CN113759832A - Intelligent operation method for sewage plant - Google Patents
Intelligent operation method for sewage plant Download PDFInfo
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- 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]
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- G—PHYSICS
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- 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
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- 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]
- G05B19/4183—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 data acquisition, e.g. workpiece identification
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- G05B19/41835—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 programme execution
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- 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]
- G05B19/41845—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 system universality, reconfigurability, modularity
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- 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
- G05B19/41855—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 local area network [LAN], network structure
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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
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- G05B19/02—Programme-control systems electric
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- 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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Abstract
The invention discloses a method for intelligently operating a sewage plant, which comprises the following steps: s1, monitoring various index parameters of water in subsystems of each level of the sewage treatment plant in real time by an online monitoring module, and transmitting the obtained various index parameters to an environment management cloud platform, wherein the various index parameters comprise DO, PH, COD and NH3-N, TP, TN, SS; s2, the environment management cloud platform performs judgment analysis on the obtained index parameters by combining the learned knowledge base through the deep learning module, obtains optimal water quality data according to judgment analysis results, and sends the optimal water quality data to the PLC control module; and S3, the PLC control module controls all electric appliances with communication protocols in the sewage treatment plant according to the received optimal water quality data, and the effluent is discharged after reaching the standard. The invention can ensure that the effluent of the sewage treatment plant is discharged after reaching the standard, can save energy and reduce emission, reduces the labor input cost of the sewage treatment plant, and can automatically treat the sewage treatment plant in time after abnormal data problems occur.
Description
Technical Field
The invention relates to the technical field of sewage treatment, in particular to an intelligent operation method for a sewage plant.
Background
At present, the operation mode of most sewage treatment plants in operation is mainly the traditional manual mode. Most sewage treatment plants have a data online platform, and the data online platform receives data from terminal equipment through a sensor and uploads the data to the data online platform to generate a report; the field worker carries out inspection according to a specified time period, the fault problem found in the inspection process and abnormal data of the data online platform need to be fed back to the upper stage, and a technical worker analyzes the fault problem and the abnormal data and provides a solution for the field worker. In the conventional operation mode, the timeliness and the systematicness are the fatal defects. When finding problems and faults from field workers, recording and summarizing the problems and faults and feeding the problems and faults back to technicians for analysis, the time can be delayed in the middle, the feedback received by the technicians can be the next day or even longer, and if the problems and abnormal data cannot be fed back to the technicians in time, the operation safety and standard discharge of the whole sewage treatment plant can be influenced. There are other problems in the traditional sewage treatment plant operation: multiple departments and multiple personnel are needed to cooperate, and a large amount of index data needs to be contrasted and analyzed every day; a large amount of manpower is consumed for manual inspection for multiple shifts; when the technical problems of abnormal fluctuation of inlet water quality, equipment operation failure and substandard outlet water are encountered, field technicians cannot timely perform correct treatment, so that substandard outlet water discharge and secondary environment pollution can be caused. In order to overcome the defects of the traditional sewage plant operation mode, the invention provides a method for realizing automatic operation of a sewage plant through deep learning.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides an intelligent operation method for a sewage plant.
The method for intelligently operating the sewage plant comprises subsystems of all levels of an online monitoring module, a PLC (programmable logic controller) control module, an environment management cloud platform and the sewage treatment plant, wherein the online monitoring module is electrically connected with the environment management cloud platform, the PLC control module is electrically connected with the environment management cloud platform, the online monitoring module is electrically connected with the subsystems of all levels of the sewage treatment plant, a deep learning module is embedded into the environment management cloud platform, and the method comprises the following steps:
s1, monitoring various index parameters of water in subsystems of each level of the sewage treatment plant in real time by an online monitoring module, and transmitting the obtained various index parameters to an environment management cloud platform, wherein the index parameters comprise DO, PH, COD and NH3-N、TP、TN、SS；
S2, the environment management cloud platform performs judgment analysis on the obtained index parameters by combining the learned knowledge base through the deep learning module, obtains optimal water quality data according to judgment analysis results, and sends the optimal water quality data to the PLC control module;
and S3, the PLC control module controls all electric appliances with communication protocols in the sewage treatment plant according to the received optimal water quality data, and the effluent is discharged after reaching the standard.
Furthermore, each level of subsystem of the sewage treatment plant comprises a water collecting well, an adjusting tank, an anaerobic tank, an anoxic tank, an aerobic tank, a middle tank, a secondary sedimentation tank, a floatation tank, a sludge tank and a pasteurization tank, wherein the water collecting well, the adjusting tank, the anaerobic tank, the anoxic tank, the aerobic tank, the middle tank, the secondary sedimentation tank and the floatation tank are sequentially connected, and the floatation tank is respectively connected with the pasteurization tank and the sludge tank.
Furthermore, the online monitoring module comprises one or a combination of more than two of an online water quality monitor, an online DO instrument, an online PH instrument, an ultrasonic flowmeter, a sludge concentration instrument or an online liquid level instrument; the electrical appliance is arranged in each level of subsystem of the sewage treatment plant and comprises: the water pump is used for pumping water and sludge in each level of subsystem of the sewage treatment plant; the submerged stirrers are arranged in the regulating tank, the anaerobic tank and the anoxic tank and are used for creating water flow, enhancing the stirring function, homogenizing solid liquid gas and preventing sludge from precipitating; the fan is used for providing oxygen for subsystems of various levels of the sewage treatment plant; the electric valve is used for automatically controlling the opening and closing of the valve or the opening of the valve so as to control the flow of sewage or the air quantity of aeration of the fan; the air dissolving equipment is arranged in the air floatation tank and is used for removing solid suspended matters in the sewage; and the screw stacking machine is used for dehydrating the sludge.
Furthermore, the water pump includes stealthily dirty pump, pipeline centrifugal pump and screw pump, the fan is the roots blower.
Further, the environment improvement cloud platform further comprises: the report unit is used for storing the real-time monitoring data transmitted by the online monitoring module; and a report generation unit for generating an analysis report.
The invention also aims to provide a sewage treatment process applying the intelligent operation method of the sewage plant, which comprises the following steps:
s11, enabling sewage raw water to flow into a water collecting well, monitoring the inflow raw water through an online PH meter installed in the water collecting well, transmitting the obtained real-time PH value to an environment management cloud platform, judging and analyzing the obtained real-time PH value by combining a learned knowledge base through a deep learning module by the environment management cloud platform, sending an instruction to a PLC (programmable logic controller) control module to start a water pump to pump the raw water in the water collecting well to an adjusting pool when the real-time PH value obtained by the environment management cloud platform is judged to be a normal value, and sending an instruction to the PLC control module to stop the water pump when the real-time PH value is judged to be an abnormal value so as to prevent the raw water which does not reach the standard from entering a rear terminal system;
s12, pumping the raw water into a regulating reservoir through a water pump, enabling a submersible stirrer installed in the regulating reservoir to be normally opened for 24 hours, monitoring the water in the regulating reservoir through an online water quality monitor, an online DO (DO) instrument and an online PH (potential of hydrogen) instrument installed in the regulating reservoir to obtain seven index parameters, namely COD (chemical oxygen demand) and NH (NH)3N, TP, TN, SS, DO and PH, and transmitting the obtained seven index parameters to an environment management cloud platform, and automatically storing the obtained seven index parameters in a report unit by the environment management cloud platform;
s13, pumping the water in the regulating reservoir to an anaerobic pool through a water pump, enabling a submersible stirrer installed in the anaerobic pool to be normally opened for 24 hours, monitoring the water in the anaerobic pool through an ultrasonic flowmeter arranged in the anaerobic pool, transmitting the obtained real-time flow value to an environment management cloud platform, and automatically storing the obtained real-time flow value in a report unit by the environment management cloud platform;
s14, the water in the anaerobic tank automatically flows into the anoxic tank, the submersible stirrer arranged in the anoxic tank is normally opened for 24 hours, the water flowing into the anoxic tank automatically is monitored by an online DO meter and an online PH meter which are arranged in the anoxic tank, and transmitting the obtained real-time DO value and real-time PH value to an environment management cloud platform, the environment management cloud platform automatically stores the obtained real-time DO value and real-time PH value in a report unit, the environment management cloud platform respectively judges and analyzes the obtained real-time DO value and real-time PH value by combining a learned knowledge base through a deep learning module, when the real-time DO value obtained by the environment improvement cloud platform is judged to be an abnormal value, the environment improvement cloud platform sends an instruction to the PLC control module to start the water pump of the middle pool to flow back, when the real-time PH value obtained by the environment improvement cloud platform is judged to be an abnormal value, the environment improvement cloud platform sends an instruction to the PLC control module to start a dosing device to dose the caustic soda flake;
s15, enabling water in the anoxic tank to automatically flow into the aerobic tank, monitoring the water in the aerobic tank through an online DO (DO) instrument, an online PH (potential of Hydrogen) instrument and an online thermometer which are installed in the aerobic tank, and transmitting the obtained real-time DO value, real-time PH value and real-time temperature value to an environment management cloud platform, wherein the environment management cloud platform automatically stores the obtained real-time DO value, real-time PH value and real-time temperature value in a report unit, the environment management cloud platform judges and analyzes the obtained real-time DO value by combining a learned knowledge base through a deep learning module, and when the real-time DO value obtained by the environment management cloud platform is judged to be an abnormal value, the environment management cloud platform sends an instruction to a PLC (programmable logic controller) control module to adjust the rotating speed and frequency of a fan and the opening degree of a valve of an electric ball valve;
s16, the water in the aerobic tank automatically flows into the intermediate tank, the water in the intermediate tank is monitored through an ultrasonic flowmeter arranged in the intermediate tank, the obtained real-time flow value is transmitted to an environment management cloud platform, and the environment management cloud platform automatically stores the obtained real-time flow value in a report unit;
s17, water in the intermediate tank respectively flows back to the front-end anoxic tank and automatically flows to the secondary sedimentation tank, the water automatically flowing to the secondary sedimentation tank is monitored through a sludge concentration meter installed in the secondary sedimentation tank, the obtained real-time sludge concentration value is transmitted to an environment treatment cloud platform, the environment treatment cloud platform automatically stores the obtained real-time sludge concentration value in a report unit, the environment treatment cloud platform performs judgment and analysis on the obtained real-time sludge concentration value by combining a deep learning module with a learned knowledge base, and when the real-time sludge concentration value obtained by the environment treatment cloud platform is judged to be an abnormal value, the environment treatment cloud platform sends an instruction to a PLC (programmable logic controller) control module to open an electric ball valve and discharge sludge;
s18, the water in the secondary sedimentation tank automatically flows into the air flotation tank, the water-containing sludge scraped out by the air dissolving device arranged in the air flotation tank automatically flows into the sludge tank, the water automatically flows into the pasteurization tank at the tail end, wherein, the water-containing sludge in the sludge tank is monitored by an online liquid level meter arranged in the sludge tank, and transmitting the obtained real-time level value to an environment management cloud platform, automatically storing the obtained real-time level value in a report unit by the environment management cloud platform, carrying out judgment and analysis on the obtained real-time level value by combining a learned knowledge base through a deep learning module by the environment management cloud platform, when the real-time liquid level value obtained by the environment improvement cloud platform is judged to be an abnormal value, the environment improvement cloud platform sends an instruction to the PLC control module platform to start the screw pump, pumping the sludge to a screw stacking machine through a screw pump for dehydration treatment, and then storing the sludge in a sludge hopper; monitoring the water entering the pasteurizing tank by an online water quality monitor, an online DO meter and an online PH meter which are arranged in the pasteurizing tank to obtain seven index parameters, namely COD (chemical oxygen demand) and NH (NH)3The method comprises the steps of-N, TP, TN, SS, DO and PH, transmitting the obtained seven index parameters to an environment treatment cloud platform, automatically storing the obtained seven index parameters in a report unit by the environment treatment cloud platform, then comparing the seven index parameters of the water in the regulating pond with the seven index parameters of the water in the Pasteur tank by the environment treatment cloud platform, and automatically generating an analysis report by an analysis report generating unit.
Further, in step S11, the inflow raw water is monitored by an on-line PH meter installed in the sump, and the normal value of the real-time PH value is 6.5 to 8.5.
Further, in step S14, the water flowing into the anoxic tank is monitored by the online DO meter and the online PH meter installed in the anoxic tank, and the obtained normal value of the real-time DO value is 0.2-0.5 and the obtained normal value of the real-time PH value is 6.3-8.0.
Further, in step S15, the water in the aerobic tank is monitored by an online DO meter installed in the aerobic tank, and the normal value of the real-time DO value is 2.0-4.0.
Compared with the prior art, the invention has the following beneficial effects:
compared with the traditional operation mode of the sewage treatment plant, the intelligent operation method of the sewage treatment plant provided by the invention has the advantages that the environment treatment cloud platform with deep learning capability (which is equivalent to the master control of the sewage treatment plant) can learn the experiences and knowledge of different expert scholars through continuous learning, so that the loss value is continuously reduced, the accuracy is continuously improved, the stable standard discharge of the effluent of the sewage treatment plant is ensured, the purposes of saving energy, reducing emission and reducing labor cost are realized, and the sewage treatment plant can automatically treat the effluent in time at the first time after abnormal data problems occur.
Drawings
FIG. 1 is a flow chart of a sewage treatment process in a sewage treatment plant using a conventional operation method;
FIG. 2 is a flow chart of a sewage treatment process of a sewage treatment plant applying the method for intelligent operation of a sewage plant of the present invention.
Detailed Description
The invention is further illustrated with reference to the accompanying drawings and specific embodiments.
The invention provides an intelligent operation method for a sewage plant, which comprises subsystems of all levels of an online monitoring module, a PLC control module, an environment management cloud platform and the sewage plant. Wherein, online monitoring module and environmental management cloud platform electric connection, PLC control module and environmental management cloud platform electric connection, online monitoring module and the subsystem electric connection at different levels of sewage treatment plant, just it has the degree of depth learning module to embed in the environmental management cloud platform, include following step:
s1, monitoring various index parameters of water in subsystems of each level of the sewage treatment plant in real time by an online monitoring module, and transmitting the obtained various index parameters to an environment management cloud platform, wherein the index parameters comprise DO, PH, COD and NH3-N、TP、TN、SS；
S2, the environment management cloud platform performs judgment analysis on the obtained index parameters by combining the learned knowledge base through the deep learning module, obtains optimal water quality data according to judgment analysis results, and sends the optimal water quality data to the PLC control module;
and S3, the PLC control module controls all electric appliances with communication protocols in the sewage treatment plant according to the received optimal water quality data, and the effluent is discharged after reaching the standard.
Wherein, above-mentioned deep learning module embedding environment improvement cloud platform (being equivalent to sewage treatment plant's total accuse mechanism), given the environment and administered the cloud platform and have deep learning ability, specific process is as follows:
s1', compiling a crawler program based on python language, acquiring professional knowledge of sewage treatment from the Internet through the crawler program, and packaging the professional knowledge into a data set in a data format, or instructing an industry expert to convert the experience of the industry expert into the data format and storing the data format into the data set, wherein the data set comprises a test set and a training set, and the knowledge comprises but is not limited to anaerobic digestion, nitrification, denitrification and biological phosphorus removal;
s2', creating a deep learning model, feeding a training set in a data set to the deep learning model for training, selecting a proper higher mathematical function for network configuration of the deep learning model, training the deep learning model, and reducing a training error;
s3', a test set in a feeding data set evaluates the deep learning model, observes an intermediate result, and can be used if the loss value is low and the accuracy rate reaches the standard, or retrain if the loss value is low and the accuracy rate does not reach the standard;
s4', after the accuracy of the deep learning model is stable, the deep learning module is successfully established, and the deep learning module is embedded into an environment management cloud platform (equivalent to a master control of a sewage treatment plant) to operate, so that the environment management cloud platform has the deep learning capability.
Referring to fig. 1, the process flow chart of the sewage treatment process of the Baiyushan sewage treatment plant applying the traditional operation mode adopts a process route A which is mainstream in the industry2And O. The field staff need consume 10 manual works at least every day, can produce a large amount of data after patrolling and examining the water quality test of laboratory every time, and data can pass back the technical division, carries out manual data analysis by the technician, and this in-process needs to spend greatlyThe time of the measurement.
Referring to fig. 2, the process flow chart of the sewage treatment process of the sewage treatment plant of the white jade mountain applying the intelligent operation method of the sewage plant provided by the invention is shown. Four layers in total: from top to bottom do in proper order: the first layer is the intelligent operation method of the sewage plant (a deep learning module is established, and an environment treatment cloud platform (the master control of the sewage plant) is endowed with the deep learning capability); the second layer is a sewage treatment plant; the third layer is all subsystems of each level from water inlet to water outlet of the sewage treatment plant; the fourth layer is all terminal equipment in the sewage treatment plant. The specific process flow is as follows:
s11, sewage raw water flows into the water collecting well, the inflowing raw water is monitored through an online PH meter installed in the water collecting well, the obtained real-time PH value is transmitted to an environment management cloud platform, the environment management cloud platform judges and analyzes the obtained real-time PH value by combining a learned knowledge base through a deep learning module, when the real-time PH value obtained by the environment management cloud platform is judged to be a normal value, the environment management cloud platform sends an instruction to a PLC (programmable logic controller) control module to start a submersible sewage pump to pump the raw water in the water collecting well to an adjusting pool, and when the real-time PH value is judged to be an abnormal value (the normal value of the PH is 6.5-8.5), the environment management cloud platform sends an instruction to the PLC control module to shut the submersible sewage pump so as to prevent the raw water which does not reach the standard from entering a rear terminal system;
s12, conveying the raw water into the regulating reservoir through a submersible sewage pump, wherein a submersible stirrer arranged in the regulating reservoir is normally opened for 24h and is arranged on line in the regulating reservoir (the index parameters of the monitored water quality comprise COD and NH)3-N, TP, TN, SS) water quality monitor, on-line DO meter and on-line PH meter monitor the water in the regulating tank to obtain seven index parameters, namely COD and NH respectively3N, TP, TN, SS, DO and PH, and transmitting the obtained seven index parameters to an environment management cloud platform, and automatically storing the obtained seven index parameters in a report unit by the environment management cloud platform;
s13, pumping water in the regulating reservoir to an anaerobic pool through a submersible sewage pump, enabling a submersible stirrer installed in the anaerobic pool to be normally opened for 24 hours, monitoring the water in the anaerobic pool through an ultrasonic flowmeter arranged on a main pipeline in the anaerobic pool, transmitting the obtained real-time flow value to an environment treatment cloud platform, and automatically storing the obtained real-time flow value in a report unit by the environment treatment cloud platform;
s14, when the water in the anaerobic pool automatically flows into the anoxic pool, a submersible stirrer arranged in the anoxic pool is normally opened for 24 hours, the water automatically flows into the anoxic pool is monitored through an online DO meter and an online PH meter arranged in the anoxic pool, the obtained real-time DO value and real-time PH value are transmitted to an environment treatment cloud platform, the environment treatment cloud platform automatically stores the obtained real-time DO value and real-time PH value in a report unit, the environment treatment cloud platform judges and analyzes the obtained real-time DO value and real-time PH value by combining a learned knowledge base through a deep learning module, when the real-time DO value obtained by the environment treatment cloud platform is judged to be an abnormal value (the normal value of DO is 0.2-0.5), the environment treatment cloud platform sends an instruction to a PLC control module to start the backflow of a middle pool pipeline centrifugal pump, and when the real-time PH value obtained by the environment treatment cloud platform is judged to be an abnormal value (the normal value of PH is 6.3-8.0), the environment management cloud platform sends an instruction to the PLC control module to start a dosing device to dose the caustic soda flakes;
s15, the water in the anoxic tank automatically flows into the aerobic tank, the water in the aerobic tank is monitored by an online DO (DO) instrument, an online PH (potential of Hydrogen) instrument and an online thermometer which are installed in the aerobic tank, the obtained real-time DO value, real-time PH value and real-time temperature value are transmitted to an environment management cloud platform, the environment management cloud platform automatically stores the obtained real-time DO value, real-time PH value and real-time temperature value in a report unit, the environment management cloud platform judges and analyzes the obtained real-time DO value by a deep learning module by combining with a learned knowledge base, and when the real-time DO value obtained by the environment management cloud platform is judged to be an abnormal value (the normal value of DO is 2.0-4.0), the environment management cloud platform sends an instruction to a PLC (programmable logic controller) module to adjust the rotating speed and frequency of a Roots blower and the opening degree of a valve of an electric ball valve;
s16, the water in the aerobic pool automatically flows into the intermediate pool, the water in the intermediate pool is monitored through an ultrasonic flowmeter arranged in a main return pipe of the intermediate pool, the obtained real-time flow value is transmitted to an environment management cloud platform, and the environment management cloud platform automatically stores the obtained real-time flow value in a report unit;
s17, water in the intermediate tank respectively flows back to the front-end anoxic tank and automatically flows to the secondary sedimentation tank, the water automatically flowing to the secondary sedimentation tank is monitored through a sludge concentration meter installed in the secondary sedimentation tank, the obtained real-time sludge concentration value is transmitted to an environment treatment cloud platform, the environment treatment cloud platform automatically stores the obtained real-time sludge concentration value in a report unit, the environment treatment cloud platform performs judgment and analysis on the obtained real-time sludge concentration value by combining a deep learning module with a learned knowledge base, and when the real-time sludge concentration value obtained by the environment treatment cloud platform is judged to be an abnormal value, the environment treatment cloud platform sends an instruction to a PLC (programmable logic controller) control module to open an electric ball valve and discharge sludge;
s18, enabling water in the secondary sedimentation tank to automatically flow into the air flotation tank, enabling water-containing sludge scraped by a dissolved air device arranged in the air flotation tank to automatically flow into the sludge tank, enabling the water to automatically flow into a tail-end pasteurizing tank, monitoring the water-containing sludge in the sludge tank through an online liquid level meter arranged in the sludge tank, sending obtained real-time monitoring data to an environment management cloud platform, automatically storing the obtained real-time liquid level value in a report unit by the environment management cloud platform, carrying out judgment analysis on the obtained real-time liquid level value by combining a learned knowledge base through a deep learning module, and sending an instruction to a PLC (programmable logic controller) control module to start a screw pump when the obtained real-time liquid level value of the environment management cloud platform is judged to be an abnormal value, pumping the sludge to a screw stacking machine through the screw pump for dehydration treatment, and then storing the sludge in a sludge hopper; by being arranged on line in a pasteurizing tank (monitoring water quality index parameters comprise COD and NH)3-N, TP, TN, SS) water quality monitor, online DO meter and online PH meter monitor the water entering the pasteurizing tank to obtain seven index parameters, namely COD and NH respectively3N, TP, TN, SS, DO and PH, transmitting the obtained seven index parameters to an environment treatment cloud platform, automatically storing the obtained seven index parameters in a report unit by the environment treatment cloud platform, comparing the seven index parameters of the water in the regulating pond with the seven index parameters of the water in the Pasteur tank by the environment treatment cloud platform, and analyzing the seven index parametersThe report generation unit automatically generates an analysis report.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. The utility model provides a method of sewage plant intelligence operation, includes subsystems at every level of online monitoring module, PLC control module, environmental management cloud platform, sewage treatment plant, wherein, online monitoring module and environmental management cloud platform electric connection, PLC control module and environmental management cloud platform electric connection, online monitoring module and sewage treatment plant subsystem electric connection at every level, and the embedding of environmental management cloud platform has deep learning module, its characterized in that, includes following step:
s1, monitoring various index parameters of water in subsystems of each level of the sewage treatment plant in real time by an online monitoring module, and transmitting the obtained various index parameters to an environment management cloud platform, wherein the index parameters comprise DO, PH, COD and NH3-N、TP、TN、SS；
S2, the environment management cloud platform performs judgment analysis on the obtained index parameters by combining the learned knowledge base through the deep learning module, obtains optimal water quality data according to judgment analysis results, and sends the optimal water quality data to the PLC control module;
and S3, the PLC control module controls all electric appliances with communication protocols in the sewage treatment plant according to the received optimal water quality data, and the effluent is discharged after reaching the standard.
2. The method according to claim 1, wherein each of the subsystems of the sewage treatment plant comprises a water collecting well, a regulating tank, an anaerobic tank, an anoxic tank, an aerobic tank, a middle tank, a secondary sedimentation tank, an air flotation tank, a sludge tank and a pasteurizing tank, and the water collecting well, the regulating tank, the anaerobic tank, the anoxic tank, the aerobic tank, the middle tank, the secondary sedimentation tank and the air flotation tank are sequentially connected, and the air flotation tank is respectively connected with the pasteurizing tank and the sludge tank.
3. The method for intelligently operating a sewage plant according to claim 1, wherein the online monitoring module comprises one or a combination of more than two of an online water quality monitor, an online DO meter, an online PH meter, an ultrasonic flowmeter, a sludge concentration meter and an online liquid level meter; the electrical appliance is arranged in each level of subsystem of the sewage treatment plant and comprises: the water pump is used for pumping water and sludge in each level of subsystem of the sewage treatment plant; the submerged stirrers are arranged in the regulating tank, the anaerobic tank and the anoxic tank and are used for creating water flow, enhancing the stirring function, homogenizing solid liquid gas and preventing sludge from precipitating; the fan is used for providing oxygen for subsystems of various levels of the sewage treatment plant; the electric valve is used for automatically controlling the opening and closing of the valve or the opening of the valve so as to control the flow of sewage or the air quantity of aeration of the fan; the air dissolving equipment is arranged in the air floatation tank and is used for removing solid suspended matters in the sewage; and the screw stacking machine is used for dehydrating the sludge.
4. The method of claim 3, wherein the water pump comprises a submersible sewage pump, a pipe centrifugal pump and a screw pump, and the blower is a roots blower.
5. The method of claim 1, wherein the environmental remediation cloud platform further comprises: the report unit is used for storing the real-time monitoring data transmitted by the online monitoring module; and a report generation unit for generating an analysis report.
6. A sewage treatment process applying the intelligent operation method of the sewage plant as described in any one of claims 1 to 5, characterized by comprising the following steps:
s11, enabling sewage raw water to flow into a water collecting well, monitoring the inflow raw water through an online PH meter installed in the water collecting well, transmitting the obtained real-time PH value to an environment management cloud platform, judging and analyzing the obtained real-time PH value by combining a learned knowledge base through a deep learning module by the environment management cloud platform, sending an instruction to a PLC (programmable logic controller) control module to start a water pump to pump the raw water in the water collecting well to an adjusting pool when the real-time PH value obtained by the environment management cloud platform is judged to be a normal value, and sending an instruction to the PLC control module to stop the water pump when the real-time PH value is judged to be an abnormal value so as to prevent the raw water which does not reach the standard from entering a rear terminal system;
s12, pumping the raw water into a regulating reservoir through a water pump, enabling a submersible stirrer installed in the regulating reservoir to be normally opened for 24 hours, monitoring the water in the regulating reservoir through an online water quality monitor, an online DO (DO) instrument and an online PH (potential of hydrogen) instrument installed in the regulating reservoir to obtain seven index parameters, namely COD (chemical oxygen demand) and NH (NH)3N, TP, TN, SS, DO and PH, and transmitting the obtained seven index parameters to an environment management cloud platform, and automatically storing the obtained seven index parameters in a report unit by the environment management cloud platform;
s13, pumping the water in the regulating reservoir to an anaerobic pool through a water pump, enabling a submersible stirrer installed in the anaerobic pool to be normally opened for 24 hours, monitoring the water in the anaerobic pool through an ultrasonic flowmeter arranged in the anaerobic pool, transmitting the obtained real-time flow value to an environment management cloud platform, and automatically storing the obtained real-time flow value in a report unit by the environment management cloud platform;
s14, the water in the anaerobic tank automatically flows into the anoxic tank, the submersible stirrer arranged in the anoxic tank is normally opened for 24 hours, the water flowing into the anoxic tank automatically is monitored by an online DO meter and an online PH meter which are arranged in the anoxic tank, and transmitting the obtained real-time DO value and real-time PH value to an environment management cloud platform, the environment management cloud platform automatically stores the obtained real-time DO value and real-time PH value in a report unit, the environment management cloud platform respectively judges and analyzes the obtained real-time DO value and real-time PH value by combining a learned knowledge base through a deep learning module, when the real-time DO value obtained by the environment improvement cloud platform is judged to be an abnormal value, the environment improvement cloud platform sends an instruction to the PLC control module to start the water pump of the middle pool to flow back, when the real-time PH value obtained by the environment improvement cloud platform is judged to be an abnormal value, the environment improvement cloud platform sends an instruction to the PLC control module to start a dosing device to dose the caustic soda flake;
s15, enabling water in the anoxic tank to automatically flow into the aerobic tank, monitoring the water in the aerobic tank through an online DO (DO) instrument, an online PH (potential of Hydrogen) instrument and an online thermometer which are installed in the aerobic tank, and transmitting the obtained real-time DO value, real-time PH value and real-time temperature value to an environment management cloud platform, wherein the environment management cloud platform automatically stores the obtained real-time DO value, real-time PH value and real-time temperature value in a report unit, the environment management cloud platform judges and analyzes the obtained real-time DO value by combining a learned knowledge base through a deep learning module, and when the real-time DO value obtained by the environment management cloud platform is judged to be an abnormal value, the environment management cloud platform sends an instruction to a PLC (programmable logic controller) control module to adjust the rotating speed and frequency of a fan and the opening degree of a valve of an electric ball valve;
s16, the water in the aerobic tank automatically flows into the intermediate tank, the water in the intermediate tank is monitored through an ultrasonic flowmeter arranged in the intermediate tank, the obtained real-time flow value is transmitted to an environment management cloud platform, and the environment management cloud platform automatically stores the obtained real-time flow value in a report unit;
s17, water in the intermediate tank respectively flows back to the front-end anoxic tank and automatically flows to the secondary sedimentation tank, the water automatically flowing to the secondary sedimentation tank is monitored through a sludge concentration meter installed in the secondary sedimentation tank, the obtained real-time sludge concentration value is transmitted to an environment treatment cloud platform, the environment treatment cloud platform automatically stores the obtained real-time sludge concentration value in a report unit, the environment treatment cloud platform performs judgment and analysis on the obtained real-time sludge concentration value by combining a deep learning module with a learned knowledge base, and when the real-time sludge concentration value obtained by the environment treatment cloud platform is judged to be an abnormal value, the environment treatment cloud platform sends an instruction to a PLC (programmable logic controller) control module to open an electric ball valve and discharge sludge;
s18, the water of the secondary sedimentation tank automatically flows into an air floatation tank, the water-containing sludge scraped out by a dissolved air device arranged in the air floatation tank automatically flows into a sludge tank, and the water automatically flows into a pasteurization tank at the tail end, wherein the water-containing sludge in the sludge tank is treated by an online liquid level meter arranged in the sludge tankMonitoring the sludge, transmitting the obtained real-time liquid level value to an environment management cloud platform, automatically storing the obtained real-time liquid level value in a report unit by the environment management cloud platform, judging and analyzing the obtained real-time liquid level value by combining a learned knowledge base through a deep learning module by the environment management cloud platform, sending an instruction to a PLC (programmable logic controller) control module platform to start a screw pump when the real-time liquid level value obtained by the environment management cloud platform is judged to be an abnormal value, pumping the sludge to a screw stacking machine through the screw pump for dehydration treatment, and storing the sludge in a sludge hopper; monitoring the water entering the pasteurizing tank by an online water quality monitor, an online DO meter and an online PH meter which are arranged in the pasteurizing tank to obtain seven index parameters, namely COD (chemical oxygen demand) and NH (NH)3The method comprises the steps of-N, TP, TN, SS, DO and PH, transmitting the obtained seven index parameters to an environment treatment cloud platform, automatically storing the obtained seven index parameters in a report unit by the environment treatment cloud platform, then comparing the seven index parameters of the water in the regulating pond with the seven index parameters of the water in the Pasteur tank by the environment treatment cloud platform, and automatically generating an analysis report by an analysis report generating unit.
7. The wastewater treatment process according to claim 6, wherein in step S11, the normal value of the real-time pH value obtained by monitoring the inflow raw water through an on-line pH meter installed in the sump is 6.5-8.5.
8. The wastewater treatment process according to claim 6, wherein in step S14, the water flowing into the anoxic tank is monitored by an online DO meter and an online pH meter installed in the anoxic tank, and the obtained real-time DO value is 0.2-0.5 and the obtained real-time pH value is 6.3-8.0.
9. The wastewater treatment process according to claim 6, wherein in step S15, the normal value of the real-time DO value obtained by monitoring the water in the aerobic tank through an on-line DO meter installed in the aerobic tank is 2.0-4.0.
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