Intelligent crushing system and control method thereof

Abstract

The invention relates to the field of refractory material production, and discloses an intelligent crushing system and a control method thereof.The intelligent crushing system comprises a crushing module, the crushing module is used for crushing, processing and producing raw materials for producing refractory materials, and the crushing module is connected with a sensing and detecting module; the sensing and detecting module is used for detecting various parameters of raw materials in the crushing process and transmitting the detected parameters of the raw materials to the driving execution module, the driving execution module is connected to the sensing and detecting module, and the driving execution module uses a calculation formula and substitutes the parameters of the raw materials into the calculation formula. And a corresponding crushing adjustment scheme is selected according to the result. The crushing parameters are dynamically generated by detecting the hardness and viscosity of the raw materials in real time, and the optimal crushing strength and rotating speed are automatically matched in combination with a dynamic adjustment algorithm, so that the qualified rate of the granularity of a finished product after the refractory material is crushed is improved, the loss of the crusher is reduced, and the problem of hysteresis of manual parameter adjustment is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of refractory material production, in particular to an intelligent crushing system and a control method thereof. Background Art

[0002] In industrial fields such as refractory materials and metallurgical raw material processing, material crushing is one of the core processes. By crushing the raw materials used to make refractory materials, subsequent processing is facilitated.

[0003] In recent years, some intelligent improvement solutions have attempted to dynamically adjust the crushing intensity by introducing sensors to monitor crusher load or motor current fluctuations. However, such systems lack direct detection of raw material properties. For example, composition and viscosity rely on offline laboratory analysis, and parameter adjustment has a lag. In addition, the lack of a closed-loop feedback mechanism between crushing strategy and finished product quality leads to a long optimization cycle, usually requiring several weeks of manual parameter adjustment. It is difficult to cope with real-time fluctuations in continuous production scenarios. As a result, when crushing different refractory raw materials, it is impossible to dynamically adjust the crushing force and speed in a timely manner, which affects the quality of the crushed raw material products and even fails to meet production standards. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides an intelligent crushing system and a control method thereof, which solves the problem that the existing intelligent crushing solutions rely on indirect monitoring and lack real-time quality closed-loop feedback, resulting in parameter correction lag and inefficient manual parameter adjustment, and are unable to stably respond to real-time working condition changes in continuous production.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent crushing system, including a crushing module, which is used to crush and process raw materials for producing refractory materials. The crushing module is connected to a sensing and detection module, which detects various parameters of the raw materials during the crushing process and transmits the detected raw material parameters to a driving execution module. The sensing and detection module is connected to a driving execution module, which uses a calculation formula and substitutes the raw material parameters, and selects a corresponding crushing adjustment scheme according to the results. The crushing module is connected to a finished product detection module, which performs detection after the raw materials are crushed.

[0006] Preferably, the sensing and detection module includes an acquisition module, and the acquisition module is connected to a material property identification module.

[0007] Preferably, the driving execution module includes a crushing scheme adjustment module, and the crushing scheme adjustment module is provided with different crushing schemes according to different crushing forces and crushing rotation speeds.

[0008] Preferably, the crushing scheme adjustment module is connected to a dynamic adjustment algorithm module, and the dynamic adjustment algorithm module uses a dynamic adjustment algorithm to calculate the rotation speed and force that need to be adjusted according to the conclusion calculated by the sensing and detection module. The crushing scheme adjustment module is connected to the crushing module.

[0009] Preferably, the finished product inspection module includes a quality inspection module, and the quality inspection module uses inspection equipment to inspect the crushed refractory raw materials.

[0010] Preferably, the quality detection module is connected to an optimization module, and the optimization module performs calculations and adjustments based on historical crushing detection values, thereby optimizing the weights and values ​​in the dynamic adjustment algorithm module. The optimization module is connected to the dynamic adjustment algorithm module; the optimization module uses the optimization algorithm to perform calculations based on the historical values ​​of crushing processing after 30 days of processing, and appropriately adjusts the weight values ​​in the dynamic adjustment algorithm module, and makes corresponding adjustments based on actual conditions and the purity and quality of the materials to ensure the crushing efficiency and the loss of the crusher.

[0011] Preferably, the material property identification module is provided with an identification algorithm, and the identification algorithm includes:

[0012]

[0013] Among them; k1, k2, c1, c2 represent the material property calibration coefficients; δ 形变 Represents the material deformation during the crushing process; T 温升： Represents the difference between the temperature of the crushing area and the ambient temperature; H 阈值： Represents the critical value of material hardness; by substituting the above values ​​into calculation, the hardness H and viscosity μ of the current material can be obtained.

[0014] Preferably, the crushing scheme in the crushing scheme adjustment module is specifically:

[0015] High-intensity crushing: Suitable for high-hardness and high-viscosity refractory raw materials, using 120-200kN crushing force and 800-1200rpm speed, with coarse crushing particle size (10-30mm) as the target

[0016] Medium-intensity crushing: For refractory materials with medium hardness and medium viscosity, set a dynamic pressure of 60-120kN and a speed of 400-800rpm to accurately adapt to the medium crushing particle size (5-10mm);

[0017] Low-intensity crushing: For refractory materials with low hardness and low viscosity, it uses a low impact force of 20-60kN combined with a slow speed of 200-400rpm to precisely control the crushing to the target size of 1-5mm.

[0018] Preferably, the dynamic adjustment algorithm module is provided with a dynamic adjustment algorithm, and the dynamic adjustment algorithm includes:

[0019]

[0020] Where: W1~W5: represents the adaptive weight parameter; μ 平衡： Represents the equilibrium constant that prevents idling due to low viscosity; D 容差： Represents the allowable particle size deviation range; by entering the hardness H and viscosity μ and then calculating the crushing force F through the formula 力度 , Broken V 转速 .

[0021] A control method for an intelligent crushing system comprises the following steps:

[0022] S1. Material property identification: Real-time collection of raw material hardness, viscosity, temperature and other parameters, and algorithm analysis to match the preset material type, providing a basis for solution selection;

[0023] S2. Crushing scheme matching: Automatically select high-intensity, medium-intensity, or low-intensity crushing schemes based on material characteristics, and initialize the crusher's force and speed reference parameters;

[0024] S3. Dynamic parameter adjustment: Based on the real-time feedback of particle size and crushing resistance during the crushing process, the equipment force and speed are dynamically adjusted to ensure stable output of the target particle size;

[0025] S4. Finished product quality inspection: Use laser particle size analyzer and compression testing equipment to verify the quality of finished products;

[0026] S5. Closed-loop optimization iteration: Utilize historical batch data to optimize algorithm weights and parameter adjustment strategies to continuously improve subsequent crushing efficiency and finished product qualification rate.

[0027] The present invention provides an intelligent crushing system and a control method thereof, which has the following beneficial effects:

[0028] 1. The present invention dynamically generates crushing parameters by real-time detection of raw material hardness and viscosity, and automatically matches the optimal crushing force and rotation speed in combination with a dynamic adjustment algorithm, thereby improving the qualified particle size rate of the finished product after refractory material crushing, while reducing the loss of the crusher and solving the problem of manual parameter adjustment lag.

[0029] 2. The present invention establishes a self-optimization mechanism based on finished product quality feedback and historical data, uses a gradient descent algorithm and PID correction to update the model weights in real time, and makes corresponding adjustments based on the actual situation and the purity and quality of each batch of materials, further improving the accuracy of the dynamic algorithm in judging and adjusting the crushing force and rotation speed.

[0030] 3. The present invention sets different crushing schemes so that different crushing schemes can be used when facing different refractory raw materials, thereby further improving the adaptability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a system flow chart of the present invention;

[0032] Figure 2 This is a flow chart of the system control method of the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the present specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] Example:

[0035] Please see the attached Figure 1 - Attachment Figure 2 An embodiment of the present invention provides an intelligent crushing system, including a crushing module, which is used to crush and process raw materials for producing refractory materials. The crushing module is connected to a sensing and detection module, which detects various parameters of the raw materials during the crushing process and transmits the detected raw material parameters to a driving execution module. The sensing and detection module is connected to a driving execution module, which uses a calculation formula and substitutes the raw material parameters, and selects a corresponding crushing adjustment plan according to the result. The crushing module is connected to a finished product detection module, which performs detection after the raw materials are crushed, so as to determine whether the crushing process meets the production standards.

[0036] The sensing and detection module includes an acquisition module, the acquisition module is connected to a material property recognition module, and the material property recognition module is provided with a recognition algorithm, the recognition algorithm includes:

[0037]

[0038] Among them; k1, k2, c1, c2 represent the material property calibration coefficients; δ 形变 Represents the material deformation during the crushing process; T 温升： Represents the difference between the temperature of the crushing area and the ambient temperature; H 阈值： Represents the critical value of material hardness; by substituting the above values ​​into calculation, the hardness H and viscosity μ of the current material can be obtained;

[0039] The driving execution module includes a crushing scheme adjustment module, which provides different crushing schemes according to different crushing forces and crushing speeds. The crushing schemes are specifically:

[0040] High-intensity crushing: Suitable for high-hardness and high-viscosity refractory raw materials, using 120-200kN crushing force and 800-1200rpm speed, with coarse crushing particle size (10-30mm) as the target

[0041] Medium-intensity crushing: For refractory materials with medium hardness and medium viscosity, set a dynamic pressure of 60-120kN and a speed of 400-800rpm to accurately adapt to the medium crushing particle size (5-10mm);

[0042] Low-intensity crushing: For refractory materials with low hardness and low viscosity, it uses a low impact force of 20-60kN combined with a slow speed of 200-400rpm to precisely control the crushing to the target size of 1-5mm.

[0043] The crushing scheme adjustment module is connected to a dynamic adjustment algorithm module, which uses a dynamic adjustment algorithm to calculate the speed and force that need to be adjusted based on the conclusions calculated by the sensing and detection module. The crushing scheme adjustment module is connected to the crushing module;

[0044] The dynamic adjustment algorithm module is provided with a dynamic adjustment algorithm, and the dynamic adjustment algorithm includes:

[0045]

[0046] Where: W1~W5: represents the adaptive weight parameter; μ 平衡： Represents the equilibrium constant that prevents idling due to low viscosity; D 容差： Represents the allowable particle size deviation range; by entering the hardness H and viscosity μ and then calculating the crushing force F through the formula 力度 , Broken V 转速 ;

[0047] The finished product inspection module includes a quality inspection module, which uses inspection equipment to inspect the crushed refractory raw materials to determine the quality of the finished product. The inspection equipment includes: a laser particle size analyzer and a compression testing machine.

[0048] The quality detection module is connected to an optimization module, which performs calculations and adjustments based on historical fragmentation detection values, thereby optimizing the weights and values ​​in the dynamic adjustment algorithm module to further ensure the accuracy of the calculation. The optimization module is connected to the dynamic adjustment algorithm module;

[0049] The optimization module uses an optimization algorithm to calculate based on the historical values ​​of crushing processing after 30 days of processing, and appropriately adjusts the weight values ​​in the dynamic adjustment algorithm module. It makes corresponding adjustments based on the actual situation and the purity and quality of each batch of materials to ensure the crushing efficiency and the loss of the crusher. The optimization algorithm is specifically as follows:

[0050] Weight optimization formula (based on gradient descent):

[0051]

[0052] Partial derivative calculation:

[0053]

[0054] Regularization term: ΔW i =ΔW i -λ·W i (Prevent overfitting)

[0055] PID feedback correction (control of crushing force stability):

[0056] ΔF 修正 =K p ·(D 目标 -D 实际 )+K i ·∑(D 目标 -D 实际 )

[0057] A control method for an intelligent crushing system comprises the following steps:

[0058] S1. Material property identification: Real-time collection of raw material hardness, viscosity, temperature and other parameters, and algorithm analysis to match the preset material type, providing a basis for solution selection;

[0059] S2. Crushing scheme matching: Automatically select high-intensity, medium-intensity, or low-intensity crushing schemes based on material characteristics, and initialize the crusher's force and speed reference parameters;

[0060] S3. Dynamic parameter adjustment: Based on the real-time feedback of particle size and crushing resistance during the crushing process, the equipment force and speed are dynamically adjusted to ensure stable output of the target particle size;

[0061] S4. Finished product quality inspection: Use laser particle size analyzer and compression testing equipment to verify the quality of finished products;

[0062] S5. Closed-loop optimization iteration: Utilize historical batch data to optimize algorithm weights and parameter adjustment strategies to continuously improve subsequent crushing efficiency and finished product qualification rate.

[0063] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent crushing system, characterized in that: It includes a crushing module, which is used to crush and process the raw materials for producing refractory materials. The crushing module is connected to a sensing and detection module, which detects various parameters of the raw materials during the crushing process and transmits the detected raw material parameters to a driving execution module. The sensing and detection module is connected to a driving execution module, which uses a calculation formula and substitutes the raw material parameters, and selects a corresponding crushing adjustment plan according to the results. The crushing module is connected to a finished product detection module, which performs detection after the raw materials are crushed.

2. The intelligent crushing system according to claim 1, characterized in that: The sensing and detection module includes an acquisition module, and the acquisition module is connected to a material property recognition module.

3. The intelligent crushing system according to claim 1, characterized in that: The driving execution module includes a crushing scheme adjustment module, and the crushing scheme adjustment module is provided with different crushing schemes according to different crushing forces and crushing rotation speeds.

4. The intelligent crushing system according to claim 3, characterized in that: The crushing scheme adjustment module is connected to a dynamic adjustment algorithm module, which uses a dynamic adjustment algorithm to calculate the rotation speed and force that need to be adjusted based on the conclusions calculated by the sensing and detection module. The crushing scheme adjustment module is connected to the crushing module.

5. The intelligent crushing system according to claim 1, characterized in that: The finished product inspection module includes a quality inspection module, and the quality inspection module uses inspection equipment to inspect the crushed refractory raw materials.

6. The intelligent crushing system according to claim 5, characterized in that: The quality detection module is connected to an optimization module, and the optimization module calculates and adjusts according to the historical crushing detection values, thereby optimizing the weights and values ​​in the dynamic adjustment algorithm module. The optimization module is connected to the dynamic adjustment algorithm module; the optimization module uses the optimization algorithm to calculate according to the historical values ​​of crushing processing after 30 days of processing, and appropriately adjusts the weight values ​​in the dynamic adjustment algorithm module. Corresponding adjustments are made according to actual conditions and the purity and quality of the materials to ensure the crushing efficiency and the loss of the crusher.

7. The intelligent crushing system according to claim 2, characterized in that: The material property identification module is provided with an identification algorithm, which includes: Among them; k1, k2, c1, c2 represent the material property calibration coefficients; δ 形变 Represents the material deformation during the crushing process; T 温升： Represents the difference between the temperature of the crushing area and the ambient temperature; H 阈值： Represents the critical value of material hardness; by substituting the above values ​​into calculation, the hardness H and viscosity μ of the current material can be obtained.

8. The intelligent crushing system according to claim 3, characterized in that: The crushing scheme in the crushing scheme adjustment module is specifically: High-intensity crushing: Suitable for high-hardness and high-viscosity refractory raw materials, using 120-200kN crushing force and 800-1200rpm speed, with coarse crushing particle size (10-30mm) as the target Medium-intensity crushing: For refractory materials with medium hardness and medium viscosity, set a dynamic pressure of 60-120kN and a speed of 400-800rpm to accurately adapt to the medium crushing particle size (5-10mm); Low-intensity crushing: For refractory materials with low hardness and low viscosity, it uses a low impact force of 20-60kN combined with a slow speed of 200-400rpm to precisely control the crushing to the target size of 1-5mm.

9. The intelligent crushing system according to claim 4, characterized in that: The dynamic adjustment algorithm module is provided with a dynamic adjustment algorithm, and the dynamic adjustment algorithm includes: Where: W1~W5: represents the adaptive weight parameter; μ 平衡： Represents the equilibrium constant that prevents idling due to low viscosity; D 容差： Represents the allowable particle size deviation range; by entering the hardness H and viscosity μ and then calculating the crushing force F through the formula 力度 , Broken V 转速 .

10. A control method for an intelligent crushing system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Material property identification: Real-time collection of raw material hardness, viscosity, temperature and other parameters, and algorithm analysis to match the preset material type, providing a basis for solution selection; S2. Crushing scheme matching: Automatically select high-intensity, medium-intensity, or low-intensity crushing schemes based on material characteristics, and initialize the crusher's force and speed reference parameters; S3. Dynamic parameter adjustment: Based on the real-time feedback of particle size and crushing resistance during the crushing process, the equipment force and speed are dynamically adjusted to ensure stable output of the target particle size; S4. Finished product quality inspection: Use laser particle size analyzer and compression testing equipment to verify the quality of finished products; S5. Closed-loop optimization iteration: Utilize historical batch data to optimize algorithm weights and parameter adjustment strategies to continuously improve subsequent crushing efficiency and finished product qualification rate.

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