CN114425187B - Multistage nanofiltration tower regulation and control system based on water quality detection - Google Patents
Multistage nanofiltration tower regulation and control system based on water quality detection Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D24/00—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof
- B01D24/48—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof integrally combined with devices for controlling the filtration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D24/00—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof
- B01D24/007—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof with multiple filtering elements in series connection
- B01D24/008—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof with multiple filtering elements in series connection arranged concentrically or coaxially
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D24/00—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof
- B01D24/02—Filters comprising loose filtering material, i.e. filtering material without any binder between the individual particles or fibres thereof with the filter bed stationary during the filtration
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D35/00—Filtering devices having features not specifically covered by groups B01D24/00 - B01D33/00, or for applications not specifically covered by groups B01D24/00 - B01D33/00; Auxiliary devices for filtration; Filter housing constructions
- B01D35/14—Safety devices specially adapted for filtration; Devices for indicating clogging
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/001—Processes for the treatment of water whereby the filtration technique is of importance
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/008—Control or steering systems not provided for elsewhere in subclass C02F
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- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F2305/00—Use of specific compounds during water treatment
- C02F2305/08—Nanoparticles or nanotubes
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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
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W10/00—Technologies for wastewater treatment
- Y02W10/10—Biological treatment of water, waste water, or sewage
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Abstract
The invention relates to a multistage nanofiltration tower regulation and control system based on water quality detection, which comprises the following components: the sewage treatment main framework comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank; the series setting mechanism is used for setting the number of the currently used nano modified filter material series in the multi-stage nano filter tower; and the parameter selection equipment is used for taking each gray value of each pixel point of the reference wastewater picture corresponding to the wastewater treatment operation executed by the current wastewater treatment main structure as each input data of the intelligent prediction model so as to run the intelligent prediction model and obtain the current selection level number. According to the invention, the number of stages of nano modified filter materials needed by the current sewage filtering by the multi-stage nano filter tower can be selected in a self-adaptive manner according to the pollution severity of the current sewage, so that the sewage filtering effect is ensured as much as possible while the nano modified filter materials are prevented from being wasted.
Description
Technical Field
The invention relates to the field of sewage treatment, in particular to a multistage nanofiltration tower regulation and control system based on water quality detection.
Background
Sewage treatment refers to the process of purifying sewage to meet the water quality requirement of being discharged into a certain water body or reused. The sewage treatment is widely applied to various fields such as buildings, agriculture, traffic, energy, petrifaction, environmental protection, urban landscapes, medical treatment, catering and the like.
Sewage treatment is generally classified into production sewage treatment and domestic sewage treatment according to sewage sources. The production sewage includes industrial sewage, agricultural sewage, medical sewage, etc., and the domestic sewage is sewage produced in daily life, and refers to a complex mixture of various forms of inorganic matters and organic matters, including: (1) floating and suspended solid particles of size; (2) gelatinous and gelatinous diffusers; (3) pure solution.
The water pollution is classified into two categories according to the nature of the water pollution: one type is natural pollution; the other type is artificial pollution, and the current hazard to water is great. Water pollution can be largely classified into three categories of chemical pollution, physical pollution and biological pollution according to the difference of pollution impurities. The pollutants are mainly as follows: (1) untreated industrial wastewater; (2) untreated domestic sewage; (3) A great deal of farmland sewage using chemical fertilizers, pesticides and herbicides; (4) industrial waste and household garbage piled up on river sides; (5) water and soil loss; (6) mine sewage.
In the field of aerospace environment protection, a aerospace nano modified filter material is generally adopted as a main means for sewage environment treatment, and the core of the method is that high-frequency waves are used as energy sources, water is used as an initiator, cavitation effect generated when the high-frequency waves are transmitted in the water is utilized and accompanied by mechanical effect, natural ores are broken through hydrogen bonds and chemical bonds under the action of the cavitation effect, atomic ring atomic groups of unpaired electrons are separated, free radicals induced in a cracking groove are not immediately combined to generate new substances, then the new substances are removed by the waves, and the natural ores are modified and reamed. Compared with the traditional rubbing, grinding and drilling technology, the technology is a nano filter material produced by carrying out nano-scale processing on raw materials on a microscopic level. The filter material has extremely strong treatment capacity on sewage, and has very good effects on water ecological restoration treatment, water quality improvement up to the standard, black and odorous river treatment, landfill leachate treatment and radioactive sewage treatment.
However, on one hand, a specific sewage treatment mechanism applying the space nanometer modified filter material is lacking at present, on the other hand, the space nanometer modified filter material is relatively expensive, if excessive space nanometer modified filter material is used during sewage treatment, unnecessary space nanometer modified filter material waste is obviously caused, the cost of sewage treatment is improved, and on the contrary, if fewer space nanometer modified filter materials are used during sewage treatment, the sewage treatment is not clean enough, and the effect of sewage treatment is seriously affected.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides a multi-stage nanofiltration tower regulation and control system based on water quality detection, which adopts a customized intelligent prediction model based on a deep neural network to realize the selection operation of nano modified filter material series required by the current sewage filtration according to the corresponding relation between the gray data of a sewage picture and the nano modified filter material series on the basis of introducing a main sewage treatment framework which is designed in a targeted manner and comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank, thereby taking the sewage treatment effect and the sewage treatment cost into consideration.
For this purpose, the present invention needs to have at least the following three important points:
(1) The method comprises the steps of introducing a main sewage treatment framework which comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank and is designed in a targeted manner, and utilizing nano modified filter materials to finish the customized purification treatment of sewage to be treated, including industrial sewage, landfill leachate or rural domestic sewage;
(2) Based on the corresponding relation between the imaging picture of the sewage central area in the past purification treatment and the number of stages of the nano modified filter material, an intelligent prediction model based on a deep neural network is established, and the prediction treatment of the current number of stages of the nano modified filter material is realized;
(3) Different intelligent prediction models are designed for different multi-stage nanofiltration towers, wherein the number of times the intelligent prediction models are trained before being obtained is monotonically and positively correlated with the single-time treatment water quantity of the used multi-stage nanofiltration towers.
According to a first aspect of the present invention, there is provided a multi-stage nanofiltration tower conditioning system based on water quality detection, the system comprising:
the sewage treatment main framework comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank, wherein the first pump body is used for conveying sewage to be treated to the pretreatment tank for primary aeration and solid-liquid separation, the second pump body is arranged between the pretreatment tank and the multi-stage nanofiltration tower and is used for conveying water subjected to primary aeration and solid-liquid separation to the inside of the multi-stage nanofiltration tower for filtration treatment, the third pump body is arranged between the multi-stage nanofiltration tower and the post-treatment tank and is used for conveying the water subjected to filtration treatment to the post-treatment tank for secondary aeration and sedimentation treatment so as to obtain output purified water, and the sewage to be treated is industrial sewage, landfill leachate or domestic sewage;
the series setting mechanism is connected with the multi-stage nanofiltration tower and is used for setting the number of the currently used nano modified filter material series in the multi-stage nanofiltration tower;
the signal acquisition mechanism is used for executing picture acquisition action on the central area of the wastewater in a calm state before the wastewater is sent into the pretreatment tank by the first pump body so as to obtain a reference wastewater picture with fixed resolution and definition;
the model initial solution mechanism is respectively connected with the series setting mechanism and the signal acquisition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the sewage treatment operation executed by the sewage treatment main mechanism at one time as each input data of the deep neural network and taking the nano modified filter material series used by the sewage treatment operation executed by the sewage treatment main mechanism at one time as single output data of the deep neural network so as to establish the deep neural network;
the model re-solving mechanism is connected with the model initial solving mechanism and is used for taking all gray values of all pixel points of a reference wastewater picture corresponding to the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as all input data of the deep neural network, taking the nano modified filter material series used by the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as single output data of the deep neural network, and executing one training operation on the deep neural network to obtain the deep neural network which completes multiple training as an intelligent prediction model to be output;
the parameter selection device is connected with the model re-decomposition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the current wastewater treatment operation executed by the wastewater treatment main mechanism as each input data of the intelligent prediction model to operate the intelligent prediction model, and obtaining the nano modified filter material series output by the intelligent prediction model as the current selection series to be output;
wherein the number of times training is performed is monotonically and positively correlated with the single treatment water volume of the multi-stage nanofiltration tower.
According to a second aspect of the invention, a multi-stage nanofiltration tower regulation and control method based on water quality detection is provided, and the method comprises the step of using the multi-stage nanofiltration tower regulation and control platform based on water quality detection to introduce a specifically designed sewage treatment main framework so as to realize the selection operation of nano modified filter material series required by current sewage filtration according to the corresponding relation between sewage picture gray data and nano modified filter material series on the basis of a customized intelligent prediction model based on a deep neural network.
According to a third aspect of the present invention, there is provided a computer readable storage medium having stored thereon a computer program which, when executed, implements the steps of the multi-stage nanofiltration tower conditioning method based on water quality detection as described above.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings, in which:
FIG. 1 is a technical flow diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to the present invention.
Fig. 2 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 1 of the present invention.
Fig. 3 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 2 of the present invention.
Fig. 4 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 3 of the present invention.
Fig. 5 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 4 of the present invention.
Fig. 6 is a schematic diagram of a computer-readable storage medium shown in embodiment 6 of the present invention.
Detailed Description
The formation principle of the aerospace nano modified filter material adopted in the aerospace environment-friendly field is as follows: the vibration source of the high-frequency wave is proton vibration, the amplitude is very small, the acceleration is very large, the acting force is directional, when the liquid passes through, the sound pressure of each part of the liquid can change, cavitation effect can be generated in water, the cavitation effect can generate local high temperature and high pressure, and the strong shock wave and high-speed microjet are accompanied, so that a chemical bond with strong binding force can be instantaneously destroyed, and the method is the original power in the processing process; under the cavitation effect of natural ore, the hydrogen bond and chemical bond are broken, and the separated atoms or atomic groups of unpaired electrons are immediately combined with free radicals induced in the cracking tank to generate new substances, and removed by waves, so that the natural ore is modified and reamed.
However, at present, a specific sewage treatment mechanism applying the space nanometer modified filter material is lacking, and meanwhile, although the space nanometer modified filter material has better treatment effect compared with other materials in sewage treatment, the manufacturing cost of the space nanometer modified filter material is higher, and the cost performance of sewage treatment can be improved only under the condition of effectively controlling the cost of the used space nanometer modified filter material, so that the space nanometer modified filter material can be successfully applied to various industrial or civil treatment fields.
To solve the technical problems. The invention builds a multi-stage nanofiltration tower regulation and control system based on water quality detection, on one hand, a main sewage treatment framework which comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank and is designed in a targeted mode is introduced, so that a high-precision sewage treatment mechanism of a space nanometer modified filter material is obtained, on the other hand, a customized intelligent prediction model based on a deep neural network is introduced to intelligently and adaptively analyze the number of nanometer modified filter material stages required according to gray data of an imaging picture of current sewage, and two unexpected treatment scenes of insufficient sewage treatment or waste of sewage treatment materials are avoided while an effective sewage treatment framework is provided.
As shown in fig. 1, a technical flow diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection is provided.
Firstly, constructing a main sewage treatment framework which comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank and is designed in a targeted manner;
secondly, establishing a customized intelligent prediction model based on a depth neural network according to the corresponding relation between the gray data of the sewage picture and the nano modified filter material level, wherein different main sewage treatment frameworks have different intelligent prediction models, and the number of times of being trained before the intelligent prediction models are acquired is mainly related to the single treatment water quantity of the used multi-stage nano filter tower in a monotonic forward direction;
thirdly, performing picture acquisition on a central area of the sewage to be treated currently by using signal acquisition equipment to obtain a reference sewage picture, and taking each gray value corresponding to each pixel point of the reference sewage picture as each input data of an established intelligent prediction model to obtain a current selection level number to be sent to the sewage treatment main framework;
and fourthly, pushing the multistage nano modified filter materials of corresponding stages into the tower body of the multistage nano filter tower based on the received current selection stage numbers, so that the multistage nano filter tower can execute sewage filtering operation, and the number of the used nano modified filter materials is matched with the pollution degree of the sewage to be treated.
The key point of the invention is that a main sewage treatment framework which comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nano-filtration tower, a third pump body and a post-treatment tank and is designed specifically is that an intelligent prediction model based on a deep neural network is built based on the corresponding relation between an imaging picture of a sewage central area and the number of stages of nano-modified filter materials in the past purification treatment, so that the number of stages of nano-modified filter materials needed by the multi-stage nano-filtration tower for executing the current sewage filtration can be selected in a self-adaptive manner according to the pollution severity of the current sewage, and the sewage filtration effect is ensured as much as possible while the waste of nano-modified filter materials is avoided.
The multistage nanofiltration tower regulation and control system based on water quality detection of the present invention will be specifically described by way of example.
Example 1
Fig. 2 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 1 of the present invention.
As shown in fig. 2, the multi-stage nanofiltration tower regulation and control system based on water quality detection comprises the following components:
the sewage treatment main framework comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank, wherein the first pump body is used for conveying sewage to be treated to the pretreatment tank for primary aeration and solid-liquid separation, the second pump body is arranged between the pretreatment tank and the multi-stage nanofiltration tower and is used for conveying water subjected to primary aeration and solid-liquid separation to the inside of the multi-stage nanofiltration tower for filtration treatment, the third pump body is arranged between the multi-stage nanofiltration tower and the post-treatment tank and is used for conveying the water subjected to filtration treatment to the post-treatment tank for secondary aeration and sedimentation treatment so as to obtain output purified water, and the sewage to be treated is industrial sewage, landfill leachate or domestic sewage;
the series setting mechanism is connected with the multi-stage nanofiltration tower and is used for setting the number of the currently used nano modified filter material series in the multi-stage nanofiltration tower;
the signal acquisition mechanism is used for executing picture acquisition action on the central area of the wastewater in a calm state before the wastewater is sent into the pretreatment tank by the first pump body so as to obtain a reference wastewater picture with fixed resolution and definition;
the model initial solution mechanism is respectively connected with the series setting mechanism and the signal acquisition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the sewage treatment operation executed by the sewage treatment main mechanism at one time as each input data of the deep neural network and taking the nano modified filter material series used by the sewage treatment operation executed by the sewage treatment main mechanism at one time as single output data of the deep neural network so as to establish the deep neural network;
the model re-solving mechanism is connected with the model initial solving mechanism and is used for taking all gray values of all pixel points of a reference wastewater picture corresponding to the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as all input data of the deep neural network, taking the nano modified filter material series used by the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as single output data of the deep neural network, and executing one training operation on the deep neural network to obtain the deep neural network which completes multiple training as an intelligent prediction model to be output;
the parameter selection device is connected with the model re-decomposition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the current wastewater treatment operation executed by the wastewater treatment main mechanism as each input data of the intelligent prediction model to operate the intelligent prediction model, and obtaining the nano modified filter material series output by the intelligent prediction model as the current selection series to be output;
wherein the number of times of performing training is monotonically and positively correlated with the single treatment water amount of the multi-stage nanofiltration tower;
for example, when the single-pass water amount of the multi-stage nanofiltration tower is 1000 liters, the model re-solution mechanism selects the deep neural network to perform training 500 times, when the single-pass water amount of the multi-stage nanofiltration tower is 3000 liters, the model re-solution mechanism selects the deep neural network to perform training 600 times, when the single-pass water amount of the multi-stage nanofiltration tower is 6000 liters, the model re-solution mechanism selects the deep neural network to perform training 700 times, and when the single-pass water amount of the multi-stage nanofiltration tower is 10000 liters, the model re-solution mechanism selects the deep neural network to perform training 800 times;
the multi-stage nanofiltration tower regulation and control system based on water quality detection can further comprise a power supply mechanism which is respectively connected with the sewage treatment main framework, the stage number setting mechanism, the signal acquisition mechanism, the model primary solution mechanism, the model secondary solution mechanism and the parameter selection equipment and is used for respectively providing power supply required by the sewage treatment main framework, the stage number setting mechanism, the signal acquisition mechanism, the model primary solution mechanism, the model secondary solution mechanism and the parameter selection equipment;
in the multi-stage nanofiltration tower regulation and control system based on water quality detection, a data temporary storage chip can be adopted to be respectively connected with the sewage treatment main framework, the stage number setting mechanism, the signal acquisition mechanism, the model primary solution mechanism, the model secondary solution mechanism and the parameter selection device, and is used for temporarily storing state data of the sewage treatment main framework, the stage number setting mechanism, the signal acquisition mechanism, the model primary solution mechanism, the model secondary solution mechanism and the parameter selection device.
Example 2
Fig. 3 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 2 of the present invention.
As shown in fig. 3, compared to embodiment 1 of the present invention, the multi-stage nanofiltration tower regulation system based on water quality detection further comprises:
the filter material pushing device is arranged in the tower body of the multistage nanofiltration tower, is connected with the series setting mechanism and is used for pushing the multistage nano modified filter material which is consistent with the series of the arranged nano modified filter material series into the tower body of the multistage nanofiltration tower according to the nano modified filter material series arranged by the series setting mechanism;
the filter material pushing device comprises a mechanical arm, a positioning unit and a microcontroller, wherein the microcontroller is respectively connected with the mechanical arm and the positioning unit and is used for configuring working parameters of the mechanical arm and the positioning unit, the positioning unit is used for determining the real-time position of each level of nano modified filter material in the multi-level nano modified filter material in the tower body of the multi-level nano filter tower, and the mechanical arm is used for pushing the multi-level nano modified filter material into the tower body of the multi-level nano filter tower.
Example 3
Fig. 4 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 3 of the present invention.
As shown in fig. 4, compared to embodiment 1 of the present invention, the multi-stage nanofiltration tower regulation system based on water quality detection further comprises:
the first temperature measuring device is buried in the pretreatment tank and is used for measuring the real-time water temperature of the sewage to be treated in the pretreatment tank;
the second temperature measuring device is buried in the post-treatment tank and is used for measuring the real-time water temperature of the water body after the filtering treatment in the post-treatment tank;
the first temperature measuring equipment and the second temperature measuring equipment are contact type temperature sensors, and the types of the contact type temperature sensors selected by the first temperature measuring equipment and the second temperature measuring equipment are the same.
Example 4
Fig. 5 is a schematic structural diagram of a multi-stage nanofiltration tower regulation and control system based on water quality detection according to embodiment 4 of the present invention.
As shown in fig. 5, compared to embodiment 3 of the present invention, the multi-stage nanofiltration tower regulation system based on water quality detection further comprises:
the state alarm device is respectively connected with the first temperature measurement device and the second temperature measurement device through a Bluetooth communication link and is used for sending a state alarm signal corresponding to the water temperature out-of-range when the real-time water temperature output by any one of the first temperature measurement device and the second temperature measurement device exceeds a set temperature threshold value;
the state alarm equipment can be selected as voice alarm equipment and is used for playing a voice alarm file corresponding to water temperature out-of-range when the real-time water temperature output by any one of the first temperature measurement equipment and the second temperature measurement equipment exceeds a set temperature threshold;
or the state alarm device can be selected as a photoelectric alarm device, and is used for executing photoelectric alarm operation corresponding to water temperature out-of-range when the real-time water temperature output by any one of the first temperature measurement device and the second temperature measurement device exceeds a set temperature threshold value;
the state alarm device may be selected as a photoelectric alarm device, and the performing a photoelectric alarm operation corresponding to a water temperature out-of-range when the real-time water temperature output by any one of the first temperature measurement device and the second temperature measurement device exceeds a set temperature threshold value includes: the photoelectric alarm equipment performs lamplight flickering by adopting preset frequency to execute photoelectric alarm operation corresponding to water temperature out-of-range;
the photoelectric alarm device performs light flashing by adopting preset frequency to execute photoelectric alarm operation corresponding to water temperature out-of-range, and the photoelectric alarm device comprises: the more the water temperature is beyond the limit, the faster the frequency of lamplight flickering is;
the state alarm device comprises a Bluetooth communication unit, a water temperature comparison unit and a signal trigger unit, wherein the water temperature comparison unit is respectively connected with the Bluetooth communication unit and the signal trigger unit;
the Bluetooth communication unit is used for receiving the real-time water temperature output by the first temperature measuring device and the real-time water temperature output by the second temperature measuring device;
the water temperature comparison unit is used for comparing the real-time water temperature output by any one of the first temperature measurement equipment and the second temperature measurement equipment with the set temperature threshold value in a numerical mode;
the signal triggering unit is used for determining whether to send out a state alarm signal corresponding to the water temperature out-of-range based on a numerical comparison result;
alternatively, a mobile communication unit or a WIFI communication unit may be used instead of the bluetooth communication unit.
In any of the above embodiments, optionally, in the multi-stage nanofiltration tower conditioning system based on water quality detection:
all levels of nano modified filter materials used currently in the multi-level nano filter tower are vertically arranged from top to bottom in the tower body of the multi-level nano filter tower, and the structures of all levels of nano modified filter materials are the same;
wherein, the nano modified filter materials of each level that is used currently in the multistage nanofiltration tower is arranged from top to bottom vertically in the tower body of the multistage nanofiltration tower and the structure of the nano modified filter materials of each level is the same and comprises: each level of nano modified filter material is a nano modified filter material filling filter plate with fixed thickness;
in the tower body of the multi-stage nanofiltration tower, the water body subjected to primary aeration and solid-liquid separation is sent to the uppermost-layer primary nano modified filter material, and the water body subjected to filtration treatment flows out from the lower part of the lowermost-layer primary nano modified filter material;
the multistage nanofiltration tower comprises a multistage nanofiltration tower body, wherein the multistage nanofiltration tower body is characterized in that the multistage nanofiltration tower body also comprises a flow measurement mechanism which is arranged above the uppermost one-stage nano modified filter material and is used for measuring the real-time flow of the water body subjected to primary aeration and solid-liquid separation.
In any of the above embodiments, optionally, in the multi-stage nanofiltration tower conditioning system based on water quality detection:
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action comprises the following steps: the ratio of the area of the central area to the total area of the wastewater is equal to a set ratio;
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action further comprises: the signal acquisition mechanism performs picture acquisition action on the wastewater, and judges that the wastewater is in a calm state when the standard deviation of each depth of field value corresponding to each pixel point of the reference wastewater picture is smaller than or equal to a set standard deviation threshold value;
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action further comprises: when the standard deviation of each depth of field value corresponding to each pixel point of the reference wastewater picture is larger than the set standard deviation threshold value, judging that the wastewater is in a non-calm state;
wherein the ratio of the area of the central area relative to the total area of the wastewater is equal to a set ratio comprising: the ratio of the area of the central zone to the total area of the wastewater is equal to one quarter, one eighth or one sixteenth;
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action further comprises: the shape of the central area is a set shape;
and the shape of the central region being a set shape comprising: the central region is circular, square or diamond in shape.
In any of the above embodiments, optionally, in the multi-stage nanofiltration tower conditioning system based on water quality detection:
the synchronous control device is respectively connected with the first pump body, the second pump body and the third pump body and is used for realizing synchronous control of the first pump body, the second pump body and the third pump body;
the microcontroller is respectively connected with the first pump body, the second pump body and the third pump body and is used for realizing real-time configuration of working parameters of the first pump body, the second pump body and the third pump body;
and the multistage nanofiltration tower regulation and control system based on water quality detection can further comprise timing operation equipment, which is used for being connected with the first pump body, the second pump body and the third pump body respectively and for providing timing signals required by the connection of the first pump body, the second pump body and the third pump body respectively.
Example 5
In the embodiment, the invention discloses a water quality detection-based multi-stage nanofiltration tower regulation and control method, which comprises the steps of using the water quality detection-based multi-stage nanofiltration tower regulation and control platform to introduce a specifically designed sewage treatment main framework so as to realize the selection operation of nano modified filter material series required by current sewage filtration according to the corresponding relation between the gray data of a sewage picture and the nano modified filter material series on the basis of a customized intelligent prediction model based on a deep neural network.
Example 6
Fig. 6 is a schematic diagram of a computer-readable storage medium shown in embodiment 6 of the present invention. As shown in fig. 6, a computer-readable storage medium 60 according to an embodiment of the present disclosure has stored thereon non-transitory computer-readable instructions 61. When the non-transitory computer readable instructions 61 are executed by the processor, all or part of the steps of the multi-stage nanofiltration tower conditioning method based on water quality testing of embodiment 5 of the invention described above are performed.
In addition, in the multi-stage nanofiltration tower regulation and control system based on water quality detection, taking each gray value of each pixel point of a reference wastewater picture corresponding to a certain sewage treatment main structure executing sewage treatment operation as each input data of a deep neural network, taking a nano modified filter material level used by the certain sewage treatment main structure executing sewage treatment operation as single output data of the deep neural network, so as to establish the deep neural network, wherein the method comprises the following steps: the number of each input data of the deep neural network is the product of the horizontal resolution and the vertical resolution in the fixed resolution of the reference wastewater picture.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (10)
1. A multi-stage nanofiltration tower regulation and control system based on water quality detection, the system comprising:
the sewage treatment main framework comprises synchronous control equipment, a microcontroller, a first pump body, a pretreatment tank, a second pump body, a multi-stage nanofiltration tower, a third pump body and a post-treatment tank, wherein the first pump body is used for conveying sewage to be treated to the pretreatment tank for primary aeration and solid-liquid separation, the second pump body is arranged between the pretreatment tank and the multi-stage nanofiltration tower and is used for conveying water subjected to primary aeration and solid-liquid separation to the inside of the multi-stage nanofiltration tower for filtration treatment, the third pump body is arranged between the multi-stage nanofiltration tower and the post-treatment tank and is used for conveying the water subjected to filtration treatment to the post-treatment tank for secondary aeration and sedimentation treatment so as to obtain output purified water, and the sewage to be treated is industrial sewage, landfill leachate or domestic sewage;
the series setting mechanism is connected with the multi-stage nanofiltration tower and is used for setting the number of the currently used nano modified filter material series in the multi-stage nanofiltration tower;
the signal acquisition mechanism is used for executing picture acquisition action on the central area of the wastewater in a calm state before the wastewater is sent into the pretreatment tank by the first pump body so as to obtain a reference wastewater picture with fixed resolution and definition;
the model initial solution mechanism is respectively connected with the series setting mechanism and the signal acquisition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the sewage treatment operation executed by the sewage treatment main mechanism at one time as each input data of the deep neural network and taking the nano modified filter material series used by the sewage treatment operation executed by the sewage treatment main mechanism at one time as single output data of the deep neural network so as to establish the deep neural network;
the model re-solving mechanism is connected with the model initial solving mechanism and is used for taking all gray values of all pixel points of a reference wastewater picture corresponding to the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as all input data of the deep neural network, taking the nano modified filter material series used by the wastewater treatment operation executed by the wastewater treatment main mechanism in the past as single output data of the deep neural network, and executing one training operation on the deep neural network to obtain the deep neural network which completes multiple training as an intelligent prediction model to be output;
the parameter selection device is connected with the model re-decomposition mechanism and is used for taking each gray value of each pixel point of a reference wastewater picture corresponding to the current wastewater treatment operation executed by the wastewater treatment main mechanism as each input data of the intelligent prediction model to operate the intelligent prediction model, and obtaining the nano modified filter material series output by the intelligent prediction model as the current selection series to be output;
wherein the number of times training is performed is monotonically and positively correlated with the single treatment water volume of the multi-stage nanofiltration tower.
2. The water quality detection-based multi-stage nanofiltration tower conditioning system of claim 1, wherein the system further comprises:
the filter material pushing device is arranged in the tower body of the multistage nanofiltration tower, is connected with the series setting mechanism and is used for pushing the multistage nano modified filter material which is consistent with the series of the arranged nano modified filter material series into the tower body of the multistage nanofiltration tower according to the nano modified filter material series arranged by the series setting mechanism.
3. The water quality detection-based multi-stage nanofiltration tower conditioning system of claim 1, wherein the system further comprises:
the first temperature measuring device is buried in the pretreatment tank and is used for measuring the real-time water temperature of the sewage to be treated in the pretreatment tank;
the second temperature measuring device is buried in the post-treatment tank and is used for measuring the real-time water temperature of the water body after the filtering treatment in the post-treatment tank.
4. The water quality detection-based multi-stage nanofiltration tower conditioning system as recited in claim 3, wherein the system further comprises:
the state alarm device is respectively connected with the first temperature measurement device and the second temperature measurement device through a Bluetooth communication link and is used for sending a state alarm signal corresponding to the water temperature out-of-range when the real-time water temperature output by any one of the first temperature measurement device and the second temperature measurement device exceeds a set temperature threshold value;
the state alarm device comprises a Bluetooth communication unit, a water temperature comparison unit and a signal trigger unit, wherein the water temperature comparison unit is respectively connected with the Bluetooth communication unit and the signal trigger unit;
the Bluetooth communication unit is used for receiving the real-time water temperature output by the first temperature measuring device and the real-time water temperature output by the second temperature measuring device;
the water temperature comparison unit is used for comparing the real-time water temperature output by any one of the first temperature measurement equipment and the second temperature measurement equipment with the set temperature threshold value in a numerical mode;
the signal triggering unit is used for determining whether to send out a state alarm signal corresponding to the water temperature out-of-range based on the numerical comparison result.
5. The water quality detection-based multi-stage nanofiltration tower conditioning system as recited in any one of claims 1-4, wherein:
all levels of nano modified filter materials used currently in the multi-level nano filter tower are vertically arranged from top to bottom in the tower body of the multi-level nano filter tower, and the structures of all levels of nano modified filter materials are the same;
wherein, the nano modified filter materials of each level that is used currently in the multistage nanofiltration tower is arranged from top to bottom vertically in the tower body of the multistage nanofiltration tower and the structure of the nano modified filter materials of each level is the same and comprises: each level of nano modified filter material is a nano modified filter material filling filter plate with fixed thickness;
in the tower body of the multi-stage nanofiltration tower, the water body subjected to primary aeration and solid-liquid separation is sent to the uppermost-layer primary nano modified filter material, and the water body subjected to filtration treatment flows out from the lower part of the lowermost-layer primary nano modified filter material.
6. The water quality detection-based multi-stage nanofiltration tower conditioning system as recited in any one of claims 1-4, wherein:
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action comprises the following steps: the ratio of the area of the central area to the total area of the wastewater is equal to a set ratio;
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action further comprises: the signal acquisition mechanism performs picture acquisition action on the wastewater, and judges that the wastewater is in a calm state when the standard deviation of each depth of field value corresponding to each pixel point of the reference wastewater picture is smaller than or equal to a set standard deviation threshold value;
before the wastewater is sent into the pretreatment tank by the first pump body, performing a picture collection action on a central area of the wastewater in a calm state to obtain a reference wastewater picture with fixed resolution and definition, wherein the picture collection action further comprises: and when the standard deviation of each depth of field value corresponding to each pixel point of the reference wastewater picture is larger than the set standard deviation threshold value, judging that the wastewater is in a non-calm state.
7. The water quality detection-based multi-stage nanofiltration tower conditioning system as recited in claim 6, wherein:
the ratio of the area of the central area relative to the total area of the wastewater is equal to a set ratio comprising: the ratio of the area of the central zone to the total area of the wastewater is equal to one quarter, one eighth or one sixteenth.
8. The water quality detection-based multi-stage nanofiltration tower conditioning system as recited in any one of claims 1-4, wherein:
the synchronous control device is respectively connected with the first pump body, the second pump body and the third pump body and is used for realizing synchronous control of the first pump body, the second pump body and the third pump body;
the microcontroller is respectively connected with the first pump body, the second pump body and the third pump body and is used for realizing real-time configuration of working parameters of the first pump body, the second pump body and the third pump body.
9. A multi-stage nanofiltration tower regulation and control method based on water quality detection, the method comprising using the multi-stage nanofiltration tower regulation and control platform based on water quality detection as claimed in any one of claims 1-8 to introduce a targeted designed sewage treatment main architecture so as to realize the selection operation of nano modified filter material series required by current sewage filtration according to the corresponding relation between the gray data of a sewage picture and the nano modified filter material series on the basis of a customized intelligent prediction model based on a deep neural network.
10. A computer readable storage medium, characterized in that the readable storage medium has stored thereon a computer program which, when executed, implements the steps of the method according to claim 9.
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