Method and device for detecting concentration of floating matters in alumina crude liquid, equipment and medium

Abstract

This application provides a method, apparatus, device, and medium for detecting the concentration of suspended solids in crude alumina solution, relating to the field of concentration detection technology. The method includes: acquiring a first transmitted light signal and a first scattered light signal of the crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of the clarified solution after filtration of the crude alumina solution, and a reference transmitted light signal and a reference scattered light signal; determining the transmission normalization characteristics of the crude alumina solution based on the first and second transmitted light signals; determining the scattering normalization characteristics of the crude alumina solution based on the first and second scattered light signals; and then constructing an optical feature vector at the target time to determine the target suspended solids concentration of the crude alumina solution at the target time. The method, apparatus, device, and medium for detecting the concentration of suspended solids in crude alumina solution provided in this application can accurately assess the suspended solids concentration in crude alumina solution.

Description

Technical Field

[0001] This application relates to the field of concentration detection technology, and in particular to a method, apparatus, equipment and medium for detecting the concentration of suspended solids in crude alumina solution. Background Technology

[0002] In the alumina production process, the sedimentation process is a crucial step in separating red mud from the crude liquid (sodium aluminate solution). Changes in the concentration of suspended solids in the crude liquid directly reflect important process indicators of sedimentation efficiency. Currently, the industry mainly relies on manual sampling and offline laboratory analysis methods (such as gravimetric methods) to detect the concentration of suspended solids in the crude liquid. These methods generally suffer from long detection cycles, high reliance on manual labor, and poor real-time performance, making it difficult to meet the real-time sensing and dynamic control requirements of the alumina production process. Summary of the Invention

[0003] This application provides a method, apparatus, equipment, and medium for detecting the concentration of suspended solids in crude alumina liquor, which solves the shortcomings of existing technologies in the rapid, automatic, and timely detection of suspended solids concentration in crude alumina liquor, and achieves rapid, automatic, and timely detection of suspended solids concentration in crude alumina liquor.

[0004] In a first aspect, this application provides a method for detecting the concentration of suspended solids in crude alumina solution, comprising: The method involves acquiring a first transmitted light signal and a first scattered light signal of crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of purified alumina solution, and a reference transmitted light signal and a reference scattered light signal; wherein the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; Based on the first transmitted light signal and the second transmitted light signal, the transmission normalization characteristics of the crude alumina liquid at the target time are determined. Based on the first scattered light signal and the second scattered light signal, the scattering normalization characteristics of the crude alumina liquid at the target time are determined; Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature, an optical feature vector for the target time is constructed; Based on the optical feature vector at the target time, the target suspended solids concentration of the crude alumina solution at the target time is determined.

[0005] Optionally, constructing the optical feature vector for the target time based on the reference transmitted light signal, the reference scattered light signal, the transmission normalized feature, and the scattering normalized feature includes: The sum of the logarithm of the transmission normalized feature and the logarithm of the scattering normalized feature is taken as the combined optical feature of the crude alumina liquid at the target time. Based on the reference transmitted light signal, the reference scattered light signal, the logarithm of the transmission normalized feature, the logarithm of the scattering normalized feature, and the combined optical feature, the optical feature vector of the target time is constructed.

[0006] Optionally, determining the normalized transmission characteristics of the crude alumina solution at the target time based on the first transmitted light signal and the second transmitted light signal includes: The quotient of the second transmitted light signal and the first transmitted light signal is used as the transmission normalization feature.

[0007] Optionally, determining the scattering normalization characteristics of the crude alumina solution at the target time based on the first scattered light signal and the second scattered light signal includes: The quotient of the first scattered light signal and the second scattered light signal is used as the scattering normalization feature.

[0008] Optionally, before determining the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time, the method further includes: Construct optical feature vectors for multiple time points prior to the target time; Determine the optical feature vector at the target time, and the average and standard deviation of the optical feature vectors at multiple times prior to the target time; Based on the optical feature vector at the target time, the average value and the standard deviation, it is determined whether there is any abnormal disturbance in the crude alumina solution at the target time; If the crude alumina solution experiences abnormal disturbances at the target time, an early warning message will be issued.

[0009] Optionally, determining the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time includes: The concentration of the target planktonic matter is obtained by performing concentration characterization based on the optical feature vector at the target time using a preset concentration characterization model. The concentration characterization model is a machine learning model, which is trained in the following manner: Obtain a training sample set; wherein, the training sample set includes multiple sets of optical feature vectors at historical moments and the historical target planktonic concentration corresponding to each set of optical feature vectors at historical moments; The initial characterization model is trained based on the training sample set to obtain the concentration characterization model.

[0010] Optionally, the method for detecting the concentration of suspended solids in crude alumina liquor also includes: At preset time intervals, the actual suspended solids concentration of the target alumina crude solution is obtained by testing; wherein, the target alumina crude solution is the alumina crude solution whose target suspended solids concentration has been determined by the optical feature vector at the target time within the preset time interval of this interval. If the deviation between the actual suspended solids concentration and the target suspended solids concentration in the target alumina crude solution is greater than a preset value, the concentration characterization model is optimized.

[0011] Secondly, this application also provides a device for detecting the concentration of suspended solids in crude alumina solution, comprising: The acquisition module is used to acquire the first transmitted light signal and the first scattered light signal of the crude alumina solution at a target time, the second transmitted light signal and the second scattered light signal of the purified alumina solution, and the reference transmitted light signal and the reference scattered light signal; wherein, the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; The first determining module is used to determine the transmission normalization characteristics of the crude alumina liquid at the target time based on the first transmitted light signal and the second transmitted light signal. The second determining module is used to determine the scattering normalization characteristics of the crude alumina liquid at the target time based on the first scattered light signal and the second scattered light signal. The vector module is used to construct the optical feature vector of the target time based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature; The detection module is used to determine the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time.

[0012] Thirdly, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect.

[0013] Fourthly, this application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect.

[0014] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0015] The method, apparatus, equipment, and medium for detecting suspended solids concentration in alumina crude liquor provided in this application acquire transmitted and scattered light signals from alumina crude liquor, alumina clear liquor, and the background environment. Then, the transmission-normalized and scattering-normalized characteristics of the alumina crude liquor are determined, and an optical feature vector at a target time is constructed. This allows for the determination of the target suspended solids concentration in the alumina crude liquor at the target time. This method eliminates the need for manual intervention and enables timely, rapid, and automated detection of suspended solids concentration. Furthermore, by comprehensively considering both transmitted and scattered light signals, the accuracy of the target suspended solids concentration detection in alumina crude liquor can be improved, meeting the real-time sensing and dynamic control requirements of the alumina production process. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the method for detecting the concentration of suspended solids in crude alumina liquor provided in the embodiments of this application; Figure 2 This is a schematic diagram of the structure of the alumina crude liquid suspended solids concentration detection device provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] This application provides a method for detecting the concentration of suspended solids in crude alumina solution. The execution subject can be a terminal or a server. The following description uses a control terminal as the execution subject of the method.

[0020] The aforementioned servers can be independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers or server clusters providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms. The aforementioned terminals can be smartphones (such as Android phones, iOS phones, etc.), tablets, laptops, digital radio receivers, mobile internet devices (MIDs), handheld computers (PDAs), desktop computers, in-vehicle terminals (such as in-vehicle navigation terminals, in-vehicle computers, etc.), smart speakers, smartwatches, etc., without specific limitations. The terminals and battery management system can be directly or indirectly connected to the network via wired or wireless communication, but are not limited to these methods. Specific details can also be determined based on the actual application scenario requirements, without further limitations.

[0021] The aforementioned networks may include, but are not limited to, wired networks and wireless networks. The wired networks include local area networks (LANs), metropolitan area networks (MANs), and wide area networks (WANs). The wireless networks include Bluetooth, Wi-Fi, and other networks that enable wireless communication.

[0022] Figure 1 This is a schematic flowchart of the method for detecting suspended solids concentration in crude alumina liquor provided in this application. (Refer to...) Figure 1 The method may include: Step 110: Obtain the first transmitted light signal and the first scattered light signal of the crude alumina solution at the target time, the second transmitted light signal and the second scattered light signal of the clear alumina solution, and the reference transmitted light signal and the reference scattered light signal; wherein, the clear alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the clear alumina solution at the target time is located, and the reference scattered light signal is the scattered light signal of the background environment; Step 120: Based on the first transmitted light signal and the second transmitted light signal, determine the transmission normalization characteristics of the crude alumina liquid at the target time; Step 130: Based on the first and second scattered light signals, determine the scattering normalization characteristics of the crude alumina solution at the target time; Step 140: Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalized feature and the scattering normalized feature, construct the optical feature vector of the target time. Step 150: Determine the target suspended solids concentration in the crude alumina solution at the target time based on the optical feature vector at the target time.

[0023] Analysis of this application revealed a mapping relationship between the optical signals of crude alumina solution, such as transmitted or scattered light signals, and the concentration of suspended matter. However, due to the characteristics of crude alumina solution, including high alkalinity, high temperature, high solids content, and strong background fluctuations, coupled with complex phenomena such as particle agglomeration, bubble entrainment, and window contamination, detection methods based on a single optical signal (e.g., single transmitted or scattered light) suffer from insufficient stability in online characterization of suspended matter concentration, sensitivity to dynamic disturbances, poor background adaptability, and significant long-term online drift. Specifically: (1) Under high turbidity conditions, the transmission signal is prone to rapid attenuation, resulting in the loss of effective characterization information; (2) Agglomeration and particle size fluctuations of planktonic particles can easily cause instability in scattering characteristics; (3) Bubble entrainment and flow field fluctuations can easily lead to dynamic drift of detection results; (4) Contamination of the detection window will cause a decrease in long-term online operation stability; (5) Fluctuations in the composition of the crude liquid and operating conditions can easily cause changes in the background absorption and scattering characteristics, resulting in enhanced coupling between the characteristic signals of the planktonic matter and the background signals.

[0024] Furthermore, existing online detection methods lack a common reference mechanism for the optical characteristics of the crude liquid background, making the detection results susceptible to changes in the background and resulting in a decrease in the accuracy and stability of online characterization of suspended matter concentration.

[0025] Therefore, there is an urgent need for an online method for characterizing the concentration of suspended solids in alumina crude liquor, which is suitable for the complex operating conditions and possesses dynamic disturbance suppression and background adaptability. Specifically, this application characterizes the concentration of suspended solids in alumina crude liquor by comprehensively considering both transmitted and scattered light signals.

[0026] The control terminal can detect the background environment, namely the reference transmitted light signal and reference scattered light signal in the empty cuvette state, as blank reference signals. Then, crude alumina solution is introduced into the empty cuvette, and the first transmitted light signal and first scattered light signal of the crude alumina solution at the target time (e.g., the current time) are collected. Further, the control terminal can filter the crude alumina solution at the current time to remove suspended particles, obtain the corresponding clear alumina solution, and collect the second transmitted light signal and second scattered light signal of the clear alumina solution as clear solution reference signals.

[0027] The system employs a blank reference signal to characterize the background optical features of the environment. The clarified liquid, obtained through real-time filtration of the currently detected coarse liquid, shares the same liquid phase composition, temperature conditions, and chemical environment as the coarse liquid, except for the removal of suspended matter particles. Therefore, the clarified liquid and coarse liquid have the same liquid phase composition and chemical environment, and the clarified liquid reference signal can characterize the liquid phase optical features of the coarse liquid under current operating conditions. The coarse liquid detection signal characterizes the comprehensive optical features resulting from the combined effects of suspended matter particles and the background of the coarse liquid. Transmitted light reflects the overall turbidity and light attenuation changes of the coarse liquid, providing stable overall concentration change information for online characterization of suspended matter concentration. Scattered light reflects the changes in scattering intensity caused by suspended matter particles, improving the system's ability to identify changes in suspended matter concentration. The coordinated sensing of transmitted and scattered light enhances the stability of detection results through transmitted light and improves the resolution of suspended matter concentration changes through scattered light, thereby improving the accuracy, stability, and anti-interference capability of online characterization of suspended matter concentration under complex operating conditions. By using the blank reference signal and the clear liquid reference signal as common references for the coarse liquid signal, the particle characteristics of planktonic matter and the optical characteristics of the coarse liquid phase can be effectively separated, enabling accurate and stable online characterization of planktonic matter concentration under complex working conditions.

[0028] The control terminal can determine the scattering normalization characteristics of the crude alumina solution at the target time using the first and second scattered light signals; then, based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization characteristics, and the scattering normalization characteristics, it can construct an optical feature vector at the target time; finally, based on the optical feature vector at the target time, it can perform concentration characterization using a concentration characterization model to determine the target suspended solids concentration of the crude alumina solution at the target time.

[0029] The method for detecting suspended solids concentration in alumina crude liquor provided in this application acquires transmitted and scattered light signals from the alumina crude liquor, alumina clear liquor, and the background environment. Then, it determines the normalized transmission and normalized scattering characteristics of the alumina crude liquor and constructs an optical feature vector at a target time, thereby determining the target suspended solids concentration in the alumina crude liquor at the target time. This method does not rely on manual intervention and can achieve timely, rapid, and automated detection of suspended solids concentration. Furthermore, by comprehensively considering the transmitted and scattered light signals, it can improve the detection accuracy of the target suspended solids concentration in the alumina crude liquor, meeting the real-time sensing and dynamic control requirements of the alumina production process.

[0030] In some embodiments, an optical feature vector at a target time is constructed based on a reference transmitted light signal, a reference scattered light signal, a transmission normalized feature, and a scattering normalized feature. This includes: using the sum of the logarithm of the transmission normalized feature and the logarithm of the scattering normalized feature as the combined optical feature of the crude alumina liquid at the target time; and constructing the optical feature vector at the target time based on the reference transmitted light signal, the reference scattered light signal, the logarithm of the transmission normalized feature, the logarithm of the scattering normalized feature, and the combined optical feature.

[0031] In some embodiments, determining the transmission normalization characteristics of the crude alumina solution at a target time based on the first transmitted light signal and the second transmitted light signal includes: using the quotient of the second transmitted light signal and the first transmitted light signal as the transmission normalization characteristics.

[0032] In some embodiments, determining the scattering normalization characteristics of crude alumina solution at a target time based on the first scattered light signal and the second scattered light signal includes: using the quotient of the first scattered light signal and the second scattered light signal as the scattering normalization characteristics.

[0033] For details on the symbols and meanings of optical signals, please refer to Table 1.

[0034] Table 1. Explanation of Optical Signal Symbols

[0035] To enhance the representation of planktonic features, based on the decoupling of the coarse liquid phase, transmission features, scattering features, and combined transmission and scattering features can be further constructed. By constructing transmission-normalized features and scattering-normalized features, the particle features of planktonic matter can be separated from the features of the coarse liquid phase.

[0036] Specifically, the control terminal can control the target time. The second transmitted light signal With the first transmitted light signal The quotient, as the standardized characteristic of the transmission at the target time. ,in, ; and the target time First scattered light signal With the second scattered light signal The quotient, as the scattering normalization feature at the target time. ,in, By acquiring the transmission-normalized and scattering-normalized characteristics of crude alumina solution, it is possible to achieve light source fluctuation suppression, window contamination compensation, background drift decoupling, and enhancement of planktonic feature information.

[0037] The control terminal can normalize the transmission characteristics at the target time. Logarithmic and scattering normalization characteristics The sum of the logarithms, as the combined optical characteristics of the crude alumina solution at the target time. , Then, based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, the scattering normalization feature, and the combined optical features, an optical feature vector for the target time is constructed. Specifically, the reference transmitted light signal at the target time can be used as the reference transmitted light signal. Reference scattered light signal Logarithm of transmission normalization characteristics Logarithm of scattering normalization feature Combined optical features The combination of these elements serves as the optical feature vector at the target time. ,in, .

[0038] The method for detecting suspended solids concentration in crude alumina liquor provided in this application uses the quotient of the second transmitted light signal and the first transmitted light signal as the transmission normalized feature, the quotient of the first scattered light signal and the second scattered light signal as the scattering normalized feature, and the sum of the logarithms of the transmission normalized feature and the scattering normalized feature as the combined optical feature of the crude alumina liquor at the target time. Then, based on the reference transmitted light signal, the reference scattered light signal, the logarithm of the transmission normalized feature, the logarithm of the scattering normalized feature, and the combined optical feature, an optical feature vector at the target time is constructed. This method can fully utilize the combined optical features of scattering and transmission to accurately establish the mapping relationship between optical features and the suspended solids concentration in crude alumina liquor, thereby accurately detecting the suspended solids concentration in crude alumina liquor.

[0039] In some embodiments, before determining the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time, the method further includes: constructing optical feature vectors for multiple times prior to the target time; determining the optical feature vector at the target time, and the mean and standard deviation of the optical feature vectors at the multiple times prior to the target time; determining whether there is any abnormal disturbance in the crude alumina solution at the target time based on the optical feature vector at the target time, the mean, and the standard deviation; and issuing an early warning if there is any abnormal disturbance in the crude alumina solution at the target time.

[0040] The control terminal can construct optical feature vectors from multiple time points prior to the target time, and then combine them with the optical feature vector at the target time to form a dynamic temporal feature vector. ,in, , These are the optical feature vectors from multiple time points prior to the target time. The time window length, This represents the optical feature vector at the target time. The dynamic temporal feature vector is used to characterize the dynamic changes and disturbances in the concentration of planktonic particles.

[0041] The control terminal then calculates the average value of each optical feature vector in the dynamic temporal feature vector. and standard deviation .in, , The control terminal uses perturbation state variables. This allows for the quantification of disturbances, real-time estimation of disturbance states, and dynamic separation of disturbance information from actual planktonic object state information. If the disturbance amplitude is too large, an abnormal disturbance is detected, and an early warning message is issued, indicating that the current data is subject to significant interference, making it difficult to accurately detect the concentration of airborne particles.

[0042] The method for detecting the concentration of suspended solids in crude alumina liquor provided in this application quantifies whether there are abnormal disturbances in the crude alumina liquor at the target time by using the optical feature vectors, average value, and standard deviation of the data at the target time and multiple times before the target time. If there are abnormal disturbances in the crude alumina liquor at the target time, an early warning message is issued. This method can avoid interference from various disturbances such as bubble entrainment, flow field fluctuations, particle agglomeration, window contamination, and background drift on the detection of suspended solids concentration in crude alumina liquor, thereby improving the accuracy of the detection.

[0043] In some embodiments, determining the target suspended solids concentration of crude alumina solution at a target time based on the optical feature vector at the target time includes: performing concentration characterization based on the optical feature vector at the target time using a preset concentration characterization model to obtain the target suspended solids concentration; wherein, the concentration characterization model is a machine learning model, and the concentration characterization model is trained in the following manner: obtaining a training sample set; wherein, the training sample set includes multiple sets of optical feature vectors at historical times and the historical target suspended solids concentration corresponding to the optical feature vector at each historical time; and training the initial characterization model based on the training sample set to obtain the concentration characterization model.

[0044] In some embodiments, the method for detecting the suspended solids concentration in crude alumina solution further includes: obtaining the actual suspended solids concentration of the target crude alumina solution by means of a laboratory test at preset time intervals; wherein, the target crude alumina solution is the crude alumina solution whose target suspended solids concentration has been determined by the optical feature vector at the target time within the preset time interval; if the deviation between the actual suspended solids concentration and the target suspended solids concentration of the target crude alumina solution is greater than a preset value, optimizing the concentration characterization model.

[0045] The control terminal can predict the concentration of target planktonic matter by characterizing the concentration based on the optical feature vector at the target time using a preset concentration characterization model. Specifically, the concentration characterization model can be a machine learning model, such as a Lightweight Gradient Boosting Machine (LightGBM) model, a random forest model, a support vector regression model, or a neural network model.

[0046] The control terminal can acquire a training sample set including optical feature vectors of multiple historical moments and the historical target planktonic concentration corresponding to the optical feature vectors of each historical moment. Then, the initial representation model is trained using the training sample set. When the number of training times reaches the expected level or the prediction accuracy reaches the expected level, the initial representation model at this time is used as the concentration representation model.

[0047] The control terminal can also initiate the optimization program of the concentration characterization model at preset intervals. For example, within the preset interval, the target alumina crude liquid with the target suspended solids concentration determined by the optical feature vector at the target time is acquired, and the actual suspended solids concentration of the target alumina crude liquid is detected by manual testing. If the deviation between the actual suspended solids concentration and the target suspended solids concentration of the target alumina crude liquid determined by the optical feature vector is greater than a preset value, the parameters of the concentration characterization model can be further optimized.

[0048] The method for detecting the concentration of suspended solids in alumina crude solution provided in this application uses a concentration characterization model obtained through training to predict the target suspended solids concentration in alumina crude solution based on optical feature vectors. Furthermore, the accuracy of the concentration characterization model prediction is detected at preset time intervals, and the concentration characterization model is optimized when the prediction accuracy is low, which can continuously improve the accuracy of suspended solids concentration detection in alumina crude solution.

[0049] Based on the description of the above embodiments, the method provided by this application can: (1) Achieve dynamic separation of crude liquid phase and suspended matter based on characteristics This application constructs a three-state optical reference system consisting of a blank reference, a crude liquid detection system, and a homologous clear liquid reference, thereby achieving dynamic separation of planktonic feature information from crude liquid background information and improving the accuracy of online characterization of planktonic concentration under complex working conditions.

[0050] (2) Improve the stability of online operation under complex working conditions By constructing a transmission and scattering synergistic feature based on a common-source reference constraint, the impact of crude liquid component fluctuations, color changes, and background drift on the detection results is reduced, thereby improving the stability of long-term online operation.

[0051] (3) Improve the system's anti-interference capability This application introduces a dynamic disturbance observation and online compensation mechanism, which can compensate for dynamic disturbances such as bubble entrainment, flow field fluctuations, window contamination and particle agglomeration in real time, thereby improving the anti-interference capability and adaptability of online characterization of suspended matter concentration in complex industrial scenarios.

[0052] The following describes the alumina crude liquor suspended solids concentration detection device provided in this application. The alumina crude liquor suspended solids concentration detection device described below can be referred to in correspondence with the alumina crude liquor suspended solids concentration detection method described above.

[0053] Figure 2 This is a schematic diagram of the structure of the alumina crude liquid suspended solids concentration detection device provided in the embodiments of this application. (Refer to...) Figure 2 The alumina crude liquor suspended solids concentration detection device provided in this application embodiment may include: The acquisition module 210 is used to acquire the first transmitted light signal and the first scattered light signal of the crude alumina solution at a target time, the second transmitted light signal and the second scattered light signal of the purified alumina solution, and the reference transmitted light signal and the reference scattered light signal; wherein, the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; The first determining module 220 is used to determine the transmission normalization characteristics of the crude alumina liquid at the target time based on the first transmitted light signal and the second transmitted light signal. The second determining module 230 is used to determine the scattering normalization characteristics of the crude alumina liquid at the target time based on the first scattered light signal and the second scattered light signal. Vector module 240 is used to construct an optical feature vector for the target time based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature; The detection module 250 is used to determine the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time.

[0054] The alumina crude liquid suspended solids concentration detection device provided in this application acquires the transmitted light signals and scattered light signals of the alumina crude liquid, alumina clear liquid, and background environment. Then, it determines the transmission normalization characteristics and scattering normalization characteristics of the alumina crude liquid and constructs the optical feature vector at the target time, thereby determining the target suspended solids concentration of the alumina crude liquid at the target time. It does not rely on manual labor and can realize timely, rapid, and automated detection of suspended solids concentration. Moreover, by comprehensively considering the transmitted light signals and scattered light signals, it can improve the detection accuracy of the target suspended solids concentration of the alumina crude liquid, meeting the real-time sensing and dynamic control requirements of the alumina production process.

[0055] In some embodiments, the vector module is used for: The sum of the logarithm of the transmission normalized feature and the logarithm of the scattering normalized feature is taken as the combined optical feature of the crude alumina liquid at the target time. Based on the reference transmitted light signal, the reference scattered light signal, the logarithm of the transmission normalized feature, the logarithm of the scattering normalized feature, and the combined optical feature, the optical feature vector of the target time is constructed.

[0056] In some embodiments, the first determining module is configured to: The quotient of the second transmitted light signal and the first transmitted light signal is used as the transmission normalization feature.

[0057] In some embodiments, the second determining module is configured to: The quotient of the first scattered light signal and the second scattered light signal is used as the scattering normalization feature.

[0058] In some embodiments, the detection module is further configured to: Construct optical feature vectors for multiple time points prior to the target time; Determine the optical feature vector at the target time, and the average and standard deviation of the optical feature vectors at multiple times prior to the target time; Based on the optical feature vector at the target time, the average value and the standard deviation, it is determined whether there is any abnormal disturbance in the crude alumina solution at the target time; If the crude alumina solution experiences abnormal disturbances at the target time, an early warning message will be issued.

[0059] In some embodiments, the detection module is used for: The concentration of the target planktonic matter is obtained by performing concentration characterization based on the optical feature vector at the target time using a preset concentration characterization model. The concentration characterization model is a machine learning model, which is trained in the following manner: Obtain a training sample set; wherein, the training sample set includes multiple sets of optical feature vectors at historical moments and the historical target planktonic concentration corresponding to each set of optical feature vectors at historical moments; The initial characterization model is trained based on the training sample set to obtain the concentration characterization model.

[0060] In some embodiments, the detection module is further configured to: At preset time intervals, the actual suspended solids concentration of the target alumina crude solution is obtained by testing; wherein, the target alumina crude solution is the alumina crude solution whose target suspended solids concentration has been determined by the optical feature vector at the target time within the preset time interval of this interval. If the deviation between the actual suspended solids concentration and the target suspended solids concentration in the target alumina crude solution is greater than a preset value, the concentration characterization model is optimized.

[0061] Specifically, the alumina crude liquid suspended solids concentration detection device provided in this application embodiment can realize all the method steps implemented by the method embodiment with the execution subject as the control terminal, and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0062] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 3 As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute a method for detecting the concentration of suspended solids in crude alumina solution, such as: The method involves acquiring a first transmitted light signal and a first scattered light signal of crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of purified alumina solution, and a reference transmitted light signal and a reference scattered light signal; wherein the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; Based on the first transmitted light signal and the second transmitted light signal, the transmission normalization characteristics of the crude alumina liquid at the target time are determined. Based on the first scattered light signal and the second scattered light signal, the scattering normalization characteristics of the crude alumina liquid at the target time are determined; Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature, an optical feature vector for the target time is constructed; Based on the optical feature vector at the target time, the target suspended solids concentration of the crude alumina solution at the target time is determined.

[0063] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0064] On the other hand, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the alumina crude liquor suspended solids concentration detection method provided by the above methods, including, for example: The method involves acquiring a first transmitted light signal and a first scattered light signal of crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of purified alumina solution, and a reference transmitted light signal and a reference scattered light signal; wherein the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; Based on the first transmitted light signal and the second transmitted light signal, the transmission normalization characteristics of the crude alumina liquid at the target time are determined. Based on the first scattered light signal and the second scattered light signal, the scattering normalization characteristics of the crude alumina liquid at the target time are determined; Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature, an optical feature vector for the target time is constructed; Based on the optical feature vector at the target time, the target suspended solids concentration of the crude alumina solution at the target time is determined.

[0065] Furthermore, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to perform the steps of the alumina crude liquor suspended solids concentration detection method provided by the above methods, for example including: The method involves acquiring a first transmitted light signal and a first scattered light signal of crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of purified alumina solution, and a reference transmitted light signal and a reference scattered light signal; wherein the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; Based on the first transmitted light signal and the second transmitted light signal, the transmission normalization characteristics of the crude alumina liquid at the target time are determined. Based on the first scattered light signal and the second scattered light signal, the scattering normalization characteristics of the crude alumina liquid at the target time are determined; Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature, an optical feature vector for the target time is constructed; Based on the optical feature vector at the target time, the target suspended solids concentration of the crude alumina solution at the target time is determined.

[0066] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0067] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0068] It should also be noted that in the embodiments of this application, the terms "first," "second," etc., are used to distinguish similar objects, and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, and the number of objects is not limited. For example, the first object can be one or more.

[0069] In this application embodiment, the term "and / or" describes the association relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0070] In this application's embodiments, "determine B based on A" means that factor A must be considered when determining B. It is not limited to "B can be determined based solely on A," but should also include: "determine B based on A and C," "determine B based on A, C, and E," "determine C based on A, and further determine B based on C," etc. Additionally, it can include using A as a condition for determining B, for example, "when A meets the first condition, determine B using the first method"; another example, "when A meets the second condition, determine B," etc.; another example, "when A meets the third condition, determine B based on the first parameter," etc. Of course, it can also be a condition where A is a factor in determining B, for example, "when A meets the first condition, determine C using the first method, and further determine B based on C," etc.

[0071] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0072] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for detecting the concentration of suspended solids in crude alumina solution, characterized in that, include: The method involves acquiring a first transmitted light signal and a first scattered light signal of crude alumina solution at a target time, a second transmitted light signal and a second scattered light signal of purified alumina solution, and a reference transmitted light signal and a reference scattered light signal; wherein the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; Based on the first transmitted light signal and the second transmitted light signal, the transmission normalization characteristics of the crude alumina liquid at the target time are determined. Based on the first scattered light signal and the second scattered light signal, the scattering normalization characteristics of the crude alumina liquid at the target time are determined; Based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature, an optical feature vector for the target time is constructed; Based on the optical feature vector at the target time, the target suspended solids concentration of the crude alumina solution at the target time is determined.

2. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 1, characterized in that, The construction of the optical feature vector at the target time based on the reference transmitted light signal, the reference scattered light signal, the transmission normalized feature, and the scattering normalized feature includes: The sum of the logarithm of the transmission normalized feature and the logarithm of the scattering normalized feature is taken as the combined optical feature of the crude alumina liquid at the target time. Based on the reference transmitted light signal, the reference scattered light signal, the logarithm of the transmission normalized feature, the logarithm of the scattering normalized feature, and the combined optical feature, the optical feature vector of the target time is constructed.

3. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 1, characterized in that, The determination of the transmission normalization characteristics of the crude alumina solution at the target time based on the first transmitted light signal and the second transmitted light signal includes: The quotient of the second transmitted light signal and the first transmitted light signal is used as the transmission normalization feature.

4. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 1, characterized in that, The step of determining the scattering normalization characteristics of the crude alumina solution at the target time based on the first scattered light signal and the second scattered light signal includes: The quotient of the first scattered light signal and the second scattered light signal is used as the scattering normalization feature.

5. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 1, characterized in that, Before determining the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time, the method further includes: Construct optical feature vectors for multiple time points prior to the target time; Determine the optical feature vector at the target time, and the average and standard deviation of the optical feature vectors at multiple times prior to the target time; Based on the optical feature vector at the target time, the average value and the standard deviation, it is determined whether there is any abnormal disturbance in the crude alumina solution at the target time; If the crude alumina solution experiences abnormal disturbances at the target time, an early warning message will be issued.

6. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 1, characterized in that, Determining the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time includes: The concentration of the target planktonic matter is obtained by performing concentration characterization based on the optical feature vector at the target time using a preset concentration characterization model. The concentration characterization model is a machine learning model, which is trained in the following manner: Obtain a training sample set; wherein, the training sample set includes multiple sets of optical feature vectors at historical moments and the historical target planktonic concentration corresponding to each set of optical feature vectors at historical moments; The initial characterization model is trained based on the training sample set to obtain the concentration characterization model.

7. The method for detecting the concentration of suspended solids in crude alumina liquor according to claim 6, characterized in that, Also includes: At preset time intervals, the actual suspended solids concentration of the target alumina crude solution is obtained by testing; wherein, the target alumina crude solution is the alumina crude solution whose target suspended solids concentration has been determined by the optical feature vector at the target time within the preset time interval of this interval. If the deviation between the actual suspended solids concentration and the target suspended solids concentration in the target alumina crude solution is greater than a preset value, the concentration characterization model is optimized.

8. A device for detecting the concentration of suspended solids in crude alumina solution, characterized in that, include: The acquisition module is used to acquire the first transmitted light signal and the first scattered light signal of the crude alumina solution at a target time, the second transmitted light signal and the second scattered light signal of the purified alumina solution, and the reference transmitted light signal and the reference scattered light signal; wherein, the purified alumina solution is obtained by filtering the crude alumina solution at the target time; the reference transmitted light signal is the transmitted light signal of the background environment in which the crude alumina solution or the purified alumina solution is located at the target time, and the reference scattered light signal is the scattered light signal of the background environment; The first determining module is used to determine the transmission normalization characteristics of the crude alumina liquid at the target time based on the first transmitted light signal and the second transmitted light signal. The second determining module is used to determine the scattering normalization characteristics of the crude alumina liquid at the target time based on the first scattered light signal and the second scattered light signal. The vector module is used to construct the optical feature vector of the target time based on the reference transmitted light signal, the reference scattered light signal, the transmission normalization feature, and the scattering normalization feature; The detection module is used to determine the target suspended solids concentration of the crude alumina solution at the target time based on the optical feature vector at the target time.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for detecting the concentration of suspended solids in crude alumina liquor as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for detecting the concentration of suspended solids in crude alumina liquor as described in any one of claims 1 to 7.

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