Method for intelligently adjusting flow in rare earth extraction production process

Abstract

The invention discloses a method for intelligently adjusting flow in a rare earth extraction production process, which is characterized by comprising the following steps of: acquiring flow and stage sample data, the flow comprises feed liquid flow, organic phase flow, acid washing flow and water washing flow, and the stage sample data is the mass percentage content of cerium element in a water phase of a sampling point; establishing a flow adjustment equation by taking the level sample data as an independent variable and the flow as a dependent variable; and obtaining an independent variable after flow adjustment according to the flow adjustment equation and the dependent variable before flow adjustment, adjusting the flow in real time according to the independent variable after flow adjustment, and displaying a groove distribution curve before and after flow adjustment. The method solves the problems that the flow in the extraction process is adjusted according to the experience of operators and the product quality is greatly influenced by human factors in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rare earth extraction, and particularly relates to a method for intelligent adjustment of flow in a rare earth extraction production process. BACKGROUND

[0002] Rare earths are a total of 17 elements including 15 lanthanide series elements and scandium and yttrium which have similar chemical properties to the lanthanide series elements. Because rare earth elements have excellent physical and chemical properties, they are widely used in hydrogen storage, magnetic materials, luminescent materials and other fields. In the application process of rare earth elements, mixed rare earth elements in minerals need to be separated into single or two-element mixtures, so the solvent extraction method is currently mainly used for separating rare earth elements.

[0003] The rare earth solvent extraction separation system includes an organic phase and an aqueous phase, wherein the aqueous phase is divided into a feed solution, washing acid and washing water, and the feed solution is an aqueous solution containing multiple rare earth elements. The role of the organic phase is to extract the extractable elements in the aqueous phase into the organic phase. The role of the washing acid is to dissociate the extracted substances in the organic phase, and the role of the washing water is to adjust the acidity of the aqueous phase. In the rare earth extraction separation process, a single extraction cannot achieve effective separation, so the fractional extraction process is currently used. Since the 1970s, through the long-term efforts of scientific research and enterprise workers, and under the guidance of the cascade extraction theory proposed by Academician Xu Guangxian, the rare earth extraction separation process has been popularized.

[0004] However, in the current rare earth extraction separation production process, the flow is still adjusted by the on-site operator according to the off-line analysis results of the mass percentage content of a certain rare earth element in the sampling point aqueous phase and long-term experience, so that the quality of the rare earth product is greatly affected by human factors.

[0005] Chinese Publication No. CN116798538A discloses a simulation system for a mixed clarifying tank and a calculation method thereof. By setting initial flow parameters and mixed clarifying tank equipment parameters, setting changes in external flow parameters during simulation and simulation calculation of the running state of the mixing chamber according to the set initial flow parameters and related data of intermediate process external variables to control the minimum time unit and iteration number of the iteration calculation process for iteration operation. By using the method disclosed in the present application, various theoretical models such as pressure balance, weir flow model, extraction balance and heterogeneous mixing process are comprehensively applied, and a simulation system for the liquid volume and flow of the mixed clarifying tank is constructed by a numerical simulation method, thereby providing reliable data support for the construction of an intelligent control system for rare earth extraction separation. The technology belongs to the mixed clarifying chamber part of the rare earth extractor, and computer simulation is performed by applying extraction separation theory.

[0006] Chinese patent application CN111142582A discloses an intelligent control system for a rare earth extraction production process. The system establishes a database and utilizes the relationship between the discharge ratio and the actual production time at the extraction site to achieve real-time data acquisition of the extraction production line. It also enables visual comparison of historical tank distribution curves. This invention establishes an interactive relationship between the control system and the feed liquid distribution, enabling the control system to monitor the actual tank distribution of the production line even under fluctuating feed liquid distribution. While other technologies use only trial-and-error methods for flow adjustment without applying relevant data equations, resulting in a large amount of data to be processed and increased computation time, this patent innovatively uses data equations for calculation.

[0007] Chinese patent application CN111506123A discloses an intelligent flow control device for rare earth extraction, comprising: a housing, a feed channel, a pressure sensing mechanism, a drive mechanism, a passive mechanism, and a flow control mechanism. The passive mechanism includes: a rotary wheel, an amplitude rod, a transmission unit, and a warning unit. Through the cooperation of the pressure sensing mechanism, drive mechanism, passive mechanism, and flow control mechanism, the pressure sensing mechanism acquires the pressure value of the fluid in the feed channel. Then, by precisely controlling the pitch of the screw thread on the drive mechanism screw, the flow control mechanism's main core moves down or up by a certain distance per revolution of the screw to accurately determine the change in the fluid pressure value. This change is pre-set in the signal converter, and the number of screw revolutions is determined based on this change to obtain the appropriate pressure value of the fluid in the feed channel, achieving intelligent control and precise flow control. This technology belongs to single-unit flow control, which only refers to pressure parameters to customize the flow rate. Summary of the Invention

[0008] The purpose of this invention is to provide a method for intelligent adjustment of flow rate in the rare earth extraction production process, which solves the problem that in the prior art, the flow rate of the extraction process is adjusted based on the operator's experience, and the product quality is greatly affected by human factors.

[0009] To achieve the above objectives, the technical solution used in this invention is: A method for intelligent flow rate adjustment in rare earth extraction production processes, characterized by comprising: Collect flow rate and graded sample data. Flow rate includes: liquid flow rate, organic phase flow rate, acid washing flow rate, and wash water flow rate. Graded sample data is the mass percentage content of cerium in the aqueous phase at the sampling point. Using sample data as the independent variable and flow rate as the dependent variable, a flow rate adjustment equation is established; The independent variable after flow adjustment is obtained based on the flow adjustment equation and the dependent variable before flow adjustment. The flow is adjusted in real time based on the independent variable after flow adjustment, and the slot distribution curve before and after flow adjustment is displayed.

[0010] Furthermore, the flow rate adjustment equation is: Y = 5.3 × 10⁻⁷ × X₁ + 2.4 × 10⁻⁶ × X₂ + 10.2 × ln(X₃) + 0.28 × X₄ - 15.7; Y is the mass percentage of cerium in the aqueous phase at the sampling point, X₁ is the feed liquid flow rate in L / min, X₂ is the organic phase flow rate in L / min, X₃ is the wash water flow rate in L / min, and X₄ is the acid washing flow rate in L / min.

[0011] Furthermore, the value range of Y is 50-55, the value range of X1 is 950-960, the value range of X2 is 260-270, the value range of X3 is 40-50, and the value range of X4 is 100-110.

[0012] Furthermore, in the actual countercurrent extraction production line, the flow rate adjustment equation is used for calculation, and the independent variable after flow rate adjustment is fed back to the control system as the calculation result to adjust the flow rate of the production line, thereby realizing intelligent flow rate adjustment.

[0013] Furthermore, an intelligent flow rate adjustment and prediction module is established to display the tank distribution curve. This module displays the tank distribution curve before and after flow rate changes and includes a flow rate adjustment submodule and a tank distribution curve prediction submodule. The flow rate adjustment submodule is used to establish interaction with the flow controller of the extraction production line and collect flow rate data in real time. The tank distribution curve prediction submodule is used to display the tank distribution curve, and the displayed content includes the mass percentage of rare earth elements in the aqueous and organic phases.

[0014] Furthermore, the rare earth elements selected are La, Ce, Pr, and Nd.

[0015] Furthermore, the trough distribution curve prediction submodule is established based on the extraction dynamic equilibrium simulation method in cascade extraction theory.

[0016] Furthermore, interaction is established through the OPC protocol.

[0017] Furthermore, a traffic intelligent adjustment and prediction module was built using Visual C++.

[0018] Furthermore, in the groove distribution curve, the horizontal axis represents the series, and the vertical axis represents the purity of the rare earth elements.

[0019] The technical effects of this invention include: This invention addresses the issue of intelligent adjustment of production lines, resolving the problem that in existing technologies, the flow rate of the extraction process is adjusted based on the operator's experience, resulting in product quality being greatly affected by human factors. This invention improves the automation and intelligence of the rare earth extraction process.

[0020] This invention collects flow rate and sample data, establishes a flow rate adjustment equation, and builds an automatic flow rate adjustment prediction module to achieve intelligent flow rate adjustment. By replacing manual flow rate adjustment with automatic adjustment, human error and labor costs are reduced. It also enables visual prediction of the effects of flow rate adjustments, ensuring stable tank operation and product quality, and improving the automation and intelligence level of the rare earth extraction process.

[0021] This invention establishes an equation relating the flow rate to the cerium content in the aqueous phase at the sampling point during the extraction process, which can change the flow rate adjustment from manual to automatic, reducing human error and labor costs. Attached Figure Description Figure 1 This is a diagram showing the tank distribution balance curve before flow adjustment provided in Embodiment 1 of the present invention; Figure 2 This is a diagram showing the balanced distribution curve of the tank after flow adjustment provided in Embodiment 1 of the present invention. Figure 3 This is a diagram showing the tank distribution balance curve before flow adjustment provided in Embodiment 2 of the present invention; Figure 4 This is a diagram showing the balanced distribution curve of the tank after flow rate adjustment provided in Embodiment 2 of the present invention. Figure 5 This is a diagram showing the tank distribution balance curve before flow adjustment provided in Embodiment 3 of the present invention; Figure 6 This is a diagram showing the balanced distribution curve of the slots after flow adjustment, provided in Embodiment 3 of the present invention. Detailed Implementation

[0022] The following description fully illustrates specific embodiments of the invention to enable those skilled in the art to practice and reproduce it. The specific embodiments of the invention are further described in detail below with reference to the accompanying drawings and examples.

[0023] A method for intelligent flow rate adjustment in rare earth extraction production process is proposed. This method involves collecting flow rate and sample data, establishing a flow rate adjustment equation, and creating an automatic flow rate adjustment prediction module to achieve intelligent flow rate adjustment and display.

[0024] Methods for intelligent flow rate adjustment in rare earth extraction production processes include: 1. Collect flow rate and graded sample data. Flow rate includes: feed liquid flow rate, organic phase flow rate, acid washing flow rate, and wash water flow rate. Graded sample data is the mass percentage content of cerium in the aqueous phase at the sampling point. In the actual countercurrent extraction production line, the flow rates of the feed liquid, organic phase, washing acid, and washing water are collected, along with the mass percentage of cerium in the aqueous phase at the sampling points.

[0025] 2. Based on the collected flow rate and graded sample data, with the graded sample data as the independent variable and the feed liquid flow rate, organic phase flow rate, acid washing flow rate, and wash water flow rate as the dependent variables, establish a flow rate adjustment equation; Flow rate adjustment equation: Y = 5.3 × 10 -7 ×X1+2.4×10 -6 ×X2+10.2×ln(X3)+0.28×X4-15.7; Where Y is the mass percentage of cerium in the aqueous phase at the sampling point, in %, and the value of Y ranges from 50 to 55. X1 is the feed flow rate in L / min, and the value of X1 ranges from 950 to 960. X2 is the organic phase flow rate in L / min, and the value of X2 ranges from 260 to 270. X3 is the wash water flow rate, in L / min, and the value of X3 ranges from 40 to 50. X4 represents the acid washing flow rate in L / min, and its value ranges from 100 to 110.

[0026] 3. Obtain the independent variable after flow adjustment based on the flow adjustment equation and the dependent variable before flow adjustment, adjust the flow in real time based on the independent variable after flow adjustment, and display the slot distribution curve before and after flow adjustment.

[0027] Real-time data is acquired from automated equipment such as DCS and PLC on site, and calculations are performed using flow adjustment equations. The independent variable after flow adjustment is used as the calculation result and fed back to the control system to adjust the flow of the production line, thereby realizing intelligent flow adjustment.

[0028] A traffic intelligent adjustment and prediction module is established to display the content slot distribution curve. In the slot distribution curve, the horizontal axis represents the series, and the vertical axis represents the purity of rare earth elements.

[0029] The intelligent flow adjustment and prediction module is used to display the slot distribution curves before and after flow changes, including: flow adjustment submodule and slot distribution curve prediction submodule; The flow adjustment submodule is used to establish interaction with the flow controller of the extraction production line to collect the feed liquid flow, organic phase flow, acid washing flow, and wash water flow in real time. The trough distribution curve prediction submodule is used to display the trough distribution curve, which includes the mass percentage of each component of rare earth elements La, Ce, Pr, and Nd in the aqueous phase and the rare earth elements La, Ce, Pr, and Nd in the organic phase.

[0030] The trough distribution curve prediction submodule is established based on the extraction dynamic equilibrium simulation method in cascade extraction theory.

[0031] Interaction is established through the OPC (Object Linking and Embedding (OLE) for Process Control) protocol, which is Microsoft's application of object linking and embedding technology in process control. The OPC specification evolved from OLE / COM / DCOM technology and established a unified standard for the development of object-oriented industrial automation software in a client / server (C / S) model. This standard defines methods for real-time exchange of automated data between PC-based clients.

[0032] A traffic intelligent adjustment and prediction module was built using Visual C++, which can visualize the effect of traffic adjustment.

[0033] The following examples are used to illustrate the present invention, but are not intended to limit the scope of the invention.

[0034] This embodiment establishes a flow rate adjustment equation based on the flow rate of the feed liquid, organic phase, acid washing, and washing water during the production process, as well as the mass percentage of cerium in the aqueous phase at the sampling point. Simultaneously, an intelligent flow rate adjustment prediction module based on Visual C++ is used to realize intelligent control of flow rate adjustment during the rare earth extraction production process.

[0035] Example 1 like Figure 1 The diagram shown is a balance curve of the tank distribution before flow adjustment provided in Embodiment 1 of the present invention; as shown... Figure 2 The figure shown is a diagram of the trough distribution balance curve after flow adjustment provided in Embodiment 1 of the present invention.

[0036] When the feed flow rate X1 is 957 L / min, the organic phase flow rate X2 is 265 L / min, the wash water flow rate X3 is 45 L / min, and the acid washing flow rate X4 is 105 L / min, the intelligent flow rate adjustment and prediction module calculates and displays a Y value of 52.46%. When production requires controlling the mass percentage of cerium in the aqueous phase at the sampling point to be 52%, and the fixed flow rates are X1 (957 L / min), X2 (265 L / min), and X3 (45 L / min), the acid washing flow rate X4 should be adjusted to 103 L / min according to the flow rate adjustment equation. The adjusted flow rate is then calculated again using the intelligent flow rate adjustment and prediction module, showing that the Y value is 52.04%.

[0037] Example 2 like Figure 3 The diagram shown is a balance curve of the slot distribution before flow adjustment provided in Embodiment 2 of the present invention; as shown... Figure 4 The figure shown is a diagram of the trough distribution balance curve after flow adjustment provided in Embodiment 2 of the present invention.

[0038] When the feed flow rate X1 is 953 L / min, the organic phase flow rate X2 is 268 L / min, the wash water flow rate X3 is 40 L / min, and the acid washing flow rate X4 is 110 L / min, the intelligent flow rate adjustment and prediction module calculates and displays a Y value of 52.75%. When production requires controlling the mass percentage of cerium in the aqueous phase at the sampling point to be 52%, and the fixed flow rates are X1 (953 L / min), X2 (268 L / min), and X3 (40 L / min), the acid washing flow rate X4 should be adjusted to 107.5 L / min according to the flow rate adjustment equation. The adjusted flow rate is then calculated again using the intelligent flow rate adjustment prediction module, showing that the Y value is 51.99%.

[0039] Example 3 like Figure 5 The diagram shown is a diagram of the tank distribution balance curve before flow adjustment provided in Embodiment 3 of the present invention; as shown Figure 6 The figure shown is a diagram of the trough distribution balance curve after flow adjustment provided in Embodiment 3 of the present invention.

[0040] When the feed flow rate X1 is 953 L / min, the organic phase flow rate X2 is 268 L / min, the wash water flow rate X3 is 50 L / min, and the acid washing flow rate X4 is 100 L / min, the intelligent flow rate adjustment and prediction module calculates and displays a Y value of 52.25%. When production requires controlling the mass percentage of cerium in the aqueous phase at the sampling point to be 52%, and the fixed flow rates are X1 (953 L / min), X2 (268 L / min), and X3 (49 L / min), the acid washing flow rate X4 should be adjusted to 100 L / min according to the flow rate adjustment equation. The adjusted flow rate is then calculated again using the intelligent flow rate adjustment prediction module, showing that the Y value is 52.02%.

[0041] The terminology used in this invention is descriptive and exemplary, not restrictive. Since this invention can be embodied in many forms without departing from the spirit or essence of the technical solution, it should be understood that the above embodiments are not limited to any of the foregoing details, but should be interpreted broadly within the spirit and scope defined by the appended claims. Therefore, all variations and modifications falling within the scope of the claims or their equivalents should be covered by the appended claims.

Claims

1. A method for intelligent flow rate adjustment in a rare earth extraction production process, characterized in that, include: Collect flow rate and graded sample data. Flow rate includes: liquid flow rate, organic phase flow rate, acid washing flow rate, and wash water flow rate. Graded sample data is the mass percentage content of cerium in the aqueous phase at the sampling point. Using sample data as the independent variable and flow rate as the dependent variable, a flow rate adjustment equation is established; The independent variable after flow adjustment is obtained based on the flow adjustment equation and the dependent variable before flow adjustment. The flow is adjusted in real time based on the independent variable after flow adjustment, and the slot distribution curve before and after flow adjustment is displayed.

2. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 1, characterized in that, The flow rate adjustment equation is: Y = 5.3 × 10⁻⁷ × X₁ + 2.4 × 10⁻⁶ × X₂ + 10.2 × ln(X₃) + 0.28 × X₄ - 15.7; Y is the mass percentage of cerium in the aqueous phase at the sampling point, X₁ is the feed liquid flow rate in L / min, X₂ is the organic phase flow rate in L / min, X₃ is the wash water flow rate in L / min, and X₄ is the acid washing flow rate in L / min.

3. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 2, characterized in that, The value range of Y is 50~55, the value range of X1 is 950-960, the value range of X2 is 260-270, the value range of X3 is 40-50, and the value range of X4 is 100-110.

4. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 2, characterized in that, In actual countercurrent extraction production lines, the flow rate is adjusted using a flow rate adjustment equation. The adjusted independent variable is then fed back to the control system to adjust the flow rate of the production line, thus achieving intelligent flow rate adjustment.

5. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 1, characterized in that, Establish a traffic intelligent adjustment and prediction module, and display the content slot distribution curve through the traffic intelligent adjustment and prediction module; The intelligent flow adjustment and prediction module is used to display the tank distribution curve before and after the flow change. It includes: a flow adjustment submodule and a tank distribution curve prediction submodule. The flow adjustment submodule is used to establish interaction with the flow controller of the extraction production line and collect the flow in real time. The tank distribution curve prediction submodule is used to display the tank distribution curve, and the display content includes: the mass percentage content of rare earth elements in the aqueous phase and organic phase.

6. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 5, characterized in that, Rare earth elements selected are La, Ce, Pr, and Nd.

7. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 5, characterized in that, The trough distribution curve prediction submodule is established based on the extraction dynamic equilibrium simulation method in cascade extraction theory.

8. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 5, characterized in that, Interaction is established via the OPC protocol.

9. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 5, characterized in that, A traffic intelligent adjustment and prediction module was built using Visual C++.

10. The method for intelligent flow adjustment in the rare earth extraction production process as described in claim 1, characterized in that, In the trough distribution curve, the horizontal axis represents the series, and the vertical axis represents the purity of the rare earth elements.

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