CN116062945B - Coal chemical industry energy-saving data prediction system based on neural network - Google Patents
Coal chemical industry energy-saving data prediction system based on neural network Download PDFInfo
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Abstract
The invention relates to a coal chemical industry energy-saving data prediction system based on a neural network, which comprises the following steps: the automatic water supplementing device is used for automatically supplementing purified water bodies with the volume equal to the timing water supplementing difference into the coal chemical industry circulating cooling water mechanism through an automatic operation mode based on the received timing water supplementing difference of the next time interval when the next time interval arrives; and the numerical analysis device is connected with the automatic water supplementing device and is used for predicting the volume of sewage of the coal chemical industry circulating cooling water mechanism and the volume of the second-stage purified water body in the next time interval based on the water purification parameters corresponding to each time interval. The coal chemical industry energy-saving data prediction system based on the neural network is compact in structure and wide in application. The water volume of the water replenishing and recycling in the next time interval can be predicted according to the water volume of the actual water replenishing and recycling in the previous time intervals, so that key information is provided for executing automatic water replenishing operation based on the differential water volume.
Description
Technical Field
The invention relates to the field of circulating water treatment, in particular to a coal chemical industry energy-saving data prediction system based on a neural network.
Background
The coal chemical industry is a process of using coal as raw material, converting the coal into gas, liquid and solid products or semi-products through chemical processing, and then further processing into chemical industry and energy products, and mainly comprises gasification, liquefaction and carbonization of the coal, tar processing, calcium carbide acetylene chemical industry and the like. With the continuous reduction of world petroleum resources, the coal chemical industry has wide prospect.
Among the production technologies available in the coal industry, coking is the earliest process used and has so far remained an important component of the chemical industry. The gasification of coal plays an important role in coal chemical industry, is used for producing various gas fuels, is a clean energy source, and is beneficial to improving the living standard of people and protecting the environment; the synthetic gas produced by coal gasification is the raw material of various products such as synthetic liquid fuel, chemical raw material and the like. The direct coal liquefaction, namely the high-pressure hydrogenation liquefaction of coal, can produce artificial petroleum and chemical products. In the event of a shortage of oil, the liquefied products of coal will replace natural oil.
As auxiliary materials, coolant and cleaning agent for executing the coal chemical industry, the circulating water is an important material used by various coal chemical industry processing institutions, and is used in a large amount in each use period, if the used sewage is directly discarded, the environment is polluted, and precious water resources are wasted. Therefore, a mode of purification and recovery is generally adopted to perform multi-layer purification operation on a large amount of sewage discharged from the coal chemical industry so as to obtain a part of recoverable water body, and the residual insufficient water quantity is complemented by adopting a manual mode, however, the sewage discharge quantity, the residual water quantity after purification and the variability of various purification parameters in different use periods make the water supplementing quantity in the subsequent use period difficult to predict, and further reduce the instantaneity and the effectiveness of the water supplementing operation.
In the aspect of energy conservation and environmental protection, although enterprises also propose own design schemes, for example:
1. the invention discloses: low-carbon energy-saving water-saving car washing system
Application publication number: CN113442879A
Application publication date: 2021.09.28
Application number: 2021108899699
Filing date: 2021.08.04
Applicants: new energy Co., ltd
The invention aims to solve the technical problems of low-carbon, energy-saving and water-saving car washing, namely, the car washing is carried out by utilizing solar energy to provide warm water, the car washing is carried out by utilizing reclaimed water under the condition of drinking water, the comprehensive recycling of water is realized, and the energy is saved, and the car washing device comprises a solar water tank, a solar heat collector, a water mixing valve, a water purifier, a reclaimed water tank, a car washer, a sewage tank and a sewage purification and recovery system; the solar heat collector is circularly communicated with the solar water tank through a medium circulating pump and a medium pipeline, a reclaimed water outlet of the water purifier is communicated with the reclaimed water tank through a pipeline, one part of the reclaimed water outlet of the reclaimed water tank enters a water inlet of a water mixing valve through a pipeline, the other part of the reclaimed water outlet of the reclaimed water tank enters the solar water tank, and a hot water pipe of the solar water tank is communicated with the water inlet of the water mixing valve; the water outlet of the water mixing valve is communicated with the car washer, sewage of the car washer flows into the sewage pool through the grille, and the sewage pool is communicated with the sewage purifying and recycling system.
2. The invention discloses: sewage multistage purification split-flow type recycling equipment
Application publication number: CN106495387A
Application publication date: 2017.03.15
Application number: 2016110841089
Filing date: 2016.11.30
Applicants: intelligent and environment protection technology limited company in bergamot
The invention aims to solve the technical problems of recycling sewage in a multi-stage purification and split-flow mode, and achieves the effect of primary stirring, precipitation and filtration on dregs in domestic sewage through the arrangement of a driving motor and a driving stirring sheet.
3. The invention discloses: sewage purification recovery system
Application publication number: CN105152377A
Application publication date: 2015.12.16
Application number: 2015105749745
Filing date: 2015.09.10
Applicants: shenhua group Limited liability company
The invention aims to solve the technical problems of reducing sewage discharge and sewage pollution degree, and comprises the following steps: the first reverse osmosis subsystem comprises a first water inlet tank, a first precipitation filtering part and a first reverse osmosis device which are sequentially communicated, wherein the first reverse osmosis device is provided with a first water conveying port and a first concentrated solution discharge port; the sewage purification recovery system further comprises: the second reverse osmosis subsystem comprises a second water inlet tank, a second precipitation filtering part and a second reverse osmosis device which are sequentially communicated, and a water inlet of the second water inlet tank is communicated with the first concentrated solution discharge port; wherein the second sediment filter part includes: the water inlet of the filtering tank is communicated with the water outlet of the second water inlet tank, and the water outlet of the filtering tank is communicated with the water inlet of the second reverse osmosis device.
In view of the prior art disclosed in the prior art, no solution is provided for solving the problem of accurate prediction of various parameters in the recycling process of the circulating water.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides a coal chemical industry energy-saving data prediction system based on a neural network, which can predict the water volume of water replenishing and recycling in the next time interval according to the water volume of actual water replenishing and recycling in each previous time interval, and adopts an automatic water replenishing device to automatically replenish purified water with the same volume as the water volume of water replenishing and recycling into a coal chemical industry circulating cooling water mechanism through an automatic operation mode when the water volume of water replenishing and recycling in the next time interval arrives according to the predicted water volume of water replenishing and recycling in the next time interval, so that the numerical value time-sharing quantitative balance of the water volume of circulating cooling water used by the coal chemical industry circulating cooling water mechanism in the next time interval is maintained together with the water body of the circulating cooling water mechanism of backwater to the coal chemical industry after sewage in the next time interval, and the performance stability of the coal chemical industry circulating cooling water mechanism is effectively maintained.
The system may include:
the sedimentation filter device is used for sequentially performing flocculation sedimentation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and conveying the first-stage purified water body to the ion removal device through a first water supply transmission pipeline;
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage;
a first water supply transmission pipe provided between the precipitation filtration device and the ion removal device;
the second water supply transmission pipeline is arranged between the ion removing device and the coal chemical industry circulating cooling water mechanism;
the automatic water supplementing device is used for automatically supplementing purified water with the same volume as the timing water supplementing differential through an automatic operation mode to the coal chemical industry circulating cooling water mechanism based on the received timing water supplementing differential of the next time interval when the next time interval arrives, so that the numerical value of the water volume of circulating cooling water used by the coal chemical industry circulating cooling water mechanism in the next time interval is fixed together with the water from the ion removing device to the coal chemical industry circulating cooling water mechanism through the second water supply transmission pipeline;
the numerical analysis device is connected with the automatic water supplementing device and is used for predicting the volume of sewage of the coal chemical industry circulating cooling water mechanism in the next time interval and the volume of the second-stage purified water body in the next time interval by adopting a deep neural network based on all water body purification parameters respectively corresponding to all past time intervals;
the deep neural network comprises a single-layer input layer, a single-layer output layer and a plurality of hidden layers, wherein the plurality of hidden layers are arranged between the single-layer input layer and the single-layer output layer, and the number of the plurality of hidden layers is positively associated with the duration of any time interval;
the depth neural network is trained for a fixed number of times, and the fixed number of values is in direct proportion to the average value of the pipe diameters of the first water supply transmission pipeline and the second water supply transmission pipeline;
the difference identification equipment is respectively connected with the automatic water supplementing device and the numerical analysis equipment and is used for subtracting the volume of the second-stage purified water body in the next time interval from the volume of the sewage of the coal chemical industry circulating cooling water mechanism in the next time interval to obtain a manual water supplementing numerical value in the next time interval and sending the manual water supplementing numerical value to the automatic water supplementing device as a timing water supplementing difference in the next time interval;
wherein, adopt the volume of the blowdown water of coal industry recirculated cooling water mechanism in the time interval of degree of depth neural network prediction and the volume of the second grade purified water in the time interval of next down based on each water purification parameter that each time interval corresponds respectively in the past includes: the time length of each time interval is equal, and the water purification parameters corresponding to each time interval are the volume of sewage of the coal chemical industry circulating cooling water mechanism in the time interval, the volume of the first-stage purified water in the time interval, the volume of the second-stage purified water in the time interval, the timing duration of executing flocculation precipitation treatment in the time interval and the membrane quantity of nanofiltration membranes adopted in the time interval.
The coal chemical industry energy-saving data prediction system based on the neural network is compact in structure and wide in application. The water volume of the water replenishing and recycling in the next time interval can be predicted according to the water volume of the actual water replenishing and recycling in the previous time intervals, so that key information is provided for executing automatic water replenishing operation based on the differential water volume.
Drawings
Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic structural diagram of a coal chemical industry energy-saving data prediction system based on a neural network according to an embodiment of the present invention.
Detailed Description
Embodiments of the neural network-based coal chemical industry energy saving data prediction system of the present invention will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic structural diagram of a neural network-based coal chemical industry energy saving data prediction system according to an embodiment of the present invention, the system including:
the sedimentation filter device is used for sequentially performing flocculation sedimentation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and conveying the first-stage purified water body to the ion removal device through a first water supply transmission pipeline;
for example, the flocculation precipitation treatment and the nanofiltration membrane-based filtration treatment may be sequentially performed on the sewage of the coal chemical industry circulating cooling water mechanism by adopting a time-sharing treatment mode, that is, the flocculation precipitation treatment is performed on the sewage of the coal chemical industry circulating cooling water mechanism when the first timing signal arrives, and the nanofiltration membrane-based filtration treatment is performed on the sewage after the flocculation precipitation treatment is completed when the second timing signal arrives;
wherein, the first timing signal is earlier than the second timing signal, and the interval between the first timing signal and the second timing signal sets the duration;
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage;
a first water supply transmission pipe provided between the precipitation filtration device and the ion removal device;
illustratively, the pipe bodies of the first water supply transmission pipeline and the subsequent second water supply transmission pipeline are cast by 304 stainless steel materials;
the second water supply transmission pipeline is arranged between the ion removing device and the coal chemical industry circulating cooling water mechanism;
the automatic water supplementing device is used for automatically supplementing purified water with the same volume as the timing water supplementing differential through an automatic operation mode to the coal chemical industry circulating cooling water mechanism based on the received timing water supplementing differential of the next time interval when the next time interval arrives, so that the numerical value of the water volume of circulating cooling water used by the coal chemical industry circulating cooling water mechanism in the next time interval is fixed together with the water from the ion removing device to the coal chemical industry circulating cooling water mechanism through the second water supply transmission pipeline;
illustratively, the automatic water replenishing device is internally provided with a water replenishing pump body and a flow analysis device, and the flow analysis device is connected with the water replenishing pump body so as to complete automatic water replenishing operation;
the numerical analysis device is connected with the automatic water supplementing device and is used for predicting the volume of sewage of the coal chemical industry circulating cooling water mechanism in the next time interval and the volume of the second-stage purified water body in the next time interval by adopting a deep neural network based on all water body purification parameters respectively corresponding to all past time intervals;
the difference identification equipment is respectively connected with the automatic water supplementing device and the numerical analysis equipment and is used for subtracting the volume of the second-stage purified water body in the next time interval from the volume of the sewage of the coal chemical industry circulating cooling water mechanism in the next time interval to obtain a manual water supplementing numerical value in the next time interval and sending the manual water supplementing numerical value to the automatic water supplementing device as a timing water supplementing difference in the next time interval;
wherein, adopt the volume of the blowdown water of coal industry recirculated cooling water mechanism in the time interval of degree of depth neural network prediction and the volume of the second grade purified water in the time interval of next down based on each water purification parameter that each time interval corresponds respectively in the past includes: the time length of each time interval is equal, and the water purification parameters corresponding to each time interval are the volume of sewage of the coal chemical industry circulating cooling water mechanism in the time interval, the volume of the first-stage purified water in the time interval, the volume of the second-stage purified water in the time interval, the timing duration of executing flocculation precipitation treatment in the time interval and the membrane quantity of nanofiltration membranes adopted in the time interval.
Next, a specific structure of the neural network-based coal chemical industry energy-saving data prediction system of the present invention will be further described.
In a neural network-based coal chemical industry energy saving data prediction system according to various embodiments of the present invention:
predicting the volume of sewage of the coal chemical industry circulating cooling water mechanism in the next time interval and the volume of the second-stage purified water body in the next time interval by adopting a deep neural network based on the water body purification parameters respectively corresponding to the previous time intervals comprises: the deep neural network comprises a single-layer input layer, a single-layer output layer and a plurality of hidden layers, wherein the hidden layers are arranged between the single-layer input layer and the single-layer output layer;
wherein, adopt the volume of the blowdown water of coal industry recirculated cooling water mechanism in the time interval of degree of depth neural network prediction and the volume of the second grade purified water in the time interval of next down based on each water purification parameter that each time interval corresponds respectively in the past includes: the number of hidden layers is positively correlated with the duration of any time interval.
In a neural network-based coal chemical industry energy saving data prediction system according to various embodiments of the present invention:
the sedimentation filter device is used for sequentially performing flocculation precipitation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and the first-stage purified water body is conveyed to the ion removal device through a first water supply transmission pipeline and comprises: the sedimentation filter device comprises a first purification unit and a second purification unit, wherein the first purification unit is used for sequentially performing flocculation sedimentation treatment on the sewage of the coal chemical industry circulating cooling water mechanism;
wherein, precipitate the filter equipment for carry out flocculation and precipitation to the sewage of coal industry recirculated cooling water mechanism in proper order and carry out flocculation and precipitation and based on the filtration treatment of nanofiltration membrane, in order to obtain first level purified water body, and will first level purified water body is through first water supply transmission pipeline transport to ion removal device still includes: the precipitation filter device comprises a second purification unit which is connected with the first purification unit and is used for performing nanofiltration membrane-based filtration treatment on the water body after flocculation precipitation treatment so as to obtain a first-stage purified water body.
In a neural network-based coal chemical industry energy saving data prediction system according to various embodiments of the present invention:
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage, and the second-stage purified water body comprises: the ion removing device comprises a first removing unit and a second removing unit, wherein the first removing unit is used for performing calcium and magnesium ion removing treatment on the first-stage purified water body;
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning water of the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage, and the ion removing device further comprises: the ion removing device comprises a second removing unit which is connected with the first removing unit and is used for performing heavy metal ion removing treatment on the water body with calcium and magnesium ion removing treatment to obtain a second-stage purified water body.
And in a neural network-based coal chemical industry energy saving data prediction system according to various embodiments of the present invention:
the sedimentation filter device is used for sequentially performing flocculation precipitation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and the first-stage purified water body is conveyed to the ion removal device through a first water supply transmission pipeline and comprises: and the sewage of the coal chemical industry circulating cooling water mechanism is conveyed to the precipitation filter device by the coal chemical industry circulating cooling water mechanism through a third water supply transmission pipeline.
In addition, in the coal chemical industry energy-saving data prediction system based on the neural network, predicting the volume of the sewage of the coal chemical industry circulating cooling water mechanism in the next time interval and the volume of the second-stage purified water body in the next time interval by adopting the deep neural network based on each water body purification parameter respectively corresponding to each time interval in the past comprises: the deep neural network is trained for a fixed number of times, and the fixed number of values is in direct proportion to the average value of the pipe diameters of the first water supply transmission pipeline and the second water supply transmission pipeline.
According to the embodiment of the invention, the remarkable essential characteristics of the invention are as follows:
(1) Aiming at the same coal chemical industry circulating cooling water mechanism, in order to keep the water volume of each time interval stable, the purified water body which needs to complement the difference volume between the sewage water volume and the recovered water volume in the next time interval is predicted based on the sewage water volume, the recovered water volume and various purification parameters of the past time intervals, so that the stable working performance of the coal chemical industry circulating cooling water mechanism is ensured;
(2) The method comprises the steps that a deep neural network is adopted to specifically execute prediction processing, the deep neural network comprises a single-layer input layer, a single-layer output layer and a plurality of hidden layers, the plurality of hidden layers are arranged between the single-layer input layer and the single-layer output layer, and the number of the plurality of hidden layers is positively correlated with the duration of a time interval;
(3) The deep neural network is trained after a fixed number of times, and the fixed number of values is in direct proportion to the average value of the pipe diameters of the first water supply transmission pipeline and the second water supply transmission pipeline, so that the effectiveness of the deep neural network for executing prediction is guaranteed.
In the above, although the present disclosure discusses embodiments of the present invention and the accompanying drawings, the present invention is not limited thereto but may be variously modified and changed by those skilled in the art to which the present disclosure pertains without departing from the spirit and scope of the present disclosure as claimed in the appended claims.
Claims (5)
1. A neural network-based coal chemical industry energy saving data prediction system, the system comprising:
the sedimentation filter device is used for sequentially performing flocculation sedimentation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and conveying the first-stage purified water body to the ion removal device through a first water supply transmission pipeline;
the sedimentation filter device comprises a first purification unit and a second purification unit, wherein the first purification unit is used for sequentially performing flocculation sedimentation treatment on the sewage of the coal chemical industry circulating cooling water mechanism;
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage;
a first water supply transmission pipe provided between the precipitation filtration device and the ion removal device;
the second water supply transmission pipeline is arranged between the ion removing device and the coal chemical industry circulating cooling water mechanism;
the automatic water supplementing device is used for automatically supplementing purified water with the same volume as the timing water supplementing differential through an automatic operation mode to the coal chemical industry circulating cooling water mechanism based on the received timing water supplementing differential of the next time interval when the next time interval arrives, so that the numerical value of the water volume of circulating cooling water used by the coal chemical industry circulating cooling water mechanism in the next time interval is fixed together with the water from the ion removing device to the coal chemical industry circulating cooling water mechanism through the second water supply transmission pipeline;
the numerical analysis device is connected with the automatic water supplementing device and is used for predicting the volume of sewage of the coal chemical industry circulating cooling water mechanism in the next time interval and the volume of the second-stage purified water body in the next time interval by adopting a deep neural network based on all water body purification parameters respectively corresponding to all past time intervals;
the deep neural network comprises a single-layer input layer, a single-layer output layer and a plurality of hidden layers, wherein the plurality of hidden layers are arranged between the single-layer input layer and the single-layer output layer, and the number of the plurality of hidden layers is positively associated with the duration of any time interval;
the depth neural network is trained for a fixed number of times, and the fixed number of values is in direct proportion to the average value of the pipe diameters of the first water supply transmission pipeline and the second water supply transmission pipeline;
the difference identification equipment is respectively connected with the automatic water supplementing device and the numerical analysis equipment and is used for subtracting the volume of the second-stage purified water body in the next time interval from the volume of the sewage of the coal chemical industry circulating cooling water mechanism in the next time interval to obtain a manual water supplementing numerical value in the next time interval and sending the manual water supplementing numerical value to the automatic water supplementing device as a timing water supplementing difference in the next time interval;
wherein, adopt the volume of the blowdown water of coal industry recirculated cooling water mechanism in the time interval of degree of depth neural network prediction and the volume of the second grade purified water in the time interval of next down based on each water purification parameter that each time interval corresponds respectively in the past includes: the time length of each time interval is equal, and the water purification parameters corresponding to each time interval are the volume of sewage of the coal chemical industry circulating cooling water mechanism in the time interval, the volume of the first-stage purified water in the time interval, the volume of the second-stage purified water in the time interval, the timing duration of executing flocculation precipitation treatment in the time interval and the membrane quantity of nanofiltration membranes adopted in the time interval.
2. The neural network-based coal chemical industry energy saving data prediction system according to claim 1, wherein:
the sedimentation filter device is used for sequentially performing flocculation sedimentation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and the first-stage purified water body is conveyed to the ion removal device through a first water supply transmission pipeline and further comprises: the precipitation filter device comprises a second purification unit which is connected with the first purification unit and is used for performing nanofiltration membrane-based filtration treatment on the water body after flocculation precipitation treatment so as to obtain a first-stage purified water body.
3. The neural network-based coal chemical industry energy saving data prediction system according to claim 1, wherein:
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage, and the second-stage purified water body comprises: the ion removing device comprises a first removing unit for performing calcium and magnesium ion removing treatment on the first-stage purified water body.
4. The neural network-based coal chemical industry energy saving data prediction system according to claim 3, wherein:
the ion removing device is used for sequentially performing calcium and magnesium ion removal treatment and heavy metal ion removal treatment on the first-stage purified water body to obtain a second-stage purified water body, and returning the second-stage purified water body to the coal chemical industry circulating cooling water mechanism through a second water supply transmission pipeline to be used as circulating water, wherein the volume of the second-stage purified water body is smaller than that of the sewage, and the ion removing device further comprises: the ion removing device comprises a second removing unit which is connected with the first removing unit and is used for performing heavy metal ion removing treatment on the water body with calcium and magnesium ion removing treatment to obtain a second-stage purified water body.
5. The neural network-based coal chemical industry energy saving data prediction system according to claim 1, wherein:
the sedimentation filter device is used for sequentially performing flocculation precipitation treatment and nanofiltration membrane-based filtration treatment on the sewage of the coal chemical industry circulating cooling water mechanism so as to obtain a first-stage purified water body, and the first-stage purified water body is conveyed to the ion removal device through a first water supply transmission pipeline and comprises: and the sewage of the coal chemical industry circulating cooling water mechanism is conveyed to the precipitation filter device by the coal chemical industry circulating cooling water mechanism through a third water supply transmission pipeline.
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| Application Number | Priority Date | Filing Date | Title |
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| CN108675466A (en) * | 2018-04-23 | 2018-10-19 | 天津大学 | A kind of preprocess method preventing fouling membrane in coal chemical industry recirculated water reuse |
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| CN108675466A (en) * | 2018-04-23 | 2018-10-19 | 天津大学 | A kind of preprocess method preventing fouling membrane in coal chemical industry recirculated water reuse |
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