阅读说明：本技术 多元废液/固废水煤浆多通道联合气化喷嘴智能控制系统 (Multi-waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle intelligent control system ) 是由 柳菁 杨志建 章磊 章晓飞 李亚平 虞晓东 何啸 于 2021-09-16 设计创作，主要内容包括：本发明涉及水煤浆气化喷嘴智能控制系统,旨在提供一种多元废液/固废水煤浆多通道联合气化喷嘴智能控制系统。包括：有机废水流量控制回路、内环氧流量控制回路、废水/清水水煤浆流量控制回路、有机固废水煤浆流量控制回路和外环氧流量控制回路；各控制回路中,进料泵或风机的出口分别通过管路连接至多元废液/固废水煤浆多通道联合气化喷嘴,在所述管路上分别设有流量计。本发明能实现多种废弃物的可控高校协同回收利用；根据几种废弃物及水煤浆的气化特性,通过神经网络预测及筛选符合生产指标的流量配比方案,从而实现智能调节进料量以保证气化装置满足不同生产工况下的需求；可进一步提高资源回收利用率,改造安装成本低,经济环保效益高。(The invention relates to an intelligent control system for a coal water slurry gasification nozzle, and aims to provide an intelligent control system for a multi-element waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle. The method comprises the following steps: an organic wastewater flow control loop, an inner epoxy flow control loop, a wastewater/clear water coal water slurry flow control loop, an organic solid waste coal water slurry flow control loop and an outer epoxy flow control loop; in each control loop, the outlet of the feed pump or the fan is respectively connected to a multi-element waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle through a pipeline, and the pipelines are respectively provided with a flowmeter. The invention can realize the controllable college cooperative recycling of various wastes; according to the gasification characteristics of several wastes and coal water slurry, a flow rate proportioning scheme meeting production indexes is predicted and screened through a neural network, so that the intelligent adjustment of the feeding amount is realized to ensure that the gasification device meets the requirements under different production working conditions; the resource recycling rate can be further improved, the modification and installation cost is low, and the economic and environmental-friendly benefits are high.)

1. The utility model provides a many first waste liquid/useless coal slurry multichannel unites gasification nozzle intelligence control system admittedly which characterized in that includes: an organic wastewater flow control loop (10), an inner epoxy flow control loop (20), a wastewater/clean water coal water slurry flow control loop (30), an organic solid waste coal water slurry flow control loop (40) and an outer epoxy flow control loop (50); in each control loop, the outlet of a feed pump or a fan is respectively connected to a multi-element waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle (70) through a pipeline, and a flowmeter is respectively arranged on the pipeline;

wherein, the organic wastewater flow control loop (10), the wastewater/clean water coal water slurry flow control loop (30) and the organic solid waste coal water slurry flow control loop (40) are all provided with a rotating speed regulator and a flow regulator, each feeding pump is respectively connected with the rotating speed regulator and the flow regulator in turn through signal lines, and each flow regulator is connected with a flowmeter through signal lines; flow regulating valves and flow regulators are arranged on pipelines in the inner epoxy flow control loop (20) and the outer epoxy flow control loop (50), each flow regulating valve is connected with each flow regulator through a signal line, and each flow regulator is connected with a flowmeter through a signal line; the flow regulators in each flow control loop are respectively connected to a computer neural network predictive control system (60) through signal lines.

2. The system of claim 1, wherein the computer neural network predictive control system (60) comprises:

the combined gasification nozzle multi-channel flow inquiry module (100) is used for receiving flow signals transmitted by each flow control loop and displaying all flow data in the system;

a combined gasification nozzle multi-channel flow ratio optimizing module (200) which is used for optimizing and determining the material flow of each channel according to the input actual production target of the project and determining the flow ratio scheme of each channel;

a combined gasification nozzle multi-channel flow regulation module (300); the module is used for transmitting flow adjusting signals to each flow control loop according to a flow proportioning scheme given by the combined gasification nozzle multi-channel flow proportioning optimizing module, and adjusting the flow of each material to a specific proportion.

3. The system according to claim 2, characterized in that said joint gasification nozzle multi-channel flow query module (100) comprises in particular:

the multi-channel material type database unit (101) is used for inputting and storing material type data information of a fuel channel of the gasification nozzle, wherein the material type data information comprises an organic wastewater type, a wastewater/clear water coal water slurry type and an organic solid waste coal water slurry type;

the multi-channel flow database unit (102) is used for receiving and storing flow data information of each channel of the gasification nozzle, and comprises organic wastewater flow data information, inner epoxy flow data information, wastewater/clear water coal water slurry flow data information, organic solid waste coal water slurry flow data information and outer epoxy flow data information which are transmitted by each flow control loop;

a gasification index database unit (103) for inputting and storing gasification index data information of the gasification furnace under the condition that the material types and the flow rates of all channels of the gasification nozzle are fixed, wherein the gasification index data information comprises gasification reaction temperature, synthesis gas flow rate and effective gas content;

and the data information display unit (104) is used for matching, displaying and exporting the data information of the material types and the flow rates of all the channels of the gasification nozzle and corresponding gasification indexes, the data information of the material types and the flow rates comprises the types and the flow rates of organic wastewater, inner epoxy flow rates, the types and the flow rates of wastewater/clean water coal water slurry, the types and the flow rates of organic solid waste coal water slurry and outer ring oxygen flow rates, and the data information of the gasification indexes comprises gasification reaction temperature, synthesis gas flow rate and synthesis gas components corresponding to the types and the flow rates of the materials.

4. The system of claim 2, wherein the joint gasification nozzle multi-channel flow proportioning optimization module (200) specifically comprises:

the system comprises a multichannel flow ratio optimizing presetting unit (201) and a data processing unit, wherein the multichannel flow ratio optimizing presetting unit is used for calling data information of a multichannel material type database unit (101) and a gasification index database unit (103) and selecting material types adopted by each channel and gasification indexes required to be achieved;

the multi-channel flow ratio optimizing calculation unit (202) is used for calculating the optimal ratio of the flow of each channel, calling data information provided by the combined gasification nozzle multi-channel flow query module (100), carrying out neural network training on the material type and flow data information of each channel and corresponding gasification index data information, carrying out ratio optimizing calculation according to the material type adopted by each channel selected by the multi-channel flow ratio optimizing presetting unit (201) and the gasification index required to be achieved, and outputting an optimal ratio scheme.

5. The system according to claim 2, characterized in that said combined gasification nozzle multi-channel flow regulation module (300) comprises in particular:

multichannel flow ratio signal conversion unit (301): the unit is used for receiving the flow proportioning scheme of each channel output by the multi-channel flow proportioning optimizing module (200) of the combined gasification nozzle or receiving the manually input flow proportioning scheme of each channel, converting the flow proportioning scheme into a flow adjusting signal of each channel control loop, and displaying and storing the flow adjusting signal;

a multi-channel flow proportioning signal output unit (302): the unit is used for transmitting each channel flow adjusting signal output by the multi-channel flow proportioning signal conversion unit (301) to a flow regulator in each flow control loop, and regulating the flow of organic wastewater, the flow of inner epoxy, the flow of wastewater/clean water coal water slurry, the flow of organic solid waste coal water slurry and the flow of outer epoxy to a specific proportion.

6. The multi-waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle intelligent control method based on the system of claim 1 is characterized by comprising the following steps:

a. inputting material type information into a multi-channel flow ratio optimizing presetting unit (201);

b. gasification index information required by production is input into a multi-channel flow ratio optimization preset unit (201);

c. the multichannel flow ratio optimizing presetting unit (201) calls complete data information of corresponding types in the multichannel flow database unit (102) and the gasification index database unit (103) according to the determined material type information;

d. the multi-channel flow ratio optimizing calculation unit (202) calls complete data information of specific material types in the multi-channel flow ratio optimizing preset unit (201) to conduct neural network training; the input of the neural network comprises organic wastewater flow, inner epoxy flow, wastewater/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow, and the output of the neural network comprises gasification reaction temperature, synthesis gas flow and effective gas content; optimizing weight parameters of the neural network by adopting a particle swarm algorithm, starting training, and finishing the training when set iteration times or accuracy are reached;

e. the multi-channel flow ratio optimizing calculation unit (202) calls a trained neural network to perform enumeration method prediction according to input gasification index information; when the gasification index output by the neural network and the input gasification index meet the error requirement, the prediction is stopped;

f. the multi-channel flow ratio optimizing calculation unit (202) outputs prediction data of the flow of each channel when the gasification index required by production is reached.

7. The method according to claim 6, wherein in the step a, the material type information specifically includes: organic wastewater type, wastewater/clear water coal water slurry type, and organic solid waste coal water slurry type.

8. The method according to claim 6, wherein in the step b, the gasification index information specifically includes: gasification reaction temperature, synthesis gas flow rate and effective gas content.

9. The method according to claim 6, wherein in the step c, the set of data information specifically includes: the flow rate of the specific organic wastewater, the flow rate of the internal epoxy, the flow rate of the specific wastewater/clear water coal water slurry, the flow rate of the specific organic solid waste coal water slurry, the flow rate of the external epoxy and gasification indexes corresponding to each working condition under a plurality of working conditions.

10. The method according to claim 6, wherein in step f, the prediction data of each channel flow specifically includes: comprises organic waste water flow, inner epoxy flow, waste water/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow.

Technical Field

The invention relates to an intelligent control system for a coal water slurry gasification nozzle, in particular to an intelligent regulation and control system for the material flow of each channel of a multi-channel combined gasification nozzle for organic wastewater, wastewater/clear water coal water slurry and organic solid waste coal water slurry.

Background

With the rapid development of economy and society, new requirements on ecological environment protection are provided, and under the new background of carbon neutralization goal, the effective utilization of energy resources and the reduction of pollutant emission become important tongs for realizing beautiful Chinese construction. The industrial wastewater contains a large amount of phenols, ammonia nitrogen, tar, cyanides, polycyclic aromatic hydrocarbons, oxygen-containing polycyclic and heterocyclic compounds and other various refractory toxic and harmful substances, and if the treatment is not proper, the environment is seriously polluted, while the organic solid wastes such as household garbage, sludge, waste plastic, industrial leather, medicine dregs and the like have large annual output and contain a large amount of combustible components, so that the energy utilization potential is very large. The traditional wastewater and solid waste treatment mode has the problems of high cost, low efficiency, secondary pollution and the like, so that the seeking of the wastewater and solid waste treatment process with good treatment effect, stronger process stability and higher recycling efficiency is a necessary way for realizing a long-range goal.

The coal water slurry technology is a petroleum fuel substitution technology developed in the 70 th of the 20 th century and is an important component of clean coal technology. The coal water slurry is coal water solid-liquid two-phase slurry fluid formed by ore grinding and strong stirring 60-70% of coal powder, 30-40% of water and less than 1% of additives, and is called liquid coal product. The application field of the coal water slurry covers a plurality of aspects of electric power, chemical industry, metallurgy, building materials, light industry and the like, and at present, China becomes the country with the largest coal water slurry productivity, the widest application industry and the most advanced technology in the world. In recent years, with the development of a technology for preparing coal water slurry from wastewater/solid waste, raw materials for producing the coal water slurry are not limited to clean water and coal, but also industrial wastewater and organic solid waste which are complex in components and difficult to dispose can be utilized, and simple and efficient waste treatment and reutilization can be realized while energy is prepared.

The coal water slurry gasification technology is adopted to cooperatively treat the waste water and the organic solid waste, and the waste in various forms such as dry, wet, homogeneous, heterogeneous and the like can be treated simultaneously to form homogeneous slurry fuel which is beneficial to thermal conversion treatment. In addition, the main components of the waste can be converted into resources such as synthesis gas and the like for utilization in the gasification process, and the added value is high; in the treatment process, because of the high temperature, high pressure and quenching process, not only are harmful elements in the wastewater and the solid waste thoroughly decomposed, but also the generation of organic gaseous pollutants such as dioxin and the like is blocked; heavy metals are fixed in the molten slag, and the generated high-concentration organic wastewater difficult to be biochemically generated can be reused for pulping. The whole technical process has no secondary pollution to the environment, and researches and practices aiming at the cooperative gasification of three materials of organic wastewater, organic solid waste and coal water slurry at present continuously prove that the organic wastewater, the organic solid waste and the coal water slurry have better economic benefit and environmental benefit, but how to cooperate and gasify the materials with different properties and achieve and maintain better gasification effect is a problem to be solved urgently in engineering practice.

In the coal water slurry gasification process, a gasification nozzle is one of key devices, and the structure and the performance of the gasification nozzle can directly influence the continuity, the economy and the safety of the coal water slurry gasification process. Aiming at the gasification furnace which needs to treat various materials such as wastewater, organic solid waste, coal water slurry and the like at the same time, because the property difference of various raw materials is huge, the change of the feeding proportion of different raw materials can generate great influence on the gasification process, and the proper gasification nozzle adjusting method can greatly improve the stability and the gasification efficiency of the gasification process. However, in the domestic and foreign literature on the regulation and control system of the coal water slurry gasification nozzle, although there is a simple control loop for the coal water slurry nozzle with the traditional structure, there is no intelligent control system corresponding to the multi-channel combined gasification nozzle suitable for the gasification of organic wastewater, wastewater/clear water coal water slurry and organic solid waste coal water slurry.

Therefore, the invention provides an intelligent control system of the multi-channel combined gasification nozzle for organic wastewater, wastewater/clear water coal water slurry and organic solid waste coal water slurry, aiming at the problems, the feed ratio of the wastewater, the coal water slurry and the wastewater/solid waste coal water slurry is intelligently optimized by utilizing a neural network according to the characteristics of raw materials in actual production and production needs, and the gasification efficiency and the economic benefit of the cooperative gasification process of the coal water slurry with various wastes are improved.

Disclosure of Invention

The invention aims to solve the technical problem of overcoming the defects in the prior art and provides an intelligent control system of a multi-component waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle.

In order to solve the technical problem, the solution of the invention is as follows:

the utility model provides a many first waste liquid/useless coal slurry multichannel unites gasification nozzle intelligence control system admittedly, includes: an organic wastewater flow control loop, an inner epoxy flow control loop, a wastewater/clear water coal water slurry flow control loop, an organic solid waste coal water slurry flow control loop and an outer epoxy flow control loop; in each control loop, the outlet of a feed pump or a fan is respectively connected to a multi-element waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle through a pipeline, and a flowmeter is respectively arranged on the pipeline;

wherein, the organic wastewater flow control loop, the wastewater/clean water coal water slurry flow control loop and the organic solid waste coal water slurry flow control loop are all provided with a rotating speed regulator and a flow regulator, each feeding pump is respectively connected with the rotating speed regulator and the flow regulator in turn through signal lines, and each flow regulator is connected with a flowmeter through the signal lines; the pipelines in the inner epoxy flow control loop and the outer epoxy flow control loop are respectively provided with a flow regulating valve and a flow regulator, each flow regulating valve is respectively connected with the flow regulator through a signal line, and each flow regulator is connected with the flowmeter through a signal line; and the flow regulators in the flow control loops are respectively connected to the computer neural network predictive control system through signal lines.

The invention further provides a multi-waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle intelligent control method based on the system, which comprises the following steps:

a. inputting material type information into a multi-channel flow ratio optimizing preset unit;

b. gasification index information required by production is input into a multi-channel flow ratio optimizing preset unit;

c. the multichannel flow ratio optimizing presetting unit calls complete data information of corresponding types in the multichannel flow database unit and the gasification index database unit according to the determined material type information;

d. the multichannel flow ratio optimizing calculation unit calls complete data information of specific material types in the multichannel flow ratio optimizing preset unit to perform neural network training; the input of the neural network comprises organic wastewater flow, inner epoxy flow, wastewater/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow, and the output of the neural network comprises gasification reaction temperature, synthesis gas flow and effective gas content; optimizing weight parameters of the neural network by adopting a particle swarm algorithm, starting training, and finishing the training when set iteration times or accuracy are reached;

e. the multi-channel flow ratio optimizing calculation unit calls a trained neural network to perform enumeration method prediction according to input gasification index information; when the gasification index output by the neural network and the input gasification index meet the error requirement, the prediction is stopped;

f. and the multi-channel flow ratio optimizing calculation unit outputs the prediction data of the flow of each channel when the gasification index required by production is reached.

Compared with the prior art, the invention has the technical effects that:

(1) according to the invention, a special multi-channel combined gasification nozzle intelligent control system is designed according to the physicochemical properties and production requirements of three materials of organic wastewater, wastewater/clear water coal water slurry and organic solid waste coal water slurry, so that controllable efficient synergistic recycling of various wastes can be realized, and the blank suitable for the waste and coal water slurry gasification combined nozzle intelligent control system is filled.

(2) According to the gasification characteristics of several wastes and coal water slurry, the invention predicts and screens the flow proportioning scheme according with the production index through the neural network, thereby realizing intelligent adjustment of the feeding amount to ensure that the gasification device meets the requirements under different production conditions, such as low load during driving, full load during normal production, overload during single furnace operation and the like, and simultaneously meeting the dynamic adjustment and collocation of different raw materials such as waste water, solid waste, coal water slurry and the like according to the actual production requirements, realizing the specific production target and improving the gasification efficiency and economic benefit.

(3) The invention optimizes the feeding method of the multi-material cooperative gasification of the coal water slurry gasification furnace, opens up a new way for the high-efficiency comprehensive recycling of high-concentration organic wastewater, low-concentration organic wastewater and organic solid waste, and the intelligent control system provided by the invention is carried on the coal water slurry gasification furnace provided with the multi-channel combined gasification nozzle, so that the simultaneous feeding and cooperative gasification of the organic wastewater, the wastewater/clear water coal water slurry and the organic solid waste coal water slurry can be realized, the resource recycling rate can be further improved through intelligent regulation and control, the modification and installation cost is low, and the economic benefit and the environmental protection benefit are high.

Drawings

FIG. 1 is a schematic diagram of the structure of the integrated gasification nozzle intelligent control system loop of the present invention.

FIG. 2 is a block diagram of a computer neural network predictive control system according to the present invention.

The reference numerals in the figures are as follows:

10 organic wastewater flow control loop, 11 organic wastewater feed pump, 12 organic wastewater feed pump tachometer, 13 organic wastewater feed pump speed regulator, 14 organic wastewater flowmeter, 15 organic wastewater flow regulator, 20 internal epoxy flow control loop, 21 internal epoxy blower, 22 internal epoxy flowmeter, 23 internal epoxy flow regulator, 24 internal epoxy flow control valve, 30 wastewater/clear water coal slurry flow control loop, 31 wastewater/clear water coal slurry feed pump, 32 wastewater/clear water coal slurry feed pump tachometer, 33 wastewater/clear water coal slurry feed pump speed regulator, 34 wastewater/clear water coal slurry flowmeter, 35 wastewater/clear water coal slurry flow regulator, 40 organic solid wastewater flow control loop, 41 organic solid waste feed pump, 42 organic solid waste coal slurry feed pump tachometer, 43 organic solid waste coal water slurry feed pump rotating speed regulator, 44 organic solid waste coal water slurry flow meter, 45 organic solid waste coal water slurry flow regulator, 50 outer epoxy flow control loop, 51 outer epoxy fan, 52 outer epoxy flow meter, 53 outer epoxy flow regulator, 54 outer epoxy flow control valve, 60 computer neural network predictive control system, 70 multi-channel combined gasification nozzle;

the system comprises a 100 combined gasification nozzle multi-channel flow query module, a 101 multi-channel material variety database unit, a 102 multi-channel flow database unit, a 103 gasification index database unit, a 104 data information display unit, a 200 combined gasification nozzle multi-channel flow ratio optimization searching module, a 201 multi-channel flow ratio optimization searching preset unit, a 202 multi-channel flow ratio optimization calculating unit, a 300 combined gasification nozzle multi-channel flow regulation module, a 301 multi-channel flow ratio signal conversion unit and a 302 multi-channel flow ratio signal output unit.

Detailed Description

The technical solutions in the embodiments of the present invention will be described more clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The multi-waste liquid/solid waste water-coal-slurry is prepared by mixing high-concentration organic wastewater and organic solid waste water-coal-slurry in water-coal-slurry prepared by clear water or wastewater, and using a mixture of the three materials as the multi-waste liquid/solid waste water-coal-slurry for producing a water-coal-slurry gasification furnace. Wherein, the high-concentration organic wastewater generally refers to organic wastewater with complex components and containing COD, ammonia nitrogen and a plurality of organic salts, the COD concentration is generally higher than 2000mg/L and can reach tens of thousands of mg/L at most, and the high-concentration organic wastewater is not suitable for a conventional biochemical treatment mode. The organic solid waste coal water slurry is prepared by mixing organic solid waste such as sludge, oil sludge, rectification residue, medicine slag or waste activated carbon and the like into coal powder. In the invention, when all the materials are fed into the nozzle and enter the coal water slurry gasification furnace as the mixed coal water slurry, the outer epoxy and the inner epoxy are sprayed from the inner side and the outer side of the coal water slurry channel, so that the mixed coal water slurry can be assisted to burn, and the burnout rate is improved.

Referring to the attached drawings, the intelligent control system of the multi-waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle comprises an organic waste water flow control loop 10, an inner epoxy flow control loop 20, a waste water/clear water coal water slurry flow control loop 30, an organic solid waste coal water slurry flow control loop 40 and an outer epoxy flow control loop 50; in each control loop, the outlet of the feeding pump or the fan is respectively connected to a multi-element waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle 70 through a pipeline, and a flowmeter is respectively arranged on the pipeline of each control loop;

wherein, the organic wastewater flow control loop 10, the wastewater/clear water coal water slurry flow control loop 30 and the organic solid waste coal water slurry flow control loop 40 are all provided with a rotating speed regulator and a flow regulator, each feeding pump is respectively connected with the rotating speed regulator and the flow regulator in turn through signal lines, and each flow regulator is connected with a flowmeter through the signal lines; the pipelines in the inner epoxy flow control loop 20 and the outer epoxy flow control loop 50 are respectively provided with a flow regulating valve and a flow regulator, each flow regulating valve is respectively connected with the flow regulator through a signal line, and each flow regulator is connected with a flowmeter through a signal line; the flow regulators in each flow control loop are connected to the computer neural network predictive control system 60 via signal lines, respectively.

The flow meters arranged in the flow control loops transmit the flow information of the corresponding materials to the computer neural network predictive control system 60 through the flow regulators; the flow regulator receives the control signal from the computer neural network predictive control system 60 and sends the control signal to the rotation speed regulator to regulate the rotation speed of the feeding pump, or the flow regulator directly regulates the opening of the flow regulating valve on the outlet pipeline of the fan.

The computer neural network predictive control system 60 includes: a combined gasification nozzle multi-channel flow query module 100, which is used for receiving flow signals transmitted by each flow control loop and displaying all flow data in the system; a combined gasification nozzle multi-channel flow ratio optimizing module 200, which is used for optimizing and determining the material flow of each channel according to the input actual production target of the project and determining the flow ratio scheme of each channel; a combined gasification nozzle multi-channel flow regulation module 300; the module is used for transmitting flow adjusting signals to each flow control loop according to a flow proportioning scheme given by the combined gasification nozzle multi-channel flow proportioning optimizing module, and adjusting the flow of each material to a specific proportion.

Wherein, the multi-channel flow query module 100 of the combined gasification nozzle specifically comprises:

a multi-channel material type database unit 101, which is used for inputting and storing material type data information of a fuel channel of a gasification nozzle, wherein the material type data information comprises an organic wastewater type, a wastewater/clean water coal water slurry type and an organic solid waste coal water slurry type;

a multi-channel flow database unit 102, which is used for receiving and storing the flow data information of each channel of the gasification nozzle, including the flow data information of organic wastewater, inner epoxy flow data information, wastewater/clear water coal water slurry flow data information, organic solid waste coal water slurry flow data information and outer epoxy flow data information transmitted by each flow control loop;

a gasification index database unit 103 for inputting and storing gasification index data information of the gasification furnace under the condition that the material types and the flow rates of all channels of the gasification nozzle are fixed, wherein the gasification index data information comprises gasification reaction temperature, synthesis gas flow rate and effective gas content;

and the data information display unit 104 is used for matching, displaying and exporting the data information of the material types and the flow rates of all the channels of the gasification nozzle and corresponding gasification indexes, wherein the data information of the material types and the flow rates comprises the types and the flow rates of organic wastewater, inner epoxy flow rates, the types and the flow rates of wastewater/clean water coal water slurry, the types and the flow rates of organic solid waste coal water slurry and outer ring oxygen flow rates, and the data information of the gasification indexes comprises gasification reaction temperature, synthesis gas flow rate and synthesis gas components corresponding to the types and the flow rates of the materials.

The multi-channel flow ratio optimizing module 200 of the combined gasification nozzle specifically comprises:

a multichannel flow ratio optimizing presetting unit 201, which is used for calling data information of the multichannel material type database unit 101 and the gasification index database unit 103, and selecting the material type adopted by each channel and the gasification index required to be reached;

a multi-channel flow ratio optimizing calculation unit 202, configured to calculate an optimal ratio of the flow of each channel, call data information provided by the multi-channel flow query module 100 of the combined gasification nozzle, perform neural network training on the material type and flow data information of each channel and corresponding gasification index data information, perform ratio optimizing calculation according to the material type and the gasification index that needs to be reached, which are adopted by each channel and selected by the multi-channel flow ratio optimizing presetting unit 201, and output an optimal ratio scheme.

The combined gasification nozzle multi-channel flow regulation module 300 specifically includes:

multi-channel flow proportioning signal conversion unit 301: the unit is used for receiving the flow proportioning scheme of each channel output by the multi-channel flow proportioning optimizing module 200 of the combined gasification nozzle or receiving the flow proportioning scheme of each channel input manually, converting the flow proportioning scheme into the flow adjusting signal of each channel control loop, and displaying and storing the flow adjusting signal;

multi-channel flow proportioning signal output unit 302: the unit is used for transmitting each channel flow adjusting signal output by the multi-channel flow proportioning signal conversion unit 301 to the flow regulator in each flow control loop, and regulating the flow of organic wastewater, the flow of internal epoxy, the flow of wastewater/clean water coal water slurry, the flow of organic solid waste coal water slurry and the flow of external epoxy to a specific proportion.

The invention relates to an intelligent control method of a multi-waste liquid/solid waste coal water slurry multi-channel combined gasification nozzle, which is realized based on the system and comprises the following steps:

a. inputting material type information into the multichannel flow ratio optimization searching preset unit 201 specifically includes: organic wastewater type, wastewater/clear water coal water slurry type, and organic solid waste coal water slurry type.

b. Inputting gasification index information required by production into the multichannel flow ratio optimization presetting unit 201 specifically includes: gasification reaction temperature, synthesis gas flow rate and effective gas content.

c. The multichannel flow ratio optimization presetting unit 201 calls the complete data information of the corresponding types in the multichannel flow database unit 102 and the gasification index database unit 103 according to the determined material type information, and specifically includes: the flow rate of the specific organic wastewater, the flow rate of the internal epoxy, the flow rate of the specific wastewater/clear water coal water slurry, the flow rate of the specific organic solid waste coal water slurry, the flow rate of the external epoxy and gasification indexes corresponding to each working condition under a plurality of working conditions.

d. The multi-channel flow ratio optimization calculation unit 202 calls complete data information of specific material types in the multi-channel flow ratio optimization presetting unit 201 to perform neural network training; the input of the neural network comprises organic wastewater flow, inner epoxy flow, wastewater/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow, and the output of the neural network comprises gasification reaction temperature, synthesis gas flow and effective gas content; optimizing weight parameters of the neural network by adopting a particle swarm algorithm, starting training, and finishing the training when set iteration times or accuracy are reached;

e. the multi-channel flow ratio optimizing calculation unit 202 calls a trained neural network to perform enumeration method prediction according to input gasification index information; when the gasification index output by the neural network and the input gasification index meet the error requirement, the prediction is stopped;

f. the multi-channel flow ratio optimization calculation unit 202 outputs prediction data of the flow of each channel when the gasification index required by production is reached, and specifically includes: comprises organic waste water flow, inner epoxy flow, waste water/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow.

More detailed embodiments are described below:

the computer neural network predictive control system 60 performs neural network and proportioning optimization calculations according to the material type and the required gasification index in actual production, and transmits a flow adjustment signal to each channel flow control loop of the combined gasification nozzle. Namely, the organic wastewater flow control loop 10, the inner epoxy flow control loop 20, the wastewater/clear water coal water slurry flow control loop 30, the organic solid waste coal water slurry flow control loop 40 and the outer oxygen flow control loop 50 respectively control the flow of the organic wastewater, the inner ring oxygen, the wastewater/clear water coal water slurry, the organic solid waste coal water slurry and the outer ring oxygen entering the multi-channel combined gasification nozzle 70 according to the flow adjusting signal of the computer neural network prediction control system 60.

The combined gasification nozzle multi-channel flow query module 100 in the computer neural network predictive control system 60 may store past data information and display current data information. The data information includes the material type organic wastewater type, wastewater/clean water coal water slurry type, organic solid wastewater coal water slurry type data information, different channel flow (organic wastewater flow, inner ring oxygen flow, wastewater/clean water coal water slurry flow, organic solid wastewater coal water slurry flow, outer ring oxygen flow) data information of the nozzle stored in the multi-channel material type database unit 101, and gasification index gasification reaction temperature, synthesis gas flow, and effective gas content data information stored in the gasification index database unit 103. All data information can be displayed by the data information display unit 104.

The data information is stored and displayed in a one-to-one correspondence manner, for example, the specific flow ratio of specific material types corresponds to specific gasification indexes.

The material type data information of the multi-channel material type database unit 101 needs to be manually input and stored, and the corresponding multi-channel flow data information of the multi-channel flow database unit 102 and the gasification index data information of the gasification index database unit 103 can be manually input or can be from a real-time production process. Wherein, the multi-channel flow data information is from an organic wastewater flow control loop 10, an inner epoxy flow control loop 20, a wastewater/clear water coal water slurry flow control loop 30, an organic solid waste coal water slurry flow control loop 40 and an outer oxygen flow control loop 50. The gasification index data information comes from conventional testing equipment equipped with the coal water slurry gasification furnace.

The combined gasification nozzle multi-channel flow ratio optimizing module 200 can calculate and provide an optimal material flow ratio scheme according to the manually input material types and the gasification indexes required to be achieved.

The multi-channel flow ratio optimization presetting unit 201 calls the multi-channel material type database unit 101, the corresponding data information of the complete set of multi-channel flow database unit 102 and the data information of the gasification index database unit 103 according to the manually input material types and gasification indexes;

the multi-channel flow ratio optimization calculation unit 202 calls the multi-channel flow ratio optimization preset unit 201 set data information, performs neural network training on the multi-channel flow data information and gasification index data information corresponding to each manually input channel material type, performs ratio optimization calculation according to the gasification index required to be reached by manual input in the multi-channel flow ratio optimization preset unit 201, and outputs an optimal ratio scheme.

In the combined gasification nozzle multi-channel flow proportioning optimization module 200, the following operations may be implemented:

(1) in the multi-channel flow ratio optimization preset unit 201, the material type information is manually input, and the organic wastewater type, the wastewater/clean water coal water slurry type and the organic solid waste coal water slurry type are determined;

(2) in the multi-channel flow ratio optimization preset unit 201, gasification index information required by production is manually input, wherein the gasification index information comprises gasification reaction temperature, synthesis gas flow and effective gas content;

(3) the multichannel flow ratio optimization preset unit 201 calls complete data information of types corresponding to the multichannel flow database unit 102 and the gasification index database unit 103 according to the determined material type information, wherein the complete data information comprises specific type organic wastewater flow, internal epoxy flow, specific type wastewater/clear water coal water slurry flow, specific type organic solid waste coal water slurry flow, external epoxy flow and gasification indexes corresponding to each working condition under a plurality of working conditions;

(4) the multi-channel flow ratio optimization calculation unit 202 calls the complete data information of the specific material type in the multi-channel flow ratio optimization preset unit 201 to perform neural network training. The input of the neural network comprises organic wastewater flow, inner epoxy flow, wastewater/clear water coal water slurry flow, organic solid waste coal water slurry flow and outer epoxy flow, and the output of the neural network comprises gasification reaction temperature, synthesis gas flow and effective gas content. Optimizing weight parameters of the neural network by adopting a particle swarm algorithm, starting training, and finishing the training when set iteration times or accuracy are reached;

(5) the multi-channel flow ratio optimizing calculation unit 202 calls the trained neural network to perform enumeration method prediction according to the input gasification index information, and when the gasification index output by the neural network and the input gasification index reach the error requirement, the prediction is stopped;

(6) the multi-channel flow ratio optimization calculation unit 202 outputs the prediction data of the flow of each channel of the gasification index required by production, including the flow of organic wastewater, the flow of internal epoxy, the flow of wastewater/clean water coal water slurry, the flow of organic solid waste coal water slurry, and the flow of external epoxy.

The combined gasification nozzle multi-channel flow regulating module 300 receives a flow proportioning scheme obtained by manual input or neural network calculation, converts the flow proportioning scheme into a flow regulating signal and transmits the flow regulating signal to each control loop;

the multi-channel flow ratio signal conversion unit 301 receives the flow ratio schemes of the channels output by the multi-channel flow ratio optimizing calculation unit 202 or the manually input flow ratio schemes of the channels, converts the flow ratio schemes into flow adjustment signals of the control loops of the channels, and displays and stores the flow adjustment signals;

the multi-channel flow proportioning signal output unit 302 transmits the flow adjusting signals of each channel output by the multi-channel flow proportioning signal conversion unit 301 to the flow regulators in the control loops of each channel, including the organic wastewater flow regulator 15, the inner epoxy flow regulator 23, the wastewater/clear water coal water slurry flow regulator 35, the organic solid waste coal water slurry flow regulator 45 and the outer epoxy flow regulator 53.

The flow control loops of the channels of the combined gasification nozzle complete flow adjustment according to the flow adjustment signal transmitted by the computer neural network predictive control system 60.

Based on the above-mentioned predictive calculation of the computer neural network predictive control system 60, the control contents of each flow control loop are exemplified as follows:

the organic waste water flow control loop 10 comprises: an organic wastewater feeding pump 11, an organic wastewater feeding pump tachometer 12, an organic wastewater feeding pump speed regulator 13, an organic wastewater flowmeter 14 and an organic wastewater flow regulator 15; the organic wastewater feed pump 11 is connected with the organic wastewater channel in the multi-channel combined gasification nozzle 70 through a pipeline; the organic wastewater flow control loop 10 receives a flow adjustment signal from the computer neural network predictive control system 60 and adjusts the flow of organic wastewater. Wherein, the organic wastewater flowmeter 14 transmits the flow signal of the organic wastewater to the computer neural network predictive control system 60 through the organic wastewater flow regulator 15; the organic wastewater flow regulator 15 receives the flow regulating signal from the computer neural network predictive control system 60, converts the flow regulating signal into a rotating speed regulating signal and transmits the rotating speed regulating signal to the organic wastewater feeding pump rotating speed regulator 13. The organic wastewater feeding pump rotating speed regulator 13 regulates the rotating speed of the organic wastewater feeding pump through the organic wastewater feeding pump rotating speed meter 12 according to the rotating speed regulating signal, so that the flow regulation of the organic wastewater is realized.

The inner epoxy flow control loop 20 includes: an inner epoxy fan 21, an inner epoxy flowmeter 22, an inner epoxy flow regulator 23 and an inner epoxy flow regulating valve 24; the inner epoxy blower 21 is connected with the inner epoxy channel in the multi-channel combined gasification nozzle 70 through a pipeline; the inner epoxy flow control loop 10 receives a flow adjustment signal from the computer neural network predictive control system 60 and adjusts the flow of the inner epoxy. Wherein, the inner epoxy flow meter 22 transmits the inner epoxy flow signal to the computer neural network predictive control system 60 through the inner epoxy flow regulator 23. The inner epoxy flow regulator 23 receives the flow regulation signal from the computer neural network predictive control system 60, converts the flow regulation signal into a valve opening regulation signal, and regulates the opening of the inner epoxy flow regulating valve 24, thereby realizing the inner epoxy flow regulation.

The wastewater/clean water coal slurry flow control loop 30 includes: a wastewater/clean water coal-slurry feeding pump 31, a wastewater/clean water coal-slurry feeding pump tachometer 32, a wastewater/clean water coal-slurry feeding pump speed regulator 33, a wastewater/clean water coal-slurry flow meter 34, and a wastewater/clean water coal-slurry flow regulator 35; wherein, the wastewater/clean water coal water slurry feeding pump 31 is connected with the wastewater/clean water coal water slurry channel in the multi-channel combined gasification nozzle 70 through a pipeline; the wastewater/clean water coal-water-slurry flow control loop 30 receives the flow adjustment signal from the computer neural network predictive control system 60 and adjusts the flow of the wastewater/clean water coal-water-slurry. Wherein, the flow signal of the wastewater/clean water coal-water slurry is transmitted to the computer neural network predictive control system 60 by the wastewater/clean water coal-water slurry flow regulator 35 by the wastewater/clean water coal-water slurry flow meter 34. The wastewater/clean water coal water slurry flow regulator 35 receives the flow regulation signal from the computer neural network predictive control system 60, converts the flow regulation signal into a rotating speed regulation signal and transmits the rotating speed regulation signal to the wastewater/clean water coal water slurry feeding pump rotating speed regulator 33; the rotation speed regulator 33 of the wastewater/clean water coal-slurry feeding pump adjusts the rotation speed of the wastewater/clean water coal-slurry feeding pump through the rotation speed meter 32 of the wastewater/clean water coal-slurry feeding pump according to the rotation speed adjusting signal, thereby realizing the adjustment of the flow of the wastewater/clean water coal-slurry.

The organic solid waste coal water slurry flow control loop 40 comprises: an organic solid waste coal water slurry feeding pump 41, an organic solid waste coal water slurry feeding pump tachometer 42, an organic solid waste coal water slurry feeding pump speed regulator 43, an organic solid waste coal water slurry flow meter 44 and an organic solid waste coal water slurry flow regulator 45. The organic solid waste coal water slurry feeding pump 41 is connected with the organic solid waste coal water slurry channel in the multi-channel combined gasification nozzle 70 through a pipeline; the organic solid waste coal water slurry flow control loop 40 receives a flow adjustment signal from the computer neural network predictive control system 60 and adjusts the flow of the organic solid waste coal water slurry. Wherein, the organic solid waste coal water slurry flow meter 44 transmits the flow signal of the organic solid waste coal water slurry to the computer neural network predictive control system 60 through the organic solid waste coal water slurry flow regulator 45. The organic solid waste water coal slurry flow regulator 45 receives the flow regulation signal from the computer neural network prediction control system 60, converts the flow regulation signal into a rotating speed regulation signal and transmits the rotating speed regulation signal to the organic solid waste water coal slurry feed pump rotating speed regulator 43; the organic solid waste coal water slurry feeding pump rotating speed regulator 43 regulates the rotating speed of the organic solid waste coal water slurry feeding pump through the organic solid waste coal water slurry feeding pump rotating speed instrument 42 according to the rotating speed regulating signal, so that the flow regulation of the organic solid waste coal water slurry is realized.

The outer oxygen flow control loop 50 includes: an outer epoxy blower 51, an outer annular oxygen flow meter 52, an outer annular oxygen flow regulator 53, and an outer annular oxygen flow regulating valve 54; the outer epoxy blower 51 is connected with the outer epoxy channel in the multi-channel combined gasification nozzle 70 through a pipeline. The outer epoxy flow control loop 50 receives a flow adjustment signal from the computer neural network predictive control system 60 and adjusts the flow of the outer epoxy. Wherein, the outer ring oxygen flow meter 52 transmits the outer ring oxygen flow signal to the computer neural network predictive control system 60 through the outer ring oxygen flow regulator 53. The outer oxygen flow regulator 53 receives the flow regulation signal from the computer neural network predictive control system 60, converts the flow regulation signal into a valve opening regulation signal, and regulates the opening of the outer oxygen flow regulating valve 54, thereby realizing the outer oxygen flow regulation.

The invention designs a special multi-channel combined gasification nozzle intelligent control system according to different gasification properties and production needs of three materials of organic wastewater, wastewater/clear water coal water slurry and organic solid waste coal water slurry, realizes controllable and efficient cooperative recycling of various wastes, and predicts and screens a flow ratio scheme according with production indexes through a neural network, thereby realizing intelligent adjustment of feeding amount to ensure that a gasification device meets requirements under different production working conditions.

Those skilled in the art will appreciate that, in addition to implementing a portion of the system and its various devices, modules, units provided by the present invention as pure computer readable program code, the system and its various devices, modules, units provided by the present invention can be implemented with the same functionality in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like, simply by logically programming the method steps. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units included in the system for realizing various functions can also be regarded as structures in the hardware component; means, modules, units for performing the various functions may also be regarded as structures within both software modules and hardware components for performing the method.

The particular embodiments of the invention disclosed above are illustrative only. The examples are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.