Sodium aluminate solution online analysis system and method

Abstract

The invention relates to the technical field of sodium aluminate solution analysis, and provides a sodium aluminate solution on-line analysis system and method.The sodium aluminate solution on-line analysis system comprises an on-line sampling module used for automatically collecting a sodium aluminate solution sample from a production pipeline and conducting pretreatment on the sodium aluminate solution sample, and filtering suspended particles and conducting automatic dilution according to the concentration range; the multi-channel analysis module integrates a near infrared spectrum analysis unit, a potentiometric titration analysis unit and a conductivity / TOC sensor unit and is used for synchronously detecting the contents of aluminum oxide, total alkali, caustic alkali and carbon alkali in the sodium aluminate solution; and the intelligent control module is based on a PLC (Programmable Logic Controller) or an industrial computer and is used for controlling an analysis process and optimizing detection parameters. Through synchronous operation of the multi-channel module, the traditional manual detection period of 2-6 hours is greatly shortened to 20-40 minutes, and the real-time performance is improved by matching with the full-process automatic design of automatic sampling, filtering and diluting; meanwhile, due to cooperative application of technologies such as near infrared spectrum and potentiometric titration, the detection precision reaches + / -0.5%.

Description

Technical Field

[0001] This invention relates to the field of sodium aluminate solution analysis technology, specifically to an online analysis system and method for sodium aluminate solution. Background Technology

[0002] In the alumina production process, sodium aluminate solution is a core intermediate product in the leaching process. The accurate analysis of its composition (such as aluminum oxide, total alkali, caustic soda, and carbon-alkali content) directly affects leaching efficiency, decomposition rate, and product quality stability. With the alumina industry's transformation towards intelligent and continuous production, the demand for real-time online analysis of sodium aluminate solution is increasingly urgent. There is a pressing need for an analytical system that can adapt to the dynamic operating conditions of the production pipeline and provide accurate compositional data to support the real-time control of process parameters.

[0003] Currently, the compositional analysis of sodium aluminate solutions still largely relies on manual operations, such as manual titration and ignition weighing. These techniques suffer from drawbacks, including long testing cycles of 2–6 hours, significant human error (accuracy only ±1.5%), and high labor intensity. Furthermore, some existing automated testing equipment only detects single indicators (such as alumina or total alkali), lacking the ability to simultaneously analyze multiple components. This results in the inability to obtain comprehensive compositional data in a timely manner during production, hindering the coordinated optimization of process parameters. More importantly, traditional testing methods have poor integration with the production system; testing data cannot be fed back to the Manufacturing Execution System (MES) in real time to form a "detection-control" closed loop, leading to lag in production adjustments and potentially causing product quality fluctuations and raw material waste. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an online analysis system and method for sodium aluminate solution, which solves the problems of long detection cycles, large human error, and high labor intensity.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an online analysis system for sodium aluminate solution, comprising:

[0006] Online sampling module: used to automatically collect sodium aluminate solution samples from the production pipeline and pre-treat them, including filtering suspended particles and automatically diluting according to the concentration range;

[0007] Multi-channel analysis module: integrates near-infrared spectroscopy analysis unit, potentiometric titration analysis unit and conductivity / TOC sensor unit, used for simultaneous detection of aluminum oxide, total alkali, caustic soda and carbon alkali content in sodium aluminate solution;

[0008] Intelligent control module: Based on PLC or industrial computer, used to control the analysis process and optimize detection parameters, including temperature, reaction time and sample flow rate;

[0009] Data processing module: Uses partial least squares regression algorithm to correct the detection data, compares it with historical data in real time and triggers anomaly warnings;

[0010] Data upload module: Uploads analysis results to the manufacturing execution system in real time via OPC-UA or Industrial IoT protocol;

[0011] Calibration and maintenance module: Supports automatic calibration and fault diagnosis, reducing the need for manual intervention;

[0012] Online monitoring system: Electrically connected to the multi-channel analysis module, intelligent control module, data processing module and data upload module, used to coordinate the operation of each module and control the adjustment of production parameters based on the detection results.

[0013] Preferably, the online sampling module includes a corrosion-resistant pump, a microporous filter, and an automatic dilution unit, wherein the automatic dilution unit dynamically dilutes high-concentration samples according to a preset concentration threshold.

[0014] Preferably, in the multi-channel analysis module: the near-infrared spectroscopy analysis unit is used to determine the content of aluminum oxide and caustic soda, with a detection wavelength range of 1000–2500 nm; the potentiometric titration analysis unit is used to determine the content of total alkali and carbon alkali, with a titration accuracy of ±0.1 mL; and the conductivity / TOC sensor unit is used to monitor the organic carbon content in the solution, with a detection range of 0.1–1000 ppm.

[0015] Preferably, the intelligent control module dynamically adjusts the detection parameters through a PID algorithm to ensure analysis stability, wherein the temperature control accuracy is ±0.5℃ and the reaction time control accuracy is ±1s.

[0016] Preferably, the data processing module further includes a machine learning model for predicting component fluctuation trends and optimizing detection parameters based on historical data.

[0017] Preferably, the data upload module supports bidirectional communication with the MES system to achieve closed-loop feedback between detection data and production control.

[0018] Preferably, the calibration and maintenance module includes an automatic cleaning unit and a standard sample calibration unit, with a calibration frequency of once every 24 hours.

[0019] An online analysis method for sodium aluminate solution includes the following steps:

[0020] Step 1: Automatically collect sodium aluminate solution samples using an online sampling module, and perform filtration and dilution pretreatment;

[0021] Step 2: Simultaneously detect the contents of aluminum oxide, total alkali, caustic soda, and carbon alkali using a multi-channel analysis module;

[0022] Step 3: Optimize detection parameters through the intelligent control module to ensure analysis stability;

[0023] Step 4: Use the PLS algorithm to correct the detection data and compare it with historical data in real time;

[0024] Step 5: Upload the analysis results to the MES system and adjust the production process parameters based on the test results.

[0025] Preferably, the detection time of the multi-channel analysis module is 20 to 40 minutes, and the detection accuracy is ±0.5%.

[0026] Preferably, the method further includes an automatic calibration step, with a calibration frequency of once every 24 hours.

[0027] This invention provides an online analysis system and method for sodium aluminate solution. It has the following beneficial effects:

[0028] 1. This invention significantly reduces the traditional 2-6 hour manual testing cycle to 20-40 minutes through synchronous operation of multi-channel modules. Combined with the fully automated design of automatic sampling, filtration and dilution, the real-time performance is improved. At the same time, the synergistic application of near-infrared spectroscopy and potentiometric titration technologies enables the detection accuracy to reach ±0.5%. The intelligent control module uses PID algorithm to precisely regulate parameters such as temperature and flow rate, further ensuring the stability of the detection and reducing the error compared to traditional methods.

[0029] 2. This invention achieves simultaneous analysis and closed-loop management of multiple component indicators. Integrating near-infrared spectroscopy, potentiometric titration, and TOC sensors, it can simultaneously measure key parameters such as alumina, total alkali, and carbon-alkali, avoiding the lag of single-indicator detection. Through real-time linkage with the MES system via the OPC-UA protocol, when anomalies such as excessive carbon-alkali are detected, the system can automatically adjust production parameters such as lime addition, achieving dynamic optimization within 30 minutes. Combined with the LSTM model for early prediction of component fluctuations, it provides precise decision support for production process control.

[0030] 3. This invention effectively reduces labor costs and improves industrial adaptability through automated design and a compatible architecture. The calibration and maintenance module supports 24-hour automatic calibration and fault diagnosis, reducing the need for manual intervention and lowering maintenance costs. The data processing module continuously optimizes detection parameters by comparing historical data with the PLS algorithm. The standardized industrial protocol and modular design not only facilitate seamless integration with existing intelligent manufacturing systems but also reserve space for future functional expansion, providing an efficient and flexible technical solution for the digital transformation of alumina production. Attached Figure Description

[0031] Figure 1 This is a flowchart of the present invention;

[0032] Figure 2 This is a system diagram of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Example:

[0035] Please see the appendix Figure 1 - Appendix Figure 2 This invention provides an online analysis system for sodium aluminate solution, comprising:

[0036] Online sampling module: used to automatically collect sodium aluminate solution samples from the production pipeline and pre-treat them, including filtering suspended particles and automatically diluting according to the concentration range;

[0037] Multi-channel analysis module: integrates near-infrared spectroscopy analysis unit, potentiometric titration analysis unit and conductivity / TOC sensor unit, used to simultaneously detect the contents of aluminum oxide (Al2O3), total alkali (Na2O), caustic soda (NaOH) and carbonaceous soda (Na2CO3) in sodium aluminate solution;

[0038] Intelligent control module: Based on PLC or industrial computer, used to control the analysis process and optimize detection parameters, including temperature, reaction time and sample flow rate;

[0039] Data processing module: Uses partial least squares regression algorithm to correct the detection data, compares it with historical data in real time and triggers anomaly warnings;

[0040] Data upload module: Uploads analysis results to the manufacturing execution system in real time via OPC-UA or Industrial IoT protocol;

[0041] Calibration and maintenance module: Supports automatic calibration and fault diagnosis, reducing the need for manual intervention;

[0042] Online monitoring system: Electrically connected to the multi-channel analysis module, intelligent control module, data processing module, and data upload module, used to coordinate the operation of each module and control the adjustment of production parameters based on the detection results.

[0043] The online sampling module includes a corrosion-resistant pump, a microporous filter, and an automatic dilution unit. The automatic dilution unit dynamically dilutes high-concentration samples according to a preset concentration threshold. The multi-channel analysis module includes: a near-infrared spectroscopy unit for determining the content of aluminum oxide and caustic soda, with a detection wavelength range of 1000–2500 nm; a potentiometric titration unit for determining the content of total alkali and carbon alkali, with a titration accuracy of ±0.1 mL; and a conductivity / TOC sensor unit for monitoring the organic carbon content in the solution, with a detection range of 0.1–1000 ppm. The intelligent control module dynamically adjusts the detection parameters using a PID algorithm to ensure analytical stability, with temperature control accuracy of ±0.5℃ and reaction time control accuracy of ±1 s. The data processing module also includes a machine learning model for predicting component fluctuation trends and optimizing detection parameters based on historical data. The data upload module supports bidirectional communication with the MES system, achieving closed-loop feedback between detection data and production control. The calibration and maintenance module includes an automatic cleaning unit and a standard sample calibration unit, with a calibration frequency of once every 24 hours.

[0044] Specifically, the online sampling module uses a centrifugal pump made of fluoroplastic material, which is resistant to the high corrosiveness of sodium aluminate solution. The flow rate control range is 50-200 mL / min. Automatic start-up and flow rate adjustment are achieved through PLC control to ensure the stability of sample collection. It has a built-in 0.22 μm polytetrafluoroethylene membrane filter element and adopts cross-flow filtration to effectively remove suspended aluminum hydroxide particles and mechanical impurities in the solution. The filtration pressure is maintained at 0.1-0.3 MPa to avoid filter element clogging. It also integrates a peristaltic pump and a proportional valve, and presets concentration thresholds (e.g., triggered when Al2O3 concentration > 200 g / L). It achieves gradient dilution of 1:1 to 1:10 through dynamic ratio of deionized water with a dilution accuracy of ±2%, ensuring that the subsequent detection instrument is not damaged by high concentration samples. That is, after the sample is drawn from the production pipeline by the corrosion-resistant pump, it is first purified by a microporous filter and then monitored in real time by a concentration sensor. If the threshold is exceeded, the dilution unit is automatically started. The diluted sample is stored in a constant temperature sample cell (temperature controlled at 25±1℃) for analysis.

[0045] The near-infrared spectroscopy analysis unit uses a Fourier transform near-infrared spectrometer with a wavelength range of 1000–2500 nm and a resolution of 8 cm⁻¹. -1 The scanning speed was 10 scans per second. Al-O bonds (1650 nm) and OH groups were collected. - The characteristic absorption peak at (3400 nm) was used, combined with the partial least squares (PLS) model, to detect Al2O3 (detection range 50–300 g / L) and caustic soda (Na2O). k Quantitative analysis with a detection range of 80–250 g / L, repeatability of ±0.3%, non-contact detection, no chemical reagents required, and analysis cycle ≤5 minutes;

[0046] The potentiometric titration analysis unit employs an automated potentiometric titrator equipped with a composite pH electrode and silver nitrate titrant (0.1 mol / L), achieving a titration accuracy of ±0.1 mL. Total alkali (Na₂O₂) is determined using a two-step titration method. t ) and alkali (Na2O) e The first step is to use phenolphthalein as an indicator and titrate with standard hydrochloric acid solution to the endpoint to determine the total alkali content. The second step is to add barium chloride to precipitate carbonate ions, and then titrate with hydrochloric acid to calculate the carbon-alkali content.

[0047] The conductivity / TOC sensor unit uses a four-electrode titanium alloy electrode with a detection range of 0.1–100 mS / cm to monitor the ionic strength of the solution. The TOC sensor uses a combustion oxidation-non-dispersive infrared method with a detection range of 0.1–1000 ppm and a response time of <2 minutes to monitor the impact of organic carbon pollution (such as sodium oxalate) on production in real time.

[0048] The intelligent control module utilizes an Advantech industrial computer as its core, equipped with WinCC monitoring software. It employs a PID algorithm to achieve multi-parameter collaborative control: Temperature control: The sample cell and reaction unit are equipped with a PT100 temperature sensor and an electric heating rod. PID parameters (Kp = 2.5, Ti = 120s, Td = 30s) are adjusted to stabilize the temperature within ±0.5℃ of the set value, preventing temperature fluctuations from interfering with the spectrum and titration reaction. Reaction time control: During the titration reaction stage, a timer precisely controls the stirring time (e.g., 30±1s) to ensure sufficient indicator color development. The isothermal equilibrium time before spectral acquisition is controlled at 5±1s to ensure signal stability. Flow rate regulation: An electromagnetic flowmeter linked with a proportional valve maintains the sample flow rate at 100±5mL / min, preventing flow rate fluctuations from causing a decrease in detection repeatability.

[0049] In the data processing and intelligent analysis module, the PLS algorithm calibration process establishes a standard sample database (covering concentration gradients of components such as Al2O3 and total alkali), collects near-infrared spectroscopy and titration data, and constructs a prediction model using the PLS algorithm. The model correlation coefficient R0 is... 2 With a mean square error (RMSE) >0.995 and a root mean square error (RMSE) <0.5%, the system automatically inputs spectral data into the model calculation during real-time detection and cross-validates it with the titration results. If the deviation exceeds 1%, an early warning is triggered. The machine learning prediction model uses an LSTM (Long Short-Term Memory) model, inputting parameters such as component concentration, temperature, and flow rate from the past 24 hours to predict the component fluctuation trend for the next hour, with a prediction error <0.8%. For example, when the system predicts that the Al2O3 concentration is about to decrease, it automatically prompts for adjustment of the leaching process parameters.

[0050] Data upload and closed-loop control: The data upload module interfaces with the MES system via the OPC-UA protocol (supporting TLS1.2 encryption), transmitting data once per minute. The data includes fields such as real-time concentration data, equipment status codes, and warning information. When the carbon-alkali content is detected to exceed 30 g / L, the system automatically sends an instruction to the leaching process to increase the lime addition by 5%, and records the carbon-alkali change trend within 30 minutes after the adjustment, forming a control closed loop.

[0051] The calibration process in the calibration and maintenance module is a routine calibration: the calibration program is automatically started at 2:00 AM every day, using the sodium aluminate standard solution specified in GB / T6609.2-2022 (e.g., Al2O3 = 150 g / L, Na2O...). t =200g / L) for spectral and titration calibration. Automatic recalibration is performed when the calibration deviation exceeds 1%. Cleaning procedure: After each test, rinse the titration tubing three times with deionized water (conductivity <1μS / cm) and wipe the spectrometer window with ethanol to prevent sample residue. Its built-in sensor fault detection algorithm will automatically switch to the backup sensor and generate a maintenance work order if an abnormal TOC sensor signal is detected (deviation >5% for 10 minutes). The system will notify the maintenance personnel via SMS.

[0052] An online analysis method for sodium aluminate solution includes the following steps:

[0053] Step 1: Automatically collect sodium aluminate solution samples using an online sampling module, and perform filtration and dilution pretreatment;

[0054] Step 2: Simultaneously detect the contents of aluminum oxide, total alkali, caustic soda, and carbon alkali using a multi-channel analysis module;

[0055] Step 3: Optimize detection parameters through the intelligent control module to ensure analysis stability;

[0056] Step 4: Use the PLS algorithm to correct the detection data and compare it with historical data in real time;

[0057] Step 5: Upload the analysis results to the MES system and adjust the production process parameters based on the test results.

[0058] The detection time of the multi-channel analysis module is 20 to 40 minutes, and the detection accuracy is ±0.5%. The method also includes an automatic calibration step, with a calibration frequency of once every 24 hours and a calibration standard of GB / T6609.2-2022.

[0059] Specifically, the sampling cycle during the sample pretreatment stage is as follows: automatic sampling every 30 minutes, with a sampling volume of 500 mL. After filtration, 100 mL is taken to the dilution unit. If the Al2O3 concentration is >200 g / L, it is diluted 5 times. When the Al2O3 concentration is detected to be lower than the target value (e.g., 180 g / L), the system sends a command to the dissolution tank to increase the dissolution temperature from 240℃ to 245℃ and increase the circulating mother liquor flow rate by 10%. After 30 minutes, the concentration is retested and rises back to 185 g / L, thus achieving dynamic optimization.

[0060] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An online analysis system for sodium aluminate solution, characterized in that, include: Online sampling module: used to automatically collect sodium aluminate solution samples from the production pipeline and pre-treat them, including filtering suspended particles and automatically diluting according to the concentration range; Multi-channel analysis module: integrates near-infrared spectroscopy analysis unit, potentiometric titration analysis unit and conductivity / TOC sensor unit, used for simultaneous detection of aluminum oxide, total alkali, caustic soda and carbon alkali content in sodium aluminate solution; Intelligent control module: Based on PLC or industrial computer, used to control the analysis process and optimize detection parameters, including temperature, reaction time and sample flow rate; Data processing module: Uses partial least squares regression algorithm to correct the detection data, compares it with historical data in real time and triggers anomaly warnings; Data upload module: Uploads analysis results to the manufacturing execution system in real time via OPC-UA or Industrial IoT protocol; Calibration and maintenance module: Supports automatic calibration and fault diagnosis, reducing the need for manual intervention; Online monitoring system: Electrically connected to the multi-channel analysis module, intelligent control module, data processing module and data upload module, used to coordinate the operation of each module and control the adjustment of production parameters based on the detection results.

2. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, The online sampling module includes a corrosion-resistant pump, a microporous filter, and an automatic dilution unit. The automatic dilution unit dynamically dilutes high-concentration samples according to a preset concentration threshold.

3. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, In the multi-channel analysis module: the near-infrared spectroscopy analysis unit is used to determine the content of aluminum oxide and caustic soda, with a detection wavelength range of 1000–2500 nm; the potentiometric titration analysis unit is used to determine the content of total alkali and carbon alkali, with a titration accuracy of ±0.1 mL; the conductivity / TOC sensor unit is used to monitor the organic carbon content in the solution, with a detection range of 0.1–1000 ppm.

4. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, The intelligent control module dynamically adjusts the detection parameters through a PID algorithm to ensure analysis stability, with temperature control accuracy of ±0.5℃ and reaction time control accuracy of ±1s.

5. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, The data processing module also includes a machine learning model for predicting component fluctuation trends and optimizing detection parameters based on historical data.

6. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, The data upload module supports bidirectional communication with the MES system, enabling closed-loop feedback between detection data and production control.

7. The online analysis system for sodium aluminate solution according to claim 1, characterized in that, The calibration and maintenance module includes an automatic cleaning unit and a standard sample calibration unit, with a calibration frequency of once every 24 hours.

8. An online analysis method for sodium aluminate solution, using an online analysis system for sodium aluminate solution as described in any one of claims 1-7, characterized in that, Includes the following steps: Step 1: Automatically collect sodium aluminate solution samples using an online sampling module, and perform filtration and dilution pretreatment; Step 2: Simultaneously detect the contents of aluminum oxide, total alkali, caustic soda, and carbon alkali using a multi-channel analysis module; Step 3: Optimize detection parameters through the intelligent control module to ensure analysis stability; Step 4: Use the PLS algorithm to correct the detection data and compare it with historical data in real time; Step 5: Upload the analysis results to the MES system and adjust the production process parameters based on the test results.

9. The online analysis method for sodium aluminate solution according to claim 8, characterized in that, The detection time of the multi-channel analysis module is 20 to 40 minutes, and the detection accuracy is ±0.5%.

10. The method for online analysis of sodium aluminate solution according to claim 8, characterized in that, The method also includes an automatic calibration step, with a calibration frequency of once every 24 hours.

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