Alumina calcination process monitoring method based on DCS control
By using a DCS-based alumina calcination process monitoring method, the calcination process can be monitored and adjusted in real time using a preset model. This solves the problem of strong subjectivity in existing technologies' human monitoring, realizes the intelligent and precise operation of the alumina calcination process, and improves product quality and equipment operating efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HENAN TIANMA NEW MATERIALS CO LTD
- Filing Date
- 2025-06-19
- Publication Date
- 2026-06-09
AI Technical Summary
The existing process monitoring of alumina calcination relies on human monitoring, which is highly subjective. The DCS system can only realize single-variable threshold alarms and lacks intelligent and multi-variable monitoring, resulting in unstable alumina quality.
A DCS-based alumina calcination process monitoring method is adopted. By acquiring alumina raw material information and calcination requirements, inputting a preset alumina process model, the calcination information is monitored in real time. Based on the model, the calcination results and parameter suggestions are judged, and the process is automatically adjusted to ensure the scientificity and accuracy of the calcination process.
Intelligent monitoring of the alumina calcination process has been achieved, which has improved the stability of alumina quality and the safety of equipment operation, and reduced human error and energy consumption.
Smart Images
Figure CN120783904B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of alumina calcination, and in particular to a method for monitoring the alumina calcination process based on DCS control. Background Technology
[0002] Alumina (chemical formula Al₂O₃) is an inorganic compound with high hardness and a high melting point, and it has a wide range of industrial applications. Alumina calcination is a core step in the Bayer process or sintering process for producing alumina, and its process monitoring directly affects product quality, energy consumption, and equipment lifespan. Current process monitoring of alumina calcination is often done manually, which is highly subjective and requires highly experienced professionals. Existing DCS systems can only achieve single-variable threshold alarms, and the monitoring content is relatively limited. Therefore, how to intelligently monitor the alumina calcination process and improve alumina quality is a key research focus. Summary of the Invention
[0003] To address the aforementioned problems, the present invention aims to provide a DCS-based method for monitoring alumina calcination processes, which can intelligently monitor the alumina calcination process and improve alumina quality.
[0004] Based on this, the present invention provides a method for monitoring alumina calcination process based on DCS control, the method comprising:
[0005] Obtain alumina raw material information and calcination requirements. The alumina raw material information includes: alumina content and alumina raw material weight. The calcination requirements include: alumina weight, calcination mode, and required alumina type. The calcination mode includes normal mode, environmental protection mode, and energy-saving mode.
[0006] The alumina raw material information and the calcination requirements are input into a preset alumina process model, and the alumina process model outputs calcination results and process parameter suggestions.
[0007] The alumina raw material is calcined in the calcining equipment according to the process parameters recommended above, and the calcination information of the alumina raw material in the calcining equipment is acquired in real time.
[0008] When the calcination information is input into the alumina process model, the alumina process model determines whether the calcination information is normal. If it is not normal, the operation of the calcination equipment is stopped.
[0009] The alumina process model includes a normal process detection algorithm, which includes determining whether the effective alumina weight is greater than the alumina weight required for calcination. If not, the calcination result is that calcination is not feasible and the operation of the calcination equipment is stopped. The process of obtaining the effective alumina includes:
[0010] After multiplying the alumina content by the adsorption value, the sum of the product values of each impurity content and the corresponding impurity influence coefficient is subtracted to obtain the first subtraction. The first subtraction is then multiplied by the weight of the alumina raw material to obtain the effective alumina weight.
[0011] The adsorption value is equal to the product of the second preset coefficient and the value measured by the isothermal adsorption method, plus the value of the first preset coefficient.
[0012] Wherein, when the calcination result indicates that calcination is feasible, the calcination method is output according to the calcination mode in the calcination requirements, including:
[0013] If the calcination mode is normal mode, then fuel heating is used to heat the calcination equipment;
[0014] If the calcination mode is an environmentally friendly mode, then electric heating is used to heat the calcination equipment;
[0015] If the calcination mode is an energy-saving mode, then the calcination equipment is heated by a combination of fuel heating and electric heating.
[0016] Wherein, when the calcination result is that calcination is feasible, the calcination process is output according to the required alumina type in the calcination requirements, including:
[0017] If the required alumina type is γ-alumina, then a pre-set single-stage calcination process is adopted;
[0018] If the required alumina type is β-type alumina, then a pre-set two-stage calcination process is adopted;
[0019] If the required alumina type is α-alumina, then a pre-set three-stage calcination process is adopted.
[0020] When the calcination mode is normal mode, the alumina process model outputs the amount of fuel used for calcination based on the alumina raw material information;
[0021] The fuel consumption information and heating stage information are monitored and fed back to the alumina process model. The alumina process model determines whether the consumption information and the heating stage information match, and outputs whether the calcination equipment has experienced a calcination abnormality based on the matching result.
[0022] The heating stage information includes the temperature information and calcination time inside the calcination equipment. The current calcination stage of the alumina raw material is determined based on the temperature information and calcination time. When the fuel consumption in the current calcination stage exceeds the corresponding preset fuel consumption threshold, the alumina process model outputs a calcination anomaly.
[0023] The alumina process model includes:
[0024] A normal process detection algorithm module is used to receive the alumina raw material information and the calcination requirements, and to output the calcination results.
[0025] The calcination method module and the calcination process module are connected to the process normal detection algorithm module. Both the calcination method module and the calcination process module receive the alumina raw material information and the calcination requirements. The calcination method module is used to output the calcination method, and the calcination process module is used to output the calcination process.
[0026] The calcination method module is connected to the calcination process module and the process parameter module, and the process parameter module is used to output the process parameter suggestions.
[0027] The process parameter module is also connected to the process monitoring module, which is used to determine whether any abnormalities occur during the actual calcination process.
[0028] The method further includes: when the alumina raw material is calcined using a combination of resistance and microwave heating, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is greater than the internal temperature and the internal temperature is greater than a preset first minimum calcination temperature, the power of the resistance heating is reduced by unit power.
[0029] When the alumina raw material is calcined using a heating method combining fuel and microwave, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is greater than the internal temperature and the internal temperature is greater than the preset second minimum calcination temperature, the proportion of high-calorific-value coal added to the fuel is reduced by a unit percentage.
[0030] The calcination information further includes: environmental data inside the calcination equipment, including pressure data, temperature data, and gas data. The DTW algorithm built into the calcination monitoring module calculates anomaly scores based on the environmental data. When the anomaly score is within a first preset score range, the calcination monitoring module outputs the process parameter suggestions. When the anomaly score is greater than the anomaly score threshold, the operation of the calcination equipment is stopped.
[0031] In this invention, firstly, information on alumina raw materials and calcination requirements are obtained. The alumina raw material information includes alumina content and alumina raw material weight. The calcination requirements include alumina weight, calcination mode, and required alumina type. The calcination mode includes normal mode, environmentally friendly mode, and energy-saving mode. Both the alumina raw material information and the calcination requirements are obtained in advance by personnel.
[0032] The alumina raw material information and calcination requirements are input into a preset alumina process model, which outputs calcination results and process parameter suggestions. The alumina process model determines the feasibility of calcination and provides scientifically sound process reference suggestions.
[0033] The alumina raw material is calcined in the calcining equipment according to the recommended process parameters, and the calcination information of the alumina raw material in the calcining equipment is acquired in real time. The calcination information includes environmental data inside the calcining equipment.
[0034] When the calcination information is input into the alumina process model, the alumina process model determines whether the calcination information is normal. If it is abnormal, the operation of the calcination equipment is stopped. The alumina process model can also make real-time adjustments to the process parameters based on the calcination information, making the alumina calcination process more precise and of better quality. Attached Figure Description
[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0036] Figure 1 This is a flowchart of a DCS-based alumina calcination process monitoring method provided in an embodiment of the present invention;
[0037] Figure 2 This is a schematic diagram of the alumina process module provided in an embodiment of the present invention. Detailed Implementation
[0038] 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.
[0039] Figure 1 This is a flowchart of a DCS-based alumina calcination process monitoring method provided in an embodiment of the present invention. The method includes:
[0040] S101. Obtain alumina raw material information and calcination requirements. The alumina raw material information includes: alumina content and alumina raw material weight. The calcination requirements include: alumina weight, calcination mode, and required alumina type. The calcination mode includes normal mode, environmental protection mode, and energy-saving mode.
[0041] The process of obtaining the alumina content is as follows: a number of alumina raw material samples are randomly selected from the alumina raw material at a predetermined number of times, and the total weight of the samples reaches a predetermined percentage of the weight of the alumina raw material, such as one percent. The alumina content is obtained from the alumina raw material samples based on the average value of the alumina content.
[0042] The required types of alumina include: γ-alumina, β-alumina, and α-alumina.
[0043] The alumina weight in the calcination requirement is the desired weight of alumina to be obtained by calcining the alumina raw material.
[0044] S102. Input the alumina raw material information and the calcination requirements into the preset alumina process model, and the alumina process model outputs the calcination results and process parameter suggestions.
[0045] The alumina process module includes:
[0046] The process normal detection algorithm module is used to receive the alumina raw material information and the calcination requirements, and to output the calcination results; the calcination results are directly output to the user.
[0047] The calcination method module and the calcination process module are connected to the process normal detection algorithm module. Both the calcination method module and the calcination process module receive the alumina raw material information and the calcination requirements. The calcination method module is used to output the calcination method, and the calcination process module is used to output the calcination process.
[0048] The calcination method module is connected to the calcination process module and the process parameter module, and the process parameter module is used to output the process parameter suggestions.
[0049] The process parameter module is also connected to the process monitoring module, which is used to determine whether any abnormalities occur during the actual calcination process.
[0050] Specifically, the normal process detection algorithm module includes: determining whether the effective alumina weight is greater than the alumina weight in the calcination requirement; if not, the calcination result is that calcination is not feasible and the operation of the calcination equipment is stopped. The process of obtaining the effective alumina includes:
[0051] After multiplying the alumina content by the adsorption value, the sum of the product values of each impurity content and the corresponding impurity influence coefficient is subtracted to obtain the first subtraction. The first subtraction is then multiplied by the weight of the alumina raw material to obtain the effective alumina weight.
[0052] The adsorption value is equal to the product of the second preset coefficient and the value measured by the isothermal adsorption method, plus the value of the first preset coefficient.
[0053] It can be represented as:
[0054]
[0055] f1(SSA) = R1 + R2 × SSA;
[0056] Wherein, M2 is the effective weight of alumina, M0 is the weight of the alumina raw material, and K... i The impurity influence coefficient is M1, where M1 is the alumina content and C is the alumina content. i The content of the i-th impurity, where n is the type of impurity, the SSA is determined by isothermal adsorption, R1 is a preset first coefficient, and R2 is a preset second coefficient.
[0057] When the calcination result indicates that calcination is feasible, the calcination method module outputs the calcination method according to the calcination mode in the calcination requirements, including:
[0058] If the calcination mode is normal mode, then fuel heating is used to heat the calcination equipment;
[0059] If the calcination mode is an environmentally friendly mode, then electric heating is used to heat the calcination equipment;
[0060] If the calcination mode is an energy-saving mode, then the calcination equipment is heated by a combination of fuel heating and electric heating.
[0061] When the calcination result indicates that calcination is feasible, the calcination process module outputs the calcination process according to the required alumina type in the calcination requirements, including:
[0062] If the required alumina type is γ-alumina, then a pre-set single-stage calcination process is adopted;
[0063] If the required alumina type is β-type alumina, then a pre-set two-stage calcination process is adopted;
[0064] If the required alumina type is α-alumina, then a pre-set three-stage calcination process is adopted.
[0065] After receiving the calcination method output by the calcination method module and the calcination process output by the calcination process module, the process parameter module further determines the calcination process parameters, as detailed in the table below:
[0066]
[0067]
[0068] The temperature range for the first stage of calcination can be 300-800℃, the temperature range for the second stage of calcination can be 900-1100℃, and the temperature range for the third stage of calcination can be 1200-1400℃.
[0069] Single-stage calcination includes the first stage of calcination.
[0070] The two-stage calcination includes the first stage of calcination and the second stage of calcination.
[0071] The three-stage calcination includes the first stage of calcination, the second stage of calcination, and the third stage of calcination.
[0072] It should be noted that the calcination times for the first, second, and third stages of calcination can all be set independently and are not restricted here.
[0073] S103. The alumina raw material is calcined in the calcining equipment according to the process parameters recommended above, and the calcination information of the alumina raw material in the calcining equipment is obtained in real time.
[0074] The calcination information may include: fuel consumption information and environmental data inside the calcination equipment, etc.
[0075] S104. When the calcination information is input into the alumina process model, the alumina process model determines whether the calcination information is normal. If it is not normal, the operation of the calcination equipment is stopped.
[0076] When the calcination mode is normal mode, the calcination monitoring module in the alumina process model can also output the amount of fuel used for calcination based on the alumina raw material information.
[0077] The system monitors the fuel consumption information and heating stage information, and feeds back the consumption information and heating stage information to the calcination monitoring module in the alumina process model. The calcination monitoring module determines whether the consumption information and the heating stage information match, and outputs whether the calcination equipment has experienced a calcination abnormality based on the matching result.
[0078] The heating stage information includes the temperature information and calcination time inside the calcination equipment. The current calcination stage of the alumina raw material is determined based on the temperature information and calcination time. When the fuel consumption in the current calcination stage exceeds the corresponding preset fuel consumption threshold, the calcination monitoring module outputs a calcination abnormality.
[0079] Based on the temperature information and calcination time, the current stage of calcination can be determined, because the heating temperature and calcination time are different in each calcination stage.
[0080] The fuel consumption information corresponds one-to-one with the current calcination stage; that is, each calcination stage corresponds to a fuel consumption range.
[0081] When the cost information does not match the current stage of calcination, the calcination equipment will experience a calcination abnormality. In this case, the calcination equipment should be stopped and relevant personnel should be notified to further investigate the cause.
[0082] The method further includes: when the alumina raw material is calcined using a combination of resistance and microwave heating, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is greater than the internal temperature and the internal temperature is greater than a preset first minimum calcination temperature, the power of the resistance heating is reduced by a unit power. This saves energy.
[0083] In this process, when the alumina raw material is calcined using a combination of fuel and microwave heating, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is higher than the internal temperature and the internal temperature is higher than a preset second minimum calcination temperature, the proportion of high-calorific-value coal added to the fuel is reduced by a unit percentage. This can save energy.
[0084] The calcination information further includes: environmental data inside the calcination equipment, including pressure data, temperature data, and gas data. The DTW algorithm built into the calcination monitoring module calculates anomaly scores based on the environmental data. When the anomaly score is within a first preset score range, the calcination monitoring module outputs the process parameter suggestions. When the anomaly score is greater than the anomaly score threshold, the operation of the calcination equipment is stopped.
[0085] The DTW algorithm is existing technology. The calcination monitoring module determines which data(s) in the environmental data exceed a preset data threshold corresponding to the current calcination stage, and then outputs a corresponding solution strategy, namely, a process parameter suggestion, to reduce the data value until the abnormal score falls within a preset normal score range. For example, if the temperature is higher than the temperature threshold corresponding to the current calcination stage, the heating module of the calcination module is controlled to reduce the heating power, i.e., the process parameter suggestion is to reduce the temperature value.
[0086] Anomaly monitoring can further ensure the quality of the generated alumina.
[0087] In this invention, firstly, information on alumina raw materials and calcination requirements are obtained. The alumina raw material information includes alumina content and alumina raw material weight. The calcination requirements include alumina weight, calcination mode, and required alumina type. The calcination mode includes normal mode, environmentally friendly mode, and energy-saving mode. Both the alumina raw material information and the calcination requirements are obtained in advance by personnel.
[0088] The alumina raw material information and calcination requirements are input into a preset alumina process model, which outputs calcination results and process parameter suggestions. The alumina process model determines the feasibility of calcination and provides scientifically sound process reference suggestions.
[0089] The alumina raw material is calcined in the calcining equipment according to the recommended process parameters, and the calcination information of the alumina raw material in the calcining equipment is acquired in real time. The calcination information includes environmental data inside the calcining equipment.
[0090] When the calcination information is input into the alumina process model, the alumina process model determines whether the calcination information is normal. If it is abnormal, the operation of the calcination equipment is stopped. The alumina process model can also make real-time adjustments to the process parameters based on the calcination information, making the alumina calcination process more precise and of better quality.
[0091] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.
Claims
1. A method for monitoring alumina calcination process based on DCS control, characterized in that, include: The process involves acquiring alumina raw material information and calcination requirements. The alumina raw material information includes alumina content and weight. The calcination requirements include alumina weight, calcination mode, and required alumina type. The calcination modes include normal mode, environmentally friendly mode, and energy-saving mode. The alumina raw material information and calcination requirements are input into a preset alumina process model. The alumina process model outputs calcination results and suggested process parameters. The alumina raw material is calcined in a calcination device according to the suggested process parameters, and the calcination information is acquired in real time. When the calcination information is input into the alumina process model, the model determines whether the calcination information is normal. If it is abnormal, the operation of the calcination device is stopped. The alumina process model includes a normal process detection algorithm, which includes: determining whether the effective alumina weight is greater than the alumina weight in the calcination requirement; if not, the calcination result is that calcination is not feasible and the operation of the calcination equipment is stopped. The process of obtaining the effective alumina includes: multiplying the alumina content by the adsorption value, then subtracting the sum of the product values of each impurity content and its corresponding impurity influence coefficient to obtain a first subtraction factor; multiplying the first subtraction factor by the weight of the alumina raw material to obtain the effective alumina weight; the adsorption value is equal to the product of a second preset coefficient and the isothermal adsorption method measurement value, plus the value of the first preset coefficient.
2. The method for monitoring alumina calcination process based on DCS control as described in claim 1, characterized in that, When the calcination result indicates that calcination is feasible, the calcination method output according to the calcination mode in the calcination requirements includes: if the calcination mode is normal mode, then fuel heating is used to heat the calcination equipment; if the calcination mode is environmental protection mode, then electric heating is used to heat the calcination equipment; if the calcination mode is energy-saving mode, then a combination of fuel heating and electric heating is used to heat the calcination equipment.
3. The method for monitoring alumina calcination process based on DCS control as described in claim 1, characterized in that, When the calcination result indicates that calcination is feasible, the calcination process is output according to the required alumina type in the calcination requirements, including: if the required alumina type is γ-type alumina, a preset single-stage calcination process is adopted; if the required alumina type is β-type alumina, a preset two-stage calcination process is adopted; if the required alumina type is α-type alumina, a preset three-stage calcination process is adopted.
4. The method for monitoring alumina calcination process based on DCS control as described in claim 2, characterized in that, When the calcination mode is normal mode, the alumina process model outputs the amount of fuel used for calcination based on the alumina raw material information; it monitors the fuel usage information and heating stage information, and feeds back the usage information and heating stage information to the alumina process model. The alumina process model determines whether the usage information and the heating stage information match, and outputs whether the calcination equipment has experienced a calcination abnormality based on the matching result.
5. The method for monitoring alumina calcination process based on DCS control as described in claim 4, characterized in that, The heating stage information includes the temperature information and calcination time inside the calcination equipment. The current calcination stage of the alumina raw material is determined based on the temperature information and calcination time. When the fuel consumption in the current calcination stage exceeds the corresponding preset fuel consumption threshold, the alumina process model outputs a calcination anomaly.
6. The method for monitoring alumina calcination process based on DCS control as described in claim 1, characterized in that, The alumina process model includes: a process normal detection algorithm module, which receives the alumina raw material information and the calcination requirements, and outputs the calcination results; a calcination method module and a calcination process module connected to the process normal detection algorithm module, which also receive the alumina raw material information and the calcination requirements, with the calcination method module outputting the calcination method and the calcination process module outputting the calcination process; a process parameter module connected to the calcination method module and the calcination process module, which outputs process parameter suggestions; and a process monitoring module connected to the process parameter module, which determines whether any abnormalities occur during the actual calcination process.
7. The method for monitoring alumina calcination process based on DCS control as described in claim 6, characterized in that, The method further includes: when the alumina raw material is calcined using a combination of resistance and microwave heating, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is greater than the internal temperature and the internal temperature is greater than a preset first minimum calcination temperature, the power of the resistance heating is reduced by unit power.
8. The method for monitoring alumina calcination process based on DCS control as described in claim 6, characterized in that, When the alumina raw material is calcined using a heating method combining fuel and microwave, the calcination monitoring module acquires the surface temperature and internal temperature of the alumina. When the surface temperature is greater than the internal temperature and the internal temperature is greater than the preset second minimum calcination temperature, the proportion of high-calorific-value coal added to the fuel is reduced by a unit percentage.
9. The method for monitoring alumina calcination process based on DCS control as described in claim 6, characterized in that, The calcination information also includes: environmental data inside the calcination equipment, including: pressure data, temperature data, and gas data. The DTW algorithm built into the calcination monitoring module calculates anomaly scores based on the environmental data. When the anomaly score is within a first preset score range, the calcination monitoring module outputs the process parameter suggestions. When the anomaly score is greater than the anomaly score threshold, the operation of the calcination equipment is stopped.