A steel plant sedimentation tank multi-parameter fusion sludge discharge control method and device and storage medium

Abstract

This invention discloses a method, device, and storage medium for multi-parameter fusion sludge discharge control in sedimentation tanks of steel plants, within the field of wastewater treatment technology for the steel industry. The method includes: acquiring real-time multi-parameter data; calculating pre-calibrated multi-parameter data based on the real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data; performing fuzzy mapping on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter; constructing a fuzzy output set from all triggered rules in a pre-defined fuzzy rule set based on the membership degree of each parameter; and defuzzifying the fuzzy output set to obtain the sludge discharge pump frequency conversion command. This invention can alleviate the technical problems affecting sludge discharge efficiency caused by excessive or insufficient sludge discharge leading to water quality exceeding standards, interference of traditional sensors by ferromagnetic sludge, response lag due to manual reliance, and wasted water and electricity costs in existing technologies.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology in the steel industry, and in particular to a method, device and storage medium for multi-parameter integrated sludge discharge control in sedimentation tanks of steel plants. Background Technology

[0002] Traditional steel plant sedimentation tank sludge removal relies on manual experience, which has many drawbacks: excessive sludge removal or insufficient sludge removal can lead to water quality exceeding standards; ferromagnetic sludge can interfere with traditional sensors; reliance on manual labor can result in response delays and wasted water and electricity costs, thus affecting sludge removal efficiency.

[0003] Therefore, there is an urgent need for a multi-parameter integrated sludge discharge control method, device, and storage medium for steel plant sedimentation tanks to solve the above-mentioned technical problems. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a multi-parameter integrated sludge discharge control method, device and storage medium for sedimentation tanks in steel plants. This invention can alleviate the technical problems of existing technologies, such as water quality exceeding standards due to excessive or insufficient sludge discharge, interference of traditional sensors by ferromagnetic sludge, response lag due to manual reliance and waste of water and electricity costs, which affect sludge discharge efficiency.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants, comprising:

[0007] Obtain real-time multi-parameter data;

[0008] Calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data;

[0009] Fuzzy mapping is performed on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data.

[0010] Based on the membership degree of each parameter data, all triggered rules in the preset fuzzy rules are constructed into a fuzzy output set;

[0011] The fuzzy output set is defuzzified to obtain the frequency conversion command for the sludge pump.

[0012] Furthermore, obtaining theoretical prediction values ​​from multi-parameter data includes:

[0013] Obtain historical multi-parameter data;

[0014] The historical multi-parameter data is preprocessed to obtain preprocessed historical multi-parameter data;

[0015] The preprocessed historical multi-parameter data is input into the pre-trained digital twin model, and the theoretical predicted value of the multi-parameter data is output.

[0016] The state equations of the digital twin model include:

[0017] ;

[0018] The output expression of the digital twin model includes:

[0019] ;

[0020] in, For the current discrete time, For the previous moment, for Historical multi-parameter data input at any time, for Real historical multi-parameter data within the time system, The inertia coefficient, For input gain, for Historical multi-parameter data measured by the time sensor For observation gain, for Theoretical prediction values ​​of historical multi-parameter data at any given time. This is the optimal estimate of the true data after calibration based on the measurements from the previous time step;

[0021] The preprocessing includes wavelet noise reduction and temperature compensation;

[0022] The preliminary calibrated multi-parameter data is calculated based on real-time multi-parameter data and theoretically predicted values ​​from pre-acquired multi-parameter data. The expression includes:

[0023] ;

[0024] in, The data represents the multi-parameter data after initial calibration, where α is the dynamic trust weight.

[0025] Furthermore, the pre-calibrated multi-parameter data is fuzzified and mapped to obtain the membership degree of each parameter data, including:

[0026] ;

[0027] in, Membership degree of each parameter data, The lower limit of the preset parameters, This is the preset upper limit for parameters.

[0028] Furthermore, based on the membership degree of each parameter data, all triggered rules in the preset fuzzy rules are constructed into a fuzzy output set, including:

[0029] Based on the membership degree of each parameter data, the trigger strength of each pre-defined fuzzy rule is calculated using the Mamdani minimum method;

[0030] The trigger strength is used to cut the output fuzzy set corresponding to the rule;

[0031] Perform a union operation on all the cut fuzzy output sets to merge them into a fuzzy output set.

[0032] Further, the fuzzy output set is defuzzified to obtain the sludge pump frequency conversion command, including:

[0033] The centroid method is used for defuzzification, and the calculation formula includes:

[0034] ;

[0035] in, This is a frequency conversion command for the sludge pump. The specific values ​​for the frequency conversion commands of the sludge pump are as follows: This is a fuzzy output set.

[0036] Furthermore, the multi-parameter data includes turbidity, sludge interface height, and iron ion concentration.

[0037] Secondly, the present invention provides a multi-parameter integrated sludge discharge control device for sedimentation tanks in steel plants, comprising:

[0038] The data acquisition module is used to acquire real-time multi-parameter data;

[0039] The calibration module is used to calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data;

[0040] The fuzzification processing module is used to perform fuzzification mapping on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data.

[0041] The trimming module is used to construct a fuzzy output set from all triggered rules in the preset fuzzy rules based on the membership degree of each parameter data.

[0042] The defuzzing module is used to defuzzify the fuzzy output set to obtain the frequency conversion command for the sludge pump.

[0043] Thirdly, the present invention provides an electronic terminal, including a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method described in any of the preceding claims are performed.

[0044] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0045] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0046] This invention first proposes a multi-parameter fusion sludge discharge control method for sedimentation tanks in steel plants. It acquires real-time multi-parameter data, performs preliminary calibration, then fuzzifies the calibrated data, constructs a fuzzy output set from all triggered rules in a pre-defined fuzzy rule set, and finally defuzzifies the fuzzy output set to obtain the final sludge pump frequency conversion command, thereby controlling the pump frequency. This method alleviates the shortcomings of existing technologies, such as water quality exceeding standards due to excessive or insufficient sludge discharge, interference from traditional sensors by ferromagnetic sludge, response lag due to manual intervention, and wasted water and electricity costs, thus improving sludge discharge efficiency.

[0047] The problem of metal interference is solved by using a three-parameter composite probe (turbidity / ultrasound / iron ion), and a fuzzy-PID hybrid algorithm is used to dynamically adjust the sludge discharge intensity. A digital twin model is then used to calibrate the sensor data in real time. This system upgrade cost is less than 80,000 yuan per tank, sludge discharge energy consumption can be reduced by more than 35%, and the risk of environmental penalties can be avoided. It is suitable for sedimentation tanks containing iron sludge from hot rolling mills and cold rolling mills. Attached Figure Description

[0048] Figure 1 This is a flowchart of a multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants, provided by an embodiment of the present invention.

[0049] Figure 2 This is an architectural diagram of a multi-parameter fusion sludge discharge control device for a steel plant sedimentation tank provided in an embodiment of the present invention;

[0050] Figure 3 This is a cross-sectional view of the multi-parameter composite sensor in a multi-parameter fusion sludge discharge control method for a steel plant sedimentation tank provided in an embodiment of the present invention. Detailed Implementation

[0051] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0052] In this invention, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B together, or B alone. Additionally, in this invention, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0053] Example 1:

[0054] Figure 1 This is a flowchart of the multi-parameter integrated sludge discharge control method for steel plant sedimentation tanks according to Embodiment 1 of the present invention. This flowchart only illustrates the logical sequence of the methods described in this embodiment. Provided there are no conflicts, different methods may be used in other possible embodiments of the present invention. Figure 1 Complete the steps shown or described in the order indicated.

[0055] The multi-parameter integrated sludge discharge control method for steel plant sedimentation tanks provided in this embodiment can be applied to a terminal and can be executed by a mechanical equipment fault identification device. This device can be implemented in software and / or hardware and can be integrated into the terminal, such as any smartphone, tablet, or computer device with communication capabilities. The method in this embodiment specifically includes the following steps:

[0056] Step 1: Real-time multi-parameter data is obtained by using a multi-parameter composite sensor that integrates a turbidity detection module, an ultrasonic level module, and an iron ion concentration detection module into the same probe. The multi-parameter data includes turbidity, sludge interface height, and iron ion concentration. A 0.15-0.25mm thick PTFE anti-adhesion film can also be used to cover the probe surface, with an electromagnetic shielding layer (impedance > 80dB) inside.

[0057] Step 2: Calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of multi-parameter data pre-acquired through the digital twin model.

[0058] Obtaining theoretical prediction values ​​from multi-parameter data includes:

[0059] Obtain historical multi-parameter data;

[0060] The historical multi-parameter data is preprocessed to obtain preprocessed historical multi-parameter data;

[0061] The preprocessed historical multi-parameter data is input into the pre-trained digital twin model, and the theoretical predicted value of the multi-parameter data is output.

[0062] The state equations of the digital twin model include:

[0063] ;

[0064] The output expression of the digital twin model includes:

[0065] ;

[0066] in, For the current discrete time, For the previous moment, for Historical multi-parameter data input at any time, for Real historical multi-parameter data within the time system, The inertia coefficient, For input gain, for Historical multi-parameter data measured by the time sensor For observation gain, for Theoretical prediction values ​​of historical multi-parameter data at any given time. This is the optimal estimate of the true data after calibration based on the measurements from the previous time step;

[0067] The preprocessing includes wavelet denoising algorithm and temperature compensation circuit. Both wavelet denoising algorithm and temperature compensation circuit are conventional preprocessing methods and will not be described in detail here.

[0068] The preliminarily calibrated multi-parameter data is calculated based on real-time multi-parameter data and theoretically predicted values ​​of multi-parameter data pre-acquired through a digital twin model. The expressions include:

[0069] ;

[0070] in, For the multi-parameter data after preliminary calibration, The dynamic trust weight is set under normal operating conditions (the deviation between real-time multi-parameter data and the theoretical prediction value of multi-parameter data is less than a preset threshold). =0.8, mainly relying on measured data; under interference conditions (the deviation between real-time multi-parameter data and theoretical predicted values ​​of multi-parameter data is greater than the preset threshold). It automatically drops to 0.3, relying primarily on model predictions to eliminate measurement errors caused by metal interference.

[0071] Step 3: Perform fuzzy mapping on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data. The expression includes:

[0072] ;

[0073] in, Membership degree of each parameter data, The lower limit of the preset parameters, This is the preset upper limit for parameters.

[0074] Step 4: Based on the membership degree of each parameter data, construct a fuzzy output set from all triggered rules in the preset fuzzy rules, including:

[0075] Based on the membership degree of each parameter data, the trigger strength of each pre-defined fuzzy rule is calculated using the Mamdani minimum method;

[0076] The trigger strength is used to cut the output fuzzy set corresponding to the rule;

[0077] Perform a union operation (taking the maximum value) on all the cut fuzzy output sets to merge them into a fuzzy output set.

[0078] The fuzzy rules may also include: an iron ion concentration compensation factor, which increases the output value by 30-50% when Fe > 150 mg / L.

[0079] Step 5: Defuzzify the fuzzy output set to obtain the sludge pump frequency conversion command, including:

[0080] The centroid-of-gravity (COG) method is used for defuzzification, and the calculation formula includes:

[0081] ;

[0082] in, This is a frequency conversion command for the sludge pump. The specific values ​​for the frequency conversion commands of the sludge pump are as follows: This is a fuzzy output set.

[0083] Regarding specific variable frequency commands for the sludge pump, there are three modes: Dynamic mode, when the turbidity is greater than 95 NTU and lasts for 10 seconds, the variable frequency pump is started at a frequency of 25-50 Hz; Emergency mode, when the turbidity change rate is greater than 5 NTU / s, full-speed sludge discharge and audible and visual alarms are executed; Timed mode, when the time is 8:00 or 16:00 every day, low-speed sludge discharge is executed for 15 minutes for maintenance.

[0084] In summary, by comparing the multi-parameter integrated sludge discharge control method for steel plant sedimentation tanks provided in this application with the manual sludge discharge method before the modification, the implementation effect comparison chart is shown in the table below. It can reduce the system modification cost to less than 80,000 yuan / tank, reduce sludge discharge energy consumption by more than 35%, avoid the risk of environmental fines, and is applicable to iron-containing sludge sedimentation tanks in hot rolling, cold rolling and other industries.

[0085] Table 1 shows a comparison of the implementation effects.

[0086]

[0087] Example 2:

[0088] Embodiment 2 of the present invention provides a multi-parameter integrated sludge discharge control device for sedimentation tanks in steel plants, comprising:

[0089] The data acquisition module is used to acquire real-time multi-parameter data;

[0090] The calibration module is used to calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data;

[0091] The fuzzification processing module is used to perform fuzzification mapping on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data.

[0092] The trimming module is used to construct a fuzzy output set from all triggered rules in the preset fuzzy rules based on the membership degree of each parameter data.

[0093] The defuzzing module is used to defuzzify the fuzzy output set to obtain the frequency conversion command for the sludge pump.

[0094] Based on the above modules, in specific implementation, as shown in the appendix. Figure 2 and attached Figure 3 As shown, in this implementation, a sedimentation tank with dimensions of 25m (L) × 6m (W) × 4.5m (H) can be selected, which has a capacity of 1200m³. 3 The treatment capacity is [amount] / h. The sludge characteristics are iron oxide content (Fe>180mg / L) and high viscosity. The original sludge discharge method was manual timed discharge. In addition, the specific hardware configuration of the system on which the sludge discharge depends is as follows: a customized (Hanwei Technology HY-MPS01) three-parameter composite sensor, installed 1.2m from the bottom of the tank; an Advantech ARK-3520 industrial control computer with i7 / 16GB edge computing gateway, installed in the field control cabinet; a Grundfos CR45-6, 45kW variable frequency sludge pump, installed in the sludge discharge pipeline. This application mainly realizes the control of the variable frequency sludge pump; a Dell PowerEdge-R750, NVIDIA-T4 digital twin server, installed in the central control room.

[0095] Preferably, the sensor can also be equipped with anti-interference design: 316L stainless steel shell + 0.2mm PTFE coating (to prevent iron powder adhesion), double-layer electromagnetic shielding (copper mesh + aluminum foil, shielding effectiveness 82dB), and sapphire light-transmitting window (to prevent scratches).

[0096] The multi-parameter fusion sludge discharge control device for steel plant sedimentation tanks provided in Embodiment 2 of the present invention can execute the multi-parameter fusion sludge discharge control method for steel plant sedimentation tanks provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0097] Example 3:

[0098] Embodiment 3 of the present invention also provides an electronic terminal, including a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and the processor is used to perform operations according to the instructions to execute the steps of the method described in Embodiment 1.

[0099] The electronic terminal provided in Embodiment 3 of the present invention can execute the multi-parameter fusion sludge discharge control method for sedimentation tanks in steel plants provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0100] Example 4:

[0101] Embodiment 4 of the present invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the method described in Embodiment 1, and has the corresponding functional modules and beneficial effects of the method.

[0102] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] 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 modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants, characterized in that, include: Obtain real-time multi-parameter data; Calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data; Fuzzy mapping is performed on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data. Based on the membership degree of each parameter data, all triggered rules in the preset fuzzy rules are constructed into a fuzzy output set; The fuzzy output set is defuzzified to obtain the frequency conversion command for the sludge pump.

2. The multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants according to claim 1, characterized in that, Obtaining theoretical predictions from multi-parameter data includes: Retrieve historical multi-parameter data; The historical multi-parameter data is preprocessed to obtain preprocessed historical multi-parameter data; The preprocessed historical multi-parameter data is input into the pre-trained digital twin model, and the theoretical predicted value of the multi-parameter data is output. The state equations of the digital twin model include: ； The output expression of the digital twin model includes: ； in, For the current discrete time, For the previous moment, for Historical multi-parameter data input at any time, for Real historical multi-parameter data within the time system, The inertia coefficient, For input gain, for Historical multi-parameter data measured by the time sensor For observation gain, for Theoretical prediction values ​​of historical multi-parameter data at any given time. This is the optimal estimate of the true data after calibration based on the measurements from the previous time step; The preprocessing includes wavelet noise reduction and temperature compensation; The pre-calibrated multi-parameter data is calculated based on real-time multi-parameter data and theoretically predicted values ​​from pre-acquired multi-parameter data. The expression includes: ； in, For the multi-parameter data after preliminary calibration, This is a dynamic trust weight.

3. The multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants according to claim 1, characterized in that, The multi-parameter data after preliminary calibration is fuzzified and mapped to obtain the membership degree of each parameter data, including: ； in, Membership degree of each parameter data, The lower limit of the preset parameters, This is the preset upper limit for parameters.

4. The multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants according to claim 1, characterized in that, Based on the membership degree of each parameter data, a fuzzy output set is constructed from all triggered rules in the preset fuzzy rules, including: Based on the membership degree of each parameter data, the trigger strength of each pre-defined fuzzy rule is calculated using the Mamdani minimum method; The trigger strength is used to cut the output fuzzy set corresponding to the rule; Perform a union operation on all the cut fuzzy output sets to merge them into a fuzzy output set.

5. The multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants according to claim 1, characterized in that, Defuzzify the fuzzy output set to obtain the sludge pump frequency conversion command, including: The centroid method is used for defuzzification, and the calculation formula includes: ； in, This is a frequency conversion command for the sludge pump. The specific values ​​for the frequency conversion commands of the sludge pump are as follows: This is a fuzzy output set.

6. The multi-parameter integrated sludge discharge control method for sedimentation tanks in steel plants according to claim 1, characterized in that, The multi-parameter data includes turbidity, sludge interface height, and iron ion concentration.

7. A multi-parameter integrated sludge discharge control device for sedimentation tanks in steel plants, characterized in that, include: The data acquisition module is used to acquire real-time multi-parameter data; The calibration module is used to calculate the pre-calibrated multi-parameter data based on real-time multi-parameter data and theoretically predicted values ​​of pre-acquired multi-parameter data; The fuzzification processing module is used to perform fuzzification mapping on the pre-calibrated multi-parameter data to obtain the membership degree of each parameter data. The trimming module is used to construct a fuzzy output set from all triggered rules in the preset fuzzy rules based on the membership degree of each parameter data. The defuzzing module is used to defuzzify the fuzzy output set to obtain the frequency conversion command for the sludge pump.

8. An electronic terminal, characterized in that, It includes a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it performs the steps of the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 6.

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