Design scheme of metal wastewater purification device in industrial park

: Due to the limitation of chemical process technology and management system, the traditional treatment mode of heavy metal waste liquid pollution has many problems, such as high power consumption in the process, high wear of consuming steel, high management cost, and secondary pollution caused by complex solid waste residue in data detection. Team based on the front end of deep learning module and back-end soft measurement model of collaborative structures, design and improvement of the learning algorithm combined with nested integration depth control series new front end treatment module, the successful implementation of heavy metal ions in industrial wastewater concentration of accurate prediction, and according to the predicted results and the analysis of liquid ingredients, targeted treatment after intelligent classification.


The introduction 1.1 Current situation of existing products
The team conducted field investigations in panzhihua, Kunshan and other iron and steel forging bases and found the following problems in existing processes and assembly lines.

[Limitations of chemical method technology]
The traditional chemical process treatment has technical limitations.With the launch of discharge standards or about to reach their limits, there is an urgent need for innovation in the treatment technology of heavy metal wastewater, as well as the development of efficient and cost-effective devices and new schemes.
[Secondary processing produces dangerous waste, which cannot be reused] Traditional chemical processes turn metal ions in industrial heavy metal wastewater into precipitated sludge and other hazardous wastes, requiring retreatment and landfill of secondary hazardous wastes, and cannot be recycled.

[High comprehensive cost of chemical method]
Chemical method has low initial cost, dangerous waste deposition after long-term use, and there is no matching intelligent monitoring system, which requires manual maintenance, high maintenance and repair cost, and short service life.simple operation and convenient maintenance, but it has some shortcomings such as low sensitivity, easy to be interfered by coexisting ions, and can not be used to determine multiple ions at the same time.[1][Lack of "wisdom" management, high management cost] Most of the existing smart water concepts are only for regional monitoring, inspection, data management, etc.The traditional industrial management mode is single, the effluent management mode is chaotic, the phenomenon of illegal discharge, leakage and discharge is not rare, and the relevant enterprises need to spend a lot of manpower and time to manually manage and detect the wastewater treatment situation.Front-line technical personnel urgently need a safe intelligent management and detection system to assist water management and purification, and collect relevant data for visual management.

[Lack of management innovation, single mode]
There are many existing wastewater treatment processes.Whether the chemical method which has been mature for many years or the biological method which is in the early stage of development, they are all aimed at the technical innovation of chemical process, but ignore the management system of electroplating waste liquid treatment, and the mode innovation and design of control system.At present, most one-stop water treatment suppliers only provide simple automation devices and control consoles with single functions, such as remote control, which only meet simple functions such as operation of control devices.This is in contradiction with the ratio of the industrial Internet of Things in the future development.

Product design objectives
In the disposal process, industrial ion exchange technology is combined with the integration of deep learning algorithm and distributed control of exchange bin module to achieve a technical solution of high efficiency, low pollution and low comprehensive cost from the perspective of process control.

Process Route
The device is deeply treated by ion exchange adsorption system, which makes the effluent reach the standard stably, reduces waste solids and realizes resource reuse.At the same time, the heavy metal wastewater without organic matter and cyanide can be directly into the ion exchange adsorption system for comprehensive treatment, discharge standards.The ion exchange adsorption system concentrates heavy metal ions through regeneration process.According to actual requirements, the reclaimed liquid can be processed by returning to the collection tank or recycling, and the real-time interaction with the backend data module can be maintained.

Targeted ion exchange bin 2.1 Function Design [Structural design]
Heavy metal pollution has caused more and more harm to the environment and human beings, with the further implementation of the global sustainable development strategy, the heavy metal wastewater treatment requirements will be increasingly strict.Heavy metal wastewater is a very complicated mixed system, and it is difficult to meet the treatment requirements with single treatment technology.[2,3] The prototype should be small in size, light in weight, convenient in transportation, and have strong emergency handling ability.The device has continuous treatment capacity and high treatment efficiency for heavy metal (electroplating) wastewater.It can treat wastewater with concentration ranging from 0.1mg/L to 500mg/L.The whole device is standardized design, each column is designed as a standardized column, the column between the general, easy to replace the material in the tank; The main parts are standardized parts, convenient for maintenance and disassembly repair work.The device uses standardized cylinder as filling container of ion exchange material.The cylinder is composed of cylinder and upper and lower end cover with the same design parameters.The material is low alloy steel, and the inner wall of the cylinder is lined with rubber, which has the performance of acid and alkali resistance and corrosion resistance.

[Automation design]
The system adopts force control configuration, Siemens S7-200 PLC and touch screen as operation interface and logic control unit.According to the different ions and concentration, water quantity, standard column adsorption saturation capacity and other parameters in the field wastewater, the corresponding column passing time is calculated, and based on this, the automatic switching function of the system is realized, and the online storage, long-distance transmission and fault alarm functions of key data are completed.

[Standard modularization]
The device adopts standard modular design, with three single columns and their supporting pipes as a module group, and the columns in the module group are connected in series through pipes.The whole device is currently provided with two module groups.The computing model of soft-sensing neural technology has been verified based on neural network, and the modeling principle of BP neural network has been elaborated in detail in Literature [5].Simple contains three layers BP neural network input layer, hidden layer and output layer, each node in the diagram represents a neurons; The neurons of the preceding layer and the following layer are connected by corresponding weights.BP neural network training is mainly divided into two processes: positive transfer and error signal of the reverse [5] In order to cooperate with the module group, a series of common accessories are configured for the two groups of modules.The module group is connected in parallel through pipes, and the connecting pipes between the module group and the module group are provided with solenoid valves.Various working modes of the module group can be realized by controlling the solenoid valve

Material adsorption experimental verification
To check the strength of the column, the design pressure of the device is P = 0.5mpa, and the yield strength of low alloy steel [σ]t=345MPa.Then the diameter ratio coefficient K of the tank is: Therefore, the internal pressure cylinder strength can be checked according to the maximum tensile stress criterion.Refer to the national standard GB150-2011 "Fixed pressure vessel" can be obtained, the cylinder cylinder welding joint coefficient ϕ=0.85, cylinder diameter Di=250mm, the actual wall thickness of the cylinder δ I =15mm, and the cylinder calculated wall thickness, namely the minimum wall thickness of the cylinder is:He Dan et al. from South China Normal University established a soft sensor model (PSO-BP model) by optimizing BP neural network through particle swarm optimization algorithm (PSO), and used the nonlinear approximation ability of BP neural network and the global search ability of PSO to accurately predict CODEFF and SSEFF in the process of sewage treatment [4] = 0.

2[ ]
In the formula, PC is the calculated pressure of the cylinder, and its value is PC =1.1× P = 0.5mpa.It is known from above that the cylinder design of the tank meets the requirements of working strength.Similarly, with reference to the national standard GB150-2011 "Solid 6 Type Pressure Vessel", the tank end cover can be checked for strength, and the check result is: the tank end cover design meets the working strength requirements.[6]Because the external pressure is small when the tank works, there is no instability of the tank, so the tank can not be stability check.At this point, the overall structure of the device tank design check completed, in line with GB150-2011 "Fixed pressure vessel" standard requirements.The saturated adsorption capacity of the fiber for a specific metal ion is set as D mg/g, the fiber column is filled with X Kg, the flow rate of the equipment is Y m3/h, the concentration of specific metal ions in the original liquid is Z mg/L, and the saturation adsorption time of metal ions is T h.
The following equation can be obtained: It can be concluded that: Copper was adsorbed by cation exchange fiber and regenerated with 5%HCl solution.The saturated adsorption capacity of the fiber to a specific metal ion is D mg/g, C(H+)=1.44mol/L, the fiber column is filled with X Kg, the regeneration flow rate is K m3/ H, and the regeneration time is T H. B represents the relative atomic mass of the metal element, and the relative submass of copper is 64.According to the regeneration principle, one molecule of copper needs two molecules of hydrochloric acid solution to regenerate, The equation obtained is: Nickel was adsorbed by cation exchange fiber and regenerated with 5%HCl solution.The saturated adsorption capacity of the fiber to a specific metal ion is D mg/g, C(H+)=1.44mol/L, the fiber column is filled with X Kg, the regeneration flow rate is K m3/ H, and the regeneration time is T H. B represents the relative atomic mass of the metal element, and the relative submass of nickel is 59.According to the regeneration principle, 1 molecule of nickel needs 2 molecules of hydrochloric acid solution to regenerate, The equation obtained is: According to the saturation regeneration formula above, the prediction time of ion concentration of each module is calculated, and the results are input into the automatic control program, and the device can complete the intelligent allocation of targeted modules at the corresponding time.

Training samples based on concentration prediction results
Experimental process: Dayu front-end switch module was used for adsorption regeneration process.Sodium hydroxide solution with a mass fraction of 5% was configured with caustic soda.After soaking for 30min, the regeneration process was completed by washing and discharge with water.The water sample taken is the outlet water sample of the front-end disposal module.After repeated process verification for other switch modules, the content of hexavalent chromium is 4.87mg/ L, the PH value is 12.36, and the total content of copper and zinc is 0.36mg/ L and 0.475mg/ L, respectively, far better than the national emission threshold.Therefore, it is verified again that the wastewater entering the switch module can be purified with higher efficiency after concentration prediction and assisted intelligent distribution.Due to the low concentration of chromium-containing wastewater, the material cannot be saturated in a short time, so the saturation time of each adsorption tank is set as 2 hours.The experimental raw water is chromiumcontaining wastewater, the concentration of raw water is 11.97mg/ L, the content of other heavy metal ions is < 0.05mg/ L, the PH value of raw water is 8.66, and the ambient temperature is 30℃.The experimental raw water was treated by connecting the exchange bin in series.The experimental flow was set at 1m³/h, and the actual flow was 0.9566-1.005m3/h.The adsorption process lasted for 180min, and the chromium containing wastewater was treated from 2.868m³ to 3.015m³.All the tested water samples after treatment are the total outlet water samples of the device.

Intelligent scheduling platform construction
Basic platform architecture: The dispatching system is mainly equipped with concentration prediction and intelligent distribution technology, which plays an intelligent control of the frontend water control module on the whole.The system is divided into four parts, including perception layer, transmission layer, application layer and terminal layer.
(1) Perception layer.Mainly for the acquisition of enterprise data set, these data through the acquisition system of each module.The module consists of water pressure sensor, detection sensor, hydraulic detection, dynamic fan, lifting pump, and fault detector and other hardware equipment.It is mainly used to detect safety information, water quantity and other information data sets used for research.
(2) Transport layer.It is composed of various communication modules, including gateways, Purple Bee wireless connection equipment, and various wireless and wired transmission networks, so as to achieve remote control.
(3) Application layer.Here, the switching device is assembled in a distributed architecture mainly by outsourcing customized parts through selective selection.(4) Terminal layer.IPC and PC can obtain the real-time operation data of the equipment in the system in time, and the concentration prediction report and intelligent distribution information can be visually presented here.

Conclusion
This chapter makes a more detailed analysis of the frontend water treatment module from two perspectives, and shows the heavy metal wastewater treatment process based on back-end intelligent analysis through pilot test verification and comparison of effluent data indicators: 1. Briefly explain the drawbacks and pain points of the general assembly line operation found by the team through field research.And detailed analysis of many pain points under the need to solve the core problems.2. Through a series of experiments and data verification design optimization of the traditional process, determine the front-end processing device design concept and indicators.3.Under the intelligent control of the back-end platform, a complete cycle is completed, and the results are compared with the set indicators, which are in line with the design standards.

Figure 2 Figure 3
Figure 2 Manual guided operating equipment

Figure 4
Figure 4 Front and rear Cloud Trinity mode tray

Figure 5
Figure 5 Structure and layout of the mobile device

Figure 6
Figure 6 Standardized single cylinder

Figure 7
Figure 7 Multi-bin heavy metal switch module

Figure 8
Figure 8 Experimental data of adsorption function verification