equipment manufacturers and operation and maintenance experts to perform online analysis and diagnosis, troubleshoot equipment faults and repair program BUG, and the remote controllability of sewage treatment is further improved.
Referring to fig. 2, the present invention also provides a control method of the artificial intelligence control system of the sewage plant, which comprises the following steps:
(1) collecting daily operation data and integrating the data into groups;
(2) establishing an operation mode model according to the data, and analyzing and comparing the operation mode model with historical data;
(3) establishing a maintenance data file;
(4) collecting system debugging data;
(5) simulating various limit working conditions;
(6) and training to obtain an optimal starting and stopping operation data scheme.
Examples
Referring to fig. 3, for further explanation, the present invention further provides an application of the artificial intelligence control system of the sewage plant in MBR membrane sewage treatment, which is specifically as follows:
the data acquisition system comprises four data acquisition units, wherein the first data acquisition unit is arranged on a raw water pipe 1 of sewage, a first COD (chemical oxygen demand) amount detection sensor 71, a first ammonia nitrogen amount detection sensor 72, a first total nitrogen and total phosphorus amount detection sensor 73 are arranged on the raw water pipe 1 through a first detection pipe 7 with a plurality of installation positions and are used for acquiring water quality parameters in the raw water, the second data acquisition unit is arranged on a first water outlet pipe 21 of a regulating tank 2 and is positioned at the upstream of a first self-priming pump 61, a second COD amount detection sensor 81, a second ammonia nitrogen amount detection sensor 82, a second total nitrogen and total phosphorus amount detection sensor 83 are arranged on the first water outlet pipe 21 through a second detection pipe 8 with a plurality of installation positions and are used for acquiring water quality parameters after passing through the regulating tank 2, the third data acquisition unit is arranged on a second water outlet pipe 34 of the MBR tank 3 and is positioned at the upstream of a second self-priming pump 64, the third COD amount detection sensor 91 is installed on the second water outlet pipe 34 through a third detection pipe 9 provided with a plurality of installation positions, the third ammonia nitrogen amount detection sensor 92, the third total nitrogen and total phosphorus amount detection sensor 93 is used for collecting water quality parameters processed by the MBR tank 3, the fourth data acquisition unit comprises a first electromagnetic flow meter 52, a second electromagnetic flow meter 63, a third electromagnetic flow meter 66, a first liquid level meter 10 and a second liquid level meter 11, the first electromagnetic flow meter 52 is used for collecting medicine adding amount data parameters of the medicine adding tank 5, the second electromagnetic flow meter 63 is used for collecting water conveying amount of the adjusting tank 2 to the facultative tank 31, the third electromagnetic flow meter 66 is used for collecting water conveying amount of the MBR tank 3 to the clear water tank, the first liquid level meter 10 is used for collecting liquid level amount of the adjusting tank 2, and the second liquid level meter 11 is used for collecting liquid level amount of the MBR tank 3.
The data acquisition system establishes respective databases by combining data information acquired by the four data acquisition units daily, integrates the data and wirelessly transmits the data to the artificial intelligence system through the Internet of things gateway, and the artificial intelligence system establishes an operation mode model for the data and respectively establishes a conventional operation model, an energy-saving operation model and an emergency operation model.
The artificial intelligence system integrates historical data analysis and comparison according to the established operation mode model, carries out artificial intelligence training of the system and trains four stable operation schemes of the system.
The control field device comprises a sludge pump 33, a fan 4, a dosing pump 51, a first self-sucking pump 61 and a second self-sucking pump 64, the automatic control system is used for executing an operation scheme instruction issued by the artificial intelligence system, the sludge pump 33, the fan 4, the dosing pump 51, the first self-sucking pump 61 and the second self-sucking pump 64 of the control field device automatically operate, the sludge pump 33 is used for sucking sludge in the sewage treatment process, and the sucking amount of the sludge is comprehensively determined by the first operation scheme and the third operation scheme; the air supply quantity of the fan 4 to the aeration component 41 comprehensively determines the aeration quantity according to the second operation scheme and the third operation scheme; the dosing pump 51 determines the dosing amount comprehensively according to a first operation scheme and a second operation scheme, and the first self-sucking pump 61 and the second self-sucking pump 64 determine the water delivery amount according to a fourth operation scheme.
When the water quality parameters in the data acquisition system slightly fluctuate, the artificial intelligence system firstly finely adjusts each system according to the recommended scheme, if the fluctuation of the parameters is not relieved, or when the water quality parameters suddenly fluctuate greatly, the alarm emergency processing module and the manual diagnosis and analysis module intervene, the alarm emergency processing module is started, and closing the sludge pump 33, the fan 4, the dosing pump 51, the first self-priming pump 61, the second self-priming pump 64, the first direct-current electromagnetic valve 53 and the second direct-current electromagnetic valve 67, and starting the manual diagnosis and analysis module, the remote diagnosis PC end or the mobile monitoring system, remotely consulting the fluctuation of the water quality parameters and carrying out manual intervention by equipment manufacturers and operation and maintenance experts through the PC end or the mobile monitoring system, inputting the repaired parameters into the system, re-analyzing the system and recommending an operation scheme, and after the repair is finished, starting the field equipment again by the alarm emergency processing module.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a sewage factory artificial intelligence control system, its characterized in that includes long-range central data acquisition and control system, artificial intelligence system, data acquisition system, autonomous system, wherein:
the data acquisition system comprises at least one data acquisition unit for acquiring water quality parameters after field sewage treatment, and at least one database for integrating data in the data acquisition system;
the data acquisition system is in wireless communication connection with the artificial intelligence system through the gateway of the Internet of things and is used for sending the integrated data information to the artificial intelligence system;
the artificial intelligence system establishes an operation mode model through the received data and recommends an optimal operation scheme for the remote central data acquisition and control system, and the remote central data acquisition and control system and the artificial intelligence system establish wireless communication connection through a wireless network;
the automatic control system is used for executing an instruction issued by the artificial intelligence system and controlling the field device to automatically operate, data uploading or downloading is carried out between the automatic control system and the artificial intelligence system through the internet of things gateway, and wireless communication connection is established;
the remote central data acquisition and control system is also in wireless connection with a monitoring center for monitoring the sewage treatment water quality parameters through a large screen and a PC (personal computer) end or a mobile monitoring system for remote diagnosis.
2. The artificial intelligence control system of a sewage plant of claim 1, wherein the data acquisition unit includes sensors, instruments and meters for acquiring parameters of the quality of the treated sewage.
3. The artificial intelligence control system of claim 1, wherein the database includes at least one of a daily operation data set, a maintenance data set, a system debugging data set, various operation condition simulation and operation parameter sets, and an on/off data set.
4. The artificial intelligence control system of the sewage plant of claim 3, wherein the operation mode model establishes at least a normal operation model, an energy-saving operation model and an emergency operation model according to a plurality of groups of data information in the database.
5. The sewage plant artificial intelligence control system of claim 4, wherein the artificial intelligence system is internally provided with an actual operation parameter module, a system stability requirement module and an optimal operation scheme recommendation module for data training, and the artificial intelligence system is trained by combining historical data analysis and comparison according to the operation mode model, so as to train a stable operation scheme of the system.
6. The sewage plant artificial intelligence control system of claim 5, wherein the artificial intelligence system is further provided with an alarm emergency processing module and an artificial diagnosis and analysis module, and is used for performing artificial intervention when the artificial intelligence system recommends a solution, inputting repaired parameters into the system, and re-analyzing the system and recommending an operation solution.
7. The artificial intelligence control system of the sewage plant of claim 1, wherein an expert diagnosis module for troubleshooting equipment faults and repairing a program BUG, an equipment plant on-line diagnosis module and an operation and maintenance expert on-line analysis and diagnosis module are arranged in the PC end or the mobile monitoring system.
8. The control method of the artificial intelligence control system of the sewage plant as recited in any one of claims 1 to 7, comprising the steps of:
(1) collecting daily operation data and integrating the data into groups;
(2) establishing an operation mode model according to the data, and analyzing and comparing the operation mode model with historical data;
(3) establishing a maintenance data file;
(4) collecting system debugging data;
(5) simulating various limit working conditions;
(6) and training to obtain an optimal starting and stopping operation data scheme.
9. Use of the artificial intelligence control system of a sewage plant of any of claims 1-7 in MBR membrane sewage treatment.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112578751A (en) * | 2020-12-08 | 2021-03-30 | 南京唯友环保科技有限公司 | Well control system based on sewage drainage station |
| CN112939246A (en) * | 2021-04-22 | 2021-06-11 | 广西科技大学 | Hospital sewage online treatment platform based on Internet of things |
| CN114326499A (en) * | 2021-12-27 | 2022-04-12 | 南京谱瑞环境科技有限公司 | Remote automatic control system and method based on Internet of things wastewater pretreatment |
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